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Book ChapterDOI

AFMEACI: A Framework for Mobile Execution Augmentation Using Cloud Infrastructure

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TLDR
A scalable, fault-tolerant framework for dynamically and optimally partition the application using the proposed genetic algorithm to alleviate the resource scarcity problem of the mobile devices.
Abstract
Due to advancement in mobile device technology, mobile devices are becoming an inevitable part of human lives. In context of running massive applications on mobile devices, users can’t utilize the potential of mobile devices in an efficient manner since mobile devices are constrained by processing power, memory requirements and battery capacity. To alleviate this resource scarcity problem of the mobile devices, mobile cloud computing is the most promising solution which combines the technologies from both the mobile computing and the cloud computing. The execution of heavy application on mobile devices is augmented by powerful and resource-abundant cloud servers. This is achieved by partitioning an application into tasks such that the computational intensive tasks are offloaded to cloud and after executing task on cloud, results are sent back to mobile device, referred to as computation offloading. In this paper, we have put forth a scalable, fault-tolerant framework for dynamically and optimally partition the application using our proposed genetic algorithm.

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Proceedings ArticleDOI

A survey on Data Analytic Platforms for Internet of Things

TL;DR: The fully matured cloud computing technology best fit the scenario of IoT and big data analytics offering powerful resources to carry out analytical and management tasks.

Rethinking Trust in E-Commerce in a Context-aware, Mobile World

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Journal ArticleDOI

Adaptive Proximate Computing Framework for Mobile Resource Augmentation

TL;DR: This research work provides a feasible solution for the development of resource intensive mobile application and its accessibility by mobile user regardless of the resource scarcity of mobile device.
Journal ArticleDOI

Comparative study of Transformer and LSTM Network with attention mechanism on Image Captioning

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References
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Proceedings ArticleDOI

MAUI: making smartphones last longer with code offload

TL;DR: MAUI supports fine-grained code offload to maximize energy savings with minimal burden on the programmer, and decides at run-time which methods should be remotely executed, driven by an optimization engine that achieves the best energy savings possible under the mobile device's current connectivity constrains.
Proceedings ArticleDOI

CloneCloud: elastic execution between mobile device and cloud

TL;DR: The design and implementation of CloneCloud is presented, a system that automatically transforms mobile applications to benefit from the cloud that enables unmodified mobile applications running in an application-level virtual machine to seamlessly off-load part of their execution from mobile devices onto device clones operating in a computational cloud.
Proceedings ArticleDOI

ThinkAir: Dynamic resource allocation and parallel execution in the cloud for mobile code offloading

TL;DR: This paper proposes ThinkAir, a framework that makes it simple for developers to migrate their smartphone applications to the cloud and enhances the power of mobile cloud computing by parallelizing method execution using multiple virtual machine (VM) images.

Augmented smartphone applications through clone cloud execution

TL;DR: This paper proposes a novel architecture that addresses challenges via seamlessly--but partially--off-loading execution from the smartphone to a computational infrastructure hosting a cloud of smartphone clones, called CloneCloud.
Journal ArticleDOI

A framework for partitioning and execution of data stream applications in mobile cloud computing

TL;DR: This work studies the computation partitioning, which aims at optimizing the partition of a data stream application between mobile and cloud such that the application has maximum speed/throughput in processing the streaming data.
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