[Saxena, 3(10): October 2016] ISSN 2348 – 8034 DOI- 10.5281/zenodo.163783 Impact Factor- 4.022 (C)Global Journal Of Engineering Science And Researches 134 GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES ONLINE RESOURCE ALLOCATION OPTIMIZATION AND WORKLOAD BALANCING SCHEDULING ON IAAS CLOUD SYSTEM Deepika Saxena *1 , Dr. R.K. Chauhan 2 and Shilpi Saxena 3 *1 Assisstant Professor ,Department Of Computer Science And Applications, Kurukshetra University Kurukshetra 2 Professor ,Department Of Computer Science And Applications, Kurukshetra University Kurukshetra 3 Assisstant Professor, Dpartment Of Computer Science And Applications, Graphic Era University, Dehradun ABSTRACT Cloud computing is a rapidly emerging paradigm in this very new era of technology. Basically, cloud is a cluster of distributed and interlinked servers providing on-demand services to customers. Broadly, it offers software-as-a- service(SAAS), platform-as-a-service(PAAS), infrastructure-as-a-service(IAAS).Here we are focusing on IAAS cloud system which offers computational resources to remote customers in the form of leases. Here we are defining real-time or online optimized scheduling of requests of various resources arriving simultaneously at data center of IAAS cloud service provider. Being more practical, our algorithm is providing best resource utilization and better results in terms of execution time as compared to DFPT algorithm for task scheduling in cloud computing which do not considers dependency between tasks(requests). Our algorithm proposes dynamic task allocation on IAAS clouds and resource scheduling by utilizing the updated status of various Virtual machines available at real time. We have simulated this experiment using CloudSim toolkit. Surely, there is very beneficial improvement in results as compared to default FCFS scheduling and other available scheduling algorithms. Keywords- Cloud, CloudSim, Dependency, Resource allocation, Task, Virtual Machine. I. INTRODUCTION In this new digital world of Information Technology and Advancement, the cloud computing has broaden the world of internet to all most everyone in this world. It has transformed the complex internet based services to the simplest laymen requirement of computation. The term ``Cloud`` means a cluster of interconnected distributed datacenters which are expanded worldwide for example, Google, Amazon etc. At each datacenter, there are several computer systems acting as servers and providing enormous variety of services to the customers. Briefly describing, cloud computing is a model for enabling convenient, on-demand network access to shared pool of computing resources for example, networks, servers, storage, applications and several other services that can be rapidly provisioned and released with minimal management effort or cloud service provider interaction[4]. The basic idea of cloud computing is based on a very fundamental principal of reusability of IT capabilities. In this paper, specifically considering IaaS clouds i.e. Infrastructure as a Service which represents lowest level of cloud service providing resources and services on pay-as-per use to its customers. The ultimate goal of this Cloud System is to instantly provide resources whenever customer requires it on their laptops, PCs, mobile phones etc wherever possible. In an IaaS model of cloud computing, Cloud Service Provider provides hardware, software, servers, storage and other infrastructure components to its customers. IaaS clouds also provides various applications to its users and handle task including system maintenance, backup and resiliency planning. IaaS customers pay on a per-use basis typically by hour, week or month. Some Cloud Service Provider also charge customers based on amount of storage space used or VM space used [5]. In recent trends of IT world, cloud computing is emerging with growing popularity of its capability to provide unlimited VM space, storage space and other resources with extreme flexibility so that no adjustment is required at customer end. But practically, there is no datacenter which has unlimited capacity. Infact, to meet real time significant demand of resources, Cloud Service Provider has to make several arrangements and adjustments at their datacenters to concurrently schedule the thousand of requests and demand of resources arriving parallel at datacenter. In case of overflow of workload at datacenter, it can be shared among different datacenters or workload can be share in between public and private clouds with applying extreme security checks [2]. So, this