Data Fusion in Mobile Wireless Sensor Networks Muhammad Arshad, Member, IAENG, Mohamad Alsalem, Farhan A. Siddqui, N.M.Saad, Nasrullah Armi, Nidal Kamel Abstract—During the last decades, Wireless Sensor Networks (WSNs) arises as an emerging and future enable technology due to the latest development in the field of wireless communication, computing and storage devices. Cluster based routing is an immense solution to enhance the energy efficiency of nodes in wireless sensor networks. In this paper we propose, simulate and authenticate Mobile Data Collector (MDC) based cluster routing protocol for environmental applications, which is based on multi-hop routing strategy, self-organized sensor nodes, distributed cluster formation technique, randomly selection of cluster heads and finally forward the data to base station by the support of maximum residual energy MDC. Moreover, our approach explains the considerable enhancement than LEACH protocol in terms of energy consumption of sensor nodes and overall network lifetime. Index Terms—Mobile Wireless Sensor Networks, Power Aware, Cluster Based Routing and Data Gathering Technique. I. INTRODUCTION IRELESS Sensor Networks (WSNs) is a low-cost computation, storage capacity and radio technologies that assemble economical micro-sensor nodes. Micro-sensor nodes are not powerful devices like macro-sensor, but provide fault-tolerant and high quality sensor networks by the deployment of hundreds and thousands sensors within the networks region [1, 2]. Data fusion protocols were designed for network configuration and collect the data from desired environment. Each round of data collection protocol nodes must be collected and transmitted data towards BS, that helpful for end user to use this information. An easy way to do that is a combination (sum, average, min, max, count) data from different nodes. The aim is efficient transmission of all data at the base station, so the lifetime of the network is optimized in terms of rounds. Where a round is defined as the process of collecting all data from sensor nodes towards the base station, no matter how much time it takes [3, 4]. Manuscript Received January 9, 2012; Revised February 9, 2012 Muhammad Arshad, Research Scholar, Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Tronoh, Malaysia. (Email: muarshad74@gmail.com ) Naufal M. Saad, Associate Professor, Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Tronoh, Malaysia. (Email: naufal_saad@petronas.com.my ) Nidal Kamel, Associate Professor, Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Tronoh, Malaysia. (Email: nidalkamel@petronas.com.my ) Mohamad Aalsalem, Dean, Department of E-Learning and Distance Learning, University of Jazan, Kingdom of Saudi Arabia. (Email: aalsalem.m@jazanu.edu.sa ) Farhan A. Siddiqui, Lecturer, Department of Computer Science, Univeristy of Karachi, Pakistan. (Email: farhan@uok.edu.pk ) Nasrullah Armi, Research Scholar, Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Tronoh, Malaysia. (Email: narsullah.armi@gmail.com ) Mobile devices are also the best approach to resolve the data gathering issues in an efficient way. Number of the existing WSNs scenarios using mobile platforms, such as animal monitoring, traffic monitoring and battlefield surveillance applications. Mobile Wireless Sensor Network (mWSN) is a specified category of WSNs where mobility acting a primary part in the application execution. In recent years, researchers and vendors are entirely focused to retain mobility in WSNs [5]. A. Mobile WSN Architecture mWSN can be classified into a flat, 2-tier or 3-tier hierarchical architecture: Flat or level-like, the network architecture contains a set of heterogeneous devices to communicate in ad hoc mode. These devices are mobile or fixed, but to communicate within the same network. Two- tier architecture consist set of nodes in place, and set mobile nodes. Moving nodes form an overlay network or the role of data mules to transfer data across the network. In three-tier architecture, a set of fixed sensor nodes transmit the data towards set of mobile devices and then transmits to one set of access points. B. Data Collection Techniques in mWSN Various approaches to exploit the mobility of data collection methods for WSNs have been proposed. The classification of these approaches according to the characteristics of sink mobility, and wireless data transfer methods: Mobile Base Station (MBS): MBS is a mobile sink, which amend the location through transmission. The sensors data transmit to MBS without delay. Mobile Data Collector (MDC): MDC act as mobile sink which visits individually all sensors in the network. Sensor generated data buffered at source until the MDC visits and retrieves the information by single hop transmission. Rendezvous Solution: Hybrid solution of WSNs mobility, where sensor data is collected at designated point near the mobile devices. Then mobile devices downloaded the buffered data from appointed points [6, 7, 8]. C. Clustering Techniques In many research papers and projects explains that the hierarchical routing especially the clustering techniques make an immense enhancement on WSNs. These approaches to reduce the energy utilization and network performance when the entire sensor nodes of the network sending a data to base station or central collection center. The core components of the cluster based WSNs are sensor nodes, clusters, cluster heads, base station and end user [9, 10]. Fig. 1 explains the general architecture of cluster based WSNs. Sensors nodes are an essential part of WSNs. Organizational unit of WSNs are clusters. Cluster heads (CH) are the leader of cluster. W Proceedings of the International MultiConference of Engineers and Computer Scientists 2012 Vol I, IMECS 2012, March 14 - 16, 2012, Hong Kong ISBN: 978-988-19251-1-4 ISSN: 2078-0958 (Print); ISSN: 2078-0966 (Online) IMECS 2012