Abstract
Wireless mobile sensing systems are hierarchical and heterogeneous in nature with components that have different energy and performance capabilities. In such systems allocation of tasks to different devices affects both performance and the entire system battery lifetime. In this paper we formulate the problem of optimal task assignment with objectives related to minimizing the total system energy consumption and maximizing the system lifetime as an Integer Linear Program (ILP). We describe a heuristic algorithm and two dynamic graph-based partitioning algorithms that are computationally efficient and that are able to adapt in real-time to changing system conditions. ILP based solutions are able to achieve optimal task assignment, but cannot be used in dynamically changing conditions due to their computationally expensive nature. We evaluate the performance of our three dynamic algorithms using Qualnet and show that they have up to 88% longer system lifetime than the ILP based solutions.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
