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Mobile Edge Computing via Wireless Power Transfer Over Multiple Fading Blocks: An Optimal Stopping Approach
- Source :
- IEEE Transactions on Vehicular Technology. 69:10348-10361
- Publication Year :
- 2020
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2020.
-
Abstract
- To support wireless Internet of things (IoT) devices, this paper presents a new solution which combines wireless power transfer and mobile edge computing. Specifically, we consider one mobile device, which first harvests energy from radio frequency signals sent by a base station and then offloads all or part of its data to be processed to the base station. The process of energy harvesting and offloading span over multiple fading blocks. The target is to maximize the average amount of processed data in unit time. To achieve this target, we optimize the stopping rule for energy harvesting (i.e., when to stop energy harvesting and start offloading) and the number of fading blocks for data offloading. To solve the formulated problem optimally, we decompose it into two levels. In the lower level, the stopping rule for energy harvesting is optimized given a fixed number of fading blocks for offloading. The associated lower-level problem is solved optimally based on a series of special properties of the problem. In the upper level, the number of fading blocks for offloading is optimized. Efficiency of our work with fully offloading mode and partially offloading mode is shown by using simulation.
- Subjects :
- Mobile edge computing
Computer Networks and Communications
business.industry
Computer science
ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS
Real-time computing
Aerospace Engineering
020302 automobile design & engineering
02 engineering and technology
Computer Science::Performance
Base station
0203 mechanical engineering
Automotive Engineering
Computer Science::Networking and Internet Architecture
Wireless
Fading
Optimal stopping
Wireless power transfer
Electrical and Electronic Engineering
business
Energy harvesting
Mobile device
Computer Science::Distributed, Parallel, and Cluster Computing
Edge computing
Subjects
Details
- ISSN :
- 19399359 and 00189545
- Volume :
- 69
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Vehicular Technology
- Accession number :
- edsair.doi...........9258842eb624ce7f905953eac656eb7a
- Full Text :
- https://doi.org/10.1109/tvt.2020.3005406