KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
권호 표지
DOI QR코드

DOI QR Code

Joint Optimization for Residual Energy Maximization in Wireless Powered Mobile-Edge Computing Systems

  • Liu, Peng (College of Computer Science and Technology, Jilin University) ;
  • Xu, Gaochao (College of Computer Science and Technology, Jilin University) ;
  • Yang, Kun (School of Computer Science and Electronic Engineering, University of Essex) ;
  • Wang, Kezhi (Department of Computer and Information Sciences Northumbria University) ;
  • Li, Yang (College of Computer Science and Technology, Jilin University)
  • Received : 2017.12.29
  • Accepted : 2018.07.12
  • Published : 2018.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Mobile Edge Computing (MEC) and Wireless Power Transfer (WPT) are both recognized as promising techniques, one is for solving the resource insufficient of mobile devices and the other is for powering the mobile device. Naturally, by integrating the two techniques, task will be capable of being executed by the harvested energy which makes it possible that less intrinsic energy consumption for task execution. However, this innovative integration is facing several challenges inevitably. In this paper, we aim at prolonging the battery life of mobile device for which we need to maximize the harvested energy and minimize the consumed energy simultaneously, which is formulated as residual energy maximization (REM) problem where the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device are all considered as key factors. To this end, we jointly optimize the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device to solve the REM problem. Furthermore, we propose an efficient convex optimization and sequential unconstrained minimization technique based combining method to solve the formulated multi-constrained nonlinear optimization problem. The result shows that our joint optimization outperforms the single optimization on REM problem. Besides, the proposed algorithm is more efficiency.

