Skip to main content
SpringerLink
Log in

Trade-off in optimizing energy consumption and end user quality of experience in radio access network

  • Published:
Journal of Shanghai Jiaotong University (Science) Aims and scope Submit manuscript

Abstract

To reduce network access latency, network traffic volume and server load, caching capacity has been proposed as a component of evolved Node B (eNodeB) in the ratio access network (RAN). These eNodeB caches reduce transport energy consumption but lead to additional energy cost by equipping every eNodeB with caching capacity. Existing researches focus on how to minimize total energy consumption, but often ignore the trade-off between energy efficiency and end user quality of experience, which may lead to undesired network performance degradation. In this paper, for the first time, we build an energy model to formulate the problem of minimizing total energy consumption at eNodeB caches by taking a trade-off between energy efficiency and end user quality of experience. Through coordinating all the eNodeB caches in the same RAN, the proposed model can take a good balance between caching energy and transport energy consumption while also guarantee end user quality of experience. The experimental results demonstrate the effectiveness of the proposed model. Compared with the existing works, our proposal significantly reduces the energy consumption by approximately 17% while keeps superior end user quality of experience performance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. PANIGRAHI B, SHAILENDRA S, RATH H K, et al. Universal caching model andMarkov-based cache analysis for information centric networks [J]. Photonic Network Communications, 2015, 30(3): 428–438.

    Article  Google Scholar 

  2. CISCO. Cisco visual networking index forecast and methodology, 2015–2020 [M]. San Jose, CA, USA: CISCO, 2016: 1–22.

    Google Scholar 

  3. MOHAMMAD A, ALEXANDER L, AMIN V. A scalable, commodity data center network architecture [C]//Proceedings of the ACM SIGCOMM 2008 Conference on Data Communication. Seattle, WA, USA: ACM, 2008: 63–74.

    Google Scholar 

  4. LEE U, RIMAC I, HILT V. Greening the internet with content-centric networking [C]//The 1st International Conference on Energy-Efficient Computing and Networking. Passau, Germany: ACM, 2010: 179–182.

    Chapter  Google Scholar 

  5. SU A J, CHOFFNES D R, KUZMANOVIC A, et al. Drafting behind akamai (travelocity-based detouring) [C]//Proceedings of the 2006 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications. Pisa, Italy: ACM, 2006: 435–446.

    Google Scholar 

  6. LEONARD W J. Tslp: Finally in the limelight [J]. Nature Immunology, 2002, 3(7): 605–607.

    Article  Google Scholar 

  7. BARROSO L A, HOLZLE U. The case for energyproportional computing [J]. Computer, 2007, 40(12): 33–37.

    Article  Google Scholar 

  8. LAOUTARIS N, SYNTILA S, STAVRAKAKIS I. Meta algorithms for hierarchical web caches [C]//Proceedings of the 23th International Conference on Performance, Computing, and Communications Committee. Phoenix, Arizona, USA: IEEE, 2004: 445–452.

    Google Scholar 

  9. CHEN C, BARRERA D, PERRIG A. Modeling dataplane power consumption of future internet architectures [C]//IEEE 2nd International Conference on Collaboration and Internet Computing. Pittsburgh, USA: IEEE, 2016: 149–158.

    Google Scholar 

  10. BOLLA R, BRUSCHI R, CARREGA A, et al. Cutting the energy bills of internet service providers and telecoms through power management: An impact analysis [J]. Computer Networks, 2012, 56(10): 2320–2342.

    Article  Google Scholar 

  11. MAO Y, ZHANG J, LETAIEF K B. Dynamic computation offloading for mobile-edge computing with energy harvesting devices [J]. IEEE Journal on Selected Areas in Communications, 2016, 34(12): 3590–3605.

    Article  Google Scholar 

  12. NEDEVSCHI S, POPA L, IANNACCONE G, et al. Reducing network energy consumption via sleeping and rate-adaptation [C]//Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation. [s.l.]: USENIX Association, 2008: 323–336.

