Abstract

In large-area wireless sensor networks with hierarchical cluster-based routing protocols, the average number of clusters, k, and the transmission range for the control messages, R, significantly affect the network lifespan. We analyze energy consumption in depth as a function of ( k , R ) , taking into account the energy dissipation of cluster head nodes and the member nodes, separately. To achieve joint optimization of ( k o p t , R o p t ) , we adopt derivative-free Nelder–Mead Simplex method. Computer simulations have shown that our approach effectively reduces energy consumption of sensor nodes in the process of clustering and data transmission in large-area sensor fields. Our optimization can be applied to existing cluster-based routing schemes to maximize their energy efficiency.

Highlights

  • Ad-hoc wireless sensor network (WSN) is a core technology of Internet of Things (IoT) with a wide range of applications including smart home networking and industrial internet of things (IIoT) [1,2].In IoT environments, the WSNs have large area with many sensor nodes compared with conventional application specific sensor networks

  • Referring to a survey paper over a hundred of cluster-based routing protocols [20], we found some approaches [21,22] to optimization of k, without compromising decentralized-clustering features

  • We model this probability as the spatial Poisson process, which is a stationary two-dimensional Poisson point process successfully adopted in modeling wireless sensor networks [23,24,25]: (n)

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Summary

Introduction

Ad-hoc wireless sensor network (WSN) is a core technology of Internet of Things (IoT) with a wide range of applications including smart home networking and industrial internet of things (IIoT) [1,2]. In DL-LEACH [13], the network is divided into several layers and the nodes in lower layers make distance-base determine whether they are to transmit data via CHs or to send data to the BS directly It has achieved a good improvement in energy consumption with moderate-size sensor networks. In LEACH algorithm [17] and most of its variants, nodes send control messages with maximum power to reach the entire network to ensure that the messages can be received by nodes farthest away in the sensor field Using this non-optimized max-distance transmission range of R for the control messages, together with another sub-optimized fixed value of k, is one of the main causes of limited improvements in lifespan of large area sensor network in IoT [18,19]. The probability that a node has n CHs in its effective area, given k and R the probability that a node has no CHs in its effective area, given k and R length of the advertisement message, (bits) length of the Join request message, (bits) length of a TDMA message, given k and R, (bits) length of the aggregated DATA message, (bits) the expectation of the radius of a cluster modeled as a circle, (m) avg. energy by a non-CH node while sending a Join-REQ message in a round distance from a member node to its CH distance from a node to the BS avg. energy by a member node while sending a DATA message to its CH in a round avg. energy consumed by a non-CH, non-member node while sending DATA message to the BS in a round avg. energy by a non-CH node while receiving ADV messages in a round avg. energy by a non-CH node while receiving TDMA messages in a round avg. total energy expended by all non-CH nodes in a round avg. energy by a CH node receiving ADV in a round avg. energy by a CH node receiving TDMA in a round avg. data-aggregation energy in a round avg. energy by a CH node transmitting aggregated data to BS in a round avg. energy by a CH node receiving Join request messages in a round avg. energy by a CH node receiving DATA messages from its member nodes in a round avg. total energy expended by all CH nodes in a round expected amount of total energy consumption in a round

Energy Consumption Model
Cluster-Based Hierarchical Routing
Problem Statement
Energy Consumption Analysis
Energy Dissipation by Non-CH Nodes
Energy Dissipation by CH Nodes
Performance Evaluation
Findings
Conclusions
Full Text
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