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15th ACM Annual International Conference on Mobile Systems, Applications, and Services (MobiSys)

作者： Wang, Wenwen Yew, Pen-Chung Zhai, Antonia McCamant, Stephen Wu, Youfeng Bobba, Jayaram Univ Minnesota St Paul MN 55455 USA Intel Labs Pittsburgh PA USA

ISBN: (纸本)9781450349284

Work offloading allows a mobile device, i.e., the client, to execute its computation-intensive code remotely on a more powerful server to improve its performance and to extend its battery life. However, the difference in instruction set architectures (ISAs) between the client and the server poses a great challenge to work offloading. Most of the existing solutions rely on language-level virtual machines to hide such differences. Therefore, they have to tie closely to the specific programming languages. Other approaches try to recompile the mobile applications to achieve the specific goal of offloading, so their applicability is limited to the availability of the source code. To overcome the above limitations, we propose to extend the capability of dynamic binary translation across clients and servers to offload the identified computation-intensive binary code regions automatically to the server at runtime. With this approach, the native binaries on the client can be offloaded to the server seamlessly without the limitations mentioned above. A prototype has been implemented using an existing retargetable dynamic binary translator. Experimental results show that our system achieves 1.93X speedup with 48.66% reduction in energy consumption for six real-world applications, and 1.62X speedup with 42.4% reduction in energy consumption for SPEC CINT2006 benchmarks.

关键词： computation offloading Dynamic Binary Translation Dynamic Binary Optimization offloading Target Selection

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Mobile Cloud Computing: The Future Essence

Mobile Cloud Computing: The Future Essence

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International conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： Sinha, Niharika Sharma, Shilpi Burman Prashar, Priya Amity Univ Comp Sci & Engn Noida India

ISBN: (纸本)9781509056866

Mobile cloud computing is a wide-ranging blend of cloud computing and mobile development. It is a technique in which mobile applications are assembled, functioned and presented using cloud computing technology. The hastening in the advancement of cloud computing as well as mobile computing has led to the invention of an amalgamated output: Mobile Cloud Computing. These days, this is becoming one of the most amusing technologies for cloud services firms. It has become a necessity in everyday life for the mobile users as data processing and storage happens to be outside of the mobile. MCC has taken the place of major topic of discussion in the IT sector since 2009. It is important to assemble a comprehensive understanding of the techniques and future extent, since mobile cloud computing is already in the preliminary stage of enhancement. MCC has been introduced to conquer the boundaries of infinite scope of cloud resources and make it accessible right to the mobile devices. This paper presents first of all a brief review on the history followed by drawbacks of various research works in section 2, tenor of mobile cloud computing in section 3. We have also determined the Result from our research work along with the conclusion.

关键词： Cloud computing (CC) mobile cloud computing (MCC) computation offloading Mobile Computing virtualization

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Analyzing offloading inefficiencies in scalable heterogeneous applications 32nd

Analyzing offloading inefficiencies in scalable heterogeneou...

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32nd International Conference on High Performance Computing, ISC High Performance 2017

作者： Dietrich, Robert Tschüter, Ronny Juckeland, Guido Knüpfer, Andreas Center for Information Services and High Performance Computing Technische Universität Dresden Dresden01062 Germany Department of Information Service and Computing Helmholz-Zentrum Dresden-Rossendorf Bautzner Landstr. 400 Dresden01328 Germany

ISBN: (纸本)9783319676296

With the rise of accelerators in high performance computing, programming models for the development of heterogeneous applications have evolved and are continuously being improved to increase program performance and programmer productivity. The concept of computation offloading to massively parallel compute devices has established itself as a new layer of parallelism in scientific applications, next to message passing and multi-threading. To optimize the execution of a respective parallel heterogeneous program for a specific platform, performance analysis is crucial. This work abstracts from specific offloading APIs such as available with CUDA, OpenCL, OpenACC, and OpenMP and summarizes common inefficiencies for offloading. Based on the definition of inefficiency patterns, the offloading concept can be included in generic analysis techniques such as critical-path and root-cause analysis. We implemented the detection and evaluation of inefficiency patterns as a post-mortem trace analysis, which finally highlights program activities with a high potential to reduce the total program runtime. © Springer International Publishing AG 2017.