    Google Scholar 

  13. WANG K, YU J, YU Y, et al. A survey on energy internet: Architecture, approach, and emerging technologies [J]. IEEE System Journal, 2017, PP(99): 1–14.

    Google Scholar 

  14. SEETHARAM A, SOMASUNDARAM M, TOWSLEY D, et al. Shipping to streaming: Is this shift green? [C]//Proceedings of the First ACM SIGCOMM Workshop on Green Networking. New Delhi, India: ACM, 2010: 61–68.

    Chapter  Google Scholar 

  15. BRAUN T, TRINH T A. Energy efficiency issues in information-centric networking [J]. Energy Efficiency in Large Scale Distributed Systems, 2013, 8046: 271–278.

    Article  Google Scholar 

  16. LAFOND S, TRINH T A. Energy efficient thresholds for cached content in content centric networking [C]//Proceedings of the 24th Tyrrhenian International Workshop on Digital Communications-Green ICT. Genoa, Italy: IEEE, 2013: 1–6.

    Google Scholar 

  17. CHEN J, ZHANG H, ZHOU H, et al. Optimizing content routers deployment in large-scale information centric core-edge separation internet [J]. International Journal of Communication Systems, 2014, 27(5): 794–810.

    Article  Google Scholar 

  18. YANG C, YAO Y, CHEN Z, et al. Video analysis on cache-enabled wireless heterogeneous networks [J]. IEEE Transactions on Wireless Communications, 2016, 15(1): 131–145.

    Article  Google Scholar 

  19. CHOI N, GUAN K, KILPER D C, et al. In-network caching effect on optimal energy consumption in content-centric networking [C]//Proceedings of International Conference on Communication (ICC). Ottawa, Canada: IEEE, 2012: 2889–2894.

    Google Scholar 

  20. HELD M, WOLF P, CROWDER P H. Validation of subgradient optimization [J]. Mathmatical Programming, 1974, 6(1): 62–88.

    Article  MathSciNet  MATH  Google Scholar 

  21. KELLERER H, PFERSCHY U, PISINGER D. Introduction to NP-completeness of knapsack problems [M]. New York: Springer-Verlag, 2003: 483–493.

    Google Scholar 

  22. XU Y M, LI Y, WANG Z H, et al. Coordinated caching model for minimizing energy consumption in radio access network [C]//Proceedings of International Conference on Communication (ICC). Sydney, Australia: IEEE, 2014: 2406–2411.

    Google Scholar 

  23. MAVROTAS G. Effective implementation of the constraint method in multi-objective mathematical programming problems [J]. Applied Mathematics and Computation, 2009, 213(2): 455–465.

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Sciences, Beijing Foreign Studies University, Beijing, 100089, China

    Yuemei Xu  (徐月梅) & Lianqiao Cai  (蔡连侨)

  2. National Computer Network Emergency Response Technical Team, Coordination Center of China, Beijing, 100012, China

    Zihou Wang  (王子厚)

  3. Institute of Information Engineering, Chinese Academy of Science, Beijing, 100093, China

    Yang Li  (李 杨)

Authors
  1. Yuemei Xu  (徐月梅)
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zihou Wang  (王子厚)
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yang Li  (李 杨)
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lianqiao Cai  (蔡连侨)
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yuemei Xu  (徐月梅).

Additional information

Foundation item: the National Natural Science Foundation of China (No. 61502038), and the Fundamental Research Funds for the Central Universities of China (No. 023600-500110002)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xu, Y., Wang, Z., Li, Y. et al. Trade-off in optimizing energy consumption and end user quality of experience in radio access network. J. Shanghai Jiaotong Univ. (Sci.) 22, 742–751 (2017). https://doi.org/10.1007/s12204-017-1895-4

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12204-017-1895-4

Key words

CLC number

Search

Navigation