Abstract

In a WSN-assisted IoT environment, the sensors are resource constrained. The energy, computing and storage resources of deployed sensors in the sensing area are limited. A hybrid protocol named as an Energy Efficient Centroid-based Ant colony Optimization (EECAO) hybrid protocol is proposed in this paper to improve the performance of the sensor network in WSN-assisted IoT environment. This protocol uses a concept of centroid based clustering to gather the information of local clusters and ant colony optimization to relay the same to the base station. The energy level of deployed cognitive sensors is considered as a key parameter for defining the position of centroid in this protocol. The proposed protocol has a new distributed cluster formation design which includes multiple clustering factors such as energy cost, channel consistency and cognitive sensor throughput to select cluster heads. In the proposed protocol, the selection of the super cluster head is based on the energy centroid position for a defined coverage area. The path optimization between the super cluster heads and the base station is carried out using an ant routing model. Our simulation results indicate that the proposed protocol performs better when benchmarked against existing ETSP and EECRP protocols. Also, it suits well for the sensor networks that requires long lifetime when the base station is placed at either center, border or outside the network.

Highlights

  • Sensors are the dedicated devices that can detect and respond to environmental changes

  • When the base station (BS) is placed at centre of the sensing field, (Scenario 1 Fig.7) as the number of networking nodes inside the ssensing area increases, the total energy consumed by the proposed sensor network is less than the existing sensor network works. when networking node count inside the sensing area is 200, the proposed network in scenario 1 saves around 37 J, 25 J, 9 J when compared to existing Ant Colony Routing (ACR), Efficient Tree based Self-organizing Protocol (ETSP) and Efficient Centroid based Routing Protocol (EECRP) respectively

  • The selection of forwarder node termed as super cluster head is selected based on the distance of cluster heads to the centroid position of the coverage area

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Summary

RELATED WORK

Significant research works held on Centroid and ANT routing models with cognitive sensors in WSN-Assisted IoT environments are surveyed. 2.1 Related Work on WSN-Assisted IoT environments IoT consists of three layers namely perception layer, the network layer and the application layer [5]. The perception layer is a cluster of internet-enabled devices which can perceive, detect objects, gather information and exchange information with other devices through communication networks. Network layer forwards data under constraints of device capability and network limitation from perception layer to application layer. Wireless Sensor Networks (WSNs) acts as “cells” for collecting and distributing the data within IoT and enabling the development of smart and context aware applications. By utilizing different types of power sources and maintaining it for long time, these sensor network devices are real enablers in IoT in terms of metrics like lifetime, energy efficiency, less cost and interface to resources [6]. The aspects like throughput, cost of communication and energy consumption are considered as key parameters in IoT based WSNs [7]

Related Work on Location of base station in WSNAssisted IoT
Related Work on Energy Centroid based Clustering
X W W C C and
Related Work on ANT Routing Approach
EECAO PROTOCOL DESIGN
System Model
Energy Model
EECAO algorithm Scheme
Channel selection using sensors Cognitive Knowledge
Cluster Head selection and its rotation phase
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17. End if
SIMULATION ANALYSIS AND DISCUSSIONS
64 Packets 30 Sec
Analysis based on Sensor Network Throughput
CONCLUSION
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