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检索条件"主题词=computation offloading"

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Distributed Mobile Cloud Computing: Joint Optimization of Radio and computational Resources

Distributed Mobile Cloud Computing: Joint Optimization of Ra...

引用

IEEE Global Communications Conference (GLOBECOM)

作者： Sardellitti, S. Barbarossa, S. Scutari, G. Sapienza Univ Rome Dept Informat Engn Elect & Telecommun Rome Italy SUNY Buffalo Dept Elect Engn Buffalo NY USA

ISBN: (纸本)9781479974702

We consider a scenario composed by multiple mobile users asking for computation offloading of their applications to a set of cloud servers. A set of radio access points, small cell base stations possibly coexisting with macro base stations, are available to provide radio proximity access to fixed computational resources. Our objective is to find the optimal assignment of each mobile user to a cloud server through the most convenient base station and, contextually, the optimal MIMO precoding matrices and computational rates (virtual machines) to each user, under latency constraints dictated by the users Quality of Experience (QoE). The radio resources assigned to users belonging to the same cell are orthogonal to each other, whereas users of different cells might interfere against each other. The latency constraint imposes a strict relationship between the time spent for transferring the program execution from the mobile device to the fixed server (and viceversa) and the time needed to execute the computation. To properly exploit this relationship, we formulate the computation offloading problem as a joint optimization of the radio and computational resources, with the objective of minimizing the overall energy consumption, at the mobile terminal side, while meeting the latency constraints. The resulting optimization problem is nonconvex in both the objective function and in the constraints. Nevertheless, by hinging on successive convex approximation techniques, we propose an iterative algorithm able to converge to a local optimal solution of the original nonconvex problem.

关键词： computation offloading cloud computing distributed resource allocation successive convex approximation

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Bring the Cloud to Your Mobile: Transparent offloading of HTML5 Web Workers 6

Bring the Cloud to Your Mobile: Transparent Offloading of HT...

引用

6th IEEE International Conference on Cloud Computing Technology and Science (CloudCom)

作者： Zbierski, Maciej Makosiej, Przemyslaw Samsung R&D Inst Poland Warsaw Poland

ISBN: (纸本)9781479940936

computation offloading is one of the approaches used for increasing application efficiency and decreasing energy consumption on consumer devices, an issue especially important for mobile appliances. While some such systems have been previously designed, very little research has been directed towards offloading code from web applications, an alternative to native solutions recently gaining in popularity. In this paper we attempt to narrow down this gap by presenting the first practical system for offloading HTML5 web workers from mobile web applications. The system is transparent to the programmer, i.e. does not require any additional modifications to the original application to indicate which code parts should be offloaded. The results of the experiments with various sample applications have shown that for sufficiently complicated computations the offloading system can decrease both the processing time and energy consumption by even several hundred percent.

关键词： computation offloading mobile cloud computing migration JavaScript HTML5 web workers

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Distributed Joint Optimization of Radio and computational Resources for Mobile Cloud Computing 3

Distributed Joint Optimization of Radio and Computational Re...

引用

3rd IEEE International Conference on Cloud Networking (CloudNet)

作者： Sardellitti, S. Scutari, G. Barbarossa, S. Sapienza Univ Rome Dept Informat Engn Elect & Telecommun Rome Italy Sapienza Univ Rome Dept Informat Engn Elect & Telecommun Rome Italy SUNY Buffalo Dept Elect Engn Buffalo NY USA

ISBN: (纸本)9781479927302

Mobile computation offloading of computational intensive tasks from mobile devices to surrogate cloud servers has been recently envisaged as a promising technique to enhance the computational capacity of the mobile devices. Within this framework we consider a MIMO multicell system wherein several Mobile Users (MUs) ask for computation offloading to a common cloud server through their femto-access points. We formulate the computation offloading problem as a joint optimization of the radio and computational resources in order to minimize the overall users' energy consumption while meeting the latency constraints imposed by the applications. To solve this non-convex problem we hinge on successive convex approximation techniques by showing that the original problem can be decomposed in parallel convex subproblems. Hence we devise an iterative algorithm which can be implemented in a distributed manner across the access points through dual/primal decomposition techniques requiring limited coordination/signaling with the cloud.

关键词： computation offloading cloud computing distributed resource allocation successive convex approximation

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PEFC: Performance Enhancement Framework for Cloudlet in Mobile Cloud Computing

PEFC: Performance Enhancement Framework for Cloudlet in Mobi...

