Size based scheduling with differentiated services to improve response time of highly varying flow

The sizes of Internet objects are known to be highly varying. We evaluate an M/G/1 queue under foreground background N (FBN) scheduling policy for job size distributions with varying coefficient of variability (CoV) to analyze the impact of variability of job sizes to the performance of the policy. We find thatFBN is very efficient in reducing the response time and minimizing the number of jobs that are penalized (i.e., have a higher response time under FBN than under processor sharing (PS)) when job sizes have a high CoV.We also propose and analyze variants ofFBN called fixed priorityFBN (FP
FBN) and differentialFBN (DF
FBN), which introduce service differentiation by classifying jobs into high priority and low priority and then servicing the high priority before low priority jobs in an FBN related order. The numerical analysis conducted for highly varying job sizes reveals that FP
FBN achieves a perfect service differentiation at the expense of a high penalty for the low priority small jobs. While DF
FBN offers acceptable service differentiation, it does not penalize small jobs with low priority at all. Moreover, FP
FBN and DF
FBN can guarantee the service of high priority jobs even under overload.