Cloud computing is the delivery of computing services—servers, storage, databases, networking, software, analytics and more—over the Internet (“the cloud”). Companies offering these computing services are called cloud providers and typically charge for cloud computing services based on usage, similar to how you are billed for water or electricity at home. We are probably using cloud computing right now, even if you don’t realize it. If you use an online service to send email, edit documents, watch movies or TV, listen to music, play games or store pictures and other files, it is likely that cloud computing is making it all possible behind the scenes. Numerous applications which are very complex need parallel processing for executing the jobs efficiently. Because of the synchronization and communication among processes which run parallel, there is a reduction in usage of resources of CPU. So there are number of jobs that need to be executed with the available resources to achieve optimal performance, least possible total time for completion, less processing cost and efficient utilization of resources etc. . To accomplish these goals and achieve high performance, it is important to design and develop a multi objective scheduling algorithm to schedule the tasks along with satisfying the user’s Quality of Service requirements. After studying and analyze the processing time of various low level scheduling algorithms, an improved task scheduling is developed using quality of service parameters of resource nodes and priorities of the task. In order to achieve efficient consumption of cloud resources, the load balancing problem is solved by using Adaptive Load balancing algorithm. The evaluation parameters considered in the work includes total processing cost, average waiting time and total processing time.