2016 IEEE 9th International Conference on Cloud Computing (CLOUD)

June 27 2016-July 2 2016

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  • [Front cover]

    Publication Year: 2016, Page(s): c1
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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 - xviii
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  • Message from the General Chairs

    Publication Year: 2016, Page(s):xix - xx
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  • Message from the Program Chairs

    Publication Year: 2016, Page(s): xxi
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  • Organizing Committee

    Publication Year: 2016, Page(s):xxii - xxiv
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  • Program Committee

    Publication Year: 2016, Page(s):xxv - xxx
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  • IEEE Computer Society Technical Committee on Services Computing

    Publication Year: 2016, Page(s): xxxi
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  • Empirical Evaluation of Workload Forecasting Techniques for Predictive Cloud Resource Scaling

    Publication Year: 2016, Page(s):1 - 10
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (346 KB) | HTML iconHTML

    Many predictive resource scaling approaches have been proposed to overcome the limitations of the conventional reactive approaches most often used in clouds today. In general, due to the complexity of clouds, these reactive approaches were often forced to make significant limiting assumptions in either the operating conditions/requirements or expected workload patterns. As such, it is extremely di... View full abstract»

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  • Workload and Resource Aware Proactive Auto-scaler for PaaS Cloud

    Publication Year: 2016, Page(s):11 - 18
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    Elasticity is a key feature in Cloud Computing where virtualized resources are provisioned and de-provisioned via auto-scaling. However, auto-scaling in most Platform-as-a-Service (PaaS) systems is based on reactive, threshold-driven approaches. Such systems are incapable of catering to rapidly varying workloads, unless the associated thresholds are sufficiently low. Alternatively, maintaining low... View full abstract»

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  • RC3E: Reconfigurable Accelerators in Data Centres and Their Provision by Adapted Service Models

    Publication Year: 2016, Page(s):19 - 26
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (658 KB) | HTML iconHTML

    Computing performance and scalability are essential ingredients in modern data centres offering cloud services. Field Programmable Gate Arrays (FPGAs) provide a promising opportunity to improve performance, security and energy efficiency because their hardware architecture can be adapted directly to the application. In this paper we present the development of our FPGA cloud architecture, beginning... View full abstract»

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  • TAaaS: Trustworthy Authentication as a Service Based on Trusted Path

    Publication Year: 2016, Page(s):27 - 34
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1215 KB) | HTML iconHTML

    Authentication as a Service (AaaS) provides on-demand delivery of multi-factor authentication (MFA). However, current AaaS has left out of consideration the trustworthiness of user inputs at client evices and the risk of privacy exposure at the AaaS providers. To solve these concerns, we present TAaaS, Trustworthy Authentication as a Service, which offers a trusted path-based MFA service to the se... View full abstract»

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  • Thwarting Market Specific Attacks in Cloud

    Publication Year: 2016, Page(s):35 - 42
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    Market oriented methodologies have been extensively used for solving dynamic allocation problems in online systems including the Cloud. Despite their extensive use, very little has been known about their security against market specific security threats (e.g. monopoly, shill bidding, etc.). This work follows an experimental driven approach for: (i) promoting the development of threat-aware, market... View full abstract»

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  • Secure Offloading of Legacy IDSes Using Remote VM Introspection in Semi-trusted Clouds

    Publication Year: 2016, Page(s):43 - 50
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (395 KB) | HTML iconHTML

    In Infrastructure-as-a-Service (IaaS) clouds, intrusion detection systems (IDSes) increase their importance. To securely detect attacks against virtual machines (VMs), IDS offloading with VM introspection (VMI) has been proposed. In semi-trusted clouds, however, it is difficult to securely offload IDSes because there may exist insiders such as malicious system administrators. First, secure VM exec... View full abstract»

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  • OpenStack Security Modules: A Least-Invasive Access Control Framework for the Cloud

    Publication Year: 2016, Page(s):51 - 58
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (412 KB) | HTML iconHTML

