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Services Computing, IEEE Transactions on

Issue 4 • Date Fourth Quarter 2012

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Displaying Results 1 - 11 of 11
  • Editorial: Big Services Era: Global Trends of Cloud Computing and Big Data

    Page(s): 467 - 468
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    Freely Available from IEEE
  • Guest Editorial: Special Issue on Cloud Computing

    Page(s): 469 - 471
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    Freely Available from IEEE
  • A Trusted Virtual Machine in an Untrusted Management Environment

    Page(s): 472 - 483
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (826 KB) |  | HTML iconHTML  

    Virtualization is a rapidly evolving technology that can be used to provide a range of benefits to computing systems, including improved resource utilization, software portability, and reliability. Virtualization also has the potential to enhance security by providing isolated execution environments for different applications that require different levels of security. For security-critical applications, it is highly desirable to have a small trusted computing base (TCB), since it minimizes the surface of attacks that could jeopardize the security of the entire system. In traditional virtualization architectures, the TCB for an application includes not only the hardware and the virtual machine monitor (VMM), but also the whole management operating system (OS) that contains the device drivers and virtual machine (VM) management functionality. For many applications, it is not acceptable to trust this management OS, due to its large code base and abundance of vulnerabilities. For example, consider the "computing-as-a-service” scenario where remote users execute a guest OS and applications inside a VM on a remote computing platform. It would be preferable for many users to utilize such a computing service without being forced to trust the management OS on the remote platform. In this paper, we address the problem of providing a secure execution environment on a virtualized computing platform under the assumption of an untrusted management OS. We propose a secure virtualization architecture that provides a secure runtime environment, network interface, and secondary storage for a guest VM. The proposed architecture significantly reduces the TCB of security-critical guest VMs, leading to improved security in an untrusted management environment. We have implemented a prototype of the proposed approach using the Xen virtualization system, and demonstrated how it can be used to facilitate secure remote computing services. We evaluate the performance penalties incurre- by the proposed architecture, and demonstrate that the penalties are minimal. View full abstract»

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  • VNsnap: Taking Snapshots of Virtual Networked Infrastructures in the Cloud

    Page(s): 484 - 496
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    A virtual networked infrastructure (VNI) consists of virtual machines (VMs) connected by a virtual network. Created for individual users on a shared cloud infrastructure, VNIs reflect the concept of "Infrastructure as a Service” (IaaS) as part of the emerging cloud computing paradigm. The ability to take snapshots of an entire VNI-including images of the VMs with their execution, communication, and storage states-yields a unique approach to reliability as a VNI snapshot can be used to restore the operation of the entire virtual infrastructure. We present VNsnap, a system that takes distributed snapshots of VNIs. Unlike many existing distributed snapshot/checkpointing solutions, VNsnap does not require any modifications to the applications, libraries, or (guest) operating systems (OSs) running in the VMs. Furthermore, by performing much of the snapshot operation concurrently with the VNI's normal operation, VNsnap incurs only seconds of downtime. We have implemented VNsnap on top of Xen. Our experiments with real-world parallel and distributed applications demonstrate VNsnap's effectiveness and efficiency. View full abstract»

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  • Resource Provisioning with Budget Constraints for Adaptive Applications in Cloud Environments

    Page(s): 497 - 511
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    The recent emergence of clouds is making the vision of utility computing realizable, i.e., computing resources and services can be delivered, utilized, and paid for as utilities such as water or electricity. This, however, creates new resource provisioning problems. Because of the pay-as-you-go model, resource provisioning should be performed in a way to keep resource costs to a minimum, while meeting an application's needs. In this work, we focus on the use of cloud resources for a class of adaptive applications, where there could be application-specific flexibility in the computation that may be desired. Furthermore, there may be a fixed time-limit as well as a resource budget. Within these constraints, such adaptive applications need to maximize their Quality of Service (QoS), more precisely, the value of an application-specific benefit function, by dynamically changing adaptive parameters. We present the design, implementation, and evaluation of a framework that can support such dynamic adaptation for applications in a cloud computing environment. The key component of our framework is a multi-input-multi-output feedback control model-based dynamic resource provisioning algorithm which adopts reinforcement learning to adjust adaptive parameters to guarantee the optimal application benefit within the time constraint. Then a trained resource model changes resource allocation accordingly to satisfy the budget. We have evaluated our framework with two real-world adaptive applications, and have demonstrated that our approach is effective and causes a very low overhead. View full abstract»

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  • Monetary Cost-Aware Checkpointing and Migration on Amazon Cloud Spot Instances

    Page(s): 512 - 524
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    Recently introduced spot instances in the Amazon Elastic Compute Cloud (EC2) offer low resource costs in exchange for reduced reliability; these instances can be revoked abruptly due to price and demand fluctuations. Mechanisms and tools that deal with the cost-reliability tradeoffs under this schema are of great value for users seeking to lessen their costs while maintaining high reliability. We study how mechanisms, namely, checkpointing and migration, can be used to minimize the cost and volatility of resource provisioning. Based on the real price history of EC2 spot instances, we compare several adaptive checkpointing schemes in terms of monetary costs and improvement of job completion times. We evaluate schemes that apply predictive methods for spot prices. Furthermore, we also study how work migration can improve task completion in the midst of failures while maintaining low monetary costs. Trace-based simulations show that our schemes can reduce significantly both monetary costs and task completion times of computation on spot instance. View full abstract»

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  • CloudTPS: Scalable Transactions for Web Applications in the Cloud

