A Hybrid Clone Detection Technique for Estimation of Resource Requirements of a Job

Resource requirement estimation in large distributed systems is a difficult job because of the heterogeneity and dynamism of the environment involving modern distributed systems. A feedback-based job modeling scheme based on clone detection technique was proposed in [6]. This paper extends the taxonomy of clones proposed by other researchers [1] in order to make resource requirement prediction more effective. It also presents a hybrid clone-detection technique, consisting of metrics-based, PDG-based and AST-based clone detection, to make the clone detection process more reliable and robust.