SYSTEM MODELING AND EVALUATION ON FACTORS INFLUENCING POWER AND PERFORMANCE MANAGEMENT OF CLOUD LOAD BALANCING ALGORITHMS
Keywords:
Cloud computing, Server virtualization, Load balancing, Performance, Power management, Modeling and evaluationAbstract
Cloud is an on-demand IT resource provisioning technology uses server virtualization and load balancing as the underlying techniques. Power and performance management are the major concern of cloud to achieve Total Cost Ownership (TCO) in terms of user acceptance and societal importance. In this concern, there is a need to investigate the power and performance influencing factors to design a novel cloud load balancing algorithms with respect to recent hardware and software advancements. Hence, the work studied these approaches to allocate only required amount of virtual servers for varying cloud workload. In this regard, the cloud system model is designed and evaluated for different scenarios like reactive system model, cloud workload and different scaling and sizing of Virtual Machine (VM) servers for various load balancing algorithms. The simulation results infer that the launching of an optimal number of virtual machines, the cost of VM setup time in the data centre, control considerations - dynamic regulation of frequency of controller invocation, adaptive algorithms instead of dynamic algorithms, and multi-core CPU architectures are to be considered while implementing cloud load balancing methods. Appropriate consideration of the above-mentioned parameters is required to make a powerful, flexible and cost-effective load balancing methods for power and performance management for cloud data centre.
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References
Babu LD and Krishna PV, “Honey bee behavior inspired load balancing of tasks in cloud
computing environments”, Applied Soft Computing journal, vol. 13, no. 5, pp. 2292–2303, 2013.
Barham P, Dragovic B, Fraser K and Hand S et.al., “XEN and the art of virtualization”, 19th
ACM Symposium on Operating Systems Principles (SOSP ' 03), pp.16–177, 2003.
Beloglazov and Buyya R, “Optimal Online Deterministic Algorithms and Adaptive Heuristics for
Energy and Performance Efficient Dynamic Consolidation of Virtual Machines in Cloud Data
Centers”, Concurrency and Computation: practice and experiments, vol.24, no.13, pp.1397-1420,
Belolazov J, Abawajy and Buyya R “Energy-aware resource allocation heuristics for efficient
management of data centers for cloud computing”, Future Generation Computer Systems, vol.28,
no.5, pp.755-768, 2012.
Bergamaschi RA, Piga L, Rigo S, Azevedo R and Araújo G, “Data center power and performance
optimization through global selection of p-states and utilization rates, Sustainable Computing:
Informatics and Systems; vol.2, no.4, pp.198–208, 2012.
Bodik P, Fox A, Franklin M J, Jordan M I and Patterson DA, “Characterizing, Modeling, and
Generating Workload Spikes for Stateful Services”, 1st ACM symposium on Cloud computing,
pp.241-252, 2010.
Buyya R., “Introduction to the IEEE Transactions on Cloud Computing”, IEEE Transactions on
Cloud Computing, vol.1, no.1, pp.3-21, 2013.
Buyya R and Beloglazov A, “Energy efficient resource management in virtualized cloud
datacenters”, 10th IEEE / ACM International Conference on Cluster, Cloud and Grid Computing,
IEEE Computer Society, pp. 826-831, 2010.
Buyya R, Beloglazov A and Abawajy J, “Energy-Efficient management of data center resources
for cloud computing: A vision, architectural elements, and open challenges”, 2010 International
Conference on Parallel and Distributed Processing Techniques and Applications, 2010.
Buyya R, Yeo CS, Venugopal S and Broberg I Br, “Cloud computing and emerging IT platforms:
Vision, hype, and reality for delivering computing as the 5th utility”, Future Generation Computer
Systems 2009, vol.25, no.6, pp.599–616.
Chang J, Meza J, Ranganathan P and et al., “Totally green: evaluating and designing servers for
lifecycle environmental impact”, ACM SIGARCH Computer Architecture News, vol.40, no.1,
pp.25–36, 2012.
Chen F, Grundy J, Schneider J, Yang Y and He Q, “Automated analysis of performance and
energy consumption for cloud applications, 5th ACM / SPEC international conference on
Performance engineering, ACM, pp.39-50, 2014.
Chetsa GLT, Lefevre L, Pierson J and Stolf P, “Beyond CPU frequency scaling for a fine-grained
energy control of hpc systems”, 24th IEEE International Symposium on Computer Architecture
and High Performance Computing (SBAC-PAD’12), pp. 132–138, 2012.
Dahlin M, “Interpreting Stale Load Information”, UTCS Technical Report TR98-20, University
of Texas at Austin, 1998.
