Services Transactions on Cloud Computing (STCC), formerly International Journal of Cloud Computing (IJCC)

Journal Contents

== 2017 ===

Volume 4, No 4 (October-December, 2017)
Volume 4, No 3 (July-September, 2017)
Volume 4, No 2 (April-June, 2017)
Volume 4, No 1 (January-March, 2017)

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== 2016 ===

Volume 4, No 4 (October-December, 2016)
Volume 4, No 3 (July-September, 2016)
Volume 4, No 2 (April-June, 2016)
Volume 4, No 1 (January-March, 2016)

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== 2015 ===

Volume 3, No 4 (October-December, 2015)
Volume 3, No 3 (July-September, 2015)
Volume 3, No 2 (April-June, 2015)
Volume 3, No 1 (January-March, 2015)

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== 2014 ===

Volume 2, No 4 (October - December, 2014)
Volume 2, No 3 (July - September, 2014)
Volume 2, No 2 (April-June, 2014)
Volume 2, No 1 (January-March, 2014)

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== 2013 ===

Volume 1, No 2 (October - December, 2013)
Volume 1, No 1 (July - September, 2013)

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Volume 5, No 1 (January-March, 2017): [ Full Issue PDF]

Volume 4, No 4 (October-December, 2016): [ Full Issue PDF]

  • DISTRIBUTED ALGORITHMS FOR SPATIAL RETRIEVAL QUERIES IN GEOSPATIAL ANALYSIS

  • Should be cited as: [ paper pdf download]

    Pierfrancesco Bellini, Ivan Bruno, Daniele Cenni, Paolo Nesi "A KNOWLEDGE BASE DRIVEN SOLUTION FOR SMART CLOUD MANAGEMENT AND MONITORING", Services Transactions on Cloud Computing (STCC), 4(4), 2016, pp. 1-14.

    Abstract:

    Context: Cloud infrastructures needs to become more smarter and dynamic in managing resources, requiring new solutions and tools to cope with processes of configuration and reconfiguration, automatic scaling, elastic computing and healthiness control. This paper presents a Smart Cloud solution for automatically managing cloud infrastructures, and programming the monitoring aspects directly from the configuration and deploy phases. This means that the proposed solution can enforce smart cloud intelligence to almost all Cloud Configuration management systems and orchestrators by using REST calls and XML files. The solution proposed includes a Smart Cloud Engine, an advanced Supervisor and Monitor, and a Knowledge Base. The Knowledge Base is grounded on a cloud ontology modeling cloud resources and relationships, Service Level Agreements and their evolution, constraints, metrics for assessment, etc. The Knowledge Base enables the reasoning on cloud structures and permits to implement strategies of efficient smart cloud management and intelligence: (i) verify and validate the configurations and related changes according to the cloud model and available resources; (ii) easily generate the processing control for verifying cloud resource healthiness and service level agreement verification; (iii) take decision about dynamic reconfiguration on cloud, for example for scaling, balancing, migration, etc. The proposed solution has been validated in the context of ICARO project on complex cloud configurations with good performance and low operating workload. The validation has also assessed the reliability and the scalability.

  • CLOUD ANALYTICS FOR SHORT-TERM LTE METRIC PREDICTION - CAPACITY, CLOUD FRAMEWORK AND PERFORMANCE

  • Should be cited as: [ paper pdf download]

    Zulfiquar Sayeed "CLOUD ANALYTICS FOR SHORT-TERM LTE METRIC PREDICTION - CAPACITY, CLOUD FRAMEWORK AND PERFORMANCE ", Services Transactions on Cloud Computing (STCC), 4(4), 2016, pp. 15-27.

    Abstract:

    Context: The knowledge of a future link quality for a user equipment (UE) in wireless networks may be used by the application and TCP layer so that user's experience is optimized. The metrics that are relevant are available at the core of the radio link and the application or TCP layers have no knowledge of the wireless metrics. With a signaling protocol to the application/TCP layer and a prediction mechanism of the future link quality the applications will be able to avoid buffer overflows and/or congestion. In this paper we identify metrics that are suitable for application/TCP control, and analyze the performance of the prediction of the metrics. We show that the prediction of wireless metrics can be made with low error (3-10% MAPE) even with high cloud latency. This is a significant result as it states that predictions in the cloud of even short term LTE metrics are possible and that the predictions are fairly accurate to influence the proper operation of applications/TCP in wireless environments. We also show results on how short-term prediction increases the system capacity of a wireless system.

  • Network Motif Analysis in Clouds - Subgraph Enumeration with Iterative Hadoop MapReduce

  • Should be cited as: [ paper pdf download]

    Vartika Verma, Paul Park Kwon, Anand Joglekar, and Wooyoung Kim “Network Motif Analysis in Clouds - Subgraph Enumeration with Iterative Hadoop MapReduce", Services Transactions on Cloud Computing (STCC), 4(4), 2016, pp. 28-40.

    Abstract:

    Context: Finding network motifs in biological networks is a computationally intensive task as it involves traversing through a large network to enumerate all possible subgraphs of a given size, and then determining their statistical uniqueness by sampling subgraphs from a large number (more than 1,000) of random graph pools. There have been parallelization efforts in the past to mitigate the computational intensity for finding network motifs. However, they are either more for the frequent subgraphs in networks rather than network motifs, or require complex manipulations on message passing or designs. Additionally, most of the parallel algorithms are unavailable as tools for use. Here, we introduce a project of ‘complete network motif parallelization.’ This project aims to improve performance of serial algorithms for finding all subgraph patterns with given size in PPI networks by parallelizing them using iterative Hadoop MapReduce on Google Cloud, and then determining their uniqueness through explicit or direct random graph generation to determine network motifs. In this paper, we describe the parallelization of subgraph enumeration and McKay’s canonical algorithms and present the experimental results with a significant improvement in performance, up to 37 times speedup. We are continuing to parallelize network motif significance as a next step, and expecting the completion of the project in near future.

Volume 4, No 3 (July-September, 2016): [ Full Issue PDF]

  • DISTRIBUTED ALGORITHMS FOR SPATIAL RETRIEVAL QUERIES IN GEOSPATIAL ANALYSIS

  • Should be cited as: [ paper pdf download]

    Qiulei Guo, Balaji Palanisamy, Hassan A. Karimi and Liming Zhang "DISTRIBUTED ALGORITHMS FOR SPATIAL RETRIEVAL QUERIES IN GEOSPATIAL ANALYSIS", Services Transactions on Cloud Computing (STCC), 4(3), 2016, pp. 1-13.

    Abstract:

    Context: The proliferation of data acquisition devices like 3D laser scanners had led to the burst of large-scale spatial terrain data which imposes many challenges to spatial data analysis and computation. With the advent of several emerging cloud technologies, a natural and cost-effective approach to managing such large-scale data is to store and process such datasets in a publicly hosted cloud service using modern distributed computing paradigms such as MapReduce. For several key spatial data analysis and computation problems, polygon retrieval is a fundamental operation which is often computed under real- time constraints. However, existing sequential algorithms fail to meet this demand effectively given that terrain data in recent years have witnessed an unprecedented growth in both volume and rate. In this work, we present a MapReduce-based parallel polygon retrieval algorithm which aims at minimizing the IO and CPU loads of the map and reduce tasks during spatial data processing. Our proposed algorithm first hierarchically indexes the spatial terrain data using a quad-tree index, with the help of which, a significant amount of data is filtered out in the pre- processing stage based on the query object. In addition, a prefix tree based on the quad-tree index is built to query the relationship between the terrain data and query area in real time which leads to significant savings in both I/O load and CPU time. The performance of the proposed techniques is evaluated in a Hadoop cluster and the results demonstrate that the proposed techniques are flexible and scalable. Our quad tree indexing with prefix tree acceleration lead to more than 35% reduction in execution time of the polygon retrieval operation over existing distributed algorithms while the quad tree indexing without prefix tree works best for the proximity query.

  • TOWARDS ACHIEVING RELIABLE DIGITAL FORENSICS IN IAAS AND STAAS CLOUDS USING THE OPEN CLOUD FORENSICS MODEL

  • Should be cited as: [ paper pdf download]

    Shams Zawoad, Ragib Hasan, and Anthony Skjellum "TOWARDS ACHIEVING RELIABLE DIGITAL FORENSICS IN IAAS AND STAAS CLOUDS USING THE OPEN CLOUD FORENSICS MODEL", Services Transactions on Cloud Computing (STCC), 4(3), 2016, pp. 14-27.

