How to cite this paper
Adamuthe, A & Kagwade, S. (2022). Hybrid and adaptive harmony search algorithm for optimizing energy efficiency in VMP problem in cloud environment.Decision Science Letters , 11(2), 113-126.
Refrences
Abdel-Basset, M., Abdle-Fatah, L., & Sangaiah, A. K. (2019). An improved Lévy based whale optimization algorithm for bandwidth-efficient virtual machine placement in a cloud computing environment. Cluster Computing, 22(4), 8319-8334.
Abohamama, A. S., & Hamouda, E. (2020). A hybrid energy–aware virtual machine placement algorithm for cloud environments. Expert Systems with Applications, 150, 113306.
Adamuthe, A. C., & Patil, J. T. (2018). Differential Evolution Algorithm for Optimizing Virtual Machine Placement Problem in Cloud Computing. International Journal of Intelligent Systems & Applications, 10(7).
Adamuthe, A. C., Pandharpatte, R. M., & Thampi, G. T. (2013, November). Multiobjective virtual machine placement in a cloud environment. In 2013 International Conference on Cloud & Ubiquitous Computing & Emerging Technologies (pp. 8-13). IEEE.
Adamuthe, A., & Nitave, T. (2020). Harmony search algorithm with adaptive parameter setting for solving large bin packing problems. Decision Science Letters, 9(4), 581-594.
Alharbi, F., Tian, Y. C., Tang, M., Zhang, W. Z., Peng, C., & Fei, M. (2019). An ant colony system for energy-efficient dynamic virtual machine placement in data centers. Expert Systems with Applications, 120, 228-238.
Alicherry, M., & Lakshman, T. V. (2013, April). Optimizing data access latencies in cloud systems by intelligent virtual machine placement. In 2013 Proceedings IEEE INFOCOM (pp. 647-655). IEEE.
Batista, D. M., Da Fonseca, N. L., & Miyazawa, F. K. (2007, March). A set of schedulers for grid networks. In Proceedings of the 2007 ACM symposium on Applied computing (pp. 209-213).
Beloglazov, A., & Buyya, R. (2010, May). Energy efficient allocation of virtual machines in cloud data centers. In 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (pp. 577-578). IEEE.
Beloglazov, A., Abawajy, J., & Buyya, R. (2012). Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future generation computer systems, 28(5), 755-768
Biran, O., Corradi, A., Fanelli, M., Foschini, L., Nus, A., Raz, D., & Silvera, E. (2012, May). A stable network-aware vm placement for cloud systems. In 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012) (pp. 498-506). IEEE.
Breitgand, D., & Epstein, A. (2011, May). SLA-aware placement of multi-virtual machine elastic services in compute clouds. In 12th IFIP/IEEE International Symposium on Integrated Network Management (IM 2011) and Workshops (pp. 161-168). IEEE.
Chaisiri, S., Lee, B. S., & Niyato, D. (2009, December). Optimal virtual machine placement across multiple cloud providers. In 2009 IEEE Asia-Pacific Services Computing Conference (APSCC) (pp. 103-110). IEEE.
Chase, J. S., Anderson, D. C., Thakar, P. N., Vahdat, A. M., & Doyle, R. P. (2001). Managing energy and server resources in hosting centers. ACM SIGOPS operating systems review, 35(5), 103-116.
Chen, G., He, W., Liu, J., Nath, S., Rigas, L., Xiao, L., & Zhao, F. (2008, April). Energy-Aware Server Provisioning and Load Dispatching for Connection-Intensive Internet Services. In NSDI (Vol. 8, pp. 337-350).
Dang, H. T., & Hermenier, F. (2013, November). Higher SLA satisfaction in datacenters with continuous VM placement constraints. In Proceedings of the 9th workshop on hot topics in dependable systems (pp. 1-6).
Dong, J., Wang, H., & Cheng, S. (2015). Energy-performance tradeoffs in IaaS cloud with virtual machine scheduling. China communications, 12(2), 155-166
Fesanghary, M., Damangir, E., & Soleimani, I. (2009). Design optimization of shell and tube heat exchangers using global sensitivity analysis and harmony search algorithm. Applied Thermal Engineering, 29(5-6), 1026-1031.
Fidanova, S. (2021). Multiple Knapsack Problem. In Ant Colony Optimization and Applications (pp. 9-18). Springer, Cham.
Gao, Y., Guan, H., Qi, Z., Hou, Y., & Liu, L. (2013). A multi-objective ant colony system algorithm for virtual machine placement in cloud computing. Journal of computer and system sciences, 79(8), 1230-1242.
Gartner Estimates, I. C. T. (2007). Industry accounts for 2 percent of global CO2 emissions. press release.
