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A ferry-assisted solution for forwarding function in Wireless Sensor Networks
Affiliation:1. MIS/SIME, ENSIAS, Mohammed V University of Rabat, Morocco;2. MIS/MobiTic, ENSIAS, Mohammed V University of Rabat, Morocco;3. RTSE Research Group, ENSEM/MobiTic, Hassan II University, Casablanca, Morocco;4. L2TI, University of Paris 13, France;1. IIT-CNR, Pisa, Italy;2. Computer Science Department, University of Milan, Italy;1. Institute of Informatics and Telematics (IIT), Italian National Research Council (CNR), Via G. Moruzzi 1, Pisa, Italy;2. Converging Networks Laboratory, VTT Technical Research Centre of Finland, Kaitoväylä 1, 90590 Oulu, Finland;1. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China;2. Department of Computing, The Hong Kong Polytechnic University, Hongkong, China
Abstract:For sure, Wireless Sensor Networks (WSNs) are becoming an ultimate part of next generation mobile networks. They are a master piece for Ubiquitous computing. Indeed, they sustain development of numerous paradigms/ technologies such as distributed ambient intelligence, context-awareness and future mobile networking (e.g., B4G and 5G). Battery life remains one of the crucial problems to handle. In this article we propose an infrastructure-based topology using mobile ferries (mobile micro-base stations). In real life, a ferry could be robot, bus, tram, train or any other engine scrutinizing periodically a given area. Yet, message ferries are moving along concentric annulus and may collect data generated by the static sensors (could be classic sensors, smart meters, wearable devices, etc.) randomly distributed on given area. Next, transmissions are performed in a ferry-to-ferry forwarding scheme till arriving at the sink. Considered ferries could sense themselves data and therefore behave as mobile sensors allowing better awareness on the area state 1], 2], 3]. Our scheme could also assist Machine-to-Machine communications to increase the network lifetime, with potentially some cognitive-radio capabilities and opportunistic detection and access. Our proposal can easily be integrated in a smart-city for better interaction and green communications. Next, we present a queueing model (queues with finite capacity) to handle the generated traffic and to analyze the behavior of mobile ferries. We provided a close-form expression for both end-to-end throughput and end-to-end delay. The main objective of this work is to improve the energy efficiency of the cognitive sensors by asking cognitive sensors to not care about forwarding data of each other except for urgent data, this latter point is out of the scope of the paper. These static sensors will only care about data sensing, which will reduce their individual energy consumption.
Keywords:Ad hoc network  Performance evaluation  Cross-layer architecture  Ferry  Sensor  Cognitive radio
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