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http://dx.doi.org/10.3837/tiis.2022.01.011

Performance Optimization and Analysis on P2P Mobile Communication Systems Accelerated by MEC Servers  

Liang, Xuesong (The School of Communication Engineering, Hangzhou Dianzi University)
Wu, Yongpeng (The Department of Electronic Engineering, Shanghai Jiao Tong University)
Huang, Yujin (The School of Communication Engineering, Hangzhou Dianzi University)
Ng, Derrick Wing Kwan (The School of Electrical Engineering and Telecommunications, University of New South Wales)
Li, Pei (The School of Communication Engineering, Hangzhou Dianzi University)
Yao, Yingbiao (The School of Communication Engineering, Hangzhou Dianzi University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.16, no.1, 2022 , pp. 188-210 More about this Journal
Abstract
As a promising technique to support tremendous numbers of Internet of Things devices and a variety of applications efficiently, mobile edge computing (MEC) has attracted extensive studies recently. In this paper, we consider a MEC-assisted peer-to-peer (P2P) mobile communication system where MEC servers are deployed at access points to accelerate the communication process between mobile terminals. To capture the tradeoff between the time delay and the energy consumption of the system, a cost function is introduced to facilitate the optimization of the computation and communication resources. The formulated optimization problem is non-convex and is tackled by an iterative block coordinate descent algorithm that decouples the original optimization problem into two subproblems and alternately optimizes the computation and communication resources. Moreover, the MEC-assisted P2P communication system is compared with the conventional P2P communication system, then a condition is provided in closed-form expression when the MEC-assisted P2P communication system performs better. Simulation results show that the advantage of this system is enhanced when the computing capability of the receiver increases whereas it is reduced when the computing capability of the transmitter increases. In addition, the performance of this system is significantly improved when the signal-to-noise ratio of hop-1 exceeds that of hop-2.
Keywords
Mobile Edge Computing; Computing and Relaying; Block Coordinate Descent; P2P Communication;
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1 J. Ahn, J. Lee, S. Yoon, and J. K. Choi, "A novel resolution and power control scheme for energy-efficient mobile augmented reality applications in mobile edge computing," IEEE Commun. Lett., vol. 9, no. 6, pp. 750-754, Jun. 2020.   DOI
2 S.-R. Yang, Y.-J. Tseng, C.-C. Huang, and W.-C. Lin, "Multi-access edge computing enhanced video streaming: Proof- of-concept implementation and prediction/QoE models," IEEE Trans. Veh. Technol., vol. 68, no. 2, pp. 1888-1902, Feb. 2019.   DOI
3 M. P. et al, "Mobile-edge computing introductory technical white paper," White Paper, Mobile-edge Comput. Ind. Initiative, Sep. 2014.
4 O. Munoz, A. Pascual-Iserte, and J. Vidal, "Joint allocation of radio and computational resources in wireless application offloading," in Proc. of Future Network Mobile Summit, pp. 1-10, Jul. 2013.
5 W. Sun, H. Zhang, R. Wang, and Y. Zhang, "Reducing offloading latency for digital twin edge networks in 6G," IEEE Trans. Veh. Technol., vol. 69, no. 10, pp. 12240-12251, Oct. 2020.   DOI
6 M. Kamoun, W. Labidi, and M. Sarkiss, "Joint resource allocation and offloading strategies in cloud enabled cellular networks," in Proc. of IEEE International Conference on Communications (ICC), pp. 5529-5534, Jun. 2015.
7 A. Faro, D. Giordano, and M. Venticinque, "Internetworked wrist sensing devices for pervasive and M-Connected eldercare," in Proc. of IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech), Nara, Japan, pp. 454-456, Mar. 2021.
8 W. Jin, R. Xu, T. You, Y.-G. Hong, and D. Kim, "Secure edge computing management based on independent microservices providers for gateway-centric iot networks," IEEE Access, vol. 8, pp. 187975-187990, Oct. 2020.   DOI
9 Y. Mao, J. Zhang, and K. B. Letaief, "Dynamic computation offloading for mobile-edge computing with energy harvesting devices," IEEE J. Sel. Areas Commun., vol. 34, no. 12, pp. 3590-3605, Dec. 2016.   DOI
10 A. Aijaz, M. Dohler, A. H. Aghvami, V. Friderikos, and M. Frodigh, "Realizing the tactile internet: Haptic communications over next generation 5G cellular networks," IEEE Wireless Communications, vol. 24, no. 2, pp. 82-89, Apr. 2017.   DOI
11 F. Bonomi, R. A. Milito, J. Zhu, and S. Addepalli, "Fog computing and its role in the internet of things," in Proc. of IEEE International Conference on Cloud Computing Technology and Science (2012), pp. 13-16, Apr. 2012.
