Service Selection Algorithm Based on Dynamic Assessment for Web of Things

HE Xiu-qing; WANG Ying-hui

doi:10.3969/j.issn.0372-2112.2013.01.021

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Service Selection Algorithm Based on Dynamic Assessment for Web of Things

更新时间：2025-07-16

- Service Selection Algorithm Based on Dynamic Assessment for Web of Things
- Acta Electronica Sinica Vol. 41, Issue 1, Pages: 117-122(2013)
- 作者机构：
  
  1. 西安理工大学计算机科学与工程学院,陕西,西安,710048
  2. 陕西师范大学计算机科学学院,陕西,西安,710062
  3. 西安理工大学计算机科学与工程学院陕西西安,710048
  4. 陕西师范大学计算机科学学院陕西西安,710062
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61072151, No.61003061);Research Fund for the Doctoral Program of Higher Education of China (No.20090202120006);Major Scientific and Technological Innovation Project of Shaanxi Province (No.2009ZKC02-08);Industrialization Cultivation Project of Shaanxi Education Department (No.09JC08)
- DOI：10.3969/j.issn.0372-2112.2013.01.021
  CLC： TP311.5
- Published：2013
- 稿件说明：
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HE Xiu-qing, WANG Ying-hui. Service Selection Algorithm Based on Dynamic Assessment for Web of Things[J]. Acta Electronica Sinica, 2013, 41(1): 117-122.
DOI：

HE Xiu-qing, WANG Ying-hui. Service Selection Algorithm Based on Dynamic Assessment for Web of Things[J]. Acta Electronica Sinica, 2013, 41(1): 117-122. DOI： 10.3969/j.issn.0372-2112.2013.01.021.

摘要

对于物联网WoT面向服务SOA的软件架构成中基于服务质量QoS选择最优服务的问题

给出了反馈控制的QoS属性向量动态更新过程和服务动态评价选择方法.基于WoT设备资源受限的特点

通过指数加权平均和以并发引用服务的客户端个数为价格因素的随机指数标记REM方式估计服务时间

在系统在线概率中加入服务相邻状态检测实现服务可用性的估计

基于偏好权值和QoS属性向量通过TOPSIS过程选择最优服务.NS-3.13的模拟实验结果表明基于QoS属性向量动态更新选择最优服务的准确性明显优于简单QoS属性向量.

Abstract

Due to WoT (Web of Things) is composed of numbers of resources-limited devices

it is a challenging work that the optimal web service is selected from a similar functionality service group based on the non-functional properties (QoS) without heavy interactive query process in SOA (Service Oriented Architecture).This work focus on the dynamic update process of QoS attributes vector and the optimal service selection algorithm based on the client's feedback in WoT.The service time is estimated by the REM (Random Exponential Marking) which use the concurrent clients number as the price index

and the exponentially weighted average of the current service expense and the previous record.The service availability is estimated by the online probability with the service state detection.The Empirical results based on NS-3.13 simulation show that the accuracy of optimal web service selection based on our presented approaches is significantly better than the simple QoS attributes.

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