Utilization aware and network I/O intensive virtual machine placement policies for cloud data center. (September 2022)

• Record Type: Journal Article
• Authors: Karmakar, Kamalesh; Banerjee, Somrita; Das, Rajib K.; Khatua, Sunirmal
• Is Part Of: Journal of network and computer applications. Volume 205(2022)
• Publication Date: 2022-09
• Subjects: Cloud computing -- Virtual machine placement -- Data center networks -- Meta-heuristic -- Semidefinite programming -- Communication cost; Microcomputers -- Periodicals; Computer networks -- Periodicals; Application software -- Periodicals; Micro-ordinateurs -- Périodiques; Réseaux d'ordinateurs -- Périodiques; Logiciels d'application -- Périodiques; Application software; Computer networks; Microcomputers; Periodicals; 004.05; 004
• DOI: 10.1016/j.jnca.2022.103442
• Languages: English
• ISSNs: 1084-8045

Abstract

Abstract: High-performance computing in the cloud environment uses ample virtual resources, which in turn require physical infrastructures provided by cloud service providers ( CSPs ). Naturally, CSPs would like to place virtual machines ( VM ) in a cost-effective way satisfying the resource requirement of the VM s and the capacity constraints of the hosts. Such consideration has led to the well known virtual machine placement (VMP) problem. In this paper, we consider a variant of the VMP, taking into account the communication among the VM s. We introduce the concept of Virtual Cluster, made up of VM s communicating among themselves. It is desirable to place the VM s of a cluster close to each other and thus reduce the communication cost. The objective for the Virtual Cluster Placement (VCP) problem is to reduce the communication cost. For this, we have to consider the network topology of the data center. In this paper, we have proposed some heuristics for both kinds of placement problems ( VMP as well as VCP ) and given Integer Linear Programming (ILP) formulations. We have also presented algorithms based on Semidefinite Programming (SDP) and meta-heuristic based on Genetic Algorithms . We have compared the performance of proposed heuristics with other existing works and the optimal solutions obtained from ILPs. Highlights: Modeling the Virtual Machine placement problem using Integer Linear Programming. Some heuristics for Virtual Machine placement to reduce communication cost. A genetic Algorithm that further improves the performance compared to heuristics. A novel way to map the cost minimization problem to a Semidefinite Program (SDP). Simulations and comparisons of the proposed heuristics, ILP, and SDP-based solutions.