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2016 IEEE International Conference on Cloud Engineering (IC2E)

4-8 April 2016

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  • [Front cover]

    Publication Year: 2016, Page(s): C4
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  • [Title page i]

    Publication Year: 2016, Page(s): i
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  • [Title page iii]

    Publication Year: 2016, Page(s): iii
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  • [Copyright notice]

    Publication Year: 2016, Page(s): iv
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  • Table of contents

    Publication Year: 2016, Page(s):v - viii
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  • Message the IC2E 2016 General Chairs

    Publication Year: 2016, Page(s): ix
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  • Message from the IC2E 2016 Program Commitee Co-Chairs

    Publication Year: 2016, Page(s):x - xi
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  • IC2E 2016 Organizing Committee and Sponsors

    Publication Year: 2016, Page(s):xii - xiii
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  • Program Committee

    Publication Year: 2016, Page(s):xiv - xv
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  • External Reviewers

    Publication Year: 2016, Page(s): xvi
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  • Generalization versus Specialization in Cloud Computing Infrastructures

    Publication Year: 2016, Page(s): 1
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (162 KB)

    Summary form only given. Cloud computing represents a fundamental change in the business model behind IT: a shift from manufacturing of software and hardware products towards packaging infrastructure, processing, and storage as services. Cloud data centers, given their intended use for general purpose computing, would seem to push towards homogeneity in architectures and platforms. Modern applicat... View full abstract»

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  • Not All Joules are Equal: Towards Energy-Efficient and Green-Aware Data Processing Frameworks

    Publication Year: 2016, Page(s):2 - 11
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1056 KB) | HTML iconHTML

    Interests have been growing in integrating renewable energy into data centers, which attracts many research efforts in developing green-aware algorithms and systems. However, little attention was paid to the efficiency of each joule consumed by data center workloads. In fact, not all joules are equal in the sense that the amount of work that can be done by a joule can vary significantly in data ce... View full abstract»

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  • Supporting On-demand Elasticity in Distributed Graph Processing

    Publication Year: 2016, Page(s):12 - 21
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (269 KB) | HTML iconHTML

    While distributed graph processing engines have become popular for processing large graphs, these engines are typically configured with a static set of servers in the cluster. In other words, they lack the flexibility to scale-out or scale-in the number of servers, when requested to do so by the user. In this paper, we propose the first techniques to make distributed graph processing truly elastic... View full abstract»

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  • Stela: Enabling Stream Processing Systems to Scale-in and Scale-out On-demand

    Publication Year: 2016, Page(s):22 - 31
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1283 KB) | HTML iconHTML

    The era of big data has led to the emergence of new real-time distributed stream processing engines like Apache Storm. We present Stela (STream processing ELAsticity), a stream processing system that supports scale-out and scale-in operations in an on-demand manner, i.e., when the user requests such a scaling operation. Stela meets two goals: 1) it optimizes post-scaling throughput, and 2) it mini... View full abstract»

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  • Awan: Locality-Aware Resource Manager for Geo-Distributed Data-Intensive Applications

    Publication Year: 2016, Page(s):32 - 41
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (847 KB) | HTML iconHTML

    Today, many organizations need to operate on data that is distributed around the globe. This is inevitable due to the nature of data that is generated in different locations such as video feeds from distributed cameras, log files from distributed servers, and many others. Although centralized cloud platforms have been widely used for data-intensive applications, such systems are not suitable for p... View full abstract»

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  • Information Flow Audit for PaaS Clouds

    Publication Year: 2016, Page(s):42 - 51
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (286 KB) | HTML iconHTML

    With the rapid increase in uptake of cloud services, issues of data management are becoming increasingly prominent. There is a clear, outstanding need for the ability for specified policy to control and track data as it flows throughout cloud infrastructure, to ensure that those responsible for data are meeting their obligations. This paper introduces Information Flow Audit, an approach for tracki... View full abstract»

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  • Surviving Failures with Performance-Centric Bandwidth Allocation in Private Datacenters

    Publication Year: 2016, Page(s):52 - 61
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (469 KB) | HTML iconHTML

