Energy-efficient and delay-aware distributed routing with cooperative transmission for Internet of Things

被引:17
作者
Wen, Shaojie [1 ,2 ]
Huang, Chuanhe [1 ,2 ]
Chen, Xi [1 ,2 ]
Ma, Jianhua [3 ]
Xiong, Naixue [4 ]
Li, Zongpeng [1 ,2 ]
机构
[1] Wuhan Univ, State Key Lab Software Engn, Comp Sch, Wuhan, Hubei, Peoples R China
[2] Collaborat Innovat Ctr Geospatial Technol, Wuhan, Hubei, Peoples R China
[3] Hosei Univ, Sch comp & Informat Sci, Tokyo, Japan
[4] Colorado Tech Univ, Sch Comp Sci, Colorado Springs, CO USA
基金
美国国家科学基金会;
关键词
IoT and cyber-enabled applications; Distributed routing; Cooperative transmission; Delay constraint; POWER ALLOCATION; NETWORKS;
D O I
10.1016/j.jpdc.2017.08.002
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
As an important part of IoT, Flying ad hoc networks (FANETs) can provide communication services for different devices in IoT and cyber-enabled applications. However, mobility of unmanned aerial vehicle (UAV) in FANETs results in wireless link unpredictability and increases the complexity of routing algorithms in these applications, especially for real-time routing. In this work, we propose an adaptive distributed routing method with cooperative transmission to effectively solve the problem presented above, in which the transmitters only use local information to transmit packets with help from their cooperative nodes. We formulate a corresponding mathematical optimization problem, in which the objective is to maximize network utility, while keeping end-to-end delay below a prescribed threshold. To support variations in network characteristics and channel states, we estimate the single-hop delay at relay node for each transmission, and use the dual decomposition method to transform the centralized problem into a distributed problem which allows the relay nodes to use only the local channel information and estimated delays to route the packets. Simulation results show that the proposed routing method can improve network performance in terms of energy efficiency, throughput and end-to-end delay. (C) 2017 Elsevier Inc. All rights reserved.
引用
收藏
页码:46 / 56
页数:11
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