Computers and Intractability; A Guide to the Theory of NP-Completeness
Computers and Intractability; A Guide to the Theory of NP-Completeness
Markov-optimal sensing policy for user state estimation in mobile devices
Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks
Adapting task utility in externally triggered energy harvesting wireless sensing systems
INSS'09 Proceedings of the 6th international conference on Networked sensing systems
An event-driven energy efficient framework for wearable health-monitoring system
AMT'12 Proceedings of the 8th international conference on Active Media Technology
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We implemented and analyzed the battery lifetime optimization problem for wireless healthcare systems and showed that task assignment can play a major role in energy management. In the static case, where system parameters are fixed (e.g. processing and communication latency), the assignment of tasks to heterogeneous nodes in the system significantly affects performance and the level of available energy. Since task binding and scheduling problems are NP hard [1], heuristic algorithms are needed for practical solutions. Furthermore, the overall system characteristics are dynamically changing - the availability of the wireless network and its throughput, battery capacity of various nodes in the system, the user's needs, etc. To address the dynamic aspects of the system and the resource constrained nature of the mobile nodes, we will implement a heuristic algorithm to achieve a longer battery lifetime of the system. We plan to evaluate the performance of the heuristic and compare it against the optimal solutions produced by the ILP.