Wireless information networks
Proceedings of the 10th international conference on Architectural support for programming languages and operating systems
Maximizing the functional lifetime of sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Energy optimal data propagation in wireless sensor networks
Journal of Parallel and Distributed Computing
Adaptive redundancy for data propagation exploiting dynamic sensory mobility
Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems
Control Techniques for Complex Networks
Control Techniques for Complex Networks
An optimal data propagation algorithm for maximizing the lifespan of sensor networks
DCOSS'06 Proceedings of the Second IEEE international conference on Distributed Computing in Sensor Systems
An adaptive blind algorithm for energy balanced data propagation in wireless sensors networks
DCOSS'05 Proceedings of the First IEEE international conference on Distributed Computing in Sensor Systems
Routing techniques in wireless sensor networks: a survey
IEEE Wireless Communications
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In this paper, we consider wireless sensor networks where nodes have random and changeable mobility patterns. We study the problem where a particular node, called the base station, collects the data generated by the sensors/nodes. The nodes deliver the data to the base station at the time when they are close enough to the base station to ensure a direct transmission. While the nodes are too far to transmit to the base station, they store the data in a limited capacity internal FIFO queue. In the case where the queue is full, the new generated data are inserted in the queue and the oldest data are lost. In order to ensure, with a high probability, that the base station receives the generated data, the nodes disseminate the generated data in the network. The dissemination process consists in transmitting the data to others mobile nodes which are close enough to ensure a direct transmission. The nodes must control the dissemination process. Indeed, if the nodes send systematically the data to the neighbouring nodes then, the FIFO queues are going to be quickly saturated and the data lost (the dissemination process duplicate the generated data). On the other hand if the nodes do not disseminate the data, the data queued first are prone to be systematically lost if the capacity of the queue is too limited. We propose a protocol based on the estimate of the delivery probabilities of the data. Each node estimates the delivery probabilities of all the queued data. These probabilities depend on the position of the data in the queue and, on the dissemination process. The lower is the delivery probability the more the nodes disseminate the data to increase the delivery guarantee to the base station. In that way, all the messages get a high probability to be delivered to the base station (higher that some predefined threshold). Experimental validations of the protocol show that the protocol performs well and outperforms an existing protocol.