An Algorithm to Discover Service Nodes for Mobility-Aware in the Internet of Things

您当前的位置：

首页 >

文章列表页 >

An Algorithm to Discover Service Nodes for Mobility-Aware in the Internet of Things

更新时间：2025-07-09

- An Algorithm to Discover Service Nodes for Mobility-Aware in the Internet of Things
- Vol. 45, Issue 12, Pages: 6-9(2011)
- 作者机构：
  
  1. 西安交通大学电子与信息工程学院,西安,710049
  2. 陕西省计算机网络重点实验室,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP393
- Online First：10 December 2011，
  
  Published：2011
- 稿件说明：
移动端阅览
An Algorithm to Discover Service Nodes for Mobility-Aware in the Internet of Things[J]. 2011, 45(12): 6-9.
DOI：

An Algorithm to Discover Service Nodes for Mobility-Aware in the Internet of Things[J]. 2011, 45(12): 6-9. DOI：

摘要

针对物联网移动感知场景中节点移动性、随机性在时间和空间两方面给数据感知、数据传递造成的问题

提出一种基于节点社会关系认知的目标区域感知服务节点发现算法.引入交互因子和距离因子对节点社会关系进行量化

构建节点移动概率表和凝聚子群

通过信任传递与社会关系最优路径树的计算

确定目标区域感知服务节点集.仿真实验表明

该算法缩短了移动节点间最短距离以及网络平均距离

提高了感知服务节点的发现效率

解决了稀疏网络的感知空洞问题

改善了物联网感知服务质量.

Abstract

An awareness algorithm to discover service nodes is proposed to deal with the problem of data-awareness and data-transmit in both time and space in mobility-aware of Internet of Things(IoT)

which is caused by nodes mobility and random. The algorithm bases on social relations cognition

and quantizes the social relation of all nodes by introducing interconnection factor and distance factor. Then

cohesive subgroups and a node-mobile probability table are constructed to predict the trace of mobile nodes. Finally

awareness service nodes in the objective regions are determined through trust-transference and probability tree calculation. Simulation experiments show that the proposed method effectively reduces both the shortest distance among mobile nodes and the network average distance

improves the way of date acquisition and increases the quality of awareness service in IoT.

关键词

Keywords

references

ATZORI L, IERA A, GIACOMO M. The internet of things: a survey[J]. Computer Networks, 2010, 54:2787-2805.

LANE N D, MILUZZO E, LU Hong, et al. A survey of mobile phone sensing[J].IEEE Communications Magazine, 2010,48(9):140-150.

YANG Shusen, YANG Xinyu, ZHANG Chao, et al. Using social network theory for modeling human mobility[J]. IEEE Network, 2010,24(5):6-13.

李小勇,桂小林. 可信网络中基于多维决策属性的信任量化模型[J]. 计算机学报, 2009, 32(3):405-416.

LI Xiaoyong, GUI Xiaolin. Trust quantitative model with multiple decision factors in trusted network[J]. Chinese Journal of Computers,2009, 32(3):405-416.

ZHANG Huiqi, DANTU R. Predicting social ties in mobile phone networks[C]∥Proceedings of 2010 IEEE Intelligence and Security Informatics. Piscataway,NJ,USA:IEEE, 2010:25-30.

GIANNOTTI F, NANNI M, PEDRESCHI D, et al. Mining mobility behavior from trajectory data[C]∥Proceedings of 12th IEEE International Conference on Computational Science and Engineering. Piscataway,NJ,USA:IEEE, 2009:948-951.

杨博, 刘大有, LIU Jiming, 等. 复杂网络聚类算法[J]. 软件学报, 2009, 20(1):54-66.

YANG Bo, LIU Dayou, LIU Jiming. Complex network clustering algorithms [J]. Journal of Software, 2009,20(1):54-66.

EAGLE N, PENTLAND A, LAZER D. Inferring friendship network structure by using mobile phone data[J]. Proceedings of the National Academy of Sciences, 2009,106(36):15274-15278.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Research and Practice on Evolutionary Networks

A Web Service Selecting Strategy Based on Prediction with Quality of Service Parameter Values

Real-Time Transport Protocol Payload for Guaranteeing the QoS of H.264 Video Delivery

An On-Demand Service Composition Method Based on Trustworthy Quality of Service

A Fast Calculation Method for Thermal Flow Fields in Transformer Windings Based on PI-DeepONet

Related Author

刘涛 1

钱德沛 1

王锐 2

栾钟治 2

黄泳翔 1

许大炜 1

翟社平 1

魏娟丽 2

Related Institution

National Key Laboratory of Integrate Services Network, Xidian University

Key Laboratory of Knowledge Management and Network-Based Manufacture, Hunan University of Science and Technology

⁰