A distributed ADMM approach for energy-efficient resource allocation in mobile edge computing
A distributed ADMM approach for energy-efficient resource allocation in mobile edge computing
Mobile edge computing (MEC) is a new promising technique to provide cloud-computing capabilities atthe edge of cellular networks in close proximity to mobile users. In this paper, we consider joint optimization of thecommunication and computation resources in a multiuser, multiserver MEC system. The objective of this optimizationproblem is to minimize the total energy consumption of mobile devices under the time-sharing constraint. Given thefact that no coordination is involved between mobile devices, we propose a light-weight and decentralized algorithmbased on the alternating direction method of multipliers (ADMM) framework. Experimental results demonstrate thatthe proposed algorithm performs well in terms of convergence and outperforms the conventional centralized approach.
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- Satyanarayanan M. The emergence of edge computing. Computer 2017; 50: 30-39.
- You C, Huang K, Chae H, Kim BH. Energy-efficient resource allocation for mobile-edge computation offloading.
IEEE T Wirel Commun 2017; 16: 1397-1411.
- Wang S, Zhang X, Zhang Y, Wang L, Yang J, Wang W. A survey on mobile edge networks: convergence of
computing, caching and communications. IEEE Access 2017; 5: 6757-6779.
- Mao Y, You C, Zhang J, Huang K, Letaief KB. A survey on mobile edge computing: the communication perspective.
IEEE Commun Surveys Tuts 2017; 19: 2322-2358.
- Wang Y, Sheng M, Wang X, Wang L, Li J. Mobile-edge computing: Partial computation offloading using dynamic
voltage scaling. IEEE T Commun 2016; 64: 4268-4282.
- Liu J, Mao Y, Zhang J, Letaief KB. Delay-optimal computation task scheduling for mobile-edge computing systems.
In: IEEE 2016 International Symposium on Information Theory; 10–15 July 2016; Barcelona, Spain. New York,
NY, USA: IEEE. pp. 1451-1455.
- You C, Huang K, Chae H. Energy efficient mobile cloud computing powered by wireless energy transfer. IEEE J
Sel Area Comm 2016; 34: 1757-1771.
- Mao Y, Zhang J, Letaief KB. Dynamic computation offloading for mobile-edge computing with energy harvesting
devices. IEEE J Sel Area Comm; 34: 3590-3605.
- Tao X, Ota K, Dong M, Qi H, Li K. Performance guaranteed computation offloading for mobile-edge cloud
computing. IEEE Wirel Commun Le 2017; 6: 774-777.
- Dinh TQ, Tang J, La QD, Quek TQS. Adaptive computation scaling and task offloading in mobile edge computing.
In: IEEE 2017 Wireless Communications and Networking Conference; 19–22 March 2017; San Francisco, CA, USA.
New York, NY, USA: IEEE. pp. 1-6.
- Lubin M, Yamangil E, Bent R, Vielma JP. Extended formulations in mixed-integer convex programming. In:
2016 Integer Programming and Combinatorial Optimization Conference; 1–3 June 2016; Liège, Belgium. Cham,
Switzerland: Springer. pp. 102-113.
- Diamond S, Takapoui R, Boyd S. A general system for heuristic minimization of convex functions over non-convex
sets. Optim Method Softw 2018; 33: 165-193.
- Boyd S, Parikh N, Chu E, Peleato B, Eckstein J. Distributed optimization and statistical learning via the alternating
direction method of multipliers. Found Trends Mach Learn 2011; 3: 1-122.
- Boyd S, Vandenberghe L. Convex Optimization. New York, NY, USA: Cambridge University Press, 2004.
- Liu B, Cao Y, Wang W, Jiang T. Energy budget aware device-to-device cooperation for mobile videos. In: IEEE
2015 Global Communications Conference; 6–10 December 2015; San Diego, CA, USA. New York, NY, USA: IEEE.
pp. 1-7.
- Liu M, Mao Y, Leng S, Mao S. Full-duplex aided user virtualization for mobile edge computing in 5g networks.
IEEE Access 2018; 6: 2996-3007.
- Chang Z, Gong J, Li Y, Zhou Z, Ristaniemi T, Shi G, Han Z, Niu Z. Energy efficient resource allocation for wireless
power transfer enabled collaborative mobile clouds. IEEE J Sel Area Comm 2016; 34: 3438-3450.
- Fang W, Li Y, Zhang H, Xiong N, Lai J, Vasilakos AV. On the throughput-energy tradeoff for data transmission
between cloud and mobile devices. Inform Sciences 2014; 283: 79-93.
- Kim HG. A connection method of lpsolve and excel for network optimization problem. J Korea Ind Inf Syst Res
2010; 15: 187-196.