C. Liu, M. Bennis, M. Debbah and H. V. Poor, "Dynamic Task Offloading and Resource Allocation for Ultra-Reliable Low-Latency Edge Computing," in IEEE Transactions on Communications, vol. 67, no. 6, pp. 4132-4150, June 2019. doi: 10.1109/TCOMM.2019.2898573
Dynamic task offloading and resource allocation for ultra-reliable low-latency edge computing
|Author:||Liu, Chen-Feng1; Bennis, Mehdi1; Debbah, Mérouane2,3;|
1Centre for Wireless Communications, University of Oulu, 90014 Oulu, Finland
2Large Networks and System Group, CentraleSupélec, Université Paris–Saclay, 91192 Gif-sur-Yvette, France
3Mathematical and Algorithmic Sciences Laboratory, Huawei France Research and Development, 92100 Paris, France
4Department of Electrical Engineering, Princeton University, Princeton, NJ 08544, USA
|Online Access:||PDF Full Text (PDF, 6.8 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2019121046448
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2019-12-10
To overcome devices’ limitations in performing computation-intense applications, mobile edge computing (MEC) enables users to offload tasks to proximal MEC servers for faster task computation. However, the current MEC system design is based on average-based metrics, which fails to account for the ultra-reliable low-latency requirements in mission-critical applications. To tackle this, this paper proposes a new system design, where probabilistic and statistical constraints are imposed on task queue lengths, by applying extreme value theory. The aim is to minimize users’ power consumption while trading off the allocated resources for local computation and task offloading. Due to wireless channel dynamics, users are reassociated to MEC servers in order to offload tasks using higher rates or accessing proximal servers. In this regard, a user-server association policy is proposed, taking into account the channel quality as well as the servers’ computation capabilities and workloads. By marrying tools from Lyapunov optimization and matching theory, a two-timescale mechanism is proposed, where a user-server association is solved in the long timescale, while a dynamic task offloading and resource allocation policy are executed in the short timescale. The simulation results corroborate the effectiveness of the proposed approach by guaranteeing highly reliable task computation and lower delay performance, compared to several baselines.
IEEE transactions on communications
|Pages:||4132 - 4150|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work was supported in part by the Academy of Finland project CARMA, in part by the Academy of Finland project MISSION, in part by the Academy of Finland project SMARTER, in part by the INFOTECH project NOOR, in part by the Nokia Bell-Labs project FOGGY, in part by the Nokia Foundation, and in part by the U.S. National Science Foundation under Grant CNS-1702808.
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