Ghribi, C., Hadji, M., & Zeghlache, D. (2013, May). Energy-efficient vm scheduling for cloud data centers: Exact allocation and migration algorithms. In 2013 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (pp. 671-678). IEEE.
Hyser, C., McKee, B., Gardner, R., & Watson, B. J. (2007). Autonomic virtual machine placement in the data center. Hewlett Packard Laboratories, Tech. Rep. HPL-2007-189, 189.
Jayasinghe, D., Pu, C., Eilam, T., Steinder, M., Whally, I., & Snible, E. (2011, July). Improving performance and availability of services hosted on iaas clouds with structural constraint-aware virtual machine placement. In 2011 IEEE International Conference on Services Computing (pp. 72-79). IEEE.
Lee, K. S., Geem, Z. W., Lee, S. H., & Bae, K. W. (2005). The harmony search heuristic algorithm for discrete structural optimization. Engineering Optimization, 37(7), 663-684.
Mahdavi, M., Fesanghary, M., & Damangir, E. (2007). An improved harmony search algorithm for solving optimization problems. Applied mathematics and computation, 188(2), 1567-1579.
Mann, Z. Á. (2015). Allocation of virtual machines in cloud data centers—a survey of problem models and optimization algorithms. Acm Computing Surveys (CSUR), 48(1), 1-34.
Mi, H., Wang, H., Yin, G., Zhou, Y., Shi, D., & Yuan, L. (2010, July). Online self-reconfiguration with a performance guarantee for energy-efficient large-scale cloud computing data centers. In 2010 IEEE International Conference on Services Computing (pp. 514-521). IEEE.
Mohamadi, E., Karimi, M., & Heikalabad, S. R. (2011). A Novel Virtual Placement in Virtual Computing. Australian Journal of Basic and Applied Scienes, Australia, 5(10), 1149-1555.
Networking, C. V. (2016). Cisco global cloud index: Forecast and methodology, 2015-2020. white paper. Cisco Public, San Jose, 2016.
Omran, M. G., & Mahdavi, M. (2008). Global-best harmony search. Applied mathematics and computation, 198(2), 643-656.
Panigrahy, R., Talwar, K., Uyeda, L., & Wieder, U. (2011). Heuristics for vector bin packing. research. microsoft. com.
Pinheiro, E., Bianchini, R., Carrera, E. V., & Heath, T. (2001, September). Load balancing and unbalancing for power and performance in cluster-based systems. In Workshop on compilers and operating systems for low power (Vol. 180, pp. 182-195).
Salehi, M. A., Krishna, P. R., Deepak, K. S., & Buyya, R. (2012, June). Preemption-aware energy management in virtualized data centers. In 2012 IEEE Fifth International Conference on Cloud Computing (pp. 844-851). IEEE.
Shuja, J., Gani, A., Shamshirband, S., Ahmad, R. W., & Bilal, K. (2016). Sustainable cloud data centers: a survey of enabling techniques and technologies. Renewable and Sustainable Energy Reviews, 62, 195-214.
Singh, A., Korupolu, M., & Mohapatra, D. (2008, November). Server-storage virtualization: integration and load balancing in data centers. In SC'08: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (pp. 1-12). IEEE.
Song, Y., Zhang, C., & Fang, Y. (2008, November). Multiple multidimensional knapsack problem and its applications in cognitive radio networks. In MILCOM 2008-2008 IEEE Military Communications Conference (pp. 1-7). IEEE.
Speitkamp, B., & Bichler, M. (2010). A mathematical programming approach for server consolidation problems in virtualized data centers. IEEE Transactions on services computing, 3(4), 266-278.
Tang, M., & Pan, S. (2015). A hybrid genetic algorithm for the energy-efficient virtual machine placement problem in data centers. Neural processing letters, 41(2), 211-221.
Usmani, Z., & Singh, S. (2016). A survey of virtual machine placement techniques in a cloud data center. Procedia Computer Science, 78, 491-498.
Van den Bossche, R., Vanmechelen, K., & Broeckhove, J. (2010, July). Cost-optimal scheduling in hybrid iaas clouds for deadline constrained workloads. In 2010 IEEE 3rd international conference on cloud computing (pp. 228-235). IEEE.
Wang, M., Meng, X., & Zhang, L. (2011, April). Consolidating virtual machines with dynamic bandwidth demand in data centers. In 2011 Proceedings IEEE INFOCOM (pp. 71-75). IEEE.
Wood, T., Shenoy, P., Venkataramani, A., & Yousif, M. (2009). Sandpiper: Black-box and gray-box resource management for virtual machines. Computer Networks, 53(17), 2923-2938.