Keywords

References

  1. H. T. Dinh, C. Lee, D. Niyato, and P. Wang, "A survey of mobile cloud computing: architecture, applications, and approaches," Wireless Communications & Mobile Computing, vol. 13, no. 18, pp. 1587-1611, 2013. https://doi.org/10.1002/wcm.1203
  2. S. Barbarossa, S. Sardellitti, and P. D. Lorenzo, "Communicating while computing: Distributed mobile cloud computing over 5g heterogeneous networks," IEEE Signal Processing Magazine, vol. 31, no. 6, pp. 45-55, 2014. https://doi.org/10.1109/MSP.2014.2334709
  3. ETSI, "Etsi mobile-edge computing - introductory technical white paper," 2016.
  4. M. T. Beck, S. Feld, C. Linnhoff-Popien, and U. Ptzschler, "Mobile edge computing," Informatik-Spektrum, vol. 39, no. 2, pp. 1-7, 2016. https://doi.org/10.1007/s00287-015-0946-1
  5. Y. Mao, C. You, J. Zhang, K. Huang, and K. B. Letaief, "Mobile edge computing: Survey and research outlook," 2017.
  6. X. Lu, P. Wang, D. Niyato, I. K. Dong, and Z. Han, "Wireless networks with rf energy harvesting: A contemporary survey," IEEE Communications Surveys & Tutorials, vol. 17, no. 2, pp. 757-789, 2014. https://doi.org/10.1109/COMST.2014.2368999
  7. S. Bi, C. K. Ho, and R. Zhang, "Wireless powered communication: opportunities and challenges," IEEE Communications Magazine, vol. 53, no. 4, pp. 117-125, 2014. https://doi.org/10.1109/MCOM.2015.7081084
  8. K. Kumar and Y. H. Lu, "Cloud computing for mobile users: Can offloading computation save energy?," Computer, vol. 43, no. 4, pp. 51-56, 2010. https://doi.org/10.1109/MC.2010.98
  9. S. Kosta, A. Aucinas, P. Hui, and R. Mortier, "Thinkair: Dynamic resource allocation and parallel execution in the cloud for mobile code offloading," in Proc. of INFOCOM, 2012 Proceedings IEEE, pp. 945-953, 2012.
  10. E. Cuervo, A. Balasubramanian, D. K. Cho, A. Wolman, S. Saroiu, R. Chandra, and P. Bahl, "Maui:making smartphones last longer with code offload," in Proc. of International Conference on Mobile Systems, Applications,and Services, pp. 49-62, 2010.
  11. B. G. Chun, S. Ihm, P. Maniatis, M. Naik, and A. Patti, "Clonecloud: elastic execution between mobile device and cloud," in Proc. of Conference on Computer Systems, pp. 301-314, 2011.
  12. Y. Mao, C. You, J. Zhang, K. Huang, and K. B. Letaief, "A survey on mobile edge computing: The communication perspective," IEEE Communications Surveys & Tutorials, vol. PP, no. 99, pp. 1-1, 2017.
  13. S. Barbarossa, S. Sardellitti, and P. D. Lorenzo, "Joint allocation of computation and communication resources in multiuser mobile cloud computing," in Proc. of IEEE 14th Workshop on Signal Processing Advances in Wireless Communications, vol. 395, no. 6, pp. 26-30, 2013.
  14. Y. Wang, M. Sheng, X. Wang, L. Wang, and J. Li, "Mobile-edge computing: Partial computation offloading sing dynamic voltage scaling," IEEE Transactions on Communications, vol. 64, no. 10, pp. 4268-4282,2016. https://doi.org/10.1109/TCOMM.2016.2599530
  15. S. Sardellitti, G. Scutari, and S. Barbarossa, "Joint optimization of radio and computational resources for multicell mobile-edge computing," IEEE Transactions on Signal & Information Processing Over Networks, vol. 1, no. 2, pp. 89-103, 2014. https://doi.org/10.1109/TSIPN.2015.2448520
  16. P. Zhao, H. Tian, C. Qin, and G. Nie, "Energy-saving offloading by jointly allocating radio and computational resources for mobile edge computing," IEEE Access, vol. PP, no. 99, pp. 1-1, 2017.
  17. Y. Mao, J. Zhang, S. H. Song, and K. B. Letaief, "Stochastic joint radio and computational resource management for multi-user mobile-edge computing systems," IEEE Transactions on Wireless Communications,vol. 16, no. 9, pp. 5994-6009, 2017. https://doi.org/10.1109/TWC.2017.2717986
  18. C. You, K. Huang, and H. Chae, "Energy efficient mobile cloud computing powered by wireless energy transfer," IEEE Journal on Selected Areas in Communications, vol. 34, no. 5, pp. 1757-1771, 2016. https://doi.org/10.1109/JSAC.2016.2545382
  19. F. Wang, J. Xu, X. Wang, and S. Cui, "Joint offloading and computing optimization in wireless powered mobile-edge computing systems," IEEE Transactions on Wireless Communications, vol. PP, no. 99, pp. 1-1, 2017.
  20. Y. Mao, J. Zhang, and K. B. Letaief, "Dynamic computation offloading for mobile-edge computing with energy harvesting devices," IEEE Journal on Selected Areas in Communications, vol. 34, no. 12, pp. 3590-3605, 2016. https://doi.org/10.1109/JSAC.2016.2611964
  21. S. Bi and Y. J. A. Zhang, "Computation rate maximization for wireless powered mobile-edge computing with binary computation offloading," 2017.
  22. H. Gao, W. Ejaz, and M. Jo, "Cooperative wireless energy harvesting and spectrum sharing in 5g networks," IEEE Access, vol. 4, pp. 3647-3658, 2017.
  23. L. Yang, J. Cao, S. Tang, T. Li, and A. T. S. Chan, "A framework for partitioning and execution of data stream applications in mobile cloud computing," in Proc. of IEEE International Conference on Cloud Computing, pp. 23-32, 2012.
  24. O. Muoz, A. Pascual-Iserte, and J. Vidal, "Optimization of radio and computational resources for energy efficiency in latency-constrained application offloading," IEEE Transactions on Vehicular Technology,vol. 64, no. 10, pp. 4738-4755, 2014. https://doi.org/10.1109/TVT.2014.2372852
  25. Jan M. Rabaey, "Digital integrated circuits: a design perspective," Prentice Hall, 1996.
  26. G. Qu, "What is the limit of energy saving by dynamic voltage scaling?," in Proc. of Ieee/acm International Conference on Computer Aided Design, pp. 560-563, 2001.
  27. S. Boyd and L. Vandenberghe, "Convex Optimization," Cambrige University Press 2004.
  28. R. M. Corless, G. H. Gonnet, D. E. G. Hare, D. J. Jeffrey, and D. E. Knuth, "On the lambert ww function.," Advances in Computational Mathematics, vol. 5, no. 1, pp. 329-359, 1996. https://doi.org/10.1007/BF02124750
  29. Broyden-Fletcher-Goldfarb-Shanno algorithm.
  30. R. E. Perez, P. W. Jansen, and J. R. R. A. Martins, "pyopt: a python-based object-oriented framework for nonlinear constrained optimization," Structural & Multidisciplinary Optimization, vol. 45, no. 1, pp. 101-118, 2012. https://doi.org/10.1007/s00158-011-0666-3
  31. R. Andreani, E. G. Birgin, J. M. MartÍ, and N. L. Schuverdt, "On augmented lagrangian methods with general lower-level constraints," Siam Journal on Optimization, vol. 18, no. 4, pp. 1286-1309, 2007. https://doi.org/10.1137/060654797
  32. D. Kraft, "A software package for sequential quadratic programming," 1988.

Cited by

  1. Jointly Optimize the Residual Energy of Multiple Mobile Devices in the MEC-WPT System vol.12, pp.12, 2018, https://doi.org/10.3390/fi12120233