Wireless-Powered Mobile Edge Computing Systems
Feng Wang
School of Information Engineering, Guangdong University of Technology, China
Search for more papers by this authorJie Xu
School of Information Engineering, Guangdong University of Technology, China
Search for more papers by this authorXin Wang
Key Laboratory for Information Science of Electromagnetic Waves (MoE), the Shanghai Institute for Advanced Communication and Data Science, Department of Communication Science and Engineering, Fudan University, China
Search for more papers by this authorShuguang Cui
Department of Electrical and Computer Engineering, University of California, Davis, USA
Shenzhen Research Institute of Big Data, China
Search for more papers by this authorFeng Wang
School of Information Engineering, Guangdong University of Technology, China
Search for more papers by this authorJie Xu
School of Information Engineering, Guangdong University of Technology, China
Search for more papers by this authorXin Wang
Key Laboratory for Information Science of Electromagnetic Waves (MoE), the Shanghai Institute for Advanced Communication and Data Science, Department of Communication Science and Engineering, Fudan University, China
Search for more papers by this authorShuguang Cui
Department of Electrical and Computer Engineering, University of California, Davis, USA
Shenzhen Research Institute of Big Data, China
Search for more papers by this authorDerrick Wing Kwan Ng
The University of New South Wales, Australia
Search for more papers by this authorSummary
This chapter develops a joint mobile edge computing-wireless power transfer (MEC-WPT) design by considering a wireless powered multi-user MEC system that consists of a multi-antenna access point (AP) and multiple single-antenna users. A time division multiple access (TDMA) protocol is employed to coordinate computation offloading, where different users offload their respective tasks to the AP over orthogonal time slots. The chapter considers a more general case with resource sharing among multiple users and allows for more flexible partial offloading to improve the system performance in terms of the energy efficiency. It provides numerical results to illustrate the performance of the proposed optimal joint MEC-WPT design. The numerical results demonstrated the merits of the proposed joint design over alternative benchmark schemes. The proposed joint MEC-WPT design can pave the way to facilitate ubiquitous and self-sustainable computing for Internet-of-Things (IoT) devices.
Bibliography
- F. Wang, J. Xu, X. Wang, and S. Cui (2017) Joint offloading and computing optimization in wireless powered mobile-edge computing systems. IEEE Trans. Wireless Commun., accepted. [Online]. Available: https://arxiv.org/abs/1702.00606.
- M. Chiang and T. Zhang (2016) Fog and IoT: An overview of research opportunities. IEEE Internet Thing J., 3 (6): 854–864.
- Y. Mao, C. You, J. Zhang, K. Huang, and K.B. Letaief (2017) A survey on mobile edge computing: The communication perspective. IEEE Commun. Survey Tutorials, 19 (4): 2322–2358.
- S. Barbarossa, S. Sardellitti, and P.D. Lorenzo (2014) Communicating while computing: Distributed mobile cloud computing over 5G heterogenous networks. IEEE Signal Process. Mag., 31 (6): 45–55.
- E. Cuervo, A. Balasubramanian, D. Cho, A. Wolman, S. Saroiu, R. Chandra, and P. Bahl (2010) MAUI: Making smartphones last longer with code offload. In Proceedings of the ACM MobiSys, San Francisco, CA, pp. 49–62.
- S. Kosta, A. Aucinas, P. Hui, R. Mortier, and X. Zhang (2012) ThinkAir: Dynamic resource allocation and parallel execution in the cloud for mobile code offloading. In Proceedings of the IEEE INFOCOM, Orlando, pp. 945–953.
- R. Zhang and C.K. Ho (2013) MIMO broadcasting for simultaneous wireless information and power transfer. IEEE Trans. Wireless Commun., 12 (5): 1989–2001.
- D.W.K. Ng, E.S. Lo, and R. Schober (2014) Robust beamforming for secure communication in systems with wireless power transfer. IEEE Trans. Wireless Commun., 13 (8): 4599–4615.
- S. Timotheou, I. Krikidis, G. Zheng, and B. Ottersten (2014) Beamforming for MISO interference channels with QoS and RF energy transfer. IEEE Trans. Wireless Commun., 13 (5): 2646–2658.
- S. Bi, R. Zhang, and C. Ho (2015) Wireless powered communication: Opportunities and challenges. IEEE Commun. Mag., 53 (4): 117–125.
- H. Li, J. Xu, R. Zhang, and S. Cui (2015) A general utility optimization framework for energy harvesting based wireless communications. IEEE Commun. Mag., 53 (4): 79–85.
- J. Xu, L. Liu, and R. Zhang (2014) Multiuser MISO beamforming for simultaneous wireless information and power transfer. IEEE Trans. Signal Process., 62 (18): 4798–4810.
- F. Wang, T. Peng, Y. Huang, and X. Wang (2015) Robust transceiver optimization for power-splitting based downlink MISO SWIPT systems. IEEE Signal Process. Lett., 22 (9): 1492–1496.
- F. Wang, C. Xu, Y. Huang, X. Wang, and X.-Q. Gao (2017) REEL-BF design: Achieving the SDP bound for downlink beamforming with arbitrary shaping constraints. IEEE Trans. Signal Process., 65 (10): 2672–2685.
