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It is a vital necessity of a heterogeneous environment to schedule the resources efficiently among applications to optimize the execution time to provide well-regulated services to the users. The system is said to be effective only if it supplies the resources on time and assures smooth task execution. This paper introduces a dynamic task scheduling with advance reservation (DTSAR) of resources to optimize turnaround time (TAT). A task will be dynamically allocated to the resource in an advance manner that takes meanest execution time. More parameters are considered for performance comparison viz. flow time, average utilization and processing cost. Simulation results acknowledge the preferable achievements of the proposed scheduling schemes on the comparison of another state of art in literature. The experimental assessments and obtained results show that DTSAR is preferable than other considered heuristics in terms of TAT and other QoS parameters.

The emerging computational grid (CG) system is used for effective utilization of geographically dispersed computing resources in order to fulfill the compute-intensive requirement of the users. Map...

Objectives: In this paper various task scheduling algorithm along with load distribution techniques investigated to ensure efficient mapping of tasks to resources and for coherent resource utilization in heterogeneous environment. Statistical Analysis: A detailed comparative approach is conferred for different job scheduling and load balancing algorithm available in the literature. Considered parameters for comparisons are scheduling approaches, techniques, findings, benefits, pros and cons. This study facilitates to identify the efficient scheduling and load balancing approach which optimizes resource use, minimizes completion time as well as task waiting time and balanced load among resources. Findings: Make span time and flow time are two important parameters to compute and minimize job execution time. This paper explores an intense survey of minimization of task execution time with minimum make span time and flow time. Apart from this a joint review on job scheduling, load balancing and minimizing job completion time using Expected Time to Compute (ETC) matrix is presented. At the end of this paper a research model is proposed which is a novel and hybrid approach with a combination of the efficiency of scheduling and load balancing. Application: The Load Balancing (LB) is an important feature of the grid environment. The efficient LB algorithm assures cost effective resource usage by the provisioning of resources to users on demand schedule in pay-as-you-say-manner.

Effectual allocation of resources with fault tolerance is one of the key targets in any computational grid environment to accomplish the task execution on time. In this paper, a Fault Tolerant Hybrid Resource allocation Model (FTHRM) has been proposed to minimize the Turnaround Time (TAT) for the batch of tasks while ensuring fault tolerance in a dynamic grid environment. The model uses the prior reservation mechanism to allocate the resources to tasks for guaranteed task execution. Furthermore, resources are reserved in advance for time slots with resource configuration as required by the batch of tasks. Alternate resources are provided by the system in the case of resource failures. Here, the resource with the least previous workload and lowest execution time will prefer over other resources for task accomplishment. The performance evaluation of FTHRM has been carried out by comparing it with Minimum Completion Time (MCT). The simulation study reveals that the proposed model viz. FTHRM outperforms MCT on considered parameters under study. Statistical testing has been conducted to test the level of significance using SPSS 20, which also confirms the conclusions drawn in the simulation.

Task scheduling is one of the core concerns in the computational grid environment and has been proven NP-complete. In this paper, a Dynamic Task Scheduling (DTS) strategy for computational grid environment has been proposed to minimize makespan of batch of tasks by enhancing Task Level Parallelism (TLP). The strategy works in two phases. In the first phase job is divided into tasks to exploits parallelism. In the second phase, as tasks are available in memory for execution, these tasks are allocated to the most suitable and available resources dynamically as per the strategy. Efficiency of proposed work is evaluated by designing and implementing DTS in grid simulation toolkit (Gridsim) and comparing with other state of art technique in different conditions i.e. varying the number of jobs, the number of resources and the processing capability of resources with taking remaining input parameters fixed. The simulation results revealed that DTS performs better on account of makespan for all conditions under study.