Disseminação de dados baseada em trajetória e energia para redes de sensores sem fio

Abstract

Wireless sensor networks (WSNs) for the collection, processing, and communication of environmental data are considered to have an enormous potential for research and application. In a WSN, a fundamental problem is the data dissemination from a monitoring node to the sensor nodes. Based on data dissemination algorithm, a monitoring node can perform different activities such as to change the operational mode of part or the entire WSN, broadcast a new interest to the network, activate/deactivate one or more sensor nodes, and send a query to the network. An interesting data dissemination algorithm is the Trajectory Based Forwarding (TBF) in which packets are disseminated from a monitoring node to a set of nodes along a predefined curve. The key idea is to embed a trajectory in the packet to be disseminated and then let the intermediate nodes forward it in a unicast manner to those nodes that lie close to the trajectory. Since a trajectory does not explicitly encode the nodes in the path, it is to a large extent impervious to changes in specific nodes that form the topology. Two main advantages of TBF are compact representation of a route and node independence.The information about the amount of energy available at each part of the network is called the energy map and can be explored by data dissemination algorithms to disseminate data so that the energy consumption by each node is minimized. In this work, a data dissemination algorithm is proposed that adapts dynamically its dissemination route according to the energy level of the sensor nodes. This is an important feature of a system such wireless sensor networks that must have the capacity of adapting its behavior according to itsavailable resources. In a WSN, a fundamental resource is energy, since, in general, batteries cannot be recharged. The key idea of our solution is to combine concepts presented in trajectorybased forwarding with the information provided by the energy map to determine routes in a dynamic fashion to deliver information to either the entire network or part of it. Simulation results revealed that the energy spent with the data dissemination activity can be concentrated on nodes with high energy reserves, whereas low-energy nodes can use their energy only to perform sensing activity or to receive information addressed to them. In this manner, partitions of the network due to nodes that ran out of energy can be significantly delayed and the network lifetime extended.