TY - GEN
T1 - ELVMC
T2 - 20th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2020
AU - Zhao, Da ming
AU - Zhou, Jian tao
AU - Yu, Shucheng
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - Virtual machine consolidation (VMC) is a technology that aggregates virtual machines distributed on multiple physical machines into a small number of physical machines to improve resource utilization and energy efficiency of data center. However, excessive virtual machine aggregation and migration can also have a significant negative impact on performance. In this paper, an algorithm named ELVMC with multiple resource prediction is proposed for optimal virtual machine consolidation. It applies a modified Best-Fit Decreasing (BFD) algorithm for resource optimization at both overloaded hosts and underloaded hosts with consideration of load balancing. Different from current research, ELVMC aims to obtain an optimal virtual machine (VM) placement during each consolidation process by simultaneously optimizing multiple system performance metrics in terms of energy consumption, VM migrations and QoS guarantees while keeping the load balanced. Simulation results show that ELVMC is superior to the state of the arts, including the traditional BFD and SABFD-HS algorithms as well as recent research VMCUP-M and MUC-MBFD.
AB - Virtual machine consolidation (VMC) is a technology that aggregates virtual machines distributed on multiple physical machines into a small number of physical machines to improve resource utilization and energy efficiency of data center. However, excessive virtual machine aggregation and migration can also have a significant negative impact on performance. In this paper, an algorithm named ELVMC with multiple resource prediction is proposed for optimal virtual machine consolidation. It applies a modified Best-Fit Decreasing (BFD) algorithm for resource optimization at both overloaded hosts and underloaded hosts with consideration of load balancing. Different from current research, ELVMC aims to obtain an optimal virtual machine (VM) placement during each consolidation process by simultaneously optimizing multiple system performance metrics in terms of energy consumption, VM migrations and QoS guarantees while keeping the load balanced. Simulation results show that ELVMC is superior to the state of the arts, including the traditional BFD and SABFD-HS algorithms as well as recent research VMCUP-M and MUC-MBFD.
KW - Energy consumption
KW - Load balance
KW - Resource prediction
KW - Virtual machine consolidation
KW - Virtual machine migration
UR - http://www.scopus.com/inward/record.url?scp=85092696324&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85092696324&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-60239-0_5
DO - 10.1007/978-3-030-60239-0_5
M3 - Conference contribution
AN - SCOPUS:85092696324
SN - 9783030602383
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 62
EP - 81
BT - Algorithms and Architectures for Parallel Processing - 20th International Conference, ICA3PP 2020, Proceedings
A2 - Qiu, Meikang
Y2 - 2 October 2020 through 4 October 2020
ER -
