International Journal of Electrical and Computer Engineering (IJECE) Vol.9, No.1, February 2019, pp. 629~634 ISSN: 2088-8708, DOI: 10.11591/ijece.v9i1.pp629-634  629 Journal homepage: http://iaescore.com/journals/index.php/IJECE A review on various optimization techniques of resource provisioning in cloud computing K. Sumalatha 1 , M. S. Anbarasi 2 1 Department of Computer Science and Engineering, Annamacharaya Institute of Technology and Sciences, India 2 Department of Information Technology, Pondicherry Engineering College, India Article Info ABSTRACT Article history: Received Jan 4, 2018 Revised Jul 17, 2018 Accepted Aug 2, 2018 Cloud computing is the provision of IT resources (IaaS) on-demand using a pay as you go model over the internet.It is a broad and deep platform that helps customers builds sophisticated, scalable applications. To get the full benefits, research on a wide range of topics is needed. While resource over- provisioning can cost users more than necessary, resource under provisioning hurts the application performance. The cost effectiveness of cloud computing highly depends on how well the customer can optimize the cost of renting resources (VMs) from cloud providers. The issue of resource provisioning optimization from cloud-consumer potential is a complicated optimization issue, which includes much uncertainty parameters. There is a much research avenue available for solving this problem as it is in the real-world. Here, in this paper we provide details about various optimization techniques for resource provisioning. Keywords: IaaS Optimization techniques Resource provisioning Uncertinity Virtual machines Copyright © 2019 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: K. Sumalatha, Department of Computer Science and Engineering, Annamacharaya Institute of Technology and Sciences, Tirupati, India. Email: sumalathacs@yahoo.com 1. INTRODUCTION Cloud Computing is a broad and deep platform that helps customers build sophisticated scalable applications. Cloud provisioning is the allocation of a cloud provider's resources to a customer [1]. When a cloud provider accepts a request from a customer, it must create the appropriate number of virtual machines (VMs) [2] and allocate resources to support them. In this context, the term provisioning simply means “to provide”. The Provisioning has been done in several different ways. a) Advance Provisioning: The customer requests the provider for services and the provider prepares the appropriate resources [2] in advance. The customer is charged a flat fee or is billed on a monthly basis. b) Dynamic Provisioning: The provider allocates more resources when they are needed and removes them [3] when they are not needed. The customer is billed on a pay-per-use basis. Provisioning allows optimal allocation of resources to consumers in a finite time to achieve desired quality of service. Here, the problem is either the user gets over-provisioning or under-provisioning. Formally, provisioning problem involves uncertainty parameters while choosing resources subject to some constraints to optimize some objective function. The aim is to develop an optimized method that reduces over provisioning and under provisioning problems. It has remained a topic of research in various fields for decades, may it be supply of electricity or water to consumers [4]. In recent years, distributed computing paradigm [5] has gained much attention due to high scalability, reliability, and flexibility. Thus stochastic based techniques deal with these problems by