Distributed Multiple Criteria based Clustering Scheme for Wireless Sensor Networks M. Mustafa † , T. Shah † , Safdar H. Bouk †a , Syed H. Ahmed ‡b and N. Javaid †c † Dept. of EE, COSMATS Institute of Information Technology, Park Road, Chak Shahzad, Islamabad, Pakistan 44000 ‡ School of Computer Science and Engineering, Kyungpook National University, Korea. Email: a bouk@comsats.edu.pk, b hassan@monet.knu.ac.kr, c nadeemjavaid@comsats.edu.pk Abstract—Stability and lifetime of Wireless Sensor Networks (WSNs) mainly depend on energy of each node in the network. Hence, it is necessary for any technique proposed for WSNs to be energy efficient. There are different methods to preserve energy in WSNs and clustering is one of them. Clustering technique divides whole network into small groups, each having a managing node, called cluster head (CH) and rest act as members. CH is responsible to provide communication bridge between members and the base station. In this paper, we propose a distributed clustering scheme that uses multiple criteria i.e. residual energy, node degree, distance to the base station and average distance between a node and its neighbors, to select a CH. Fuzzy Technique for Preference by similarity to Ideal Solution (Fuzzy-TOPSIS) method is used to outrank the potential nodes as CHs. The realistic multi-hoping communication model is used in both, inter- cluster and intra-cluster communication, instead of single hop as in previous schemes. Simulation results show that our purposed technique performs much better than previous methods in terms of energy efficiency, network life time, less CH deformation and control overhead. Keywords—WSNs, Clustering, Cluster Head, Fuzzy-TOPSIS. I. I NTRODUCTION Low-power electronic devices have grown interest in recent years. Wireless Sensor Networks (WSNs) use these many low-power devices along with communication capabilities for sensing and monitoring various fields. Major areas of WSNs include environmental sensing of temperature and humidity, earthquake monitoring, healthcare monitoring and battle field surveillance [1]. In some applications sensor nodes are de- ployed in strategic manner but in most of the applications like battlefield, these nodes are dispersed randomly. After deployment in the field, sensor nodes have to be self-organized without human interference. These sensor nodes consist of battery operated radio devices, which have limited memory and processing capabilities [2]. Their batteries cannot be charged or replaced after deployment. Hence, energy is one of the major issues in WSNs. The sensor nodes not only sense data but they also process data and communicate with the Base Station (BS). The communication and processing of data are main causes of energy consumption and they are major requirements of WSNs, therefore, these tow must have to be energy efficient. Lots of research has been conducted in WSNs on energy efficiency to prolong network life time and stability. This includes design of various energy efficient MAC and routing protocols. Routing protocols may either be flat or hierarchical. In flat protocols, each sensor node sends data to BS directly or in a multi-hop fashion [3][4]. On the other hand, in hierarchical architecture, WSNs are divided into optimum number of groups or clusters. Inside each cluster a Cluster Head (CH) is selected to perform management and routing tasks for that cluster. Research has proved that hierarchical protocols perform much better than the flat protocols in terms of energy efficiency and stability. The CH is selected either randomly or based on some criteria [5]. After selection of a CH, other nodes join that cluster and act as member nodes. These member nodes send their data to CH, which then aggregates data and sends to the BS. Hence, the selection of a CH largely affects whole network’s performance and stability. In most of the previous clustering schemes, CH selection is based on single criterion. In single criterion, CH is mostly selected randomly or based on residual energy, node density or distance form BS. If CH is selected on the basis of residual energy only, then problem arises when a node with higher residual energy but located far away from BS is selected as CH. That node consumes more energy to forward aggregated data to BS. Similarly if CH selected no the bases of shortest distance form BS, then similar type of problem arises if node near to BS is selected as CH, but with not sufficient residual energy to communicate with BS. Hence, single criterion is not suitable for CH selection. Therefore we use all four criteria, which are necessary for efficient CH selection. In this paper we propose a technique in which we use distributed algorithm of CH selection i.e. nodes themselves decide whether to become CH or not. Fuzzy Technique for Preference by similarity to Ideal Solution (Fuzzy-TOPSIS) method is used to outrank the potential nodes as CHs. Fuzzy logic and fuzzy set theory is applied to decision making process. TOPSIS is a solution for multi-criteria optimization problem. TOPSIS was initially proposed by Hwang and Yoon [6]. Fuzzy-TOPSIS consists of decision matrix with m alter- natives and each alternative has n attributes. This technique is applied is scientific and engineering problem solving. Fuzzy- TOPSIS uses relative importance of attributes instead of using precise values, because is some situations precise assignment is not possible due to any reason. We consider four criteria for CH selection which are residual energy, number of neighbors, average distance from neighbors and distance between node and BS. In our proposed scheme we avoid quick deformation of CH, which in result reduces control overhead. Because of re- duction in control overhead energy consumption is minimized. In our proposed scheme we use realistic communication model by introducing multi-hop communication model in both intra- cluster (communication between normal nodes and CH) and inter-cluster (communication between CH and BS).