1 Geographic Routing in Clustered Wireless Sensor Networks among Obstacles Hari Prabhat Gupta * , S. V. Rao † , Amit Kumar Yadav * , Tanima Dutta * Abstract—An important issue of research in wireless sensor networks (WSNs) is to dynamically organize the sensors into a wireless network and route the sensory data from sensors to a sink. Clustering in WSNs is an effective technique for prolonging the network lifetime. In most of the traditional routing in clustered WSNs assumes that there is no obstacle in a field of interest. Although it is not a realistic assumption, it eliminates the effects of obstacles in routing the sensory data. In this paper, we first propose a clustering technique in WSNs named Energy- efficient Homogeneous Clustering that periodically selects cluster heads according to a hybrid of their residual energy and a secondary parameter, such as the utility of the sensor to its neighbors. In this way, the selected cluster heads have equal number of neighbors and residual energy. We then present a route optimization technique in clustered WSNs among obstacles using Dijkstra’s shortest path algorithm. We demonstrate that our work reduces the average hop count, packet delay, and energy-consumption of WSNs. Index Terms—Clustering, energy-efficient, obstacles, routing. I. I NTRODUCTION A typical wireless sensor network (WSN) consists of several tiny and low-power sensors which use radio frequencies to perform distributed sensing tasks. WSNs find their applica- tions in many areas that include plant monitoring, battlefield surveillance, fire detection, and leakage of toxic chemicals, radiations, and gas detection [1]–[5]. In such WSNs, a large number of sensors are deployed in a field of interest (FoI) in stochastic manner. In stochastic deployment, sensors are usually dropped randomly in large numbers to guarantee reliability [1], [4], [6], [7]. Minimising the energy consumed while ensuring the con- nectivity of a network is an important issue to be addressed in WSNs because the batteries powering the sensors may not be accessible for recharging often. Cluster-based routing in WSNs has been investigated by researchers to achieve the network scalability and management, which maximizes the lifetime of the network by using local collaboration among sensors [2]– [5], [8]–[14]. In a clustered WSN, every cluster has a cluster head (CH). CHs periodically collect, aggregate, and forward data to the sink. In any application of WSNs, connectivity is considered to be an important metric to measure the quality of service of WSNs. A network is said to be connected if all sensors in the The authors are with the Department of Computer Science and Engineering, Indian Institute of Technology Guwahati, India (e-mail: * {hprabhatgupta, amit.yadav0788, dutta.tanima}@gmail.com † svrao@iitg.ac.in). Copyright (c) 2013 IEEE. Personal use of this material is permitted. However, permission to use this material for any other purposes must be obtained from the IEEE by sending a request to pubs-permissions@ieee.org. FoI can reach to the sink. Geographic routing [15]–[23] has been considered as an attractive approach in large scale WSNs because it does not require the global topology of a WSN. A sensor can make routing decisions based on the geographic position of itself and its neighbors. The sensor forwards the sensory data to a neighbor, which is closest to the sink. This reduces the average hop count. However, geographic routing cannot optimize the number of hops when a sensor has no neighbor closer to the sink. This problem is known as local minimum problem in the literature [15]. The occurrence of the problem can be caused by many factors, such as sparse deployment of sensors, physical obstacles, and sensor failures. • Major contributions: In this paper, we propose an energy- efficient homogeneous clustering technique in WSNs and a route optimization technique in clustered WSNs among obstacles. The major contributions of our work in this area are as follows: 1) We propose an Energy-efficient Homogeneous Cluster- ing (EHC) technique in WSNs, that selects the CHs to create a connected backbone network. EHC is a dis- tributed technique, where sensors make local decisions on whether to join a backbone network as a CH or to a member of a cluster. The decision of each sensor is based on their residual energy and an estimate of how many of its neighboring CHs will benefit from it being a CH. We give a distributed technique where CHs rotate with time, demonstrating how localized sensor decisions lead to a homogeneous connected global topology. 2) We propose a Route Optimization Technique (ROT) in clustered WSNs among obstacles. ROT forms an energy-efficient path between the CHs selected by EHC technique and the sink. ROT uses Dijkstra’s shortest path algorithm [24]. What attracts us is that we do not change the underlying forwarding strategy of existing geographic routing [16]. ROT works under the routing layer and above the MAC and physical layers in WSNs. 3) We analysis message and time complexities of our work which are nearly optimal. We derive an expression to estimate the energy consumption of the network consid- ering EHC and ROT techniques. The rest of the paper is organised as follows: In the next sec- tion, we briefly discuss the literature to address the clustering and the local minimum problem in WSNs. We propose EHC and ROT techniques in Section II. The complexity analysis and the energy consumption calculation of EHC and ROT are presented in Section III. In Section IV, we present the simulation results conducted to evaluate the preference of EHC