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A Grid is a computational system consisting of a large number of geographically distributed and heterogeneous resources. Job scheduling is the key component of a Grid, and plays an important role in the efficient and effective execution of various kinds of scientific and engineering applications. This paper presents a comparative performance analysis of our proposed job scheduling algorithms along with other well known job scheduling algorithms, considering the quality of service (QoS) parameters such as waiting time, turnaround time, response time, total completion time, bounded slowdown and stretch time. The main thrust of this work was to conduct a QoS based evaluation of the scheduling algorithms on an experimental Grid using real workload traces. The experimental evaluation confirmed that the proposed scheduling algorithms possess a high degree of optimality in performance, efficiency and scalability.