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Toward Offering More Useful Data Reliably to Mobile Cloud From Wireless Sensor Network

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TLDR
A novel WSN-MCC integration scheme named TPSS is proposed, which consists of two main parts: time and priority-based selective data transmission (TPSDT) for WSN gateway to selectively transmit sensory data that are more useful to the cloud, considering the time and priorities of the data requested by the mobile user.
Abstract
The integration of ubiquitous wireless sensor network (WSN) and powerful mobile cloud computing (MCC) is a research topic that is attracting growing interest in both academia and industry. In this new paradigm, WSN provides data to the cloud and mobile users request data from the cloud. To support applications involving WSN-MCC integration, which need to reliably offer data that are more useful to the mobile users from WSN to cloud, this paper first identifies the critical issues that affect the usefulness of sensory data and the reliability of WSN, then proposes a novel WSN-MCC integration scheme named TPSS, which consists of two main parts: 1) time and priority-based selective data transmission (TPSDT) for WSN gateway to selectively transmit sensory data that are more useful to the cloud, considering the time and priority features of the data requested by the mobile user and 2) priority-based sleep scheduling (PSS) algorithm for WSN to save energy consumption so that it can gather and transmit data in a more reliable way. Analytical and experimental results demonstrate the effectiveness of TPSS in improving usefulness of sensory data and reliability of WSN for WSN-MCC integration.

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Citations
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Proceedings ArticleDOI

Sensor Cloud: Integrating Wireless Sensor Networks with Cloud Computing

TL;DR: Benefits of using sensor cloud, the integration of WSN with cloud computing, which offers multiple applications running on each sensor node concurrently with the help of virtualization are described.
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TL;DR: A Category-based Context-aware and Recommendation incentive-based reputation Mechanism (CCRM) is proposed to defend against internal attacks and enhance data veracity in MCC.
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Research on reliability analysis of computer network based on intelligent cloud computing method

TL;DR: A reliability analysis method of computer network based on intelligent cloud computing method is proposed that is integrated with the theoretical idea of analytic hierarchy process and shows that it is highly accurate and robust.
Proceedings ArticleDOI

Towards Integration of Wireless Sensor Networks and Cloud Computing

TL;DR: The analytical and experimental results conducted in the work show that the approaches proposed can effectively relieve the corresponding research problem and it is hoped this work can attract more researches into WSN-CC integration to make it develop faster and better.
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Flocking of Mobile Agents Using a New Interaction Model: A Cyber-Physical Perspective

TL;DR: The proposed flocking law can react to change of communication environments and guarantee the optimal communication link between agents and the stability and convergence of the flocking system are analyzed with nonsmooth techniques.
References
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Wireless sensor networks: a survey

TL;DR: The concept of sensor networks which has been made viable by the convergence of micro-electro-mechanical systems technology, wireless communications and digital electronics is described.
Journal ArticleDOI

A Survey of Mobile Cloud Computing Application Models

TL;DR: The mobile cloud architecture, offloading decision affecting entities, application models classification, the latest mobile cloud application models, their critical analysis and future research directions are presented.
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A Survey on Sensor-Cloud: Architecture, Applications, and Approaches

TL;DR: This paper presents a comprehensive study of representative works on Sensor-Cloud infrastructure, which will provide general readers an overview of the Sensor- Cloud platform including its definition, architecture, and applications.
Journal ArticleDOI

Underground coal mine monitoring with wireless sensor networks

TL;DR: The design of a Structure-Aware Self-Adaptive WSN system, SASA, is discussed, able to rapidly detect structure variations caused by underground collapses, and a sound and robust mechanism for efficiently handling queries under instable circumstances is developed.
Journal Article

Underground coal mine monitoring with wireless sensor networks - article no. 10

TL;DR: In this article, the authors discuss the design of a Structure-Aware Self-Adaptive WSN system, SASA, which is able to rapidly detect structure variations caused by underground collapses.
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