    In the context of private datacenters that are operated by Web service providers such as Google, multiple applications using data parallel frameworks, such as MapReduce, coexist and share a limited supply of link bandwidth capacities. It has been shown that failures are the norm, rather than the exception, in datacenters, and will negatively affect the performance of data parallel applications as ... View full abstract»

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  • LOGAN: Problem Diagnosis in the Cloud Using Log-Based Reference Models

    Publication Year: 2016, Page(s):62 - 67
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (366 KB) | HTML iconHTML

    Problem diagnosis is one crucial aspect in the cloud operation that is becoming increasingly challenging. On the one hand, the volume of logs generated in today's cloud is overwhelmingly large. On the other hand, cloud architecture becomes more distributed and complex, which makes it more difficult to troubleshoot failures. In order to address these challenges, we have developed a tool, called LOG... View full abstract»

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  • The Discovery Cloud: Accelerating and Democratizing Research on a Global Scale

    Publication Year: 2016, Page(s):68 - 77
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (568 KB) | HTML iconHTML

    Modern science and engineering require increasingly sophisticated information technology (IT) for data analysis, simulation, and related tasks. Yet the small to medium laboratories (SMLs) in which the majority of research advances occur increasingly lack the human and financial capital needed to acquire and operate such IT. New methods are needed to provide all researchers with access to state-of-... View full abstract»

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  • What could possibly go wrong? [technical and legal challenges in computing]

    Publication Year: 2016, Page(s): 78
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (166 KB)

    There are many more things with moving parts in the world than computers. These are the objects that are being connected, initially artefacts, but also the natural world. They are connected both by being sensed, and via actuators. For a true Internet of things to emerge with all its potential value for innovation in efficiencies, the sensors and actuators must actually be reachable from anywhere, ... View full abstract»

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  • Cost-Aware Scalability of Applications in Public Clouds

    Publication Year: 2016, Page(s):79 - 88
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1135 KB) | HTML iconHTML

    Scalable applications deployed in public clouds can be built from a combination of custom software components and public cloud services. To meet performance and/or cost requirements, such applications can scale-out/in their components during run-time. When higher performance is required, new component instances can be deployed on newly allocated cloud services (e.g., virtual machines). When the in... View full abstract»

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  • Cloud Instance Management and Resource Prediction for Computation-as-a-Service Platforms

    Publication Year: 2016, Page(s):89 - 98
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (493 KB) | HTML iconHTML

    Computation-as-a-Service (CaaS) offerings have gained traction in the last few years due to their effectiveness in balancing between the scalability of Software-as-a-Service and the customisation possibilities of Infrastructure-as-a-Service platforms. To function effectively, a CaaS platform must have three key properties: (i) reactive assignment of individual processing tasks to available cloud i... View full abstract»

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  • A Comparative Evaluation of Algorithms for Auction-Based Cloud Pricing Prediction

    Publication Year: 2016, Page(s):99 - 108
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (215 KB) | HTML iconHTML

    Nowadays, cloud computing providers offer idle resources through an auction-based system in order to maximize resource utilization and economical revenue. Cloud computing consumers have the opportunity to take advantage of the resources offered at very low spot price in exchange for lower reliability in the provision of these resources. In this context, the Spot Price Prediction (SPP) is a well st... View full abstract»

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  • Autoscaling for Hadoop Clusters

    Publication Year: 2016, Page(s):109 - 118
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (400 KB) | HTML iconHTML

    Unforeseen events such as node failures and resource contention can have a severe impact on the performance of data processing frameworks, such as Hadoop, especially in cloud environments where such incidents are common. SLA compliance in the presence of such events requires the ability to quickly and dynamically resize infrastructure resources. Unfortunately, the distributed and stateful nature o... View full abstract»

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  • UIE: User-Centric Interference Estimation for Cloud Applications

    Publication Year: 2016, Page(s):119 - 122
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (184 KB) | HTML iconHTML

    Interference is one of the key deterrents to cloud adoption, and is known to cause severe degradation in application performance, costing service providers in lost revenues. In this paper, we present UIE, a user-centric approach to detecting and, importantly, estimating the degree of interference experienced by user applications in the cloud. UIE employs queueing theory to model the impact of reso... View full abstract»

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