关键词： computation offloading

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Poster: EPS - Edge-hosted personal services for mobile users 17

Poster: EPS - Edge-hosted personal services for mobile users

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15th ACM International Conference on Mobile Systems, Applications, and Services, MobiSys 2017

作者： Hao, Pengzhan Bai, Yongshu Zhang, Xin Zhang, Yifan Department of Computer Science SUNY Binghamton BinghamtonNY United States

ISBN: (纸本)9781450349284

Being powered by battery and the reliance on expensive cellular data while users are on the move are holding smart mobile devices from being widely used in those long-lasted, computation-intensive, or highly network-reliant usage scenarios. In the meantime, more and more mobile workloads and optimizations now rely on the cloud, such as mobile cloud offloading, cloud-based mobile web optimization, and cloud-based network traffic redundancy reduction. However, it is hard to perform large-scale and personalized support or optimization for mobile workloads without significant computation resource increase on the cloud, as well as higher bandwidth requirement on the networks. © 2017 Copyright held by the owner/author(s).

关键词： computation offloading

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Techniques for fine-grained, multi-site computation offloading 11

Techniques for fine-grained, multi-site computation offloadi...

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Proceedings of the 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing

作者： Sinha, Kanad Kulkarni, Milind School of Electrical and Computer Engineering Purdue University West Lafayette IN United States

ISBN: (纸本)9780769543956

Increasingly, mobile devices are becoming the preferred platform for computation for many users. Unfortunately, the resource limitations, in battery life, computation power and storage, restricts the richness of applications that can be run on such devices. To alleviate these concerns, a popular approach that has gained currency in recent years is computation offloading, where a portion of an application is run off-site, leveraging the far greater resources of the cloud. Prior work in this area has focused on a constrained form of the problem: a single mobile device offloading computation to a single server. However, with the increased popularity of cloud computing and storage, it is more common for the data that an application accesses to be distributed among several servers. This paper describes algorithmic approaches for performing fine-grained, multi-site offloading. This allows portions of an application to be offloaded in a data-centric manner, even if that data exists at multiple sites. Our approach is based on a novel partitioning algorithm, and a novel data representation. We demonstrate that our partitioning algorithm outperforms existing multi-site offloading algorithms, and that our data representation provides for more efficient, fine-grained offloading than prior approaches. © 2011 IEEE.

关键词： computation offloading

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Tuning browser-to-browser offloading for heterogeneous stream processing web applications 9

Tuning browser-to-browser offloading for heterogeneous strea...

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9th Central European Workshop on Services and their Composition, ZEUS 2017

作者： Babazadeh, Masiar Switzerland

Software that runs on the Cloud may be offloaded to clients to ease the computational effort on the server side, while clients may as well offload computations back to the cloud or to other clients if it becomes too taxing on their machines. In this paper we present how we autonomically deal with browser-to-browser operator offloading in Web Liquid Streams, a stream processing framework that lets developers implement streaming topologies on any Web-enabled device. We show how we first implemented the offloading of streaming operators, and how we subsequently improved our approach. Our experimental results show how the new approach takes advantage of additional resources to reduce the end-to-end message delay and the queue sizes under heavy load. © 2017, CEUR-WS. All rights reserved.

关键词： computation offloading

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A comprehensive overview on secure offloading in mobile cloud computing 4

A comprehensive overview on secure offloading in mobile clou...

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4th International Conference on Electronics and Communication Systems, ICECS 2017

作者： Shibin, D. Kathrine, G. Jaspher W. Department of Computer Science and Engineering Karunya University Coimbatore India Department of Information Technology Karunya University Coimbatore India

ISBN: (纸本)9781509033553

Mobile applications possess insufficient resources such as bandwidth of the width, battery lifetime, storage capacity and performance of the processor. These restrictions may be comparatively reduced by computation offloading which is done by migrating heavy computation to capable servers and observing the solutions provided by the servers. Security plays an important role in cloud computation offloading. Data can be offloaded to perform computation in an easy way but the privacy of the migrated data being offloaded may be further improved. Even though remote data possession checking works with avoiding the maintenance of load of local data, it is vulnerable to attacks and deceives the users to believe that the migrated data are well hold. This paper provides a comprehensive overview of the technical background, various techniques for secure computation offloading, authentication techniques for mobile clients and preserving privacy of the offloaded data that is stored in the cloud. © 2017 IEEE.

关键词： computation offloading

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A Cloud-Based offloading Service for computation-Intensive Mobile Applications 21

A Cloud-Based Offloading Service for Computation-Intensive M...

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21st IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)

作者： Huang, Bo-Kai Cheng, Chih-Chuan Lin, Chun-Han Hsiu, Pi-Cheng Natl Taiwan Univ Dept Comp Sci & Informat Engn Taipei 10764 Taiwan Acad Sinica Res Ctr Informat Technol Innovat Taipei 115 Taiwan Natl Taiwan Normal Univ Dept Comp Sci & Informat Engn Taipei Taiwan Acad Sinica Inst Informat Sci Taipei Taiwan

ISBN: (纸本)9781467378550

Mobile devices, which are inherently of limited computing capabilities, face a growing demand to support increasingly complex applications. computation offloading addresses this issue by enabling mobile devices to offload computations to a remote server. Advancing on previous work, this paper presents a cloud-based offloading service, which models an optimization problem with the objective of minimizing the operation cost of the service provider while achieving the agreed quality of service (QoS) for subscribers. The problem is shown to be NP-hard. We propose a pseudo-polynomial-time optimal algorithm for the offline scenario, as well as an efficient online algorithm that has a provable QoS guarantee and allows practical implementations. To evaluate our algorithms, we synthesize remotable tasks and conduct extensive simulations based on real mobile user traces and application workload patterns. Our results demonstrate that our online algorithm could achieve comparable performance to the optimal offline algorithm, in terms of both the required cloud cost and the provided user benefit.

关键词： computation offloading cloud-based services service cost optimization mobile applications

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Performance Analysis of Game Engines on Mobile and Fixed Devices

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ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 2017年第4期13卷 57-57页

作者： Messaoudi, Farouk Ksentini, Adlen Simon, Gwendal Bertin, Philippe IRT B Com Paris France Eurecom Biot France Telecom Bretagne Brest France IRT B Com Orange Labs Paris France

Mobile gaming is an emerging concept wherein gamers are using mobile devices, like smartphones and tablets, to play best-seller games. Compared to dedicated gaming boxes or PCs, these devices still fall short of executing newly complex 3D video games with a rich immersion. Three novel solutions, relying on cloud computing infrastructure, namely, computation offloading, cloud gaming, and client-server architecture, will represent the next generation of game engine architecture aiming at improving the gaming experience. The basis of these aforementioned solutions is the distribution of the game code over different devices (including set-top boxes, PCs, and servers). In order to know how the game code should be distributed, advanced knowledge of game engines is required. By consequence, dissecting and analyzing game engine performances will surely help to better understand how to move in these new directions (i.e., distribute game code), which is so far missing in the literature. Aiming at filling this gap, we propose in this article to analyze and evaluate one of the famous engines in the market, that is, "Unity 3D." We begin by detailing the architecture and the game logic of game engines. Then, we propose a test-bed to evaluate the CPU and GPU consumption per frame and per module for nine representative games on three platforms, namely, a stand-alone computer, embedded systems, and web players. Based on the obtained results and observations, we build a valued graph of each module, composing the Unity 3D architecture, which reflects the internal flow and CPU consumption. Finally, we made a comparison in terms of CPU consumption between these architectures.

关键词： computation offloading cloud gaming games unity 3D rendering

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Online Cloud-Based Battery Lifetime Estimation Framework for Smartphone Devices

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Procedia Computer Science 2017年 110卷 70-77页

作者： Raja Wasim Ahmad Raja Sehrab Bashir Sharjil Saeed Yangsun Lee Kwangman Ko Yunsik Son COMSATS Institute of Information Technology Pakistan Department of Software Engineering University Malaya Malaysia Department of Computer Science and IT University of AJK Dept. of Computer Engineering Sekyungongguk University South Korea Dept. of Computer Engineering Sanji University South Korea Dept. of Computer Engineering Dongguk University South Korea

Smartphones are resource constrained external battery operated devices. The resources of smartphone devices such as a battery, CPU, and RAM are very low compared to the desktop server. However, the requirements of smartphone users are growing tremendously. As a result, smartphone applications perform rich functionality to enrich user experience. However, due to increase in the execution capacity of smartphone applications, smartphone battery lifetime minimizes. This study proposes a cloud-based framework that estimates battery lifetime of a smartphone device. Moreover, it overviews the theoretical design of computational offloading framework to present an application area for the proposed work. Finally, it presents preliminary results to evaluate the proposed framework.

关键词： Mobile Computing Cloud Computing computation offloading Battery Lifetime Estimation Energy Optimization

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