12 X. Chen, L. Jiao, W. Li, and X. Fu, "Efficient multi-user computation offloading for mobile-edge cloud computing," IEEE ACM Transactions on Networking, vol. 24, no. 5, pp. 2795-2808, Oct. 2016.   DOI
13 Y. Mao, J. Zhang, S. H. Song, and K. B. Letaief, "Power-delay tradeoff in multi-user mobile-edge computing systems," in Proc. of IEEE Global Telecommunications Conference (GLOBECOM), pp. 1-6, Dec. 2016.
14 X. Wang, Z. Ning, and L. Wang, "Offloading in internet of vehicles: A fog-enabled real-time traffic management system," IEEE Trans. Ind. Informat., vol. 14, no. 10, pp. 4568-4578, Otc. 2018.   DOI
15 Y. Zhao, S. Zhou, T. Zhao, and Z. Niu, "Energy-efficient task offloading for multiuser mobile cloud computing," in Proc. of IEEE/CIC International Conference on Communications in China (ICCC), pp. 1-5, Nov. 2015.
16 C. You, K. Huang, H. Chae, and B. Kim, "Energy-efficient resource allocation for mobile-edge computation offloading," IEEE Trans. Wireless Commun., vol. 16, no. 3, pp. 1397-1411, Mar. 2017.   DOI
17 K. Barr and K. Asanovic, "Energy-aware lossless data compression," ACM Transactions on Computer Systems, vol. 24, no. 3, pp. 250-291, Aug. 2006.   DOI
18 W. Labidi, M. Sarkiss, and M. Kamoun, "Joint multi-user resource scheduling and computation offloading in small cell networks," in Proc. of IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), pp. 794-801, Oct. 2015.
19 S. Sardellitti, G. Scutari, and S. Barbarossa, "Joint optimization of radio and computational resources for multicell mobile cloud computing," in Proc. of IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC), pp. 354-358, Jun. 2014.
20 J. Tang, H. Tang, X. Zhang, K. Cumanan, G. Chen, K.-K. Wong, and J. A. Chambers, "Energy minimization in D2D-assisted cache-enabled internet of things: A deep reinforcement learning approach," IEEE Trans. Ind. Informat., vol. 16, no. 8, pp. 5412-5423, Aug. 2020.   DOI
21 G. Gui, M. Liu, F. Tang, N. Kato and F. Adachi, "6G: Opening New Horizons for Integration of Comfort, Security, and Intelligence," IEEE Wireless Communications, vol. 27, no. 5, pp. 126-132, Oct. 2020.   DOI
22 M. Qin, L. Chen, N. Zhao, Y. Chen, F. R. Yu, and G. Wei, "Computing and relaying: Utilizing mobile edge computing for P2P communications," IEEE Trans. Veh. Technol., vol. 69, no. 2, pp. 1582-1594, Feb. 2020.   DOI
23 H. T. Dinh, C. Lee, D. Niyato, and P. Wang, "A survey of mobile cloud computing: Architecture, applications, and approaches," Wireless Communications and Mobile Computing, vol. 13, no. 18, pp. 1587-1611, Sep. 2013.   DOI
24 S. Cao, X. Tao, Y. Hou, and Q. Cui, "An energy-optimal offloading algorithm of mobile computing based on HetNets," in Proc. of International Conference on Connected Vehicles and Expo (ICCVE), pp. 254-258, Oct. 2015.
25 O. Munoz, A. Pascual Iserte, J. Vidal, and M. Molina, "Energy-latency trade-off for multiuser wireless computation offloading," in Proc. of IEEE Wireless Communications and Networking Conference Workshops (WCNCW), pp. 29-33, Apr. 2014.
26 W. Shi et al., "Joint UL/DL Resource Allocation for UAV-Aided Full-Duplex NOMA Communications," IEEE Transactions on Communications, vol. 69, no. 12, pp. 8474-8487, Sept. 2021.   DOI
27 V. Cisco, "Cisco visual networking index: Forecast and trends, 2017-2022," White Paper, Nov. 2018.
28 S. Abolfazli, Z. Sanaei, E. Ahmed, A. Gani, and R. Buyya, "Cloud-based augmentation for mobile devices: Motivation, taxonomies, and open challenges," IEEE Communications Surveys Tutorials, vol. 16, no. 1, pp. 337-368, 1st Quart. 2014.   DOI
29 Y. Xu, G. Gui, H. Gacanin and F. Adachi, "A Survey on Resource Allocation for 5G Heterogeneous Networks: Current Research, Future Trends, and Challenges," IEEE Communications Surveys & Tutorials, vol. 23, no. 2, pp. 668-695, 2021.   DOI