| Paper ID | C-1-3.1 |
| Paper Title |
Probabilistic Binary Offloading for Wireless Powered Mobile Edge Computing System |
| Authors |
Takuya Kobayashi, Koichi Adachi, The University of Electro-Communications, Japan |
| Session |
C-1-3: Emerging technologies based on signal processing for wireless sensor networks |
| Time | Tuesday, 08 December, 17:15 - 19:15 |
| Presentation Time: | Tuesday, 08 December, 17:15 - 17:30 Check your Time Zone |
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All times are in New Zealand Time (UTC +13) |
| Topic |
Wireless Communications and Networking (WCN): Special Session: Emerging technologies based on signal processing for wireless sensor networks |
| Abstract |
In recent years, with the advancement of the Internet-of-Things (IoT), some problems are listed. First, the computation resource is limited because of miniaturization and decreasing costs for IoT devices and sensors. Mobile edge computing (MEC) that can compute alternatively heavy tasks of wireless devices (WDs) has been proposed for solving this problem. Second, the WDs' battery management is troublesome because of the increasing number of IoT devices and sensors. Wireless power transfer (WPT) has been proposed for solving this problem. In WPT, an access point (AP) wirelessly charges batteries of WDs. Wireless powered-mobile edge computing (WP-MEC) system combining WPT and MEC is expected to solve these problems. This paper proposes a probabilistic binary offloading (PBO) system that selects one of two modes for each WD; offloading and local computing. The mode selection is determined by probabilistic control instead of the centralized control by the AP. Moreover, we propose a mode switching method that switches from offloading to local computing when the WD fails to offload tasks. We aim to reduce energy consumption of WDs and task processing delay and improving communication quality. |