Elephant Herding Optimization Algorithm for Wireless Sensor Network Localization Problem

被引:31
作者
Strumberger, Ivana [1 ]
Beko, Marko [2 ,3 ]
Tuba, Milan [4 ]
Minovic, Miroslav [5 ]
Bacanin, Nebojsa [1 ]
机构
[1] Singidunum Univ, Fac Informat & Comp, Danijelova 32, Belgrade 11000, Serbia
[2] ULHT, COPELABS, Lisbon, Portugal
[3] Univ Nova Lisboa, CTS, Caparica, Portugal
[4] State Univ Novi Pazar, Dept Tech Sci, Novi Pazar 36300, Serbia
[5] State Univ Belgrade, Fac Org Sci, Jove Ilica 154, Belgrade 11000, Serbia
来源
TECHNOLOGICAL INNOVATION FOR RESILIENT SYSTEMS (DOCEIS 2018) | 2018年 / 521卷
关键词
Elephant herding optimization; Swarm intelligence; Wireless sensor networks; Node localization problem; Metaheuristics;
D O I
10.1007/978-3-319-78574-5_17
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents elephant herding optimization algorithm (EHO) adopted for solving localization problems in wireless sensor networks. EHO is a relatively new swarm intelligence metaheuristic that obtains promising results when dealing with NP hard problems. Node localization problem in wireless sensor networks, that belongs to the group of NP hard optimization, represents one of the most significant challenges in this domain. The goal of node localization is to set geographical co-ordinates for each sensor node with unknown position that is randomly deployed in the monitoring area. Node localization is required to report the origin of events, assist group querying of sensors, routing and network coverage. The implementation of the EHO algorithm for node localization problem was not found in the literature. In the experimental section of this paper, we show comparative analysis with other state-of-the-art algorithms tested on the same problem instance.
引用
收藏
页码:175 / 184
页数:10
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