Joint resource allocation and coordinated computation offloading for fog radio access networks

China Communications

Volumn 13, Issue , 2016, Pages 131-139

  Liang, Kai ^a   Zhao, Liqiang ^a   Zhao, Xiaohui ^a   Wang, Yong ^a   Ou, Shumao ^b  

^a XIDIAN UNIVERSITY   (China)

^b OXFORD BROOKES UNIVERSITY   (United Kingdom)

Author keywords

C RAN; computation offloading; fog RAN; resource allocation

Indexed keywords

EID: 85011317608     PISSN: 16735447     EISSN: None     Source Type: Journal    
DOI: 10.1109/CC.2016.7833467     Document Type: Article

References (21)

1. F. Bonomi, R. Milito, J. Zhu, and S. Addepalli, "Fog computing and itsrole in the Internet of Things", In Workshop on Mobile Cloud Computing, MCC'12, Helsinki, Finland, pp. 13-16, Aug. 2012.
2. K. Kumar and Y. H. Lu, "Cloud computing for mobile users: Can offloading computation save energy?", Computer, vol. 43, no. 4, pp. 51-56, Apr. 2010.
3. S. Barbarossa, S. Sardellitti, and P. Di Lorenzo, "Computation offloading for mobile cloud computing based on wide cross-layer optimization", in Proc. Future Netw. Mobile Summit (FuNeMS'13), Lisboa, Portugal, pp. 1-10, Jul.3-5, 2013.
4. D. Huang, P. Wang, and D. Niyato, "A dynamic offloading algorithm for mobile computing", IEEE Trans. Wireless Commun., vol. 11, no. 6, pp. 1991-1995, Apr. 2012.
5. W. Zhang, Y. Wen, and D. Oliver, "Collaborative task execution in mobile cloud computing under a stochastic wireless channel", IEEE Trans. Wireless Commun, vol. 14, no. 1, pp. 81-93, January. 2015.
6. C. Wang, Y. Li and D. Jin, "Mobility-assisted opportunistic computation off loading", IEEE COMMUNICATIONS LETTERS, vol. 18, no. 10, pp. 1779-1782, October. 2014.
7. S. Sarkary, S. Chatterjee, and S. Misra, "Assessment of the Suitability of Fog Computing in the Context of Internet of Things," IEEE Trans. Cloud Computing, DOI: 10.1109/TCC.2015.2485206, 2015.
8. H. Xiang, M. Peng, Y. Cheng and H-H Chen, "Joint mode selection and ressource allocation for downlink fog radio access networks supported D2D", 2015 QSHINE, pp. 117-182, 2015.
9. M. Peng, et al. "Fog-computing-based radio access networks: issues and challenges", IEEE Network, vol.30, no. 4 pp. 46-53, 2015.
10. R. Tandon and O. Simeone. "Harnessing cloud and edge synergies: toward an information theory of fog radio access networks", IEEE Communications Magazine, vol. 54 no.6, pp. 44-50, 2016.
11. S. Sardellitti, G. Scutari, and S. Barbarossa, "Joint optimization of radio and computational resources for multicell mobile-edge computing", IEEE Transactions on Signal and Information Processing over Networks, vol. 1, no. 2, pp. 89-103, Jun. 2015.
12. L. M. Vaquero, L. Rodero-Merino. "Finding your way in the fog: Towards a comprehensive definition of fog computing", ACM SIGCOMM Computer Communication Review, vol. 44, no. 5, pp. 27-32, 2014.
13. K. Hong, et al. "Mobile fog: A programming model for large-scale applications on the internet of things. Proceedings of the second ACM SIGCOMM workshop on Mobile cloud computing. ACM, 2013.
14. N. B. Truong et al. "Software defined networking-based vehicular Adhoc Network with Fog Computing", 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM), 2015.
15. Kai Liang, Liqiang Zhao, Xiaoli Chu, and Hsiao-Hwa Chen, "An Integrated Architecture for Software Defined and Virtualized Radio Access Networks with Fog Computing", IEEE Network, 2016. (In Press). Availabe at http://web.xidian. Edu.cn/Iqzhao/files/20160923-082655.pdf
16. J. Park, G. Lee, Y. Sung and M. Yukawa, "Coordinated Beamforming With Relaxed Zero Forcing: The Sequential Orthogonal Projection Combining Method and Rate Control", IEEE Trans. signal process., vol. 61, no. 12, pp. 3100-3112, 2013.
17. W Yu, T. Kwon, and C. Shin, Multi cell Coordination via Joint Scheduling, Beamforming, and Power Spectrum Adaptation, IEEE Trans. Commun., vol. 12, no. 7, pp. 1-14, 2013.
18. S. Yamada, T. Tanino, M. Inuiguchi and K. Tatsumi, "An inner approximation method for a reverse convex programming problem", IEEE SMC 1999, pp. 521-526, 1999.
19. Y. Shu, Y. Gu and J. Chen, "Dynamic Authentication with Sensory Information for the Access Control Systems", IEEE Trans. Paral. & Distributed Systems, vol. 25, no. 2, pp. 427-436, 2014.
20. Boyd, "EE364b :Convex Optimization II", available at http://stanford.edu/class/ee364b/.
21. F. Jalali et al., "Fog Computing May Help to Save Energy in Cloud Computing", IEEE Journal on Selected Areas in Communications, vol. 34, no. 5, pp. 1728-1739, 2016.