In this paper, we develop a fault tolerant job scheduling strategy in order to tolerate faults gracefully in an economy based grid environment. We propose a novel adaptive task checkpointing based fault tolerant job scheduling strategy for an economy based grid. The proposed strategy maintains a fault index of grid resources. It dynamically updates the fault index based on successful or unsuccessful completion of an assigned task. Whenever a grid resource broker has tasks to schedule on grid resources, it makes use of the fault index from the fault tolerant schedule manager in addition to using a time optimization heuristic. While scheduling a grid job on a grid resource, the resource broker uses fault index to apply different intensity of task checkpointing (inserting checkpoints in a task at different intervals).To simulate and evaluate the performance of the proposed strategy, this paper enhances the GridSim Toolkit-4.0 to exhibit fault tolerance related behavior. We also compare "checkpointing fault tolerant job scheduling strategy" with the well-known time optimization heuristic in an economy based grid environment. From the measured results, we conclude that even in the presence of faults, the proposed strategy effectively schedules grid jobs tolerating faults gracefully and executes more jobs B. Nazir ( ) 2 B. Nazir et al.successfully within the specified deadline and allotted budget. It also improves the overall execution time and minimizes the execution cost of grid jobs.

Grid is a network of computational resources that may potentially span many continents. Maximization of the resource utilization hinges on the implementation of an efficient load balancing scheme, which provides (i) minimization of idle time, (ii) minimization of overloading, and (iii) minimization of control overhead. In this paper, we propose a dynamic and distributed load balancing scheme for grid networks. The distributed nature of the proposed scheme not only reduces the communication overhead of grid resources but also cuts down the idle time of the resources during the process of load balancing. We apply the proposed load balancing approach on Enhanced GridSim in order to gauge the effectiveness in terms of communication overhead and response time reduction. We show that significant savings are delivered by the proposed technique compared to other approaches such as centralized load balancing and no load balancing.

In order to achieve high level of reliability and availability, the grid infrastructure should be a foolproof fault tolerant. Fault tolerance plays a key role in order to assert availability and reliability of a grid system. Since the failure of resources affects job execution fatally, fault tolerance service is essential to satisfy QoS requirement in grid computing.In this paper we proposed two hybrid fault tolerance techniques (FTTs) that are called alternate task with checkpoint and alternate task with retry. These proposed hybrid FTTs inherit the good features and overcome the limitations of workflow level FTT and task level FTT. We evaluate the performance of our proposed FTTs under different experimental environments. Finally, we conclude that alternate task with checkpoint improves the reliability of a grid system more significantly than alternate task with retry.

Load balancing and task partitioning are important components of distributed computing. The optimum performance from the distributed computing system is achieved by using effective scheduling and load balancing strategy. Researchers have well explored CPU, memory, and I/O-intensive tasks scheduling, and load balancing techniques. But one of the main obstacles of the load balancing technique leads to the ignorance of applications having a mixed nature of tasks. This is because load balancing strategies developed for one kind of job nature are not effective for the other kind of job nature. We have proposed a load balancing scheme in this paper, which is known as Mixed Task Load Balancing (MTLB) for Cluster of Workstation (CW) systems. In our proposed MTLB strategy, pre-tasks are assigned to each worker by the master to eliminate the worker's idle time. A main feature of MTLB strategy is to eradicate the inevitable selection of workers. Furthermore, the proposed MTLB strategy employs Three Resources Consideration (TRC) for load balancing (CPU, Memory, and I/O). The proposed MTLB strategy has removed the overheads of previously proposed strategies. The measured results show that MTLB strategy has a significant improvement in performance.

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