The sampling problem for input-queued (IQ) randomized scheduling algorithms is analyzed.We observe that if the current scheduling decision is a maximum weighted matching (MWM),the MWM for the next slot mostly falls in...The sampling problem for input-queued (IQ) randomized scheduling algorithms is analyzed.We observe that if the current scheduling decision is a maximum weighted matching (MWM),the MWM for the next slot mostly falls in those matchings whose weight is closed to the current MWM.Using this heuristic,a novel randomized algorithm for IQ scheduling,named genetic algorithm-like scheduling algorithm (GALSA),is proposed.Evolutionary strategy is used for choosing sampling points in GALSA.GALSA works with only O(N) samples which means that GALSA has lower complexity than the famous randomized scheduling algorithm,APSARA.Simulation results show that the delay performance of GALSA is quite competitive with respect to that of APSARA.展开更多
A QoS-aware input-queued scheduling algorithm, called Smallest Timestamp First (STF), is proposed, which is improved upon iSLIP and can allocate bandwidth among inputs sharing a common output based on their reservatio...A QoS-aware input-queued scheduling algorithm, called Smallest Timestamp First (STF), is proposed, which is improved upon iSLIP and can allocate bandwidth among inputs sharing a common output based on their reservation by assigning suitable finishing tiniest-amps to contending cells. STF can also provide isolation between flows that share a common output, link. Misbehaving flows will be restricted to guarantee the behaving flows' bandwidth. Simulations prove the feasibility of our algorithm.展开更多
文摘The sampling problem for input-queued (IQ) randomized scheduling algorithms is analyzed.We observe that if the current scheduling decision is a maximum weighted matching (MWM),the MWM for the next slot mostly falls in those matchings whose weight is closed to the current MWM.Using this heuristic,a novel randomized algorithm for IQ scheduling,named genetic algorithm-like scheduling algorithm (GALSA),is proposed.Evolutionary strategy is used for choosing sampling points in GALSA.GALSA works with only O(N) samples which means that GALSA has lower complexity than the famous randomized scheduling algorithm,APSARA.Simulation results show that the delay performance of GALSA is quite competitive with respect to that of APSARA.
基金Supported by National Natural Science Foundation of China under Grant No.69896246
文摘A QoS-aware input-queued scheduling algorithm, called Smallest Timestamp First (STF), is proposed, which is improved upon iSLIP and can allocate bandwidth among inputs sharing a common output based on their reservation by assigning suitable finishing tiniest-amps to contending cells. STF can also provide isolation between flows that share a common output, link. Misbehaving flows will be restricted to guarantee the behaving flows' bandwidth. Simulations prove the feasibility of our algorithm.