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IEEE International Symposium on Robotics and Manufacturing Automation (IEEE-ROMA)

作者： Whaiduzzaman, Md Gani, Abdullah Naveed, Anjum Univ Malaya Fac Comp Sci & Informat Technol Ctr Mobile Cloud Comp Res Kuala Lumpur Malaysia

ISBN: (纸本)9781479957651

Augmenting the computing capability to the distant cloud help us to envision a new computing era named as mobile cloud computing (MCC). By leveraging the cloud resources mobile user can computation time and energy benefit. However, distant cloud has several limitations such as communication delay and bandwidth make us to think for closer cloud which brings the idea of proximate cloud of cloudlet. Cloudlet has distinct advantages and is free from several limitations of distant cloud. However, limited resources of cloudlet negatively impact the cloudlet performance with the increasing number of substantial users. In this paper, we propose a framework which helps to enhance the finite resource cloudlet performance by increasing cloudlet resources. Our aim is to increase the cloudlet performance with this limited cloudlet resource and make the better user experience for the cloudlet user in mobile cloud computing. We analyze and explain the each section of the proposed framework. In addition, we also list the important features and salient advantages of Performance Enhancement Framework of Cloudlet (PEFC).

关键词： mobile cloud computing cloudlet resources computation offloading performance enhancement

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Optimizing Performance and Fault Tolerance Through Cloud based Adaptive Replication for Mobile Applications 2

Optimizing Performance and Fault Tolerance Through Cloud bas...

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2nd International Conference on Systems and Informatics (ICSAI)

作者： Naeem, Tayyiba Sadik, Sarmad NUST Mil Coll Signals Dept Comp Software Engn Islamabad Pakistan

ISBN: (纸本)9781479954582

Cloud Computing is one of the important emerging technologies, which is considered as computing infrastructure of the next generation. Mobile cloud computing is a research paradigm that integrates cloud computing into mobile computing. This integration raises many challenges like performance, battery time, efficiency, network bottlenecks etc. In this paper, issues addressed include performance and fault tolerance. The emphasis is to improve and optimize the performance and fault tolerance characteristics of mobile applications by method of replicating their resources or computation on cloud platform at back end. As a proof of concept, a prototype will be developed. It will be designed for managing and transporting the necessary contents of mobile application from mobile phone/tablets to cloud based platform. This framework or middleware will be responsible for offloading the computation intensive code on the cloud resources as well as adaptive or dynamic replication of data on the cloud resources. This middleware will be designed for android based phones using the java framework. An android application related to N-Queen problem will also be developed which will use this middleware. Google app engine will be used as back end cloud which will be used to perform data computation as well as for storage of results. The Mobile application's developers would be able to use this middleware by making slight changes in their application's code.

关键词： Mobile Cloud Computing Android computation offloading Middleware Google app engine

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Effect of computation Offload on Performance and Energy Consumption of Mobile Face Recognition

Effect of Computation Offload on Performance and Energy Cons...

引用

IEEE Workshop on Signal Processing Systems (SiPS)

作者： Sumi, Nanoka Baba, Akiya Moshnyaga, Vasily G. Fukuoka Univ Grad Sch Engn Jonan Ku 8-19-1 Nanakuma Fukuoka 8140180 Japan

ISBN: (纸本)9781479965885

computation offloading is a paramount technology to leverage network resources for mobile devices. This paper studies effect of computation offloading on efficiency of mobile face recognition. It compares offloading alternatives used in existing mobile face-recognition system and reports on their efficiency in terms of energy consumption, processing time and recognition accuracy. The offloading method which leads to the best energy-performance tradeoff is outlined.

关键词： face recognition network-based system computation offloading performance energy consumption analysis

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Improving the Performance of Mobile Applications Using Cloud Computing 9

Improving the Performance of Mobile Applications Using Cloud...

