الفهرس 
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Abstract
Cloud computing refers to making resources and computer systems available ondemand over the internet, which makes it possible to easily provide a number of integrated computing services to users without being bound by local resources. This include providing resources and services not just for data storage and backup and self-synchronization, but also includes processing capabilities, where the user can control when it is connected to the network in these resources through a simple software interface simplifies and ignores a lot of details and internal operations. Scheduling algorithms are important for the cloud in order to provide services with objectives such as: high performance, lowered costs, minimized energy consumption …etc. Developing scheduling algorithms which optimize more than one of these objectives is an NP-hard problem. In this thesis, we provide some new heuristic scheduling algorithms to enable multi-objectives optimization and study their efficiencies by comparing them with some of the well-known scheduling algorithms. The first algorithm the performance and cost algorithm (PCA) aims to give the user which have the highest profit the priority and minimize the make span and cost for server provider in addition maximize the throughput. We notice that the proposed (PCA) algorithm may cause unbalanced distribution of tasks a many the cloud resource, so we reposed the second algorithm Load Balanced Performance And Cost Algorithm (LBPCA), as a hybrid algorithm integrates a load balancing algorithm with the preponed (PCA)Algorithm. Finally we proposed another hybrid algorithm the Performance , Cost and Temp Algorithm (PCTA) a framework for this algorithm, we modified (PCA)algorithm so that the temperature of any resource does not exceed the criticaltemperature of that resource.