Abstract
In Mobile Edge Computing (MEC) paradigm, popular and repetitive content can be cached and offloaded from nearby MEC server in order to reduce the backhaul overload. Due to hardware limitation of MEC devices, collaboration among MEC servers can greatly improve the cache performance. In this paper, we propose a Collective Behavior aware Collaborative Caching (CBCC) method. At first, we propose to discover the collective behavior of users by using content-location similarity network fusion algorithm. our analysis is based on real dataset of usage detail records and explore the heterogeneity and predictability of collective behavior during content access. Based on it, we propose a collaborative relationship model that relies on the collective behavior. Then, the collaborative caching placement is formulated by solving a multi-objective optimization problem. Our simulations are based on the real dataset from cellular systems. The numerical results show that the proposed method achieves performance gains in terms of both hit rate and transmission cost.
This work was supported in part by the National Natural Science Foundation of China under Grant 61702387, in part by the National Key Research and Development Program under Grant 2017YFB0504103 and Grant 2017YFC0503801, in part by the Development Program of China (863 Program) under Grant 2014AA01A707, and in part by the Natural Science Foundation of Hubei Province of China under Grant 2017CFB302.
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References
Altman, E., Avrachenkov, K., Goseling, J.: Coding for caches in the plane. arXiv preprint arXiv:1309.0604 (2013)
Blaszczyszyn, B., Giovanidis, A.: Optimal geographic caching in cellular networks. In: 2015 IEEE International Conference on Communications (ICC), pp. 3358–3363. IEEE (2015)
Chen, Z., Lee, J., Quek, T.Q., Kountouris, M.: Cooperative caching and transmission design in cluster-centric small cell networks. IEEE Trans. Wirel. Commun. 16(5), 3401–3415 (2017)
Cisco: Cisco visual networking index: Global mobile data traffic forecast update, 2016–2021 white paper (2016). http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/mobile-white-paper-c11-520862.html
Deb, K.: A fast elitist multi-objective genetic algorithm: NSGA-ii. IEEE Trans. Evolut. Comput. 6(2), 182–197 (2000)
Jiang, A.X., Leyton-Brown, K.: A tutorial on the proof of the existence of nash equilibria. University of British Columbia Technical report TR-2007-25 (2009)
Liu, D., Yang, C.: Energy efficiency of downlink networks with caching at base stations. IEEE J. Sel. Areas Commun. 34(4), 907–922 (2016)
Liu, J., Ahmed, E., Shiraz, M., Gani, A., Buyya, R., Qureshi, A.: Application partitioning algorithms in mobile cloud computing: taxonomy, review and future directions. J. Netw. Comput. Appl. 48(C), 99–117 (2015)
Miyamoto, T., Noguchi, S., Yamashita, H.: Selection of an optimal solution for multiobjective electromagnetic apparatus design based on game theory. IEEE Trans. Magn. 44(6), 1026–1029 (2008)
Peng, M., Yan, S., Zhang, K., Wang, C.: Fog-computing-based radio access networks: issues and challenges. IEEE Netw. 30(4), 46–53 (2016)
Peng, X., Shen, J.C., Zhang, J., Letaief, K.B.: Backhaul-aware caching placement for wireless networks. In: 2015 IEEE Global Communications Conference (GLOBECOM), pp. 1–6. IEEE (2015)
Xu, X., Liu, J., Tao, X.: Mobile edge computing enhanced adaptive bitrate video delivery with joint cache and radio resource allocation. IEEE Access 5(99), 16406–16415 (2017)
Yang, C., Yao, Y., Chen, Z., Xia, B.: Analysis on cache-enabled wireless heterogeneous networks. IEEE Trans. Wireless Commun. 15(1), 131–145 (2016)
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Jiang, H., Huang, H., Jiang, Y., Wang, Y., Zeng, Y., Zhou, C. (2018). Collective Behavior Aware Collaborative Caching for Mobile Edge Computing. In: Qiu, M. (eds) Smart Computing and Communication. SmartCom 2018. Lecture Notes in Computer Science(), vol 11344. Springer, Cham. https://doi.org/10.1007/978-3-030-05755-8_18
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DOI: https://doi.org/10.1007/978-3-030-05755-8_18
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