Abstract
Enterprise networks usually require all the computing machines to remain accessible (switched-on) at all times regardless of the workload in order to entertain user requests at any instant. This comes at the cost of excessive energy utilization. Many solutions have been put forwarded, however, only few of them are tested in a real-time environment, where the energy saving is achieved by compromising the systems’ reliability. Therefore, energy-efficient resource utilization without compromising the system’s reliability is still a challenge. In this research, a novel architecture, “Sleep Alert”, is proposed that not only avoids the excessive energy utilization but also improves the system reliability by using Resource Manager (RM) concept. In contrary to traditional approaches, Primary and Secondary Resource Managers i.e. RMP and RMS respectively are used to avoid the single point of failure. The proposed architecture is tested on a network where active users were accessing the distributed virtual storage and other applications deployed on the desktop machines, those are connected with each other through a peer-to-peer network. Experimental results show that the solution can save considerable amount of energy while making sure that reliability is not compromised. This solution is useful for small enterprise networks, where saving energy is a big challenge besides reliability.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
US Department of Energy Efficiency and Renewable Energy. http://www.eere.energy.gov/
InternetWorldStats. http://www.internetworldstats.com
Network World. http://www.networkworld.com
Wang, D.: Meeting green computing challenges. In: 10th Electronics Packaging Technology Conference. Teradata Corporation, USA. IEEE (2008)
Okaor Kennedy, C., Udeze Chidiebele, C., Okafor, E.C.N., Okezie, C.C.: Smart grids: a new framework for efficient power management in datacenter networks. In: IJACSA, vol. 3, no. 7, pp. 59–66 (2012)
Gyarmati, L., Anh Trinh, T.: How can architecture help to reduce energy consumption in data center networking? e-Energy (2010)
Marcos, A.: A survey on techniques for improving the energy efficiency of large scale distributed systems. ACM Comput. Surv. 46(4), 1–35 (2014)
Chen, X., Li, C., Jiang, Y.: Optimization model and algorithm for energy efficient virtual node embedding. IEEE Commun. Lett. 19, 1327–1330 (2015). ISSN 1089-7798
Panarello, C., et al.: Energy saving and network performance: a trade-off approach. e-Energy (2010)
Hameed, A., Khoshkbarforoushha, A., Ranjan, R., Jayaraman, P.P., Kolodziej, J., Balaji, P., Zeadally, S., Malluhi, Q.M., Tziritas, N., Vishnu, A., Khan, S.U., Zomaya, A.: A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems. Computing 98, 1–24 (2014). https://doi.org/10.1007/s00607-014-0407-8
Choi, K., Soma, R., Pedram, M.: Dynamic voltage and frequency scaling based on workload decomposition. Department of EE-Systems, University of Southern California, Los Angeles, CA 90089
Green Manufacturing Initiative, Annual Report (2012). http://www.wmich.edu/mfe/mrc/greenmanufacturing/pdf/2012%20GMI%20Annual%20Report.pdf
Reich, J., Goraczko, M., Kansal, A., Padhye, J.: Sleepless in seattle no longer. In: Proceedings of the 2010 USENIX Conference, Columbia University, Microsoft Research, June 2010
Nedevschi, S., Popa, L., Iallaccone, G., Ratnasamy, S., Wetherall, D.: Reducing network energy consumption via sleeping and rate-adaptation. In: NSDI 2008, Berkeley, CA, USA (2008)
Apple Wake On Lan. http://www.macworld.com/article/142468/2009/08/wake_on_demand.html
Agarwal, Y., Hodges, S., Chandra, R., Scott, J., Bahl, P., Gupta, R.: Somniloquy: augmenting network interfaces to reduce pc energy usage. In: NSDI 2009, Berkeley, CA, USA (2009)
Gumstix. http://www.gumstix.com
Wake on Lan. http://en.wikipedia.org/wiki/Wake-on-LAN
Kant, K.: Data center evolution: a tutorial on state of the art, issues, and challenges. Comput. Netw. 53, 2939–2965 (2009)
Koomey, J.: Growth in data center electricity use 2005 to 2010. A report by Analytical Press, completed at the request of The New York Times (2011)
Borah, J., Singh, S.K., Borah, A.D.: Cellular base station and its greening issues. Int. J. Adv. Electron. Commun. Syst. (CSIR-NISCAIR Approved) 3(2), 1–4 (2014)
Chabarek, J., Sommers, J., Barford, P., Estan, C., Tsiang, D., Wright, S.: Power awareness in network design and routing. In: The 27th Conference on Computer Communications IEEE INFOCOM 2008, pp. 457–465 (2008)
Ghani, I., Niknejad, N., Jeong, S.R.: Energy saving in green cloud computing data centers: a review. J. Theor. Appl. Inf. Technol. 74(1) (2015)
Song, Y., Wang, H., Li, Y., Feng, B., Sun, Y.: Multi-tiered on-demand resource scheduling for vm-based data center. In: Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, pp. 148–155 (2009)
Cardosa, M., Korupolu, M., Singh, A.: Shares and utilities based power consolidation in virtualized server environments. In: Proceedings of IFIP/IEEE Integrated Network Management (IM) (2009)
Beloglazov, A., Buyya, R.: Energy efficient resource management in virtualized cloud data centers. In: 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (2010). https://doi.org/10.1109/ccgrid.2010.46
Liu, C., Liu, C., Shang, Y., Chen, S., Cheng, B., Chen, J.: An adaptive prediction approach based on workload pattern discrimination in the cloud. J. Netw. Comput. Appl. (2016, in Press)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Ali, D., Raja, F.R., Saleem, M.A. (2020). Energy Efficient Resource Utilization: Architecture for Enterprise Network. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2020. Advances in Intelligent Systems and Computing, vol 1228. Springer, Cham. https://doi.org/10.1007/978-3-030-52249-0_2
Download citation
DOI: https://doi.org/10.1007/978-3-030-52249-0_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-52248-3
Online ISBN: 978-3-030-52249-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)