Published in IET Intelligent Transport Systems Received on 8th November 2009 Revised on 21st August 2010 doi: 10.1049/iet-its.2009.0099 ISSN 1751-956X Optimised random structure vehicular sensor network A.R. Momen 1 P. Azmi 2 F. Bazazan 3 A.S. Hassani 3 1 ICT Research Institute, ACECR, Tehran, Iran 2 Electrical and Computer Engineering Department, Tarbiat Modares University, Tehran, Iran 3 Iran Telecommunication Research Center (ITRC), Tehran, Iran E-mail: amir.momen@gmail.com Abstract: Providing proper coverage is one of the main applications of wireless sensor networks. In many working environments, it is necessary to take advantage of mobile sensor networks (MSNs), with the capability of having cooperation between sensor nodes and moving into appropriate positions, to provide the required coverage. However, in some applications such as intelligent transport system (ITS), where sensors are applied in complex dense urban environments, traditional MSN cannot properly cover the defined area. In this study, the authors study the use of a few unreserved selected cars as a vehicular sensor network (VSN) to cover a defined area and in this scenario, the sensors movements are assumed to be random from the network viewpoint. In the proposed random structure VSN, the coverage property is managed and controlled by introducing a suggested method for resource allocation and coverage control based on the real vehicle mobility model. Major advantages of this VSN are considering the real car mobility model, compatibility with the deployed infrastructure and processing simplicity and efficiency. The implementation results of suggested method verify the analytical results that are mentioned in the simulation section. 1 Introduction Area monitoring is a typical application of wireless sensor networks (WSNs). In this case, sensor nodes must be deployed appropriately to achieve an adequate coverage level for the successful completion of the issued sensing tasks. In traditional sensor networks, which are equipped with micro-electro-mechanical systems, the network coverage is controlled by using a large number of sensors that are distributed in the defined area by aircraft [1]. In traditional WSNs, suitable coverage in many working environments, especially in high-dense urban environments, cannot be achieved because the landing positions and distribution of the sensors is uncontrollable because of the natural obstacles and environment properties. Mobile sensors are a solution to this problem in some degree [2–5]. In some cases mobile sensors are used to correct deployment positions by moving the sensors to proper places for providing the required coverage [5–8]. Recently, many coverage analysis and control methods in the mobile sensor networks (MSN) use the Voronoi-based approaches [9–11]. The Voronoi-based approaches require exhaustive computational effort to compute the Voronoi cells continuously during a real-time implementation of the controllers, and hence they have more hardware/software complexity, and they need vast power supply. The major deficiency of almost all the previous works in MSN is the assumption of the free space movement of the sensors, resulting in the elimination of the effects of obstacles and environmental limitations (such as the topology of the streets in the coverage analysis and control) [9–12]. The topology of the obstacles and environment has major effects on sensors movement, landing possibility and inter-sensors communication/cooperation, especially in urban sensor networks [13]. Finally, because of the complexity of the topology of real environments and communication connectivity problem in some working areas (such as high- dense urban in intelligent transport system (ITS) applications), MSNs cannot solve the coverage problem. A vehicular sensor network (VSN) that uses vehicles for sensor deployment is one solution to achieve proper coverage in dense urban environments. Traditional VSNs have three major types and applications. In some cases, a VSN is a part of automatic car control systems which sends information to control centre and shares some information with other cars [14, 15]. In other cases, the VSN is used for random sensor deployment by employing a large number of random deployed vehicular sensors (VSs) as a sub-class of mobile ad hoc networks [15–17]. MobEyes and CarTel are two major implementations of such class of VSN to which more attention is being paid at present [16, 17]. In the last case, one uses reserved cars to achieve VSN for coverage control [3, 18, 19]. In this case, the network determines car travelling trace at each instance to control and manage VSN coverage. There are some ITS applications that can be implemented by WSN. For example car-guardrail collision accident building by WSN is introduced in [20]. VSN can be used for real-time traffic data extraction. Several works on VSN for traffic monitoring have been carried out in recent years [21–24]. Traffic data are a base of many other ITS applications such as travelling path suggestion, travelling time estimation and so on. Free-way real-time velocity monitoring, is another ITS application that can be implemented by VSN [22]. Road 90 IET Intell. Transp. Syst., 2011, Vol. 5, Iss. 1, pp. 90–99 & The Institution of Engineering and Technology 2011 doi: 10.1049/iet-its.2009.0099 www.ietdl.org