Dynamic Resource Allocation Using Virtual Machines and Parallel Data Processing in the Cloud


  • Bhushan YB Department of Computer Science and Engineering Sri Venkateswara Engineering College, Suryapet
  • Bhavani V Department of Computer Science and Engineering Sri Venkateswara Engineering College, Suryapet


Cloud Computing, Parallel Data Processing, Dynamic resource allocation, High-Throughput Computing, Loosely Coupled Applications


The main enabling technology for cloud computing is virtualization which generalize the physical infrastructure and makes it easy to use and manage. Virtualization is used to allocate resources based on their needs and also supports green computing concept. Parallel data processing has emerged to be one of the killer applications for Infrastructure-as-a-Service (IaaS) clouds. The processing frameworks which are currently used have been designed for static, homogeneous cluster setups and disregard the particular nature of a cloud. The allocated compute resources may be inadequate for big parts of the submitted job and unnecessarily increase processing time and cost.

In this paper we are applying the concept of “SKEWNESS” to measure the unevenness in the multi- dimensional resource utilization of a server. By minimizing skewness, we can combine different types of workloads and improve the overall utilization of server resources and discuss the opportunities and challenges for efficient parallel data processing in clouds using “NEPHELE’S ARCHITECTURE”. Nephel’s architecture offers efficient parallel data processing in clouds. It is the first data processing framework for the dynamic resource allocation offered by today’s IaaS clouds for both, task scheduling and execution


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How to Cite

Bhushan, Y., & Bhavani, V. (2024). Dynamic Resource Allocation Using Virtual Machines and Parallel Data Processing in the Cloud. COMPUSOFT: An International Journal of Advanced Computer Technology, 4(11), 2001–2005. Retrieved from https://ijact.in/index.php/j/article/view/350



Original Research Article

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