    Abstract:

    Context: The rapid adoption of cloud computing to meet storage and computation needs has changed the way computing services and resources are used. However, because of the black-box nature and multi-tenant usage models of clouds, existing digital forensics science cannot cope with current state-of-the-art cloud architectures. Because of the fundamental characteristics of such clouds, many assumptions of digital forensics are invalidated. In the digital forensics process involving clouds, the role of cloud service providers (CSPs) is extremely important; a role which needs to be considered in the science of cloud forensics. In this paper, we define cloud forensics while considering the role of the CSP and propose the Open Cloud Forensics (OCF) model. The OCF model focuses on preserving sufficient electronically stored information (ESI) required to investigate cases involving clouds and ensuring the trustworthiness of such ESI. Based on this we propose two cloud architectures: the OCF-supported Infrastructure-as-a-Service (IaaS) cloud and the OCF-supported Storage-as-a-Service (StaaS) cloud. We validate our proposed models using a case study, which is inspired from an actual civil lawsuit.

  • A New Access Control Scheme for Protecting Distributed Cloud Services and Resources

  • Should be cited as: [ paper pdf download]

    Syed Rizvi and John Mitchell "A New Access Control Scheme for Protecting Distributed Cloud Services and Resources", Services Transactions on Cloud Computing (STCC), 4(3), 2016, pp. 28-41.

    Abstract:

    Context: Cloud computing is clearly one of today’s most dominant paradigms in the Information Technology (IT) industry due to its scalable, flexible, and cost‐efficient access to infrastructure and application services. Despite these promising facilities and benefits, cloud users have serious concerns about the data security and privacy. Among all security challenges, access control is of vital importance, since it provides security mechanisms to protect customer’s data, cloud services, applications, resources against unauthorized access, and misuse of privileges. Several access control systems have been proposed in literature lately but most of them are designed to work with one specific access control policy. In this paper, we present a novel generic access control scheme, capable to work with most of the available access control policies using a global resource management system (GRMS) to effectively handle both local and remote authentication requests. The introduction of GRMS makes our proposed architecture semi‐distributed at the expense of minimal request‐response time. We have shown the applicability of our proposed architecture using a case study for three different scenarios.

Volume 4, No 2 (April-June, 2016): [ Full Issue PDF]

  • TOWARDS A MODEL-DEFINED CLOUD-OF-CLOUDS

  • Should be cited as: [ paper pdf download]

    Bo An, Zhicheng Cui, Mauricio Tsugawa, Ying Zhang, Xuanzhe Liu, Gang Huang, Joséa. B. Fortes "TOWARDS A MODEL-DEFINED CLOUD-OF-CLOUDS ", Services Transactions on Cloud Computing (STCC), 4(2), 2016, pp. 1-14.

    Abstract:

    Context: With the growth in the number of Cloud Service Providers, many enterprises and organizations are now able to use multiple cloud platforms in order to achieve improved overall Quality-of-Service (QoS), reliability and cost efficiency. However, due to the diversity in architecture and functionalities among different cloud platforms, it is difficult to build a system that simultaneously manages multiple clouds, i.e., a cloud-of-clouds. This paper presents a model-defined approach to the development of a cloud-of-clouds management (abbreviated as CCMan) system. The runtime model of a CCMan system that meets custom management requirements is constructed through model construction, model merging and model transformation. Each step of the approach is presented in detail in terms of an example. Evaluation of the approach from several perspectives shows that the efforts needed to both develop the CCMan system and operate its services are significantly reduced with negligible performance loss.

  • KEY MANAGEMENT SERVICE: ENABLING SECURE SHARING AND DELETING OF DOCUMENTS ON PUBLIC CLOUDS

  • Should be cited as: [ paper pdf download]

    Surya Nepal, Carsten Friedrich, Catherine Wise, Richard O. Sinnott, Julian Jang-Jaccard, Shiping Chen "KEY MANAGEMENT SERVICE: ENABLING SECURE SHARING AND DELETING OF DOCUMENTS ON PUBLIC CLOUDS", Services Transactions on Cloud Computing (STCC), 4(2), 2016, pp. 15-31.

    Abstract:

    Context: The primary focus of existing secure cloud storage solutions have been on securing data both in motion and at rest. These storage solutions mostly focus on three essential properties: confidentiality, integrity and availability. However, modern enterprise applications demand data can be shared within or across organizations. The challenge is how to securely share data in public clouds using federated identities without increasing data movement and computation costs. Furthermore, the consumer should be able to delete their data in the cloud in the context of collaboration without leaving any traces behind. This problem has been addressed in recent times by utilizing or developing new data encryption techniques such as identity-based encryption, attribute-based encryption and proxy-re-encryption. However, these techniques suffer from scalability and flexibility problems when dealing with big data and support for dynamic and federated access control. This paper presents a novel architecture and corresponding protocols to provide secure sharing and deletion of documents on public cloud services: CloudDocs. This system uses AES for data encryption to achieve scalability, supports identity-based access control rules using private-public key pairs to provide flexibility, and uses independent key management services to support secure deletion, whereby the data is irrecoverable once the keys are destroyed. The key management service also supports dynamic and federated access control.

  • EVERYTHING AS A SERVICE (XAAS) ON THE CLOUD: ORIGINS, CURRENT AND FUTURE TRENDS

  • Should be cited as: [ paper pdf download]

    Yucong Duan, Qiang Duan, Xiaobing Sun, Guohua Fu, Nanjangud C. Narendra, Nianjun Zhou, Bo Hu, Zhangbing Zhou "EVERYTHING AS A SERVICE (XAAS) ON THE CLOUD: ORIGINS, CURRENT AND FUTURE TRENDS", Services Transactions on Cloud Computing (STCC), 4(2), 2016, pp. 32-45.

    Abstract:

    Context: For several years now, scientists have been proposing numerous models for defining anything "as a service (aaS)", including discussions of products, processes, data & information management, and security as a service. In this paper, based on a thorough literature survey, we investigate the vast stream of the state of the art in Everything as a Service (XaaS). We then use this investigation to explore an integrated view of XaaS that will help propose approaches for migrating applications to the cloud and exposing them as services.

Volume 4, No 1 (January-March, 2016): [ Full Issue PDF]

  • A COMPETITIVE PENALTY MODEL FOR AVAILABILITY BASED CLOUD SLA

  • Should be cited as: [ paper pdf download]

    Xiaoyong Yuan, Hongyan Tang, Ying Li, Tong Jia, Tiancheng Liu, Zhonghai Wu "A COMPETITIVE PENALTY MODEL FOR AVAILABILITY BASED CLOUD SLA", Services Transactions on Cloud Computing (STCC), 4(1), 2016, pp. 1-14.

    Abstract:

    Context: Availability is one of the most essential attributes of qualities of cloud services. Most popular public cloud services claim availability commitments with corresponding penalties in their SLAs. To gain the maximal profits, cloud providers should choose an optimal penalty strategy in the competitive cloud market. In this paper, we firstly survey availability and penalty calculation methods of cloud providers. Based on the survey, we propose a competitive penalty model and a corresponding penalty based profit maximization algorithm for cloud providers. According to the model, each cloud provider would choose the best fit penalty strategy to gain the maximal expected profit during the game procedure. The proposed model is evaluated with real data of popular cloud providers with sensitive analysis, and is valuable for cloud providers to define their penalty strategy.

  • ENHANCING CLOUD APPLICATION DEVOPS USING DYNAMICALLY TAILORED DEPLOYMENT ENGINES

  • Should be cited as: [ paper pdf download]

    Johannes Wettinger, Uwe Breitenbücher, Frank Leymann "ENHANCING CLOUD APPLICATION DEVOPS USING DYNAMICALLY TAILORED DEPLOYMENT ENGINES", Services Transactions on Cloud Computing (STCC), 4(1), 2016, pp. 15-31.

    Abstract:

    Context: and other stakeholders expect quick responses to occurring issues and feature requests. DevOps practices and Cloud computing are two key paradigms to tackle these issues by enabling rapid and continuous delivery of applications, utilizing automated software delivery pipelines. However, it is a complex and sophisticated challenge to implement such pipelines by installing, configuring, orchestrating, and integrating the required deployment automation solutions. Therefore, we present a method in conjunction with a framework and implementation to dynamically generate tailored deployment automation engines for specific application stacks, which are packaged in a portable manner to run them on various platforms and infrastructures. The core of our work is based on generating APIs for arbitrary deployment executables such as scripts and plans that perform different tasks in the automated deployment process. As a result, deployment tasks can be triggered through generated API endpoints, abstracting from lower-level, technical details of diverse deployment automation tooling. Beside a quantitative evaluation, we discuss two case studies in this context, one focusing on microservice architectures, the other one considering application functionality and its relation to deployment functionality.