- Y. Zeng and R. Zhang (2015) Optimized training design for wireless energy transfer. IEEE Trans. Commun., 63 (2): 536–550.
- J. Xu and R. Zhang (2014) Energy beamforming with one-bit feedback. IEEE Trans. Signal Process., 62 (20): 5370–5381.
- J. Xu and R. Zhang (2016) A general design framework for MIMO wireless energy transfer with limited feedback. IEEE Trans. Signal Process., 64 (10): 2475–2488.
- C. Valenta and G. Durgin (2014) Harvesting wireless power: Survey of energy-harvester conversion efficiency in far-field, wireless power transfer systems. IEEE Microwave Mag., 15 (4): 108–120.
- Y. Zeng, B. Clerckx, and R. Zhang (2017) Communications and signals design for wireless power transmission. IEEE Trans. Commun., 65 (5): 2264–2290.
- S. Lee and R. Zhang (2017) Distributed wireless power transfer with energy feedback. IEEE Trans. Signal Process., 65 (7): 1685–1699.
- E. Boshkovska, D.W.K. Ng, N. Zlatanov, and R. Schober (2015) Practical non-linear energy harvesting model and resource allocation for SWIPT systems. IEEE Commun. Lett., 19 (12): 2082–2085.
- B. Clerckx and E. Bayguzina (2016) Waveform design for wireless power transfer. IEEE Trans. Signal Process., 64 (23): 6313–6328.
- F. Liu, P. Shu, H. Jin, L. Ding, J. Yu, D. Niu, and B. Li (2013) Gearing resource-poor mobile devices with powerful clouds: Architectures, challenges, and applications. IEEE Wireless Commun., 20 (3): 14–22.
- J. Liu, Y. Mao, J. Zhang, and K.B. Letaief (2016) Delay-optimal computation task scheduling for mobile-edge computing systems. In Proceedings of the IEEE ISIT, Barcelona, Spain, pp. 1451–1455.
- D. Huang, P. Wang, and D. Niyato (2012) A dynamic offloading algorithm for mobile computing. IEEE Trans. Wireless Commun., 11 (6): 1991–1995.
- O. Muñoz, A. Pascual-Iserte, and J. Vidal (2015) Optimization of radio and computational resources for energy efficiency in latency-constrained application offloading. IEEE Trans. Veh. Technol., 64 (10): 4738–4755.
- M.-H. Chen, B. Liang, and M. Dong (2016) Joint offloading decision and resource allocation for multi-user multi-task mobile cloud. In Proceedings of the IEEE ICC, Kuala Lumpur, Malaysia, pp. 1–6.
- X. Chen, L. Jiao, W. Li, and X. Fu (20160 Efficient multi-user computation offloading for mobile-edge cloud computing. IEEE/ACM Trans. Network., 24 (5): 2795–2808.
- C. You, K. Huang, H. Chae, and B. Kim (2017) Energy-efficient resource allocation for mobile-edge computation offloading. IEEE Trans. Wireless Commun., 16 (3): 1397–1411.
- S. Sardellitti, G. Scutari, and S. Barbarossa (2015) Joint optimization of radio and computational resources for multicell mobile-edge computing. IEEE Trans. Signal Inf. Process. Network., 1 (2): 89–103.
- F. Wang, J. Xu, and Z. Ding (2017) Optimized multiuser computation offloading with multi-antenna NOMA. In Proceedings of the IEEE GLOBECOM Workshop, Singapore, pp. 1–7.
- X. Cao, F. Wang, J. Xu, R. Zhang, and S. Cui (2017) Joint computation and communication cooperation for mobile edge computing. [Online]. Available: https://arxiv.org/abs/1704.06777.
- C. You, K. Huang, and H. Chae (2016) Energy efficient mobile cloud computing powered by wireless energy transfer. IEEE J. Selected Areas Commun., 34 (5): 1757–1770.
- F. Wang (2017) Computation rate maximization for wirless powered mobile edge computing. In Proceedigns of the APCC, Perth, Australia, pp. 1–6.
- S. Bi and Y. Zhang (2017) Computation rate maximization for wireless powered mobile-edge computing with binary computation offloading. [Online]. Available: https://arxiv.org/abs/1708.08810.
- T.D. Burd and R.W. Brodersen (1996) Processor design for portable systems. Kluwer J. VLSI Signal Process. Syst., 13 (2): 203–221.
- R. Corless, G. Gonnet, D. Hare, D. Jeffrey, and D. Knuth (1996) On the Lambert W function. Adv. Comput. Math., 5 (1): 329–359.
-
S. Boyd and L. Vandenberghe (2004) Convex Optimization. Cambridge University Press, Cambridge.
10.1017/CBO9780511804441 Google Scholar
- S. Boyd. Ellipsoid method notes, EE364b Lectures, Stanford University, California. [Online]. Available: http://stanford.edu/class/ee364b/lectures/ellipsoid_method_notes.pdf.
- M. Grant, S. Boyd, and Y. Ye (2009) CVX: Matlab software for disciplined convex programming. [Online]. Available: http://cvxr.com/cvx/.
