Collective Behavior Aware Collaborative Caching for Mobile Edge Computing

  • Hao Jiang
  • Hehe Huang
  • Ying Jiang
  • Yuan Wang
  • Yuanyuan ZengEmail author
  • Chen Zhou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11344)


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.


Collaborative caching Collective behavior 5G MEC 


  1. 1.
    Altman, E., Avrachenkov, K., Goseling, J.: Coding for caches in the plane. arXiv preprint arXiv:1309.0604 (2013)
  2. 2.
    Blaszczyszyn, B., Giovanidis, A.: Optimal geographic caching in cellular networks. In: 2015 IEEE International Conference on Communications (ICC), pp. 3358–3363. IEEE (2015)Google Scholar
  3. 3.
    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)CrossRefGoogle Scholar
  4. 4.
    Cisco: Cisco visual networking index: Global mobile data traffic forecast update, 2016–2021 white paper (2016).
  5. 5.
    Deb, K.: A fast elitist multi-objective genetic algorithm: NSGA-ii. IEEE Trans. Evolut. Comput. 6(2), 182–197 (2000)CrossRefGoogle Scholar
  6. 6.
    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)Google Scholar
  7. 7.
    Liu, D., Yang, C.: Energy efficiency of downlink networks with caching at base stations. IEEE J. Sel. Areas Commun. 34(4), 907–922 (2016)CrossRefGoogle Scholar
  8. 8.
    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)CrossRefGoogle Scholar
  9. 9.
    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)CrossRefGoogle Scholar
  10. 10.
    Peng, M., Yan, S., Zhang, K., Wang, C.: Fog-computing-based radio access networks: issues and challenges. IEEE Netw. 30(4), 46–53 (2016)CrossRefGoogle Scholar
  11. 11.
    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)Google Scholar
  12. 12.
    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)CrossRefGoogle Scholar
  13. 13.
    Yang, C., Yao, Y., Chen, Z., Xia, B.: Analysis on cache-enabled wireless heterogeneous networks. IEEE Trans. Wireless Commun. 15(1), 131–145 (2016)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Hao Jiang
    • 1
  • Hehe Huang
    • 1
  • Ying Jiang
    • 2
  • Yuan Wang
    • 1
  • Yuanyuan Zeng
    • 1
    Email author
  • Chen Zhou
    • 3
  1. 1.School of Electronic InformationWuhan UniversityWuhanChina
  2. 2.School of Data and Computer ScienceSun Yat-Sen UniversityGuangzhouChina
  3. 3.China Ship Development and Design CenterWuhanChina

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