  • A MODELING STRATEGY FOR CLOUD INFRASTRUCTURE PLANNING CONSIDERING PERFORMANCE AND COST REQUIREMENTS

  • Should be cited as: [ paper pdf download]

    Erica Sousa, Fernando Lins, Eduardo Tavares, Paulo Maciel "A MODELING STRATEGY FOR CLOUD INFRASTRUCTURE PLANNING CONSIDERING PERFORMANCE AND COST REQUIREMENTS", Services Transactions on Cloud Computing (STCC), 4(1), 2016, pp. 32-45.

    Abstract:

    Context: Cloud computing is a model that allows resources to be offered as services over the Internet. Due to dynamic and virtualized nature of cloud environments and diversity of client requests, providing the expected service quality while avoiding over-provisioning is not a simple task. To ensure that the provisioned service is acceptable, providers must exploit techniques and mechanisms that guarantee a minimum level of service quality. The performance evaluation of cloud infrastructures has been receiving considerable attention by providers as a prominent activity for improving service quality. This paper presents a methodology, representation models and an optimization model for cloud infrastructures planning. The proposed methodology and models aim to provide support for the planning and selection of cloud infrastructures according to performance and cost requirements. The optimization model generates cloud infrastructures with different hardware and software configurations and these infrastructures are represented using SPN and cost models. Using the proposed technique, performance metrics allows the selection of cloud infrastructures that meet the client requirements. A case study based on Eucalyptus platform is adopted to demonstrate the feasibility of the methodology and models.

Volume 3, No 4 (October-December, 2015): [ Full Issue PDF]

  • APPLICATION MIGRATION EFFORT IN THE CLOUD

  • Should be cited as: [ paper pdf download]

    Stefan Kolb, Jörg Lenhard, and Guido Wirtz "APPLICATION MIGRATION EFFORT IN THE CLOUD", Services Transactions on Cloud Computing (STCC), 3(4), 2015, pp. 1-15.

    Abstract:

    Context: Over the last years, the utilization of cloud resources has been steadily rising and an increasing number of enterprises are moving applications to the cloud. A leading trend is the adoption of Platform as a Service to support rapid application deployment. By providing a managed environment, cloud platforms take away a lot of complex configuration effort required to build scalable applications. However, application migrations to and between clouds cost development effort and open up new risks of vendor lock-in. This is problematic because frequent migrations may be necessary in the dynamic and fast changing cloud market. So far, the effort of application migration in PaaS environments and typical issues experienced in this task are hardly understood. To improve this situation, we present a cloud-to-cloud migration of a real-world application to seven representative cloud platforms. In this case study, we analyze the feasibility of the migrations in terms of portability and the effort of the migrations. We present a Dockerbased deployment system that provides the ability of isolated and reproducible measurements of deployments to platform vendors, thus enabling the comparison of platforms for a particular application. Using this system, the study identifies key problems during migrations and quantifies these differences by distinctive metrics.

  • A REST SERVICE FRAMEWORK FOR RAAS CLOUDS

  • Should be cited as: [ paper pdf download]

    Li Li, Wu Chou, and Min Luo "A REST SERVICE FRAMEWORK FOR RAAS CLOUDS", Services Transactions on Cloud Computing (STCC), 3(4), 2015, pp. 16-31.

    Abstract:

    Context: RaaS (Resource-as-a-Service) clouds represent a new market and technology driven paradigm shift from renting prebuilt virtual machines with constant capacities towards renting resources to compose elastic machines with variable capacities to better cope with unpredictable workloads. RaaS clouds differ from virtual machine (VM) based IaaS clouds in that they can offer cloud users fine-grained resources, including CPU, memory, disk and network, at short time intervals based on their demands. RaaS requires a new service layer to abstract and compose heterogeneous and dynamic fine-grained cloud resources at high frequency. This paper proposes a REST service framework consisting of Resource-Oriented Network (RON) and monadic service composition. RON abstracts heterogeneous cloud resources with uniform REST resources and it represents their dynamic relations with hypertext. Monadic service composition provides a concise functional programming language with monad to concurrently control large scale RON through dynamically generated workflows. A prototype system has been implemented based on Docker containers and Linux control groups. Our experimental results show that the approach is feasible and the performance is consistent with the client and server workloads

Volume 3, No 3 (July-September, 2015): [ Full Issue PDF]

  • METACONF: LEARNING BASED CONFIGURATION FILE DISCOVERY WITH FILE METADATA

  • Should be cited as: [ paper pdf download]

    Fan Jing Meng, Han Wang, Xuejun Zhuo, Jing Min Xu, Lin Yang, Changsheng Li "METACONF: LEARNING BASED CONFIGURATION FILE DISCOVERY WITH FILE METADATA", Services Transactions on Cloud Computing (STCC), 3(3), 2015, pp. 1-12.

    Abstract:

    Context: Discovery of configuration files is one of the prerequisite activities for a successful workload migration to the cloud. The complicated and super-sized file systems, the considerable variance of configuration files, and the multiple-presence of configuration items make configuration file discovery very difficult. Traditional approaches usually highly rely on experts to compose software specific scripts or rules to discover configuration files, which is very expensive and labor-intensive. In this paper, we propose a novel learning based approach named MetaConf to convert configuration file discovery to a supervised file classification task. We use the file metadata as learning features and learn a classifier based on these features such that it can be conducted automatically, efficiently, and independently of domain expertise. We report our evaluation with extensive and real-world case studies, and the experimental results validate that our approach is effective and outperforms the baseline method.

  • AN INVESTIGATION OF ANTICIPATED BENEFITS OF CLOUD COMPUTING ADOPTION IN AUSTRALIAN REGIONAL MUNICIPAL GOVERNMENTS

  • Should be cited as: [ paper pdf download]

    Omar Ali, Jeffrey Soar, and Jianming Yong "AN INVESTIGATION OF ANTICIPATED BENEFITS OF CLOUD COMPUTING ADOPTION IN AUSTRALIAN REGIONAL MUNICIPAL GOVERNMENTS", Services Transactions on Cloud Computing (STCC), 3(3), 2015, pp. 13-24.

    Abstract:

    Context: It is expected that computing services will increasingly be accessed as another utility a similar way to other services such as water, electricity, telephone or gas. Many organizations including government deliver their services through information and communication technology (ICT) tools including e-government. Cloud computing is a relatively new way of providing services over the internet. In this research in-depth interviews of Australian councils’ IT managers were conducted with the aim of providing insights into the perceived benefits of cloud computing adoption. Also, survey data from 480 IT staff across 47 local councils were collected to confirm the findings of the exploratory stage. The research indicated that cloud computing is seen to offer many benefits that are identified in the research literature; additional anticipated benefits emerged which related to reduced level of risk, remote access, reduce staff, and time efficiencies. The findings of this research may help IT managers and top management evaluate possible adoption by increasing their understanding about anticipated benefit which will encourage them when planning or decided to adopt cloud computing.

  • TOWARDS SEMANTIC-BASED CLOUD APPLICATION MANAGEMENT

  • Should be cited as: [ paper pdf download]

    Kyriakos Kritikos and Dimitris Plexousakis "TOWARDS SEMANTIC-BASED CLOUD APPLICATION MANAGEMENT", Services Transactions on Cloud Computing (STCC), 3(3), 2015, pp. 25-40.

    Abstract:

    Context: Cloud computing promises to transform applications and services on the web into elastic and fault-tolerant software. To aid at this target, various research prototypes and products have been already proposed. However, especially with respect to the design phase of cloud-based applications, such prototypes do not enable the appropriate composition of cloud services at different levels to realise not only the functionality but also the underlying infrastructure support for such applications. Moreover, most existing prototypes and products lack the appropriate semantics to guarantee that the respective design product is the most suitable and accurate one according to the various types of user requirements posed. To this end, this article proposes a semantic cloud application management framework that addresses the aforementioned issues by relying on ontologies to semantically describe cloud service capabilities and application requirements, on semantic cloud service matchmakers considering both functional and non-functional aspects as well as on a novel cloud service composition approach which is able to perform concurrently service concretisation and deployment plan reasoning, thus catering for the different levels involved in a cloud environment and their respective dependencies by also satisfying all types of user requirements posed. The service composition approach is experimentally evaluated deriving quite promising results indicating that the state-of-the-art is advanced.