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9th International Conference on Informatics and Systems

作者： Elgendy, Ibrahim A. El-Kawkagy, Mohamed Keshk, Arabi Menoufia Univ Dept Comp Sci Fac Comp & Informat Shibin Al Kawm Al Minufiyah Egypt

ISBN: (纸本)9789774036897

Recently, smartphones set to become the fastest spreading technology. Although smartphones support wide range of applications like augmented reality, face detection, image processing and speech recognition, they are resource-constrained devices with limited computation power and energy. Therefore, researchers trend to solve this problem by offloading these applications or part of it to execute remotely on rich resource such as cloud computing. This paper will introduce a novel framework to improve the performance of mobile applications and save battery consumption. This framework offloads only the intensive methods. The offloading process depends on the module so-called dynamic offloader. This module decide satrun time whether the application's methods will run locally on the mobile or offload to the cloud. The experimental studies are applied on three different applications and the results show that the proposed framework improves the performance and saves energy of mobile applications.

关键词： Smartphones Android computation offloading Mobile Cloud Computing Battery Consumption

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Augmented execution in mobile cloud computing: A survey

Augmented execution in mobile cloud computing: A survey

引用

International Conference on Electronic Systems, Signal Processing, and Computing Technologies, ICESC 2014

作者： Jagtap, V.S. Pawar, Karishma Vikas Pathak, Ajeet Ram Department of Computer Engineering Maharashtra Institute of Technology Pune India Department of Computer Engineering G. H. Raisoni College of Engineering Pune India

ISBN: (纸本)9781479921027

As the technology is developing with a huge rate, the functionality of smartphone is also getting higher. But the smartphones have some resource constraints like processing power, battery capacity, limited bandwidth for connecting to the Internet, etc. Therefore, to improve the performance of smartphone in terms of processing power, battery and memory, the technology namely, augmented execution is the best solution in the mobile cloud computing (MCC) scenario. Mobile cloud computing works as the combination of mobile computing and cloud computing. Augmented execution alleviates the problem of resource scarcity of smartphone. To get the benefits from the resource-abundant clouds, massive computation intensive tasks are partitioned and migrated to the cloud side for the execution. After executing the task at the cloud side, the results are sent back to the smartphone. This method is called as the computation offloading. The given survey paper focuses on the partitioning techniques in mobile cloud computing. © 2014 IEEE.

关键词： computation offloading

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DroidCloudlet: Towards Cloudlet-based Computing using Mobile Devices

DroidCloudlet: Towards Cloudlet-based Computing using Mobile...

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5th International Conference on Information and Communication Systems (ICICS)

作者： El-Derini, Mohamed Nazih Aly, Hussien H. El-Barbary, Abd El-Hameed G. El-Sayed, Layla A. A. Pharos Univ Educ & Student Affairs Alexandria Egypt Univ Alexandria Dept Comp & Syst Engn Alexandria Egypt

ISBN: (纸本)9781479930234

With the increasing ubiquity of mobile devices with computational capabilities comparable to many personal computers, while at the same time, wireless connectivity is almost available everywhere, researchers started to explore how to make use of that huge amount of potential aggregated computing resources. However, mobile devices still suffer short battery life, especially with their newly large screens and the spread use of applications which need GPS or sensors' readings. Moreover, not all mobile devices are capable of running rich- media and data-intensive applications. offloading to the cloud is a promising solution, however, long WAN latencies and the larger amount of consumed energy using cellular data connectivity guided researchers to bring cloud capabilities to local area networks to form cloudlets. In this paper, we propose a cloudlet architecture in which, any available mobile device with abundant processing or power resources, can participate as a server. offloading is carried out dynamically at runtime according to specific policies that target reducing execution time and/or saving battery. We also propose a scheme to enable applications' developers to select which parts of their code should be offloaded and parallelized among different available servers.

关键词： mobile cloud computing computation offloading cloudlet energy management performance

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Towards a new model for cyber foraging 13

Towards a new model for cyber foraging

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13th Workshop on Adaptive and Reflective Middleware, ARM 2014, co-located with ACM/IFIP/USENIX International Middleware Conference

作者： Lima, Diogo Miranda, Hugo Taïani, François LaSIGE Universidade de Lisboa Lisbon Portugal IRISA ESIR Université de Rennes 1 Rennes France

ISBN: (纸本)9781450332323

Cyber foraging seeks to expand the capabilities and battery life of mobile devices by offloading intensive computations to nearby computing nodes (the surrogates). Although promising, current approaches to cyber foraging tend to impose a strict separation between the application state maintained on the mobile device, and data processed on the surrogates. In this paper, we argue that this separation limits the applicability of cyber foraging, and explore how state sharing could be implemented in practice. Copyright 2014 ACM.

关键词： computation offloading

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