Context-Aware Computation Offloading for Mobile Cloud Computing: Requirements Analysis, Survey and Design Guideline

Orsini, Gabriel; Bade, Dirk; Lamersdorf, Winfried

doi:10.1016/j.procs.2015.07.169

Cited by 28 publications

(12 citation statements)

References 8 publications

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“…However, as stated by [59], while coexistence and deployment are reaching high results, adaptation scenarios and ease of use require further investigation. For this reason the research can reasonably be focused on an effective distributed resource management strategy, hosted on the mobile device.…”

Section: Overall Results and Limitationsmentioning

confidence: 99%

“…Regarding the development of Mobile Cloud Computingapplications, Orsini et al [59] identified six main requirements: availability, portability, portability, scalability, usability, maintainability and security. Among these, to reach the scalability requirement, one of the most used approach is to partition the application into tasks of different granularity level, although it involves some major difficulties such as:…”

Section: Computation Offloading For Mobile Systemsmentioning

confidence: 99%

See 1 more Smart Citation

Towards Distributed Mobile Computing

Massari

Zanella

Fornaciari

2016

2016 Mobile System Technologies Workshop (MST)

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Abstract-In the latest years, we observed an exponential growth of the market of the mobile devices. In this scenario, it assumes a particular relevance the rate at which mobile devices are replaced. According to the International Telecommunicaton Union in fact, smart-phone owners replace their device every 20 months, on average. The side effect of this trend is to deal with the disposal of an increasing amount of electronic devices which, in many cases, are still working. We believe that it is feasible to recover such an unexploited computational power. Through a change of paradigm in fact, it is possible to achieve a two-fold objective: 1) extend the mobile devices lifetime; 2) enable a new opportunity to speed up mobile applications. In this paper we aim at providing a survey of state-of-art solutions aim at going in the direction of a Distributed Mobile Computing paradigm. We put in evidence the challenges to be addressed in order to implement this paradigm and we propose some possible future improvements.

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Section: Overall Results and Limitationsmentioning

confidence: 99%

Section: Computation Offloading For Mobile Systemsmentioning

confidence: 99%

Towards Distributed Mobile Computing

Massari

Zanella

Fornaciari

2016

2016 Mobile System Technologies Workshop (MST)

View full text Add to dashboard Cite

show abstract

“…In order to develop a comprehensive list of general requirements for MEC applications, we started bottom‐up with adapted ISO requirements and merged them from a top‐down perspective with specific requirements inferred from the application scenarios presented in the previous section to ensure the requirements have practical relevance. The resulting list is summarized in the following (further details can be found in the work of Orsini et al).…”

Section: Main Requirementsmentioning

confidence: 99%

CloudAware: Empowering context‐aware self‐adaptation for mobile applications

Orsini

Bade

Lamersdorf

2017

Trans Emerging Tel Tech

Self Cite

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Mobile devices are already woven into our everyday life, and we became accustomed that mobile applications assist us in a multitude of daily activities. With the rise of the Internet of Things, new opportunities to further automatize tedious tasks open up. New functional and user experience requirements demand for further resources and new ways to acquire these, because mobile devices remain comparatively limited in terms of, eg, computation, storage, and battery life. To face these challenges, current approaches augment mobile applications either with cloud resources (mobile cloud computing) or with resources near the mobile device at the logical edge of the network (mobile edge computing) onto which tasks can be offloaded during runtime. However, this does not automatically solve the conflict between resource demands and good user experience, as current solutions prove. It is the dynamically changing context that makes for good or bad offloading strategies. In this paper, we corroborate this finding by first evaluating 40 existing solutions based on a requirements catalogue derived from several application scenarios as well as the International Organization for Standardization/International Electrotechnical Commission criteria for software quality. Afterward, we present CloudAware, which is a mobile cloud computing/mobile edge computing middleware that supports automated context‐aware self‐adaptation techniques that ease the development of elastic, scalable, and context‐adaptive mobile applications. Moreover, we present a qualitative evaluation of our concepts and quantitatively evaluate different offloading scenarios using real usage data to prove that mobile applications indeed benefit from context‐aware self‐adaptation techniques. Finally, we conclude with a discussion of open challenges.

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“…Chen [7] have also suggested a decentralized computation offloading game in which resource constrained mobile devices wait and learn about the state of surrogates before offloading computational tasks depending on their resource availability. Also Orsini et al [21] have proposed a context-aware mechanism for computation offloading in which mobile devices decide when and how to offload based on their state and resource capacities. Moreover, Cuervo et al [6] presented a fine grained energy aware computation offloading mechanism dubbed MAUI.…”

Section: Related Workmentioning

confidence: 99%

Resilient Framework for Distributed Computation Offloading: Overview, Challenges and Issues

Agbesi¹,

Abdulai²,

Ferdinand³

et al. 2017

ijacsa

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Abstract-Gradually, mobile and smart computing devices are becoming pervasive and prevalent in society and also increasingly being used to undertake the daily tasks and business activities of individuals and organizations worldwide as compared to their desktop counterparts. But these mobile and smart computing devices are resource constrained and sometimes lack the needed computational capacities; thus, memory, energy, storage, and processor to run the plethora of resource intensive applications available for mobile users. There is a lot of benefit of offloading resource demanding applications and intensive computations from mobile devices to other systems with higher resource capacities in the cloud. Mobile cloud computing is a form of cloud computing that seeks to enhance the capacity and capabilities of mobile and smart computing devices by enabling mobile devices to offload some computational tasks to the cloud for processing which otherwise would have been a challenge. The study setup an experiment to investigate computation offloading for mobile devices. The study also presented an energy model for computation offloading. It was observed during the experiment that by offloading intensive applications from mobile and smart computing devices to other systems with higher resource capacities, a great amount of resource efficiency is achieved.

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Context-Aware Computation Offloading for Mobile Cloud Computing: Requirements Analysis, Survey and Design Guideline

Cited by 28 publications

References 8 publications

Towards Distributed Mobile Computing

Towards Distributed Mobile Computing

CloudAware: Empowering context‐aware self‐adaptation for mobile applications

Resilient Framework for Distributed Computation Offloading: Overview, Challenges and Issues

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