    The access control mechanisms of existing cloud systems, mainly OpenStack, fail to provide two key factors: i) centralized access mediation and ii) flexible policy customization. This situation prevents cloud administrators and end customers from enhancing their security. Furthermore, a variety of clouds have implemented their access control systems and policies in separated ways. This might confu... View full abstract»

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  • End-to-End Security Formalization and Alignment for Federated Workflow Management

    Publication Year: 2016, Page(s):59 - 67
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1101 KB) | HTML iconHTML

    Traditionally, the allocation and dynamic adaptation of federated cyberinfrastructure resources residing across multiple domains for data-intensive application workflows have been performance or quality of service-centric (i.e., QSpecs), often compromising the end-to-end security requirements of scientific workflows. Lack of standardized formalization methods of the workflows' end-to-end security ... View full abstract»

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  • An Integrated Privacy Preserving Attribute Based Access Control Framework

    Publication Year: 2016, Page(s):68 - 76
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (717 KB) | HTML iconHTML

    Recent advances in IT have enabled many applications that generate/collect huge amounts of personal data. While these advances have made many personalized applications such as personalized user-centric healthcare possible there are significant system maintenance cost related to data management, and security and privacy issues that need to be first addressed. Although cloud computing presents a new... View full abstract»

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  • Efficient Peak Shaving in a Data Center by Joint Optimization of Task Assignment and Energy Storage Management

    Publication Year: 2016, Page(s):77 - 83
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    The usage of energy storage devices in data centers has been widely studied for the purpose of peak shaving in the context of dynamic utility pricing. To effectively achieve peak shaving in a data center with energy storage capability, a joint optimization framework is proposed to solve the task assignment problem and the energy storage management problem. The power hierarchy of a data center is m... View full abstract»

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  • Energy Optimal VM Placement in the Cloud

    Publication Year: 2016, Page(s):84 - 91
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (679 KB) | HTML iconHTML

    In this paper, we investigate the issue of minimizing data center energy usage. In particular, we formulate a problem of virtual machine placement with the objective of minimizing the total power consumption of all the servers. To do this, we examine a CPU power consumption model and then incorporate the model into an mixed integer programming formulation. In order to find optimal or near-optimal ... View full abstract»

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  • Hadoop in Flight: Migrating Live MapReduce Jobs for Power-Shifting Data Centers

    Publication Year: 2016, Page(s):92 - 99
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    Renewable energy sources such as wind and solar are unpredictable for power utilities, which must produce exactly as much power as is needed at any given time. To help manage the demand, some utilities have begun deploying real-time energy prices to their customers. Data centers, which often run Hadoop jobs on thousands of machines, have become some of the utilities' largest consumers. In fact, re... View full abstract»

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  • Elastic Stream Processing for the Internet of Things

    Publication Year: 2016, Page(s):100 - 107
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    Emerging trends like Big Data and the Internet of Things pose new challenges to established data stream processing engines. Especially, with the advent of the Internet of Things, the data that has to be processed can become very large. Since companies usually aim for cost efficiency, engines need to support resource elasticity to minimize the operational cost while maintaining real-time processing... View full abstract»

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  • Enabling Elastic Stream Processing in Shared Clusters

    Publication Year: 2016, Page(s):108 - 115
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    Distributed data stream processing has become an increasingly popular computational framework due to many emerging applications which require real-time processing of data such as dynamic content delivery and security event analysis. These distributed data stream processing applications are often run on shared, multi-tenant clusters as companies try to consolidate from dedicated clusters for each a... View full abstract»

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  • Utilizing Massive Viewers for Video Transcoding in Crowdsourced Live Streaming

    Publication Year: 2016, Page(s):116 - 123
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    Driven by the advances in personal computing devices and the prevalence of broadband network and wireless mobile network accesses, Crowdsourced Live Streaming (CLS) platforms have emerged in recent years, through which numerous broadcasters lively stream their video content, e.g., live events or online game scenes, to fellow viewers. Compared to professional video producers and broadcasters, these... View full abstract»

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