Xia, B., & Tan, Z. (2010). Tighter bounds of the First Fit algorithm for the bin-packing problem. Discrete Applied Mathematics, 158(15), 1668-1675
Zhu, W., Zhuang, Y., & Zhang, L. (2017). A three-dimensional virtual resource scheduling method for energy saving in cloud computing. Future Generation Computer Systems, 69, 66-74.
Abohamama, A. S., & Hamouda, E. (2020). A hybrid energy–aware virtual machine placement algorithm for cloud environments. Expert Systems with Applications, 150, 113306.
Adamuthe, A. C., & Patil, J. T. (2018). Differential Evolution Algorithm for Optimizing Virtual Machine Placement Problem in Cloud Computing. International Journal of Intelligent Systems & Applications, 10(7).
Adamuthe, A. C., Pandharpatte, R. M., & Thampi, G. T. (2013, November). Multiobjective virtual machine placement in a cloud environment. In 2013 International Conference on Cloud & Ubiquitous Computing & Emerging Technologies (pp. 8-13). IEEE.
Adamuthe, A., & Nitave, T. (2020). Harmony search algorithm with adaptive parameter setting for solving large bin packing problems. Decision Science Letters, 9(4), 581-594.
Alharbi, F., Tian, Y. C., Tang, M., Zhang, W. Z., Peng, C., & Fei, M. (2019). An ant colony system for energy-efficient dynamic virtual machine placement in data centers. Expert Systems with Applications, 120, 228-238.
Alicherry, M., & Lakshman, T. V. (2013, April). Optimizing data access latencies in cloud systems by intelligent virtual machine placement. In 2013 Proceedings IEEE INFOCOM (pp. 647-655). IEEE.
Batista, D. M., Da Fonseca, N. L., & Miyazawa, F. K. (2007, March). A set of schedulers for grid networks. In Proceedings of the 2007 ACM symposium on Applied computing (pp. 209-213).
Beloglazov, A., & Buyya, R. (2010, May). Energy efficient allocation of virtual machines in cloud data centers. In 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (pp. 577-578). IEEE.
Beloglazov, A., Abawajy, J., & Buyya, R. (2012). Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future generation computer systems, 28(5), 755-768
Biran, O., Corradi, A., Fanelli, M., Foschini, L., Nus, A., Raz, D., & Silvera, E. (2012, May). A stable network-aware vm placement for cloud systems. In 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012) (pp. 498-506). IEEE.
Breitgand, D., & Epstein, A. (2011, May). SLA-aware placement of multi-virtual machine elastic services in compute clouds. In 12th IFIP/IEEE International Symposium on Integrated Network Management (IM 2011) and Workshops (pp. 161-168). IEEE.
Chaisiri, S., Lee, B. S., & Niyato, D. (2009, December). Optimal virtual machine placement across multiple cloud providers. In 2009 IEEE Asia-Pacific Services Computing Conference (APSCC) (pp. 103-110). IEEE.
Chase, J. S., Anderson, D. C., Thakar, P. N., Vahdat, A. M., & Doyle, R. P. (2001). Managing energy and server resources in hosting centers. ACM SIGOPS operating systems review, 35(5), 103-116.
Chen, G., He, W., Liu, J., Nath, S., Rigas, L., Xiao, L., & Zhao, F. (2008, April). Energy-Aware Server Provisioning and Load Dispatching for Connection-Intensive Internet Services. In NSDI (Vol. 8, pp. 337-350).
Dang, H. T., & Hermenier, F. (2013, November). Higher SLA satisfaction in datacenters with continuous VM placement constraints. In Proceedings of the 9th workshop on hot topics in dependable systems (pp. 1-6).
Dong, J., Wang, H., & Cheng, S. (2015). Energy-performance tradeoffs in IaaS cloud with virtual machine scheduling. China communications, 12(2), 155-166
Fesanghary, M., Damangir, E., & Soleimani, I. (2009). Design optimization of shell and tube heat exchangers using global sensitivity analysis and harmony search algorithm. Applied Thermal Engineering, 29(5-6), 1026-1031.
Fidanova, S. (2021). Multiple Knapsack Problem. In Ant Colony Optimization and Applications (pp. 9-18). Springer, Cham.
Gao, Y., Guan, H., Qi, Z., Hou, Y., & Liu, L. (2013). A multi-objective ant colony system algorithm for virtual machine placement in cloud computing. Journal of computer and system sciences, 79(8), 1230-1242.
Gartner Estimates, I. C. T. (2007). Industry accounts for 2 percent of global CO2 emissions. press release.
Ghribi, C., Hadji, M., & Zeghlache, D. (2013, May). Energy-efficient vm scheduling for cloud data centers: Exact allocation and migration algorithms. In 2013 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (pp. 671-678). IEEE.
