Knapsack problems: algorithms and computer implementations
Knapsack problems: algorithms and computer implementations
Ad-hoc On-Demand Distance Vector Routing
WMCSA '99 Proceedings of the Second IEEE Workshop on Mobile Computer Systems and Applications
A Reactive Local Search-Based Algorithm for the Multiple-Choice Multi-Dimensional Knapsack Problem
Computational Optimization and Applications
Proceedings of the 3rd ACM international workshop on Performance evaluation of wireless ad hoc, sensor and ubiquitous networks
A unified framework for max-min and min-max fairness with applications
IEEE/ACM Transactions on Networking (TON)
Quick convergecast in ZigBee beacon-enabled tree-based wireless sensor networks
Computer Communications
Two-Way Beacon Scheduling in ZigBee Tree-Based Wireless Sensor Networks
SUTC '08 Proceedings of the 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008)
A survey of transport protocols for wireless sensor networks
IEEE Network: The Magazine of Global Internetworking
Interference and shortest path optimization on a ZigBee sensors network application
ICANCM'11/ICDCC'11 Proceedings of the 2011 international conference on applied, numerical and computational mathematics, and Proceedings of the 2011 international conference on Computers, digital communications and computing
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Wireless sensor networks with multiple users collecting data directly from the sensors have many potential applications. An important problem is to allocate for each user a query range to achieve certain global optimality while avoid congesting the sensors in the meanwhile. We study this problem for a ZigBee cluster tree by formulating it into a multi-dimensional multi-choice knapsack problem. Maximum overall query range and max-min fair query range objectives are investigated. Distributed algorithms are proposed which exploit the ZigBee cluster tree structure to keep the computation local. Extensive simulations show that the proposed methods achieve good approximation to the optimal solution with little overhead and improve the network performance.