An energy-efficient virtual machine placement and route scheduling scheme in data center networks

Optimal resource management is required in a data center to allocate the resources to users in a balanced manner. Balanced resource allocation is one of the key challenges in the data center. The multi-dimensional resources of a data center must be allocated in a balanced manner in all the dimensions of physical machines. The unbalanced resource allocation leads to unused residual resource fragments. The unused residual resource fragments leads to resource wastage. If the multi-dimensional data center resources are allocated in a balanced manner, the resource wastage does not occur. Also, the balanced allocation improves the power consumption. The balanced resource allocation reduces the resource wastage as well as reduces the power consumption. In this paper, we have designed a Balanced Energy Efficient Multi-Core Aware Virtual Machine Placement algorithm (MCA-BEE-VMP) using multi-dimensional resource space partition model to balance the resources like CPU and memory and also to reduce the power consumption. We used Google Cloud Jobs (GoCJ) dataset for the simulation. In our simulation of MCA-BEE-VMP using Cloud Sim simulation tool we have achieved balanced CPU and memory resources allocation in two dimensions of a physical machine. The resource wastage and power consumption is improved and the simulation results were analyzed.

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Optimized Virtual Machine Placement with Traffic-Aware Balancing in Data Center Networks

Scientific Programming ◽

10.1155/2016/3101658 ◽

2016 ◽

Vol 2016 ◽

pp. 1-10 ◽

Cited By ~ 4

Author(s):

Tao Chen ◽

Xiaofeng Gao ◽

Guihai Chen

Keyword(s):

Virtual Machine ◽

Heuristic Algorithm ◽

Data Center ◽

Virtual Machines ◽

Virtual Machine Placement ◽

Np Hard ◽

Data Center Networks ◽

Placement Problem ◽

Placement Algorithm ◽

Communication Locality

Virtualization has been an efficient method to fully utilize computing resources such as servers. The way of placing virtual machines (VMs) among a large pool of servers greatly affects the performance of data center networks (DCNs). As network resources have become a main bottleneck of the performance of DCNs, we concentrate on VM placement with Traffic-Aware Balancing to evenly utilize the links in DCNs. In this paper, we first proposed a Virtual Machine Placement Problem with Traffic-Aware Balancing (VMPPTB) and then proved it to be NP-hard and designed a Longest Processing Time Based Placement algorithm (LPTBP algorithm) to solve it. To take advantage of the communication locality, we proposed Locality-Aware Virtual Machine Placement Problem with Traffic-Aware Balancing (LVMPPTB), which is a multiobjective optimization problem of simultaneously minimizing the maximum number of VM partitions of requests and minimizing the maximum bandwidth occupancy on uplinks of Top of Rack (ToR) switches. We also proved it to be NP-hard and designed a heuristic algorithm (Least-Load First Based Placement algorithm, LLBP algorithm) to solve it. Through extensive simulations, the proposed heuristic algorithm is proven to significantly balance the bandwidth occupancy on uplinks of ToR switches, while keeping the number of VM partitions of each request small enough.

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