In this study, the authors propose an improved localisation algorithm in the software-definedsensor networks (SDSNs). This algorithm includes a node-selection strategy under the whole network power constraint, based ...
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In this study, the authors propose an improved localisation algorithm in the software-definedsensor networks (SDSNs). This algorithm includes a node-selection strategy under the whole network power constraint, based on the software-definednetworking (SDN) technique for providing the centralised control of the network. The analogous Cramer-Rao lower bound (A-CRLB) value is derived for each participating node, which represents a fundamental bound on the variance of the position estimator and is used to evaluate the contribution of each node to localisation accuracy. On the basis of A-CRLB values, the most helpful nodes for localisation are selected to maximise the sum of the nodes' contributory values to the localisation accuracy. With the global network knowledge provided by the SDN controller in the SDSN, the node-selection strategy is formulated into a 0-1 programming problem on the premise of power satisfaction of each node. Furthermore, the proposed node-selection -based localisation algorithm is applied to both noncooperative and cooperative localisation scenarios. Simulation results show that the proposed algorithms provide efficient and effective localisation schemes in SDSNs, and can improve the performance in terms of both the selection convergence speed and the localisation accuracy.
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