Research Article
Optimal Device Management Service Selection in Internet-of-Things
@INPROCEEDINGS{10.1007/978-3-030-30146-0_4, author={Weiling Li and Yunni Xia and Wanbo Zheng and Peng Chen and Jia Lee and Yawen Li}, title={Optimal Device Management Service Selection in Internet-of-Things}, proceedings={Collaborative Computing: Networking, Applications and Worksharing. 15th EAI International Conference, CollaborateCom 2019, London, UK, August 19-22, 2019, Proceedings}, proceedings_a={COLLABORATECOM}, year={2019}, month={8}, keywords={Internet-of-Things (IoT) IoT Device Management Vector bin packing problem Genetic Algorithm (GA)}, doi={10.1007/978-3-030-30146-0_4} }- Weiling Li
Yunni Xia
Wanbo Zheng
Peng Chen
Jia Lee
Yawen Li
Year: 2019
Optimal Device Management Service Selection in Internet-of-Things
COLLABORATECOM
Springer
DOI: 10.1007/978-3-030-30146-0_4
Abstract
In Internet-of-Things (IoT), IoT device management is a challenge for device owners considering the huge amount of devices and their heterogeneous quality of service (QoS) requirements. Recently, IoT device management service (MS) providers are arising to serve device owners. Device owners can now easily manage their devices by using IoT device MSs. It is critical to select suitable MSs from numerous candidates for devices. An optimal service selection must maximize the number of MS managed devices and minimize the total cost while ensuring the QoS requirements of IoT system. To optimize the IoT Device Management Service Selection problem, we propose IDMSS, a Lexicographic Goal Programming (LGP) based approach. However, due to the high computational complexity of the IoT Device Management Service Selection problem, an alternative heuristic-based approach called GA4MSS is proposed. Two series of experiments have been conducted and the experimental results show the performance of our approaches.