    Page(s): 525 - 539
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    NoSQL cloud data stores provide scalability and high availability properties for web applications, but at the same time they sacrifice data consistency. However, many applications cannot afford any data inconsistency. CloudTPS is a scalable transaction manager which guarantees full ACID properties for multi-item transactions issued by web applications, even in the presence of server failures and network partitions. We implement this approach on top of the two main families of scalable data layers: Bigtable and SimpleDB. Performance evaluation on top of HBase (an open-source version of Bigtable) in our local cluster and Amazon SimpleDB in the Amazon cloud shows that our system scales linearly at least up to 40 nodes in our local cluster and 80 nodes in the Amazon cloud. View full abstract»

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  • Component Ranking for Fault-Tolerant Cloud Applications

    Page(s): 540 - 550
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    Cloud computing is becoming a mainstream aspect of information technology. More and more enterprises deploy their software systems in the cloud environment. The cloud applications are usually large scale and include a lot of distributed cloud components. Building highly reliable cloud applications is a challenging and critical research problem. To attack this challenge, we propose a component ranking framework, named FTCloud, for building fault-tolerant cloud applications. FTCloud includes two ranking algorithms. The first algorithm employs component invocation structures and invocation frequencies for making significant component ranking. The second ranking algorithm systematically fuses the system structure information as well as the application designers' wisdom to identify the significant components in a cloud application. After the component ranking phase, an algorithm is proposed to automatically determine an optimal fault-tolerance strategy for the significant cloud components. The experimental results show that by tolerating faults of a small part of the most significant components, the reliability of cloud applications can be greatly improved. View full abstract»

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  • Social Cloud Computing: A Vision for Socially Motivated Resource Sharing

    Page(s): 551 - 563
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    Online relationships in social networks are often based on real world relationships and can therefore be used to infer a level of trust between users. We propose leveraging these relationships to form a dynamic "Social Cloud,” thereby enabling users to share heterogeneous resources within the context of a social network. In addition, the inherent socially corrective mechanisms (incentives, disincentives) can be used to enable a cloud-based framework for long term sharing with lower privacy concerns and security overheads than are present in traditional cloud environments. Due to the unique nature of the Social Cloud, a social market place is proposed as a means of regulating sharing. The social market is novel, as it uses both social and economic protocols to facilitate trading. This paper defines Social Cloud computing, outlining various aspects of Social Clouds, and demonstrates the approach using a social storage cloud implementation in Facebook. View full abstract»

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  • Agent-Based Cloud Computing

    Page(s): 564 - 577
    Multimedia
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    Agent-based cloud computing is concerned with the design and development of software agents for bolstering cloud service discovery, service negotiation, and service composition. The significance of this work is introducing an agent-based paradigm for constructing software tools and testbeds for cloud resource management. The novel contributions of this work include: 1) developing Cloudle: an agent-based search engine for cloud service discovery, 2) showing that agent-based negotiation mechanisms can be effectively adopted for bolstering cloud service negotiation and cloud commerce, and 3) showing that agent-based cooperative problem-solving techniques can be effectively adopted for automating cloud service composition. Cloudle consists of 1) a service discovery agent that consults a cloud ontology for determining the similarities between providers' service specifications and consumers' service requirements, and 2) multiple cloud crawlers for building its database of services. Cloudle supports three types of reasoning: similarity reasoning, compatibility reasoning, and numerical reasoning. To support cloud commerce, this work devised a complex cloud negotiation mechanism that supports parallel negotiation activities in interrelated markets: a cloud service market between consumer agents and broker agents, and multiple cloud resource markets between broker agents and provider agents. Empirical results show that using the complex cloud negotiation mechanism, agents achieved high utilities and high success rates in negotiating for cloud resources. To automate cloud service composition, agents in this work adopt a focused selection contract net protocol (FSCNP) for dynamically selecting cloud services and use service capability tables (SCTs) to record the list of cloud agents and their services. Empirical results show that using FSCNP and SCTs, agents can successfully compose cloud services by autonomously selecting services. View full abstract»

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  • IEEE Open Access Publishing

    Page(s): 578
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    Freely Available from IEEE

Aims & Scope

The scope covers all computing and software aspects of the science and technology of services innovation research and development. IEEE Transactions on Services Computing emphasizes the algorithmic, mathematical, statistical and computational methods that are central in services computing, the emerging field of Service Oriented Architecture, Web Services, Business Process Integration, Solution Performance Management, Services Operations and Management. Specifically, the transactions covers but is not limited to the following topics: Mathematical foundation of Services Computing, Service-Oriented Architecture (SOA), Service creation, development, and management, Linkage between IT services and business services, Web services security and privacy, Web services agreement and contract, Web services discovery and negotiation, Web services management, Web services collaboration, Quality of Service for Web services, Web services modeling and performance management, Solution frameworks for building service-oriented applications, Composite Web service creation and enabling infrastructures, Business and scientific applications using Web services and SOA, Business process integration and management using Web services, Standards and specifications of Services Computing, Utility models and solution architectures, Resource acquisition models in Utility Computing, Mathematical foundation of business process modeling, integration and management, Business process modeling, integration, and collaboration.

Additional Information:

TSC is a scholarly, archival journal published quarterly. 

It is noted that only service-oriented grid computing topics will be covered by TSC. 

Please be sure to visit the TSC Taxonomy List. [Link to http://www.computer.org/portal/web/tsc/taxonomy]

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Ling Liu
Georgia Institute of Technology
lingliu@cc.gatech.edu