Data Collection for Time-Critical Applications in the Low-Duty-Cycle Wireless Sensor Networks

Author:

Luo Shuyun1,Sun Yongmei1,Ji Yuefeng1

Affiliation:

1. State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, Beijing 100876, China

Abstract

In low-duty-cycle wireless sensor networks, wireless nodes usually have two states: active state and dormant state. The necessary condition for a successful wireless transmission is that both the sender and the receiver are awake. In this paper, we study the problem: How fast can raw data be collected from all source nodes to a sink in low-duty-cycle WSNs with general topology? Both the lower and upper tight bounds are given for this problem. We use TDMA scheduling on the same frequency channel and present centralized and distributed fast data collection algorithms to find an optimal solution in polynomial time when no interfering links happen. If interfering links happen, multichannel scheduling is introduced to eliminate them. We next propose a novel Receiver-based Channel and Time Scheduling (RCTS) algorithm to obtain the optimal solution. Based on real trace, extensive simulations are conducted and the results show that the proposed RCTS algorithm is significantly more efficient than the link schedule on one channel and achieves the lower bound. We also evaluate the proposed data collection algorithms and find that RCTS is time-efficient and suffices to eliminate most of the interference in both indoor and outdoor environment for moderate size networks.

Funder

National Natural Science Foundation of China

Publisher

SAGE Publications

Subject

Computer Networks and Communications,General Engineering

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3