Wireless sensor networks (WSNs) offer the potential to significantly improve the efficiency of existing transportation systems. Currently, collecting traffic data for traffic planning and management is achieved mostly through wired sensors. The equipment and maintenance cost and time-consuming installations of existing sensing systems prevent large-scale deployment of real-time traffic monitoring and control. Small wireless sensors with integrated sensing, computing, and wireless communication capabilities offer tremendous advantages in low cost and easy installation. In this paper, we first survey existing WSN technologies for intelligent transportation systems (ITSs), including sensor technologies, energy-efficient networking protocols, and applications of sensor networks for parking lot monitoring, traffic monitoring, and traffic control. Then, we present new methods on applying WSNs in traffic modeling and estimation and traffic control, and show their improved performance over existing solutions. Copyright as China and India as they are experiencing fast economic growth.Intelligent traffic control is very important in addressing traffic congestion. The emerging technology of wireless sensor networks (WSNs) is poised to revolutionize traffic management and control. Batterypowered low-cost traffic sensor nodes with integrated computing and wireless communication capabilities will change the landscape of real-time traffic data acquisition. As these wireless sensors become widely available and their costs come down, a tremendous challenge is the design of sensor-based traffic control systems that are large-scale, efficient, and high
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In a distributed sensor network, large number of sensors deployed which communicate among themselves to selforganize a wireless ad hoc network. We propose an energyefficient level-based hierarchical system. We compromise between the energy consumption and shortest path route by utilizing number of neighbors (NBR) of a sensor and its level in the hierarchical clustering. In addition, we design a Secure Routing Protocol for Sensor Networks (SRPSN) to safeguard the data packet passing on the sensor networks under different types of attacks. We build the secure route from the source node to sink node. The sink node is guaranteed to receive correct information using our SRPSN. We also propose a group key management scheme, which contains group communication policies, group membership requirements and an algorithm for generating a distributed group key for secure communication. IntroductionSensor networks are the new paradigm for the future communication. Sensor networks consist of tiny sensor nodes [1,2,3,4 ] that collaborate a mong themselves to establish a sensing network and provide access to information anytime, anywhere by collecting, processing, analyzing, and disseminating data. In sensor networks, researchers are focused on improving three main aspects: energy-efficiency, fault-tolerance and secure routing. This concern is due to the fact that sensor nodes are vulnerable to energy depletion [5,6,7], intrusions and attacks [5,8] and node and link failures [1,3].Security is one of the most important aspects in ad-hoc sensor networks. Intrusion and attack have become common threats to distributed sensor networks. A wireless sensor network uses radio frequency (RF) channel [5], which is not a secure channel. Attack can be active or passive. Active attacks involve some mo dification of the data stream or the creation of a false stream. Passive attacks are in the nature of eavesdropping on transmissions.In this paper, we design an overview of a secure hierarchical model for sensor networks. In the selforganization process [1,3], we divide the sensor nodes into different levels. The lower-level sensor nodes only sense and disseminate data, whereas the higher-level sensors find the shortest path to the sink node and aggregate data in addition to forwarding it. Since communication over radio is the most energy-consuming function performed by sensor devices, we need to minimize communications overhead [6]. By using hierarchical architecture we can decrease the
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