Dalapati P and Sahoo G, “Green Solution for Cloud Computing with Load Balancing and Power
Consumption Management”, International Journal of Emerging Technology and Advanced
Engineering, vol.3, no.3, pp.353–359, 2013.
Gandhi A and et al., “Optimal power allocation in server farms”, 11th International Joint
Conference on Measurement and Modeling of Computer Systems, pp.157–168, 2009.
Ghoshc S, Redekopp M and Annavaram M, “Knightshift: shifting the i/o burden in datacenters to
management processor for energy efficiency”, Computer Architecture, Springer, pp.183–197,
Goudarzi H and Pedram M, “Geographical Load Balancing for Online Service Applications in
Distributed Datacenters”, IEEE international conference on cloud computing, IEEE Computer
Society 2013, pp. 351-358.
Graubner, P and et al., “Energy-Efficient Virtual Machine Consolidation”, IT Professional,
vol.15, no.2, p.28-34, 2013.
Jonathan K, “Growth in data center electricity use 2005 to 2010”, CA: Analytics Press, 2011.
Junwei Li K and Stojmenovic I, “Optimal Power Allocation and Load Distribution for Multiple
Heterogeneous Multicore Server Processors across Clouds and Data Centers Qualitative
performance Study”, IEEE Transactions on Computers,vol.63, no.1, pp.45-58, 2014.
Y. Kivity and et al., “KVM: The Linux virtual machine monitor”, Linux Symposium, Ottawa,
pp.225–230, 2007.
Lef`evre L and Orgerie A C, “Designing and evaluating an energy efficient Cloud”, The Journal
of Supercomputing, vol.51, no.3, pp.352–373, 2010.
Mittal S, “Power Management Techniques for Data Centers: A Survey”, Technical Report, 2014.
Mitzenmacher M, “On the Analysis of Randomized Load Balancing Schemes”, 9th Annual
Symposium on Parallel Algorithm and Architectures, pp. 292-301, 1997.
Nishant K. and et al, “Load Balancing of Nodes in Cloud Using Ant Colony Optimization”, 14th
International Conference on Modelling and Simulation, pp.3-8, 2012.
Schwetman H, “CSIM19: A Powerful Tool for Building System Models”, 2001 Winter
Simulation Conference, pp.250-255, 2001.
Shirazi BA, Hurson AR and Kavi KM, “Scheduling and Load Balancing in Parallel and
Distributed Systems”, IEEE CS Press, 1995.
Shivaratri NG and Krueger P, “Two Adaptive Location Policies for Global Scheduling
Algorithms”, Proceedings of 10th International Conference on Distributed Computing Systems,
pp. 502-509, 1990.
Smith JE and Nair R, “Virtual Machines: Versatile Platforms for Systems and Processes”,
Elsevier, 2005.
Sosinsky B, Cloud Computing Bible, New Delhi, WILEY – INDIA, 2012.
Stoess J and et al., “Transparent, power-aware migration in virtualized systems”, GI/ITG
Fachgruppentreffen Betriebs system, pp. 1–6, 2007.
Suresh S and Kannan M, “A Performance Study of Hardware Impact on Full Virtualization for
Server Consolidation in Cloud Environment” Journal of Theoretical and Applied Information
Technology, vol. 60, no.3, pp.556-567, 2014.
Suresh S and Sakthivel S, “A Qualitative and Quantitative Analysis of Multi-core CPU Power
and Performance Impact on Server Virtualization for Enterprise Cloud Data Centers”, Research
Journal of Applied Sciences, Engg. and Tech,. vol.9, no.6, pp.471-477, 2015.
VMware Inc., “VMware distributed power management concepts and use”, Technical Report,
VMware Inc., “vSphere resource management guide”, Technical Report, 2009.
Wei G and et al., “The on going evolutions of power management in XEN”, Intel Corporation,
Technical Report, 2009.
Zapater M, Ayala JL and Moya JM, “Leveraging heterogeneity for energy minimization in data
centers”, 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing,
(CCGrid'12), Ottawa, pp. 752–757, 2012.
Zhang Q, Cheng L and Boutaba R, “Cloud computing: state-of-the-art and research challenges”,
Journal of Internet Services and Applications, vol.1, no.1, pp.7-18, 2010.
Zhang Y and Ansari N, “Green data centers”, Handbook of Green Information and
Communication Systems, 2012.
Zheng X and Cai Y, “Achieving Energy Proportionality in Server Clusters”, International Journal
of Computer Networks, vol.1, no.2, pp.21-35, 2010.