Elsevier

Computers & Electrical Engineering

Volume 64, November 2017, Pages 173-181
Computers & Electrical Engineering

Analysis of clustered QoS routing protocol for distributed wireless sensor network

https://doi.org/10.1016/j.compeleceng.2016.11.019Get rights and content

Abstract

A wireless network is a collection of wireless nodes within decentralized and distributed network architecture. This distributed architecture gives rise to issues concerning resilience, node mobility, link failure, routing overhead and drop rate. To avoid these issues and satisfy QoS requirements, a new routing protocol known as clustered QoS routing protocol (CQRP) is proposed. This routing protocol creates a cluster with a grouping of nodes and assigns a cluster head. This cluster head is used to assign an available link for the wireless node to avoid issues with resilience and link failure. Cluster members communicate with data packets through the cluster head. Through the use of this cluster head, quality of service requirements for a distributed network can be met. Experimental results show that the performance of the proposed clustered QoS routing protocol CQRP increases throughput, delivery rate and network efficiency, and decreases the drop rate, delay and routing overhead.

Introduction

A wireless network has a large number of wireless nodes, arranged in either a centralized or distributed architecture. In a centralized architecture, a central node will act as a server, while the remaining nodes act as clients. Client nodes can communicate only through the central server node. In distributed network architecture, each wireless node may act as either a server or a client. All the nodes in the network are able to communicate with each other independently, and are not dependent on a centralized server. This independent architecture may lead to security issues. To avoid this, clustering technology is introduced in a distributed wireless network. This forms a cluster from a group of nodes, and each cluster creates its own cluster head to enable efficient transmission between the source and destination. Another issue within wireless networks is the relatively high number of mobile nodes. These mobile nodes are able to enter or leave the network, and may cause unusable links. Due to this greater number of mobile nodes, topology maintenance is very difficult in a distributed wireless network. This node mobility and link failure may degrade the network performance and reduce the quality of service.

Tseng et al. [19] suggest a green clustering algorithm, based on a relative neighbourhood graph, to manage the number of nodes, bandwidth efficiency and transmission distance in the wireless network. This proposed algorithm reduces energy consumption and increases the network lifetime and battery lifetime of the wireless network. Arkian et al. [4] describe a stable clustering scheme for a vehicular ad hoc network to increase network performance and decrease mobility issues. Xu et al. [20] discuss performance-aware mobile computing based on video-on-demand for a vehicular ad hoc network, which addresses streaming issues. This technique is used to communicate join and leave messages, to store and search for messages, and to carry out tasks in a vehicular ad hoc network. Hammoudeh et al. [8] present a route optimization and load balancing protocol which is based on clustered technology in the wireless sensor network. This proposed routing protocol is also used to increase the delivery ratio and reduce the end-to-end delay. Sharma et al. [17] suggest a cluster-based multi-path routing protocol, based on clustering techniques and multi-path routing, for a wireless sensor network. This routing protocol is used to increase reliability and reduce energy consumption. Kapoor et al. [11] describe a dynamic allocation algorithm for increasing the lifetime of a wireless sensor network. This proposed algorithm is applicable within all types of energy-saving applications.

The organization of the paper is as follows: Section 2 deals with related work, Section 3 deals with Methodology, Section 4 deals with the proposed algorithm which is Clustered QoS Architecture and Routing Algorithm, Section 5 deals with the results and discussion, Section 6 deals with conclusion.

Section snippets

Related work

Qayyum et al. [16] solve the database issues in a mobile ad hoc network using clustering technology. They propose a data replication system within a mobile ad hoc environment which increases reliability and scalability. These database issues occur due to node mobility and frequent disconnection, and are overcome by the proposed scheme. The results are evaluated using a network simulator. Li et al. [13] present a set of online and batch scheduling heuristics for a mobile ad hoc cloud-based

Methodology

On-demand multicast routing protocol (ODMRP) is used to improve bandwidth utilization in a wireless network. This routing protocol consists of two phases: the bandwidth request phase and the bandwidth reply phase. The generation of a bandwidth reply message is in response to a bandwidth request message from the destination node, and includes the traffic flow ID. Based on this information, the source will forward data to the destination, meeting the quality of services requirements through the

Clustered QoS architecture

The objective of the proposed clustered QoS routing protocol (CQRP) is to satisfy the quality of service requirements in the wireless network. This proposed creates the distributed network architecture and this creates the cluster based on the grouping of the number of nodes in the network. Cluster head selection is based on the central node of the cluster. All the cluster heads are interconnected in the distributed network. Cluster members will transmit the data through the cluster head.

Simulation results

The simulation results were analysed using the network simulator by varying the number of nodes from 100 nodes to 600 nodes. The simulation time is 200 s and the size of the topography is 1000*1000 m. The physical layer is assigned as wireless medium and to access the data using the Omni directional antenna. The network type is wireless network and it contains the IP address for every node and the wireless channel is used as propagation channel. The transport layer is transmission control

Conclusion

The proposed clustered QoS routing protocol is used to satisfy quality of service requirements. The proposed clustered QoS routing protocol CQRP was found to achieve high network efficiency approximately 92% with a very low drop rate of 25%in stable and 30% in mobile conditions. This routing strategy has helped to achieve a higher delivery rate of 74% irrespective of its mobile nature. The network has also proved a high throughput of 1.6 and 1.7 Mbps during the both stable and mobile condition.

Dr. N.V.S. Sree Rathna Lakshmi received her B.E., M.E., and Ph.D. in Electronics and Communication Engineering. Her research interests include wireless communication, networks, embedded systems and image processing. She has published many papers in reputable international journals and conference proceedings. She is presently working as a professor in the Department of ECE at Agni College of Technology, Chennai, India.

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Dr. N.V.S. Sree Rathna Lakshmi received her B.E., M.E., and Ph.D. in Electronics and Communication Engineering. Her research interests include wireless communication, networks, embedded systems and image processing. She has published many papers in reputable international journals and conference proceedings. She is presently working as a professor in the Department of ECE at Agni College of Technology, Chennai, India.

Dr. S. Babu studied B.Tech. (IT), M.Tech. (CSE), and obtained a Ph.D. in Computer Science and Engineering from Anna University, Chennai. He has a total of 11 years’ teaching experience in undergraduate and postgraduate engineering. He also has four years of R&D experience, and has published several technical papers in both national and international conference proceedings, and has also published technical papers in 15 international journals.

Dr. N. Bhalaji received his B.E., M.E., and Ph.D. in Computer Science and Engineering. His research interests include Trust based networks, Internet of Things and mobile ad hoc networks. He has published many articles in reputable international journals and conference proceedings. He is presently working as an associate professor in the Department of Information Technology in SSN College of Engineering, Chennai, India.

This paper is for CAEE special section SI-wls8. Reviews processed and recommended for publication to the Editor-in-Chief by Associate Editor Dr. S. Smys.

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