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.
XU Yuemei1* (徐月梅), WANG Zihou2 (王子厚), LI Yang3 (李杨), CAI Lianqiao1 (蔡连侨)
. Trade-off in Optimizing Energy Consumption and End User Quality of Experience in Radio Access Network[J]. Journal of Shanghai Jiaotong University(Science), 2017
, 22(6)
: 742
-751
.
DOI: 10.1007/s12204-017-1895-4
[1] PANIGRAHI B, SHAILENDRA S, RATH H K, et al.Universal caching model andMarkov-based cache analysisfor information centric networks [J]. Photonic NetworkCommunications, 2015, 30(3): 428-438.
[2] CISCO. Cisco visual networking index forecast andmethodology, 2015-2020 [M]. San Jose, CA, USA:CISCO, 2016: 1-22.
[3] MOHAMMAD A, ALEXANDER L, AMIN V. A scalable,commodity data center network architecture[C]//Proceedings of the ACM SIGCOMM 2008 Conferenceon Data Communication. Seattle, WA, USA:ACM, 2008: 63-74.
[4] LEE U, RIMAC I, HILT V. Greening the internet withcontent-centric networking [C]//The 1st InternationalConference on Energy-Efficient Computing and Networking.Passau, Germany: ACM, 2010: 179-182.
[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 forComputer Communications. Pisa, Italy: ACM, 2006:435-446.
[6] LEONARD W J. Tslp: Finally in the limelight [J].Nature Immunology, 2002, 3(7): 605-607.
[7] BARROSO L A, HOLZLE U. The case for energyproportionalcomputing [J]. Computer, 2007, 40(12):33-37.
[8] LAOUTARIS N, SYNTILA S, STAVRAKAKISI. Meta algorithms for hierarchical web caches[C]//Proceedings of the 23th International Conferenceon Performance, Computing, and CommunicationsCommittee. Phoenix, Arizona, USA: IEEE, 2004: 445-452.
[9] CHEN C, BARRERA D, PERRIG A. Modeling dataplanepower consumption of future internet architectures[C]//IEEE 2nd International Conference on Collaborationand Internet Computing. Pittsburgh, USA:IEEE, 2016: 149-158.
[10] BOLLA R, BRUSCHI R, CARREGA A, et al. Cuttingthe energy bills of internet service providers and telecomsthrough power management: An impact analysis[J]. Computer Networks, 2012, 56(10): 2320-2342.
[11] MAO Y, ZHANG J, LETAIEF K B. Dynamic computationoffloading for mobile-edge computing with energyharvesting devices [J]. IEEE Journal on SelectedAreas in Communications, 2016, 34(12): 3590-3605.
[12] NEDEVSCHI S, POPA L, IANNACCONE G, etal. Reducing network energy consumption via sleepingand rate-adaptation [C]//Proceedings of the 5thUSENIX Symposium on Networked Systems Designand Implementation. [s.l.]: USENIX Association, 2008:323-336.
[13] WANG K, YU J, YU Y, et al. A survey on energyinternet: Architecture, approach, and emerging technologies[J]. IEEE System Journal, 2017, PP(99): 1-14.
[14] SEETHARAM A, SOMASUNDARAM M,TOWSLEY D, et al. Shipping to streaming: Isthis shift green? [C]//Proceedings of the First ACMSIGCOMM Workshop on Green Networking. NewDelhi, India: ACM, 2010: 61-68.
[15] BRAUN T, TRINH T A. Energy efficiency issues ininformation-centric networking [J]. Energy Efficiencyin Large Scale Distributed Systems, 2013, 8046: 271-278.
[16] LAFOND S, TRINH T A. Energy efficient thresholdsfor cached content in content centric networking[C]//Proceedings of the 24th Tyrrhenian InternationalWorkshop on Digital Communications-GreenICT. Genoa, Italy: IEEE, 2013: 1-6.
[17] CHEN J, ZHANG H, ZHOU H, et al. Optimizingcontent routers deployment in large-scale informationcentric core-edge separation internet [J]. InternationalJournal of Communication Systems, 2014, 27(5): 794-810.
[18] YANG C, YAO Y, CHEN Z, et al. Video analysison cache-enabled wireless heterogeneous networks[J]. IEEE Transactions on Wireless Communications,2016, 15(1): 131-145.
[19] CHOI N, GUAN K, KILPER D C, et al. In-networkcaching effect on optimal energy consumption incontent-centric networking [C]//Proceedings of InternationalConference on Communication (ICC). Ottawa,Canada: IEEE, 2012: 2889-2894.
[20] HELD M, WOLF P, CROWDER P H. Validation ofsubgradient optimization [J]. Mathmatical Programming,1974, 6(1): 62-88.
[21] KELLERER H, PFERSCHY U, PISINGER D. Introductionto NP-completeness of knapsack problems [M].New York: Springer-Verlag, 2003: 483-493.
[22] XU Y M, LI Y,WANG Z H, et al. Coordinated cachingmodel for minimizing energy consumption in radio accessnetwork [C]//Proceedings of International Conferenceon Communication (ICC). Sydney, Australia:IEEE, 2014: 2406-2411.
[23] MAVROTAS G. Effective implementation of the constraintmethod in multi-objective mathematical programmingproblems [J]. Applied Mathematics andComputation, 2009, 213(2): 455-465.