Volume 3, No 2 (April - June, 2015): [ Full Issue PDF]

  • A CLOUD-BASED XML PUBLISH/SUBSCRIBE SERVICE

  • Should be cited as: [ paper pdf download]

    Chung-Horng Lung, Yang Cao, Mohammed Sanaullah, Shikharesh Majumdar "A CLOUD-BASED XML PUBLISH/SUBSCRIBE SERVICE", Services Transactions on Cloud Computing (STCC), 3(2), 2015, pp. 1-11.

    Abstract:

    Context: XML message filtering and routing have been recognized as a standard for data exchange for XML dissemination services. These services are often realized using the Publish/Subscribe (pub/sub) model which is commonly used for various web-based systems. The conventional XML filtering and forwarding technique is an application-layer multicast approach that relies on XML-capable brokers that are built above the network layer for message dissemination. Such an overlay model introduces a great deal of overhead in terms of initial deployment and subsequent operational cost for those XML-capable brokers that are typically supported by geographically distributed Internet Service Providers (ISPs). This paper proposes an approach to the deployment of the XML pub/sub systems over the cloud without the need of any special arrangements of physical brokers across the networks or ISPs). In addition, changes to the software deployed in the cloud can be made directly and easily by the XML pub/sub service provider. The paper describes experiments that use both Amazon and Google clouds for rapid XML pub/sub deployment. In addition, the paper presents a performance comparison between the conventional XML multicast model and the cross-layer model deployed over the cloud.

  • WEBCLOUDSIM: AN OPEN ONLINE CLOUD COMPUTING SIMULATION TOOL FOR ALGORITHM COMPARISON

  • Should be cited as: [ paper pdf download]

    Youqi Chen, Qibo Sun, Ao Zhou, Shangguang Wang "WEBCLOUDSIM: AN OPEN ONLINE CLOUD COMPUTING SIMULATION TOOL FOR ALGORITHM COMPARISON", Services Transactions on Cloud Computing (STCC), 3(2), 2015, pp. 26-32.

    Abstract:

    Comparatively evaluating cloud computing algorithms via credible simulation tools is desirable by many contemporary cloud service researchers and practitioners in terms of cost efficiency and effectiveness. Common cloud computing simulation tools need nontrivial improvements in extensibility, usability, and/or manageability. Aiming to facilitate developing, analyzing and comparing advanced cloud computing algorithms, we have developed the simulation tool WebCloudSim, which is built via open source code and can be accessed for free at http://webcloudsim.org via a web browser. Under the browser-server deployment model, WebCloudSim supports custom settings of target cloud datacenters. It is easy for a WebCloudSim user to configure a specific cloud datacenter environment for several algorithms under evaluation, and to exploit the comparative analysis data and charts that the tool generates automatically. This paper presents design, implementation and usage of the WebCloudSim tool with real use cases.

Volume 3, No 1 (January - March, 2015): [ Full Issue PDF]

  • CELLCLOUD: TOWARDS A COST EFFECTIVE FORMATION OF MOBILE CLOUD BASED ON BIDDING INCENTIVE

  • Should be cited as: [ paper pdf download]

    Shahid A. Noor, Ragib Hasan, Md Haque "CELLCLOUD: TOWARDS A COST EFFECTIVE FORMATION OF MOBILE CLOUD BASED ON BIDDING INCENTIVE", Services Transactions on Cloud Computing (STCC), 3(1), 2015, pp. 1-15.

    Abstract:

    Context: In recent years, cloud computing has become one of the most dominant computing paradigms. Researchers have explored the possibility of building clouds out of loosely associated mobile computing devices. However, most such efforts failed due to the lack of a proper incentive model for the mobile device owners. In this paper, we propose CellCloud — a practical mobile cloud architecture, which can be easily deployed on existing cellular phone network infrastructures. CellCloud is based on a novel reputation-based economic incentive model in order to compensate the mobile device owners for the use of their phones as cloud computing nodes. CellCloud offers a practical model for performing cloud operations, with lower costs compared to a traditional cloud. We provide an elaborate analysis of the model with security and economic incentives as the major focus. Along with presenting a cost equation model, we perform extensive simulations to evaluate the performance and also analyze the feasibility of our proposed model. Our simulation results show that CellCloud creates a win-win scenario for all three stakeholders (client, cloud provider, and mobile device owners) to ensure the formation of a successful mobile cloud architecture.

  • END-TO-END BIG DATA PROCESSING PROTECTION IN CLOUD ENVIRONMENT USING BLACK BOXES - AN FPGA APPROACH

  • Should be cited as: [ paper pdf download]

    Lei Xu, Khoa Dang Pham, Hanyee Kim, Weidong Shi, and Taeweon Suh "BOOSTING METRICS: MEASURING CLOUD SERVICES FROM THE HOLISTIC PERSPECTIVE", Services Transactions on Cloud Computing (STCC), 3(1), 2015, pp. 16-29.

    Abstract:

    Privacy is one of the critical concerns that hinders the adoption of public cloud. For simple application, like storage, encryption can be used to protect user's data. But for outsourced data processing, i.e., big data processing with MapReduce framework, there is no satisfying solution. Users have to trust the cloud service providers that they will not leak users' data. We propose adding black boxes to the public cloud for critical computation, which are tamper resistant to most adversaries. Specifically, FPGAs are deployed in the public cloud environment as black boxes for privacy preserving computation, and proxy re-encryption is used to support dynamic job scheduling on different FPGAs. In FPGA cloud, cloud is not necessarily fully trusted, and during outsourced computation, user's data is protected by a data encryption key only accessible by trusted FPGA devices. As an important application of cloud computing, we apply FPGA cloud to the popular MapReduce programming model and extend the FPGA based MapReduce pipeline with privacy protection capabilities. Finally, we conduct experiments and evaluation for k-NN with FPGA cloud, which is an important MapReduce application. The experimental results show the practicality of FPGA cloud.

  • LEARNING-BASED HIGH-THROUGHPUT DISPATCHING FOR TRAJECTORY STREAMS

  • Should be cited as: [ paper pdf download]

    Xin Zhang, Guoqiang Hu, Ning Duan, Peng Gao, Weishan Dong,Jun Zhu, Rong Chang "LEARNING-BASED HIGH-THROUGHPUT DISPATCHING FOR TRAJECTORY STREAMS", Services Transactions on Cloud Computing (STCC), 3(1), 2015, pp.30-44.

    Abstract:

    With the development of Internet-of-Things (IoT) technologies, large-volume sensor data streams are sent to cloud in near real-time which raise an important requirement for high performance sensor big data analytics. This paper focuses on the scalability challenges for analyzing large-volume mobile data streams, as mobile data streams convey valuable spatio-temporal information (termed as trajectory or semantic trajectory). A framework for high performance trajectory streams processing is proposed together with a learning method for workload assignment optimization and a dispatching method for high-throughput geo-message dispatching. By taking the spatial connectivity implied by trajectory streams into consideration, a trajectory preserving partitioning method is proposed for improving the quality of geo- partitioning. Based on the optimized geo-partitioning, a novel Geohash Tree based dispatching method is developed for achieving high-throughput geo-message dispatching. Via mobility localization formalism, we demonstrate that an implementation of our geo-spatial partition algorithms could balance workload and minimize cross-node communication. And experimental evaluations using real world and simulated data also validate the performance of the proposed methods.

Volume 2, No 4 (October - December, 2014): [ Full Issue PDF]

  • RESEARCH GAPS AND TRENDS IN CLOUD COMPUTING: A SYSTEMATIC MAPPING STUDY

  • Should be cited as: [ paper pdf download] [ Appendix: CLOUD 2009-2014 Topic Categories]

    Liping Zhao, Liang-Jie Zhang, Tina X. O. Liu "RESEARCH GAPS AND TRENDS IN CLOUD COMPUTING: A SYSTEMATIC MAPPING STUDY", International Journal of Cloud Computing (IJCC), 2(4), 2014, pp. 1-11.

    Abstract:

    Context: Since 2009 a large number of papers have been presented at IEEE International Conference on Cloud Computing (CLOUD). Studying these papers and identifying relevant research areas from them are both difficult and time consuming. Objective: To address this problem, we aim to provide a structure to the entire collection of fulllength papers published in the proceedings of the past CLOUD conferences (from CLOUD 2009 to CLOUD 2014). Method: We undertake a Systematic Mapping study of these papers by categorizing them. Results: 523 relevant papers are selected and assessed in terms of their research topic, contribution and research type. Thematic and frequency analysis is then conducted to identify research gaps and trends. Conclusions: By research topic, technology oriented papers extensively outnumbered business oriented papers. By contribution, methods significantly outstripped other types of contribution whereas there is a desperate shortage of contribution from practical experience. By research type, empirical research papers have dominated the past six CLOUD conferences whereas theoretical research is close to none.

