Joint channel and sink assignment for data collection in cognitive wireless sensor networks

Data collection is a fundamental operation in cognitive wireless sensor networks (CWSNs). However, previous works on data collection assume that a node can transmit data to any node within its transmission range, which is not reasonable in CWSNs. To ensure that the previous works can be applied in CWSNs, this paper focuses on the joint channel and sink assignment problem, which is a critical preparatory work for data collection in CWSNs. Because the capacity performance of a CWSN is usually considered as a key problem in fundamental understanding, we are interested in finding a joint channel and sink assignment for each sensor node, such that the minimum capacity of all sensor nodes is maximized. We formulate our problem as a mixed integer linear program by some elaborate mathematical skills. Then, two algorithms based on greedy strategy and linear relaxation technique are proposed. Extensive simulations results show that our algorithms are efficient and able to achieve near-optimal performance. Copyright (C) 2015 John Wiley & Sons, Ltd.