Abstract
In object based systems, an object is an unit of computation resource. Distributed applications are composed of multiple objects. Objects in an application are replicated to multiple servers in order to increase reliability, availability, and performance. On the other hand, the large amount of electric energy is consumed in a system compared with non-replication systems since multiple replicas of each object are manipulated on multiple servers. In this paper, the energy consumption laxity-based quorum selection (ECLBQS) algorithm is proposed to construct a quorum for each method issued by a transaction so that the total electric energy consumption of servers to perform methods can be reduced in the quorum based locking protocol. The total electric energy consumption of servers, the average execution time of each transaction, and the number of aborted transactions are shown to be more reduced in the ECLBQS algorithm than the random algorithm in evaluation.
Similar content being viewed by others
References
Natural Resources Defense Council (NRDS) (2014) Data center efficiency assessment—scaling up energy efficiency across the data center industry: evaluating key drivers and barriers. http://www.nrdc.org/energy/files/data-center-efficiency-assessment-IP.pdf. Accessed 3 Apr 2015
Natural Resources Defense Council (NRDS) (2012) Is cloud computing always greener? Finding the most energy and carbon efficient information technology solutions for small- and medium-sized organizations. http://www.nrdc.org/energy/files/cloud-computing-efficiency-IB.pdf. Accessed 6 Apr 2015
Enokido T, Duolikun D, Takizawa M (2015) An extended improved redundant power consumption laxity-based (EIRPCLB) algorithm for energy efficient server cluster systems. World Wide Web 18(6):1629–1630
Tomimori M, Sugawara S (2017) Content sharing method using expected acquisition rate in hybrid peer-to-peer networks with cloud storages. Int J Space Based Situated Comput 7(4):187–196
Tanaka K, Hasegawa K, Takizawa M (2000) Quorum-based replication in object-based systems. J Inf Sci Eng 16(3):317–331
Object Management Group Inc. (2012) Common object request broker architecture (CORBA) specification, version 3.3, Part 1—Interfaces. http://www.omg.org/spec/CORBA/3.3/Interfaces/PDF. Accessed 24 Apr 2017
Bernstein PA, Hadzilacos V, Goodman N (1987) Concurrency control and recovery in database systems. Addison-Wesley, Boston
Schneider FB (1993) Replication management using the state-machine approach. Distributed systems, 2nd edn. ACM Press, New York
Gray JN (1978) Notes on database operating systems. Lect Notes Comput Sci 60:393–481
Garcia-Molina H, Barbara D (1985) How to assign votes in a distributed system. J ACM 32(4):814–860
Khan S, Kolodziej J, Li J, Zomaya AY (2013) Evolutionary based solutions for green computing. Springer, New York
Serhan Z, Diab WB (2016) Energy efficient QoS routing and adaptive status update in WMSNs. Int J Space Based Situated Comput 6(3):129–146
Qu X, Peng X (2017) An energy-efficient virtual machine scheduler based on CPU share-reclaiming policy. Int J Grid Util Comput (IJGUC) 6(2):113–120
Intel Corporation (2010) Intel Xeon Processor 5600 Series: the next generation of intelligent server processors. http://www.intel.com/content/www/us/en/processors/xeon/xeon-5600-brief.html. Accessed 24 Apr 2017
Kaushik A, Vidyarthi DP (2018) A hybrid heuristic resource allocation model for computational grid for optimal energy usage. Int J Grid Util Comput (IJGUC) 9(1):51–74
Kataoka H, Nakamura S, Duolikun D, Enokido T, Takizawa M (2017) Multi-level power consumption model and energy-aware server selection algorithm. Int J Grid Util Comput (IJGUC) 8(3):201–210
Duolikun D, Enokido T, Takizawa M (2017) An energy-aware algorithm to migrate virtual machines in a server cluster. Int J Grid Util Comput (IJGUC) 7(1):32–42
Sawada A, Kataoka H, Duolikun D, Enokido T, Takizawa M (2016) Energy-aware clusters of servers for storage and computation applications. In: Proceedings of the 30th IEEE international conference on advanced information networking and applications (AINA-2016), pp 400–407
Enokido T, Aikebaier A, Takizawa M (2010) A model for reducing power consumption in peer-to-peer systems. IEEE Syst J 4(2):221–229
Enokido T, Aikebaier A, Takizawa M (2011) Process allocation algorithms for saving power consumption in peer-to-peer systems. IEEE Trans Ind Electron 58(6):2097–2105
Enokido T, Aikebaier A, Takizawa M (2014) An extended simple power consumption model for selecting a server to perform computation type processes in digital ecosystems. IEEE Trans Ind Inform 10(2):1627–1636
Enokido T, Takizawa M (2013) Integrated power consumption model for distributed systems. IEEE Trans Ind Electron 60(2):824–836
Enokido T, Takizawa M (2013) The evaluation of the extended transmission power consumption (ETPC) model to perform communication type processes. Computing 95(10–11):1019–1037
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Enokido, T., Duolikun, D. & Takizawa, M. Energy consumption laxity-based quorum selection for distributed object-based systems. Evol. Intel. 13, 71–82 (2020). https://doi.org/10.1007/s12065-018-0157-1
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12065-018-0157-1