  • BOOSTING METRICS: MEASURING CLOUD SERVICES FROM THE HOLISTIC PERSPECTIVE

  • Should be cited as: [ paper pdf download]

    Zheng Li, Liam O’Brien, and He Zhang "BOOSTING METRICS: MEASURING CLOUD SERVICES FROM THE HOLISTIC PERSPECTIVE", International Journal of Cloud Computing (IJCC), 2(4), 2014, pp. 12-22.

    Abstract:

    Studies have shown that Cloud services evaluation would be crucial and beneficial for both service customers and providers, and metrics would play a vital role in any evaluation implementation. Considering the numerous and various aspects of Cloud services, a frequent suggestion is to perform evaluation from a holistic view. The currently normal strategy of holistic evaluation is to use a set of metrics along with a suite of benchmarks to conduct separated experiments. Given the separated, diverse, and even possibly conflicting measurement criteria, it could be still hard for customers with such evaluation reports to understand an evaluated Cloud service from a global perspective. Inspired by the boosting approaches to machine learning, we proposed the concept Boosting Metrics to represent all the potential approaches that are able to deliver summary measurement of Cloud services. Essentially, the idea of boosting metrics is to holistically measure Cloud services with concern of service properties, which supplements the strategy of employing benchmark suites that is to holistically evaluate Cloud services with concern of different workloads. This paper introduces two types of preliminary approaches, and unifies a set of sophisticated measurements into the notion of boosting metrics. In particular, we show that boosting metrics can be used as a summary Response for applying experimental design to Cloud services evaluation. Although the concept BoostingMetrics was refined based on our work in the Cloud Computing domain, we believe it can be easily adapted to the evaluation work of other computing paradigms.

  • A SLA VIOLATION DEGREE-AWARE CLOUD SERVICE EVALUATION APPROACH BASED ON HISTORICAL RECORDS

  • Should be cited as: [ paper pdf download]

    Lianyong Qi, Wanchun Dou1, Xuyun Zhang, Yuming Zhou "A SLA VIOLATION DEGREE-AWARE CLOUD SERVICE EVALUATION APPROACH BASED ON HISTORICAL RECORDS", International Journal of Cloud Computing (IJCC), 2(4), 2014, pp.23-33.

    Abstract:

    Cloud computing has provided a flexible and cost-effective resource provision manner to the public. From the perspective of cloud users, it is necessary to evaluate the cloud service’s quality based on the service’s historical execution records. However, the traditional evaluation approaches often assume that cloud service’s historical quality is a fixed quality value (i.e., quality point), while neglects the long-term running characteristic of cloud service and the unpredictability of network environment, as well as the resulted fluctuant service quality (i.e., quality curve); this may decrease the completeness of cloud service evaluation. Besides, the traditional SLA (Service Level Agreement) contract manner only considers whether the agreed SLA is violated, while neglects the SLA violation degree, which may be unfair to cloud service providers. In views of the above two challenges, a SLA violation degree-aware cloud service evaluation approach Vio_degree_eva is put forward in this paper. Vio_degree_eva not only considers two kinds of historical records (i.e., quality point and quality curve), but also includes SLA violation degree in cloud service evaluation, so as to make the evaluation more reasonable. Finally, through a set of experiments, we validate the feasibility of our proposal.

  • INCIDENT NOTIFICATION PROCESS AS BPAAS FOR ELECTRICITY SUPPLY SYSTEMS

  • Should be cited as: [ paper pdf download]

    Lai Xu, Paul de Vrieze, and Nan Jiang "INCIDENT NOTIFICATION PROCESS AS BPAAS FOR ELECTRICITY SUPPLY SYSTEMS", International Journal of Cloud Computing (IJCC), 2(4), 2014, pp.34-44.

    Abstract:

    Business Process Management (BPM) systems have been deployed in many large organizations to improve their business effectiveness and efficiency. Cloud based BPM systems have provided SMEs using BPM in a pay-per-use manner. Previous work has focused on looking at cloud based BPM from the perspectives of distribution of data, activity or/and business engine and related issues, such as scalability of system, security of data, distribution of data and activities. To achieve business agility business process collaboration needs to seamlessly connect local BPM systems and cloud based BPM systems. In this paper we look at BPM in the cloud from a new user perspective, how process models can be handled in the cloud for the fast pace of change of business collaborations. The paper proposes a distribution solution in which at the design time, the shared process model can be discovered from a process repository, and adapted to local needs; at run-time a process is distributed. A real world case is used to explain our design and implementation. Collaborative process for incident notifications is built to work across different organizations.

Volume 2, No 3 (July - September, 2014): [ Full Issue PDF]

  • TOWARDS A CLOUD-BASED APPROACH FOR SPAM URL DEDUPLICATION FOR BIG DATASETS

  • Should be cited as: [ paper pdf download]

    Shams Zawoad, Ragib Hasan, Gary Warner, Md Munirul Haque "TOWARDS A CLOUD-BASED APPROACH FOR SPAM URL DEDUPLICATION FOR BIG DATASETS ", International Journal of Cloud Computing (IJCC), 2(3), 2014, pp. 1-14.

    Abstract:

    Spam emails are often used to advertise phishing websites and lure users to visit such sites. URL blacklisting is a widely used technique for blocking malicious phishing websites. To prepare an effective blacklist, it is necessary to analyze possible threats and include the identified malicious sites in the blacklist. However, the number of URLs acquired from spam emails is quite large. Fetching and analyzing the content of this large number of websites are very expensive tasks given limited computing and storage resources. To solve the problem of massive computing and storage resource requirements, we need a highly distributed and scalable architecture, where we can provision additional resources to fetch and analyze on the fly. Moreover, there is a high degree of redundancy in the URLs extracted from spam emails, where more than one spam emails contain the same URL. Hence, preserving the contents of all the websites causes significant storage waste. Additionally, fetching content from a fixed IP address introduces the possibility of being reversed blacklisted by malicious websites. In this paper, we propose and develop CURLA – a Cloud-based spam URL Analyzer, built on top of Amazon Elastic Computer Cloud (EC2) and Amazon Simple Queue Service (SQS). CURLA allows deduplicating large number of spam-based URLs in parallel, which reduces the cost of establishing equally capable local infrastructure. Our system builds a database of unique spam-based URL and accumulates the content of these unique websites in a central repository. This database and website repository will be a great resource to identify phishing websites and other counterfeit websites. We show the effectiveness of our architecture using real-life, large-scale spam-based URL data.

  • END-TO-END BIG DATA PROCESSING PROTECTION IN CLOUD ENVIRONMENT USING BLACK BOXES - AN FPGA APPROACH

  • Should be cited as: [ paper pdf download]

    Lei Xu, Khoa Dang Pham, Hanyee Kim, Weidong Shi,Taeweon Suh"END-TO-END BIG DATA PROCESSING PROTECTION IN CLOUD ENVIRONMENT USING BLACK BOXES - AN FPGA APPROACH ", International Journal of Cloud Computing (IJCC), 2(3), 2014, pp. 14-27.

    Abstract:

    Privacy is one of the critical concerns that hinders the adoption of public cloud. For simple application, like storage, encryption can be used to protect user's data. But for outsourced data processing, i.e., big data processing with MapReduce framework, there is no satisfying solution. Users have to trust the cloud service providers that they will not leak users' data. We propose adding black boxes to the public cloud for critical computation, which are tamper resistant to most adversaries. Specifically, FPGAs are deployed in the public cloud environment as black boxes for privacy preserving computation, and proxy re-encryption is used to support dynamic job scheduling on different FPGAs. In FPGA cloud, cloud is not necessarily fully trusted, and during outsourced computation, user's data is protected by a data encryption key only accessible by trusted FPGA devices. As an important application of cloud computing, we apply FPGA cloud to the popular MapReduce programming model and extend the FPGA based MapReduce pipeline with privacy protection capabilities. Finally, we conduct experiments and evaluation for k-NN with FPGA cloud, which is an important MapReduce application. The experimental results show the practicality of FPGA cloud.