Hyser, C., McKee, B., Gardner, R., & Watson, B. J. (2007). Autonomic virtual machine placement in the data center. Hewlett Packard Laboratories, Tech. Rep. HPL-2007-189, 189.
Jayasinghe, D., Pu, C., Eilam, T., Steinder, M., Whally, I., & Snible, E. (2011, July). Improving performance and availability of services hosted on iaas clouds with structural constraint-aware virtual machine placement. In 2011 IEEE International Conference on Services Computing (pp. 72-79). IEEE.
Lee, K. S., Geem, Z. W., Lee, S. H., & Bae, K. W. (2005). The harmony search heuristic algorithm for discrete structural optimization. Engineering Optimization, 37(7), 663-684.
Mahdavi, M., Fesanghary, M., & Damangir, E. (2007). An improved harmony search algorithm for solving optimization problems. Applied mathematics and computation, 188(2), 1567-1579.
Mann, Z. Á. (2015). Allocation of virtual machines in cloud data centers—a survey of problem models and optimization algorithms. Acm Computing Surveys (CSUR), 48(1), 1-34.
Mi, H., Wang, H., Yin, G., Zhou, Y., Shi, D., & Yuan, L. (2010, July). Online self-reconfiguration with a performance guarantee for energy-efficient large-scale cloud computing data centers. In 2010 IEEE International Conference on Services Computing (pp. 514-521). IEEE.
Mohamadi, E., Karimi, M., & Heikalabad, S. R. (2011). A Novel Virtual Placement in Virtual Computing. Australian Journal of Basic and Applied Scienes, Australia, 5(10), 1149-1555.
Networking, C. V. (2016). Cisco global cloud index: Forecast and methodology, 2015-2020. white paper. Cisco Public, San Jose, 2016.
Omran, M. G., & Mahdavi, M. (2008). Global-best harmony search. Applied mathematics and computation, 198(2), 643-656.
Panigrahy, R., Talwar, K., Uyeda, L., & Wieder, U. (2011). Heuristics for vector bin packing. research. microsoft. com.
Pinheiro, E., Bianchini, R., Carrera, E. V., & Heath, T. (2001, September). Load balancing and unbalancing for power and performance in cluster-based systems. In Workshop on compilers and operating systems for low power (Vol. 180, pp. 182-195).
Salehi, M. A., Krishna, P. R., Deepak, K. S., & Buyya, R. (2012, June). Preemption-aware energy management in virtualized data centers. In 2012 IEEE Fifth International Conference on Cloud Computing (pp. 844-851). IEEE.
Shuja, J., Gani, A., Shamshirband, S., Ahmad, R. W., & Bilal, K. (2016). Sustainable cloud data centers: a survey of enabling techniques and technologies. Renewable and Sustainable Energy Reviews, 62, 195-214.
Singh, A., Korupolu, M., & Mohapatra, D. (2008, November). Server-storage virtualization: integration and load balancing in data centers. In SC'08: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (pp. 1-12). IEEE.
Song, Y., Zhang, C., & Fang, Y. (2008, November). Multiple multidimensional knapsack problem and its applications in cognitive radio networks. In MILCOM 2008-2008 IEEE Military Communications Conference (pp. 1-7). IEEE.
Speitkamp, B., & Bichler, M. (2010). A mathematical programming approach for server consolidation problems in virtualized data centers. IEEE Transactions on services computing, 3(4), 266-278.
Tang, M., & Pan, S. (2015). A hybrid genetic algorithm for the energy-efficient virtual machine placement problem in data centers. Neural processing letters, 41(2), 211-221.
Usmani, Z., & Singh, S. (2016). A survey of virtual machine placement techniques in a cloud data center. Procedia Computer Science, 78, 491-498.
Van den Bossche, R., Vanmechelen, K., & Broeckhove, J. (2010, July). Cost-optimal scheduling in hybrid iaas clouds for deadline constrained workloads. In 2010 IEEE 3rd international conference on cloud computing (pp. 228-235). IEEE.
Wang, M., Meng, X., & Zhang, L. (2011, April). Consolidating virtual machines with dynamic bandwidth demand in data centers. In 2011 Proceedings IEEE INFOCOM (pp. 71-75). IEEE.
Wood, T., Shenoy, P., Venkataramani, A., & Yousif, M. (2009). Sandpiper: Black-box and gray-box resource management for virtual machines. Computer Networks, 53(17), 2923-2938.
Xia, B., & Tan, Z. (2010). Tighter bounds of the First Fit algorithm for the bin-packing problem. Discrete Applied Mathematics, 158(15), 1668-1675
Zhu, W., Zhuang, Y., & Zhang, L. (2017). A three-dimensional virtual resource scheduling method for energy saving in cloud computing. Future Generation Computer Systems, 69, 66-74.