Distributed ant colony optimization for minimum energy broadcasting in sensor networks with realistic antennas

被引:7
作者
Hernandez, Hugo [1 ]
Blum, Christian [1 ]
机构
[1] Univ Politecn Cataluna, ALBCOM Res Grp, ES-08034 Barcelona, Spain
关键词
Minimum energy broadcast; Distributed computing; Ant colony optimization; TREES;
D O I
10.1016/j.camwa.2012.02.035
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
One of the important tasks in wireless sensor networks is broadcasting, which arises when a sender node has to communicate information to all the other nodes of the network. In order to save energy, which is often a limited resource, broadcasting has to be done efficiently from an energy perspective. Energy efficiency can hereby be achieved by adjusting the transmission power levels of the sensor nodes' antennas. This classical problem is known as the minimum energy broadcast (MEB) problem. In this work we deal with a generalization of this problem which is known as the minimum energy broadcast problem in sensor networks with realistic antennas (MEBRA). The difference to the classical MEB problem is to be found in a more realistic antenna model. In this work we propose a distributed ant colony optimization algorithm for solving the MEBRA problem. The experimental evaluation of the proposed algorithm shows that it generally improves over the centralized version of a classical heuristic. Moreover, depending on the exact antenna model used, the results of the distributed ant colony optimization algorithm are very close to the results of the centralized algorithm version. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:3683 / 3700
页数:18
相关论文
共 23 条
[1]  
agalj M. C., 2002, P 8 ANN INT C MOB CO, P172
[2]   A survey on sensor networks [J].
Akyildiz, IF ;
Su, WL ;
Sankarasubramaniam, Y ;
Cayirci, E .
IEEE COMMUNICATIONS MAGAZINE, 2002, 40 (08) :102-114
[3]   Nested Partitioning for the Minimum Energy Broadcast Problem [J].
Al-Shihabi, Sameh ;
Merz, Peter ;
Wolf, Steffen .
LEARNING AND INTELLIGENT OPTIMIZATION, 2008, 5313 :1-+
[4]   The hyper-cube framework for ant colony optimization [J].
Blum, C ;
Dorigo, M .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2004, 34 (02) :1161-1172
[5]  
[陈丽琼 CHEN Li-qiong], 2009, [高分子通报, Polymer Bulletin], P1
[6]  
Das A. K., 2002, P IEEE CAS WORKSH WI
[7]  
Das AK, 2003, GLOB TELECOMM CONF, P523
[8]  
Guo S, 2004, IEEE IPCCC, P637
[9]   Energy-aware multicasting in wireless ad hoc networks: A survey and discussion [J].
Guo, Song ;
Yang, Oliver W. W. .
COMPUTER COMMUNICATIONS, 2007, 30 (09) :2129-2148
[10]   Ant colony optimization for multicasting in static wireless ad-hoc networks [J].
Hernández H. ;
Blum C. .
Swarm Intelligence, 2009, 3 (2) :125-148