  • AN OPEN STANDARDS-BASED FRAMEWORK INTEGRATING IMS AND CLOUD COMPUTING

  • Should be cited as: [ paper pdf download]

    Wei Zhang, Weimin Lei, Xiao Chen and Shaowei Liu"AN OPEN STANDARDS-BASED FRAMEWORK INTEGRATING IMS AND CLOUD COMPUTING ", International Journal of Cloud Computing (IJCC), 2(3), 2014, pp.28-40.

    Abstract:

    As typical Internet-based applications, cloud computing services cannot guarantee the Quality of Service (QoS), which has actually become technical barriers for cloud service providers to overcome. On the other hand, as the core signaling architecture of Next Generation Networking (NGN), IP Multimedia Subsystem (IMS) is facing the problem of the lack of innovative value-added services. This paper presents an open standards-based framework to integrate IMS and cloud computing. In the target framework, cloud services are regarded as the general IMS applications and then cloud clients are allowed to access cloud services under the control of Session Initiation Protocol (SIP) signaling and QoS mechanism of IMS. This paper highlights the benefits of such integration, introduces architecture overview and cloud service relevant functional components, and mainly discusses several key issues including cloud notification mechanism, standard cloud interface protocol, QoS and charging control of IMS cloud computing services. The work in this paper provides a reference for integrating IMS and cloud computing.

  • MOVING TARGET WITH LOAD BALANCING IN A HIERARCHICAL CLOUD

  • Should be cited as: [ paper pdf download]

    Hong Liu, Johnson Thomas and Praveen Khethavath"MOVING TARGET WITH LOAD BALANCING IN A HIERARCHICAL CLOUD ", International Journal of Cloud Computing (IJCC), 2(3), 2014, pp.41-51.

    Abstract:

    In this paper we propose a ‘moving target’ security mechanism for a P2P cloud where files are partitioned and sensitive sections are moved at different times without modifying the routing or finger tables, to reduce the risk of the file being compromised. Two drawbacks with this approach are the problem of determining the locality of the data and load unbalancing. We present a hierarchical P2P cloud system that leads to scalability and efficiency. A 3-step load balancing scheme for hierarchical P2P cloud system to globally balance the network is proposed. Our simulation results show that our algorithm is effective in achieving load balancing in hierarchical peer-to-peer cloud systems. Keywords: moving target; load balancing; cloud.

Volume 2, No 2 (April-June, 2014): [ Full Issue PDF]

  • CLOUD ATLAS: A SOFTWARE DEFINED NETWORKING ABSTRACTION FOR CLOUD TO WAN VIRTUAL NETWORKING

  • Should be cited as: [ paper pdf download]

    Stephan Baucke, Racha Ben Ali, James Kempf "Cloud Atlas: A Software Defined Networking Abstraction For Cloud To Wan Virtual Networking ", International Journal of Cloud Computing (IJCC), 2(2), 2014, pp. 1-14.

    Abstract:

    One of the key principles of Software Defined Networking (SDN) is to represent networks as a collection of usable abstractions implemented as an API. Application of this principle has advanced furthest in cloud computing. The OpenStack Quantum network service provides tenants in a data center with an abstraction of an enterprise LAN. The Quantum API implements a virtual network through a plug-in that adapts the API to the physical network. However, existing OpenStack support for wide area connectivity is generally restricted, and does not support Quality of Service (QoS). In this paper, we present Cloud Atlas, a SDN abstraction and API extending the Quantum virtual network into the WAN. Cloud Atlas is built on top of existing WAN network services (L1-, L2, and L3VPNs) that do support QoS. Cloud Atlas makes these services available to OpenStack through a tight integration with Quantum. We discuss two prototypes we have built of Cloud Atlas, one based on command line scripts and one based on a network management system, and a prototype VM snapshotting service. We conclude the paper with some observations on applying the cloud service model to networking and the value of SDN abstractions in supporting such a service model.

  • MAXIMIZING PERFORMANCE OF CO-LOCATED APPLICATIONS: EXPERIENCES AND STRATEGIES WHEN CO-LOCATING MULTIPLE JAVA APPLICATIONS ON A SINGLE PLATFORM

  • Should be cited as: [ paper pdf download]

    Zhenyun Zhuang, Cuong Tran, Haricharan Ramachandra, Badri Sridharan "Maximizing Performance of Co-located Applications: Experiences and Strategies when Co-locating Multiple Java Applications on a Single Platform ", International Journal of Cloud Computing (IJCC), 2(2), 2014, pp. 15-27.

    Abstract:

    Cloud (e.g., PaaS) Computing promises a cost-effective and administration-effective solution to the needs of sharing computing resources. A widely practiced cloud deployment model is to co-locate multiple applications on a single platform. While bringing efficiency to the users thanks to the shared hardware and software, the multi-tenancy characteristics also bring unique challenges to the backend platforms. In particular, the JVM mechanisms used by Java applications, coupled with OS-level features (e.g., THP), give rise to a set of problems that are not present in other deployment scenarios. In this work, we consider the problem of maximizing performance of co-located mission-critical Java applications when deploying multiple Java applications on a single platform. Based on our experiences with LinkedIn’s platforms, we identify and solve a set of problems caused by such multi-tenancy deployment. We share the lessons and knowledge we learned during the course // An earlier version of this paper was accepted in the conference of IEEE Cloud 2014 (Alaska, AL, USA) // Conference paper title: " Optimizing JMS Performance for Cloud-based Application Servers" // The differences between the conference paper and this draft are listed at the end of the draft.

  • CLOUD COMPUTING FRAMEWORK FOR AGILE DEVELOPMENT

  • Should be cited as: [ paper pdf download]

    Gardner Mwansa,Ernest Mnkandla"Cloud Computing Framework For Agile Development ", International Journal of Cloud Computing (IJCC), 2(2), 2014, pp. 28-43.

    Abstract:

    The emergence of cloud computing is influencing how businesses develop, re-engineer, and implement critical software applications. The cloud requires developers to elevate the importance of compliance with security policies, regulations and internal engineering standards in their software development life cycles. Cloud computing and agile development methodologies are new technologies that have come with new approaches in the way computing services are provisioned and development of quality software respectively. However, the synergy between the two is bonded with technical and non-technical challenges. In this paper, a conceptual framework is proposed to support the process of migration of South African small, medium and micro enterprises (SMMEs) who are using agile software development methodologies to cloud computing environment. The framework is also analysed based on critical cloud computing adoption factors as recommended from previous studies on SMMEs adoption practices.

  • A CLOUD-FEDERATION-ORIENTED MECHANISM OF COMPUTING RESOURCE MANAGEMENT

  • Should be cited as: [ paper pdf download]

    Haopeng Chen, Wenyun Dai, Wenting Wang, Xi Chen, Yisheng Wang"A Cloud-Federation-Oriented Mechanism Of Computing Resource Management ", International Journal of Cloud Computing (IJCC), 2(2), 2014, pp. 44-58.

    Abstract:

    As the cloud of clouds, cloud federation, sometimes called as inter-cloud, provides a feasible and attractive kind of infrastructure to the cloud applications which want to obtain high performance, availability or profit. Meanwhile, the cloud providers also may consider that cloud federation is an ideal form to manage their computing resource since it can improve the utilization of their computing resources and extend the computing power of an individual provider. This paper classifies the cloud federations into different models according to their structure and control modes, including vertical, horizontal and hybrid federation, autonomous and centralized controlled federation. A design of the framework of multi-objective constrained resource management for cloud federation is proposed based on the analysis of the common objectives of such a framework, including dynamic profit-driven provisioning, availability-aware placement and power-saved consolidation. The result of our simulation has demonstrated the feasibility and effectiveness of the proposed framework.

Volume 2, No 1 (January-March, 2014): [ Full Issue PDF]

  • ON THE FINANCIFICATION OF CLOUD COMPUTING: AN AGENDA FOR PRICING AND SERVICE DELIVERY MECHANISM DESIGN RESEARCH

  • Should be cited as: [ paper pdf download]

    Robert J. Kauffman, Dan Ma, Richard Shang, Jianhui Huang,Yinping Yang, "ON THE FINANCIFICATION OF CLOUD COMPUTING: AN AGENDA FOR PRICING AND SERVICE DELIVERY MECHANISM DESIGN RESEARCH ", International Journal of Cloud Computing (IJCC), 2(1), 2014, pp. 1-14.

