A Novel Approach to Improve the SLA and Energy Consumption of Grid Networks
Publish place: The first national electronic conference on technological advances in electrical, electronics and computer engineering
Publish Year: 1393
Type: Conference paper
Language: English
View: 783
This Paper With 8 Page And PDF Format Ready To Download
- Certificate
- I'm the author of the paper
Export:
Document National Code:
TDCONF01_239
Index date: 10 July 2015
A Novel Approach to Improve the SLA and Energy Consumption of Grid Networks abstract
In recent years, the IT infrastructure due to the demand for computing power which used by applications are rapidly growing and modern data centers in grid computing are hosting a variety of advanced applications. One of the most important objectives of the VM placement algorithm is determine the optimal location of virtual machines in physical servers So that the minimum number of physical servers to be turned on for enhancing the overall performance of the grid environment. Efficient placement of VMs in PMs (Physical Machines) in grid environment improves resources utilization and energy consumption. In this paper, we employ TOPSIS method to design a integrated VM placement algorithm, called TOPSIS VM Placement (TVMP) which can reduce the number of running PMs and lower the energy consumption. Extensive simulation results in GridSim environment show that the proposed algorithm outperforms existing algorithms in terms of migration, traffic cost, SLA and energy
A Novel Approach to Improve the SLA and Energy Consumption of Grid Networks Keywords:
A Novel Approach to Improve the SLA and Energy Consumption of Grid Networks authors
Fatemeh Hourali
Network Laboratory, Esfarayen University of technology
Samira Hourali
Mohaghegh Ardabili University
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :