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针对无线传感器网络中的服务组合应用,分析具有安全约束的综合服务质量。

Analyzing comprehensive QoS with security constraints for services composition applications in wireless sensor networks.

作者信息

Xiong Naixue, Wu Zhao, Huang Yannong, Xu Degang

机构信息

School of Mathematics and Computer Science, Hubei University of Arts and Science, Xiangyang 441053, China.

出版信息

Sensors (Basel). 2014 Dec 1;14(12):22706-36. doi: 10.3390/s141222706.

DOI:10.3390/s141222706
PMID:25470488
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4299035/
Abstract

Services composition is fundamental to software development in multi-service wireless sensor networks (WSNs). The quality of service (QoS) of services composition applications (SCAs) are confronted with severe challenges due to the open, dynamic, and complex natures of WSNs. Most previous research separated various QoS indices into different fields and studied them individually due to the computational complexity. This approach ignores the mutual influence between these QoS indices, and leads to a non-comprehensive and inaccurate analysis result. The universal generating function (UGF) shows the speediness and precision in QoS analysis. However, only one QoS index at a time can be analyzed by the classic UGF. In order to efficiently analyze the comprehensive QoS of SCAs, this paper proposes an improved UGF technique-vector universal generating function (VUGF)-which considers the relationship between multiple QoS indices, including security, and can simultaneously analyze multiple QoS indices. The numerical examples demonstrate that it can be used for the evaluation of the comprehensive QoS of SCAs subjected to the security constraint in WSNs. Therefore, it can be effectively applied to the optimal design of multi-service WSNs.

摘要

服务组合是多服务无线传感器网络(WSN)软件开发的基础。由于WSN的开放性、动态性和复杂性,服务组合应用(SCA)的服务质量(QoS)面临严峻挑战。由于计算复杂性,大多数先前的研究将各种QoS指标划分为不同领域并分别进行研究。这种方法忽略了这些QoS指标之间的相互影响,导致分析结果不全面且不准确。通用生成函数(UGF)在QoS分析中显示出快速性和精确性。然而,经典UGF一次只能分析一个QoS指标。为了有效分析SCA的综合QoS,本文提出了一种改进的UGF技术——向量通用生成函数(VUGF),它考虑了包括安全性在内的多个QoS指标之间的关系,并且可以同时分析多个QoS指标。数值例子表明,它可用于评估WSN中受安全约束的SCA的综合QoS。因此,它可以有效地应用于多服务WSN的优化设计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/c2a6713c631d/sensors-14-22706f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/34043e9b8b95/sensors-14-22706f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/cc4bbfc06c1e/sensors-14-22706f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/09a291453cc7/sensors-14-22706f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/e4abe9cbf4db/sensors-14-22706f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/76246a7b7287/sensors-14-22706f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/9fd5c2e5e4b4/sensors-14-22706f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/ea7d75de1e20/sensors-14-22706f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/1ab58d799ad0/sensors-14-22706f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/4421ac71f24a/sensors-14-22706f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/c2a6713c631d/sensors-14-22706f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/34043e9b8b95/sensors-14-22706f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/cc4bbfc06c1e/sensors-14-22706f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/09a291453cc7/sensors-14-22706f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/e4abe9cbf4db/sensors-14-22706f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/76246a7b7287/sensors-14-22706f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/9fd5c2e5e4b4/sensors-14-22706f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/ea7d75de1e20/sensors-14-22706f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/1ab58d799ad0/sensors-14-22706f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/4421ac71f24a/sensors-14-22706f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44c0/4299035/c2a6713c631d/sensors-14-22706f10.jpg

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