    Abstract:

    Pricing approaches to cloud computing services balance risks and interests between vendor and client, and optimize supply and consumption in terms of cost, uncertainty and economic efficiency. They also leverage the benefits of various services delivery mechanisms for reserved, on-demand, spot-price, and re-sold services in markets that have learned how to transact in full contracts and services instances. This is like a financial market: with services supply and demand, and opportunities to supply and purchase services with spot prices, or to sell or buy contracts for the delivery of future services. Our research suggests that the financification of the cloud computing services market represents a fundamental shift from the traditional model of software sales and large contracts outsourced to services vendors, to short-term contracts and computing capacity provision mechanism designs that are evolving similar to financial markets. We develop this perspective to explain the cloud vendor market, the provision of services, and the ways in which the financification of cloud computing will shape future offerings and the structure of the market. We see these changes in the market in the many ways that vendors offer cloud services of high value to organizations, while making more profitable business models possible.

  • IMPACTS OF MULTI-CLASS OVERSUBSCRIPTION ON REVENUES AND PERFORMANCE IN THE CLOUD

  • Should be cited as: [ paper pdf download]

    Rachel A. Householder, Robert C. Green "IMPACTS OF MULTI-CLASS OVERSUBSCRIPTION ON REVENUES AND PERFORMANCE IN THE CLOUD ", International Journal of Cloud Computing (IJCC), 2(1), 2014, pp. 15-30.

    Abstract:

    Rising trends in the number of customers turning to the cloud for their computing needs has made effective resource allocation imperative for cloud service providers. In order to maximize profits and reduce waste, providers have started to explore the role of oversubscribing cloud resources. However, the benefits of oversubscription in the cloud are not without inherent risks. This work attempts to unveil the different incentives, risks, and techniques behind oversubscription in a cloud infrastructure. The discrete event simulator CloudSim is used to compare the generated revenue and performance of oversubscribed and non-oversubscribed datacenters. The idea of multi-class service levels used in other overbooked industries is implemented in simulations modeling a priority class of VMs that pay a higher price for better performance. Three simulations are implemented. The first two compare the results of different VM allocation policies without VM migration. The third implements VM migration in an oversubscribed, power-aware datacenter. Results show that oversubscription using multi-class service levels has the potential to increase datacenter revenue, but the benefit comes with the risk of degraded QoS, especially for non-priority customers.

  • A BROKER BASED CONSUMPTION MECHANISM FOR SOCIAL CLOUDS

  • Should be cited as: [ paper pdf download]

    Ioan Petri, Magdalena Punceva, Omer F. Rana, George Theodorakopoulos,Yacine Rezgui "A BROKER BASED CONSUMPTION MECHANISM FOR SOCIAL CLOUDS ", International Journal of Cloud Computing (IJCC), 2(1), 2014, pp. 31-43.

    Abstract:

    The new consumption without ownership paradigm is leading towards a “rental economy” where people can now rent and use various services from third-parties within a market of “shared” resources. The elimination of ownership has increased the marginal utility of consumption and reduced the risks associated with permanent ownership. In the absence of ownership the consumption in the global marketplace has become more dynamic and has positively impacted various economic and social sectors. The concept of “consumption without ownership” can also be used in the area of cloud computing where the interaction between clients and providers generally involves the use of data storage and computational resources. Although a number of commercial providers are currently on the market, it is often beneficial for a user to consider capability from a number of different ones. This would prevent vendor lock-in and more economic choice for a user. Based on this observation, work on “Social Clouds” has involved using social relationships formed between individuals and institutions to establish Peer-2-Peer resource sharing networks, enabling market forces to determine how demand for resources can be met by a number of different (often individually owned) providers. In this paper we identify how trading and consumption within such a network could be enhanced by the dynamic emergence (or identification) of brokers – based on their social position in the network (based on connectivity metrics within a social network). We investigate how offering financial incentives to such brokers, once discovered, could help improve the number of trades that could take place with a network, thereby increasing consumption. A social score algorithm is described and simulated with PeerSim to validate our approach. We also compare the approach to a distributed dominating set algorithm – the closest approximation to our approach.

Volume 1, No 2 (October - December, 2013): [ Full Issue PDF]

  • Cost-Driven Optimization of Cloud Resource Allocation for Elastic Processes

  • Should be cited as: [ paper pdf download]

    Stefan Schulte, Philipp Hoenisch, Schahram Dustdar, Dieter Schuller, Ulrich Lampe, and Ralf Steinmetz, "Cost-Driven Optimization of Cloud Resource Allocation for Elastic Processes", International Journal of Cloud Computing (IJCC), 1(2), 2013, pp. 1-14.

    Abstract:

    Today's extensive business process landscapes make it necessary to handle the execution of a large number of business processes and individual process steps. Especially if process steps require the invocation of resource‐intensive applications or a large number of applications need to be executed concurrently, process owners may have to allocate extensive computational resources, leading to high fixed cost. In the work at hand, we propose an alternative to the provision of fixed resources, based on automatic leasing and releasing of Cloud‐based computational resources. For this, we present an integrated approach which addresses the cost‐driven optimization of Cloud‐based computational resources for business processes in order to realize so‐called Elastic Processes. Through an evaluation, we show the practical applicability and benefits of our contributions. Specifically, we find that our approach substantially reduces the cost compared to an ad hoc approach.

  • Recommending Optimal Cloud Configuration based on Benchmarking in Black‐Box Clouds

  • Should be cited as: [ paper pdf download]

    Gueyoung Jung, Naveen Sharma, Tridib Mukherjee, Frank Goetz, and Julien Bourdaillet, "Recommending Optimal Cloud Configuration based on Benchmarking in Black‐Box Clouds", International Journal of Cloud Computing (IJCC), 1(2), 2013, pp. 15-27.

    Abstract:

    This paper focuses on recommending optimal cloud configuration for deploying complex user workloads. Such recommendation has become imperative in recent times for cloud users to reduce complexity in selecting a configuration. The number of different configuration options has increased many‐fold due to the proliferation of cloud providers and different non‐standardized offerings from these providers. Furthermore, the performance and price implications are unknown beforehand, when a cloud user deploys her workload into these different configurations. The problem gets exacerbated since cloud providers generally keep the underlying infrastructures and technologies non‐transparent to users. In this paper, we present (i) a benchmark‐based modeling approach to accurately estimate the performance of workloads on target black‐box cloud configurations; and (ii) a search algorithm that first generates a capability vector consisting of relative performance scores of resource types (e.g., CPU, memory, and disk) for each configuration and then, identifies a near optimal cloud configuration based on the capability vectors. Experiments show that our approach accurately estimates the performance capability, and performs efficient search for the near optimal cloud configuration that has the minimum price while meeting the throughput goal.

  • TAMING THE UNCERTAINTY OF PUBLIC CLOUDS

  • Should be cited as: [ paper pdf download]

    Maxim Schnjakin and Christoph Meinel, "Taming the Uncertainty of Public Clouds“, International Journal of Cloud Computing (IJCC), 1(2), 2013, pp. 28-47.

    Abstract:

    Public cloud storage services enable organizations to manage data with low operational expenses. However, the benefits come along with challenges and open issues such as security, reliability, performance unpredictability and the risk to become dependent on a provider for its service. In our work, we presented a system that improves availability, confidentiality and reliability of data stored in the cloud. To achieve this objective, we encrypt user’s data and make use of the RAID technology principle to manage data distribution across cloud storage providers. Recently, we conducted a proof-of-concept experiment for our application to evaluate the performance and cost effectiveness of our approach. We deployed our application using eight commercial cloud storage repositories in different countries. We observed that our implementation improved the perceived availability and, in most cases, the overall performance when compared with cloud providers individually. We also observed a general trend that cloud storage providers have constant throughput values - whereby the individual throughput performance differs strongly from one provider to another. With this, the experienced transmissions can be utilized to increase the throughput performance of the upcoming data transfers. The aim is to distribute the data across providers according to their capabilities utilizing the maximum of the available throughput capacity. To assess the feasibility of the approach we have to understand how providers handle high simultaneous data transfers. Thus, we put an additional focus on the performance and the scalability evaluation of those cloud storage providers, which are supported by our application.

  • Cloud Standby System and Quality Model

  • Should be cited as: [ paper pdf download]

    Alexander Lenk and Frank Pallas, "Cloud Standby System and Quality Model", International Journal of Cloud Computing (IJCC), 1(2), 2013, pp. 48-59.

