C. Liu, M. Bennis and H. V. Poor, "Latency and Reliability-Aware Task Offloading and Resource Allocation for Mobile Edge Computing," 2017 IEEE Globecom Workshops (GC Wkshps), Singapore, 2017, pp. 1-7. doi: 10.1109/GLOCOMW.2017.8269175
Latency and reliability-aware task offloading and resource allocation for mobile edge computing
|Author:||Liu, Chen-Feng1; Bennis, Mehdi1; Poor, H. Vincent2|
1Centre for Wireless Communications, University of Oulu, Finland
2Department of Electrical Engineering, Princeton University, NJ, USA
|Online Access:||PDF Full Text (PDF, 0.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2018080633390
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2018-08-06
While mobile edge computing (MEC) alleviates the computation and power limitations of mobile devices, additional latency is incurred when offloading tasks to remote MEC servers. In this work, the power-delay tradeoff in the context of task offloading is studied in a multi-user MEC scenario. In contrast with current system designs relying on average metrics (e.g., the average queue length and average latency), a novel network design is proposed in which latency and reliability constraints are taken into account. This is done by imposing a probabilistic constraint on users' task queue lengths and invoking results from extreme value theory to characterize the occurrence of low- probability events in terms of queue length (or queuing delay) violation. The problem is formulated as a computation and transmit power minimization subject to latency and reliability constraints, and solved using tools from Lyapunov stochastic optimization. Simulation results demonstrate the effectiveness of the proposed approach, while examining the power-delay tradeoff and required computational resources for various computation intensities.
|Pages:||1 - 7|
2017 IEEE Globecom Workshops (GC Wkshps)
IEEE Globecom Workshops
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This research was supported by the Academy of Finland project CARMA, the Nokia Bell-Labs project FOGGY, the Nokia Foundation, Emil Aaltosen säätiö, and the U.S. National Science Foundation under Grants CCF-1420575 and CNS-1702808.
|Academy of Finland Grant Number:||
289611 (Academy of Finland Funding decision)
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