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. 2019 Nov 30;19(23):5281.
doi: 10.3390/s19235281.

Energy-Efficient Cluster-Head Selection for Wireless Sensor Networks Using Sampling-Based Spider Monkey Optimization

Jin-Gu Lee  1 , Seyha Chim  1 , Ho-Hyun Park  1
Affiliations

Energy-Efficient Cluster-Head Selection for Wireless Sensor Networks Using Sampling-Based Spider Monkey Optimization

Jin-Gu Lee et al. Sensors (Basel). .

Abstract

Extending the lifetime and stability of wireless sensor networks (WSNs) through efficient energy consumption remains challenging. Though clustering has improved energy efficiency through cluster-head selection, its application is still complicated. In existing cluster-head selection methods, the locations where cluster-heads are desirable are first searched. Next, the nodes closest to these locations are selected as the cluster-heads. This location-based approach causes problems such as increased computation, poor selection accuracy, and the selection of duplicate nodes. To solve these problems, we propose the sampling-based spider monkey optimization (SMO) method. If the sampling population consists of nodes to select cluster-heads, the cluster-heads are selected among the nodes. Thus, the problems caused by different locations of nodes and cluster-heads are resolved. Consequently, we improve lifetime and stability of WSNs through sampling-based spider monkey optimization and energy-efficient cluster head selection (SSMOECHS). This study describes how the sampling method is used in basic SMO and how to select cluster-heads using sampling-based SMO. The experimental results are compared to similar protocols, namely low-energy adaptive clustering hierarchy centralized (LEACH-C), particle swarm optimization clustering protocol (PSO-C), and SMO based threshold-sensitive energy-efficient delay-aware routing protocol (SMOTECP), and the results are shown in both homogeneous and heterogeneous setups. In these setups, SSMOECHS improves network lifetime and stability periods by averages of 13.4%, 7.1%, 34.6%, and 1.8%, respectively.

Keywords: SSMOECHS; WSNs; energy efficient CH selection; network lifetime; network stability; sampling SMO.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Flowchart of sampling-based spider monkey optimization (SMO).
Figure 2
Figure 2
Local leader phase in the sampling-based SMO.
Figure 3
Figure 3
Flowchart of sampling-based spider monkey optimization and energy-efficient cluster head (SSMOECHS) protocol. (a) Communication between the base station (BS) and nodes and (b) communication between cluster heads (CHs) and nodes (SSMO: sampling-based SMO and TDMA: time division multiple access).
Figure 3
Figure 3
Flowchart of sampling-based spider monkey optimization and energy-efficient cluster head (SSMOECHS) protocol. (a) Communication between the base station (BS) and nodes and (b) communication between cluster heads (CHs) and nodes (SSMO: sampling-based SMO and TDMA: time division multiple access).
Figure 4
Figure 4
SSMOECHS network topology and CH distribution.
Figure 5
Figure 5
Network topology results according to protocol. (a) Initial network topology and (b) results for every evaluated protocol. (Black lines, transmission node–CH; red lines, transmission CH–CH or CH–BS).
Figure 6
Figure 6
Alive nodes according to protocol execution round under homogeneous setup.
Figure 7
Figure 7
Energy consumption according to protocol execution round under homogeneous setup.
Figure 8
Figure 8
Alive nodes according to protocol execution round under heterogeneous setup.
Figure 9
Figure 9
Energy consumption according to protocol execution round under heterogeneous setup.
See this image and copyright information in PMC

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