    Abstract:

    Contingency plans for disaster preparedness and concepts for resuming regular operation as quickly as possible have been an integral part of running a company for decades. Today, large portions of revenue generation are taking place over the Internet and it has to be ensured that the respective resources and processes are secured against disasters, too. Cloud‐Standby‐Systems are a way for replicating an IT infrastructure to the Cloud. In this work, the Cloud Standby approach and a Markov‐based model is presented that can be used to analyze and configure Cloud Standby systems on a long term basis. It is shown that by using a Cloud‐Standby‐System the availability can be increased, how configuration parameters like the replication interval can be optimized, and that the model can be used for supporting the decision whether the infrastructure should be replicated or not.

  • Efficient Private Cloud Operation using Proactive Management Service

  • Should be cited as: [ paper pdf download]

    Dapeng Dong and John Herbert, "Efficient Private Cloud Operation using Proactive Management Service", International Journal of Cloud Computing (IJCC), 1(2), 2013, pp. 60-71.

    Abstract:

    Operation management for a private cloud infrastructure faces many challenges including efficient resource allocation, load‐balancing, and quick response to real-time workload changes. Traditional manual IT operation management is inadequate for this highly dynamic and complex environment. This work presents a distributed service architecture which is designed to provide an automated, shared, and off‐site operation management service for private clouds. The service architecture incorporates important concepts such as: Metric Templates for minimising the network overhead for transmission of cloud metrics; a Cloud Projection that provides a global view of the current status and structure of the cloud, supporting optimal decision making; and a Calendar‐based Data Storage Model to reduce the storage required for cloud metric data and increase analysis performance. A proactive response to cloud events is generated based on statistical analysis of historical metrics and predicted usage. The architecture, functional components, and operation management strategies are described. A prototype implementation of the proposed architecture was deployed as a service on the IBM SmartCloud. The effectiveness and usability of the proposed proactive operation management solution has been comprehensively evaluated using a simulated private cloud with dynamic and real‐world workloa.

Volume 1, No 1 (July - September, 2013): [ Full Issue PDF]

  • QoS-Based Resource Allocation Framework for Multi-Domain SLA Management in Clouds

    [ paper pdf download]

  • Should be cited as:

    Kuan Lu, Ramin Yahyapour, Philipp Wieder, Constantinos Kotsokalis, Edwin Yaqub, Ali Imran Jehangiri, "QoS-Based Resource Allocation Framework for Multi-Domain SLA Management in Clouds ", International Journal of Cloud Computing (IJCC), 1(1), 2013, pp. 1-12.

    Abstract:

    In clouds, current virtualization technologies of IaaS enable the live migration of running VMs to achieve load balancing, fault‐tolerance and hardware consolidation in data centers. However, the downtime / service unavailability due to live migration may be substantial with relevance to the customers’ expectations on responsiveness, as the latter are declared in established SLAs, which define all relevant aspects of the services between service provider and customer. Moreover, the service unavailability may cause significant (potentially exponential) SLA violation penalties to its associated higher-level domains (e.g., PaaS and SaaS). Therefore, in order to deliver high availability service, VM live migration should be arranged and managed carefully. In this paper, we present the OpenStack version of Generic SLA Manager, alongside its strategies for VM selection and allocation during live migration of VMs. Based on the proposed autonomous SLA violation-filtering framework, we simulate a use case where IaaS (OpenStack‐SLAM) and PaaS (OpenShift) are combined; and assess performance and efficiency of the aforementioned VM placement strategies, when a multi-domain SLA pricing & penalty model is involved. We find that our proposal is efficient in managing trade-offs between the operational objectives of service providers (including financial considerations) and the customers’ expected QoS requirements.

  • Rapidly Alternating Bottlenecks: A Study of Two Cases in n-Tier Applications

  • Should be cited as: [ paper pdf download]

    Qingyang Wang, Yasuhiko Kanemasa, Jack Li, Toshihiro Shimizu, Masazumi Matsubara, Motoyuki Kawaba, and Calton Pu, "Rapidly Alternating Bottlenecks: A Study of Two Cases in n-Tier Applications", International Journal of Cloud Computing (IJCC), 1(1), 2013, pp. 13-25.

    Abstract:

    Identifying the location of performance bottlenecks is a non‐trivial challenge when scaling n‐tier applications in computing clouds. Specifically, we observed that an n-tier application may experience significant performance loss when bottlenecks alternate rapidly between component servers. Such rapidly alternating bottlenecks arise naturally and often from resource dependencies in an n-tier system and bursty workloads. These rapidly alternating bottlenecks are difficult to detect because the saturation in each participating server may have a very short lifespan (e.g., milliseconds) compared to current system monitoring tools and practices with sampling at intervals of seconds or minutes. Using passive network tracing at fine-granularity (e.g., aggregate at every 50ms), we are able to correlate throughput (i.e., request service rate) and queue length (i.e., number of concurrent requests) in each server of an n‐tier system. Our experimental results show conclusive evidence of rapidly alternating bottlenecks caused by system software (JVM garbage collection) and middleware (VM collocation).

  • Cross Cloud Mapreduce: A Result Integrity Check Framework on Hybrid Clouds

  • Should be cited as: [ paper pdf download]

    Yongzhi Wang, Jinpeng Wei, and Mudhakar Srivatsa, "Cross Cloud Mapreduce: A Result Integrity Check Framework on Hybrid Clouds", International Journal of Cloud Computing (IJCC), 1(1), 2013, pp. 26-39.

    Abstract:

    Large-scale adoption of MapReduce computations on public clouds is hindered by the lack of trust on the participating virtual machines, because misbehaving worker nodes can compromise the integrity of the computation result. In this paper, we propose a novel MapReduce framework, Cross Cloud MapReduce (CCMR), which overlays the MapReduce computation on top of a hybrid cloud: the master that is in control of the entire computation and guarantees result integrity runs on a private and trusted cloud, while normal workers run on a public cloud. In order to achieve high accuracy, we propose a result integrity check scheme on both the map phase and the reduce phase. On the other hand, we strive to reduce the performance overhead by reducing the cross-cloud communication and merging sub-tasks. We implement CCMR based on Apache Hadoop MapReduce and evaluate it on Amazon EC2. Both theoretical and experimental analysis show that our approach can guarantee high result integrity in a hybrid cloud environment while incurring non-negligible performance overhead (e.g., when 16.7% workers are malicious, CCMR can guarantee at least 99.52% of accuracy with 33.6% of overhead when replication probability is 0.3 and the credit threshold is 50).

  • Implementation and Empirical Assessment of a Web Application Cloud Deployment Tool

  • Should be cited as: [ paper pdf download]

    Américo Sampaio, Roberto Costa Jr, Nabor C. Mendonça, and Ricardo Hollanda Filho, "Implementation and Empirical Assessment of a Web Application Cloud Deployment Tool", International Journal of Cloud Computing (IJCC), 1(1), 2013, pp. 40-52.

    Abstract:

    Cloud computing is becoming mainstream in software development, with many organizations now considering migrating their applications to the cloud. However, the task of deploying applications in infrastructure-as-a-service (IaaS) clouds is generally daunting due to a number of manual steps necessary to configure all application components as a set of virtual machine images. This work presents a tool, called TREXCLOUD, which greatly simplifies the task of deploying fully functional Web applications in IaaS clouds. With TREXCLOUD, users can easily select a set of files that contain the application components (e.g., .war files, database backup files, context files), which are then used by the tool to automatically deploy and configure the whole application stack in a supported IaaS cloud provider. An empirical study, in which nine users were asked to deploy two different Java web applications in the Amazon cloud using three different deployment tools, shows how TREXCLOUD enables a significant reduction in deployment effort (over 90% in the best case) when compared to existing state-of-the-practice approaches

  • A Queuing Model to Achieve Proper Elasticity for Cloud Cluster Jobs

  • Should be cited as: [ paper pdf download]

    Khaled Salah, "A Queuing Model to Achieve Proper Elasticity for Cloud Cluster Jobs", International Journal of Cloud Computing (IJCC), 1(1), 2013, pp. 53-64.

    Abstract:

    .Achieving proper elasticity for cloud jobs is a challenging research problem and far from being solved. In this extended and revised paper, we investigate how to achieve proper elasticity for highly parallelized jobs which run on cloud clusters. In particular, we present an analytical model based on finite queuing systems that can be used to determine at any given instance of time and under current workload conditions the minimal number of cloud resources needed to satisfy the SLO requirements such as response time and request loss probability. We give numerical examples to demonstrate the applicability and usefulness of our model. In particular, we study the performance of a cloud-based clustering system in terms of queue utilization, request loss, and response service time. We also give an example of fluctuating workload to show how our model can be used to achieve proper elasticity. Discrete Event Simulation has been used to verify the correctness of our proposed model.

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