The Grid scheduler, schedules user jobs on the best available resource in terms of resource characteristics by optimizing job execution time. Resource failure in Grid is no longer an exception but a regular occurring event as resources are increasingly being used by the scientific community to solve computationally intensive problems which typically run for days or even months. It is therefore absolutely essential that these long-running applications are able to tolerate failures and avoid re-computations from scratch after resource failure has occurred, to satisfy the user’s Quality of Service (QoS) requirement. Job Scheduling with Fault Tolerance in Grid Computing using Ant Colony Optimization is proposed to ensure that jobs are executed successfully even when resource failure has occurred. The technique employed in this paper, is the use of resource failure rate, as well as checkpoint-based roll back recovery strategy. Check-pointing aims at reducing the amount of work that is lost upon failure of the system by immediately saving the state of the system. A comparison of the proposed approach with an existing Ant Colony Optimization (ACO) algorithm is discussed. The experimental results of the implemented Fault Tolerance scheduling algorithm show that there is an improvement in the user’s QoS requirement over the existing ACO algorithm, which has no fault tolerance integrated in it. The performance evaluation of the two algorithms was measured in terms of the three main scheduling performance metrics: makespan, throughput and average turnaround time.

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Wireless telecommunication networks have become fundamental to our daily activities. Today, people have access to at least one type of wireless telecommunication network with Mobile Stations (MS) supporting multiple applications that consume more battery power; as well as a constant increase in multimedia applications that possess a critical challenge in efficient battery management. MSs are battery powered devices with limited lifetime. An efficient management of the battery will extend its lifetime before recharging exercise is conducted. World Wide Interoperability for Microwave Access (WiMAX), is design to Supports Higher Bandwidth with different traffic classes support for Power Management. Due to the mobility Characteristics introduced in WiMAX, power savings became an important problem; Since MS has limited superimpose life that requires recharging exercise when the battery life is depleted. Thus, Battery Lifetime Aware Power Saving Scheme (BLAPS) and an Adaptive Power Saving Scheme were proposed to extend the Battery Life, but the first scheme resulted in frequent transition to listening mode which led to waste of energy. While the former has higher energy consumption resulting to poor QoS that degrades the overall performance of MS. Hence, a Quality of Service (QoS) Aware Power Saving Scheme is proposed to improve the QoS. The scheme introduced a Modified minimum (Tmin) and Maximum (Tmax) sleep intervals in order to enhance the parameters of the variant schemes. In addition, the scheme also introduced a modified sleep window as well as QoS Aware algorithm that enable the adjustments of the sleep Parameters more appropriately in order to minimize frequent Transition to listening mode while improving efficiency. Finally, a state transition diagram was also developed. The proposed scheme was evaluated using MATLAB simulator; the results proved that the proposed QoS Aware Scheme has superior performance in terms of consumption rate and response delay respectively. Keywords: Battery Life, Power Consumption, Response Delay.

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