An energy efficient and optimized load balanced localization method using CDS with one-hop neighbourhood and genetic algorithm in WSNs

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Abstract

Localization has always been a research concern in the domain of wireless sensor networks. The varying range of its applications has given it a wide acceptability along with the need of accuracy of the location estimation. A number of algorithms has been introduced for the purpose. While developing such algorithms, the concern of network lifetime has received a setback as wireless sensor networks are always resource constrained. The proposed algorithm balances the computational load among anchor nodes for location calculation of unknown nodes. Moreover the algorithm has been optimized using genetic algorithm. The optimized backbone is used to locate the unknown nodes. The simulation results show that our algorithm significantly improves the network lifetime as the computational load has been distributed efficiently among the anchor nodes.

Introduction

Localization defines the estimation of location of unknown nodes deployed in Wireless Sensor Networks (WSNs) (Kuriakose et al., 2014). Variety of applications of wireless sensor network ranges from environment conditions observation, agriculture, smart home environment, defence environment etc. The dynamic need of the technology and human requirement has made the WSNs from static to mobile. The mobility is incorporated in the environment for the robust output of an observation. In mobile environment estimating the location of unknown nodes is more critical. The accuracy of the location estimation in such networks depends on two basic processes (Han et al., 2013). The first one is location estimation (Ali et al., 2013) that deals with the calculation of unknown nodes' location and the second process is location verification (Ali et al., 2013), which verifies the calculated location with the actual location. Numerous algorithms have been introduced to improve the accuracy level of the localization process.

The wireless sensors are resource constrained. The anchor nodes are privileged in this regard with more power resources, but the unknown nodes are not having such resources to utilize. To perform a heavy computational task, the sensor nodes become exhausted and therefore either it has to be replaced or the communication at that part of the sensor node will be untouched further. But, the replacement of such sensors becomes vital and infeasible in some applications due to the dynamic configuration. Thus, the localization process should be efficient in the terms of resource utilization. To dynamically allocate the load among anchor nodes load balancing has been introduced in the localization process (Ko, 2015). The objective behind distributing the load among anchor nodes for location estimation is to increase network lifetime (Dietrich and Dressler, 2009).

In this paper, we have introduced a load balancing mechanism for location estimation in WSNs using Connected Dominating Set(CDS)as a backbone and Genetic Algorithm (GA). Section 2 deals with related work in this field. The proposed network model, shown in Section 3, is completed in two phases (i) to optimize the backbone by using genetic algorithm in Section 3.1. (ii) to estimate the location of unknown nodes with the help of optimized backbone in Section 3.2. The results and analysis are provided in Section 4. Finally Section 5 concludes the paper.

Section snippets

Related work

There are various approaches available to solve localization problem which differ in the assumptions including device hardware, signal propagation models, timing and energy requirements, composition of network, operational environment, beacon density, time synchronization, communication costs, error requirements, and node mobility. Localization techniques (Kuriakose et al., 2014) are broadly classified into two categories: Direct approaches and Indirect approaches. The direct approach can be

Proposed network model

The first consideration of the network model is to be self-organizing that is having no central control of deploying the sensor nodes in the network. The sensor network model N has been considered to be in Two-Dimensional (2-D) and is represented by a graph G(V,E) consists of V, a set of vertices and E, a set of edges. The connectivity in such a network is an important parameter to analyse the overall performance metrics in localization algorithm. The size of the network can be defined as:|N|=|A

Result and discussion

The proposed algorithm has been simulated in Network Simulator-2 with parameters enlisted in the Table 2.

The performance of the algorithm has been analysed in the terms of, localization error and network lifetime.

Localization error is defined as squared error of the estimation given in the Eq. (28) and the average localization error as:eavg=i=1meimThe proposed algorithm uses linear energy model for each anchor node given as:Energya=c1×Rawhere Ra is transmission range of anchor node aj and c1

Conclusion

In this paper, we have proposed a novel algorithm of optimizing a CDS which is based upon anchor nodes. Another major consideration is, the proposed algorithm applies random mobility for both the anchor nodes and the unknown nodes. The optimization process uses the genetic algorithm with elitism strategy so that the fittest solution can be retained accordingly for a fast convergence of the global solution. Obtaining the optimized CDS, the localization process executed that depends upon

Gulshan Kumar working as an Assistant Professor in Lovely Professional University, Punjab India and did his B.Tech from Amritsar College of Engineering, Amritsar (2009) in Computer Science Engineering, M.Tech from Lovely Professional University, Punjab India with area of specialization in Mobile Ad hoc and Sensor Networks. He has many publication in well renowned International journals and Conferences Mailing Address: House No-3, Gali No 3, Kamla Devi Avenue, Amritsar (Punjab), India.

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    Gulshan Kumar working as an Assistant Professor in Lovely Professional University, Punjab India and did his B.Tech from Amritsar College of Engineering, Amritsar (2009) in Computer Science Engineering, M.Tech from Lovely Professional University, Punjab India with area of specialization in Mobile Ad hoc and Sensor Networks. He has many publication in well renowned International journals and Conferences Mailing Address: House No-3, Gali No 3, Kamla Devi Avenue, Amritsar (Punjab), India.

    Mritunjay Kumar Rai received his Doctorate degree from Indian Institute of Information Technology and Management, Gwalior, India, after the completion the Master of Engineering degree in Digital system from Motilal Nehru National Institute of Technology, Allahabad, India. Presently he is working as an Associate Professor in Lovely Professional University, Phagwara, India. His research Interest include Wireless Networks, Network Security and Cognitive Radio Networks. He has published more than 40 research articles in reputed International Conferences and International Journals. Mailing Address: Room No 801, 41-C, Lovely Professional University, Phagwara (Punjab), India

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