Online Scheduling of Parallel Communications with Individual Deadlines

Packet-mode policies for input-queued switches

“…We note that [4] gives a lower bound of Ω(κ) on the performance of any deterministic online algorithm. In particular, our algorithm achieves a competitive ratio of approximately 11.123 for κ = 1, which improves upon the previous best-known upper bound for this problem [17].We complement our results by studying the offline version of the problem, which is NP-hard We give a pseudo-polynomial 3-approximation algorithm for the general case and a polynomial 3-approximation algorithm for the case of unit value packets. …”

“…We note that [4] gives a lower bound of Ω(κ) on the performance of any deterministic online algorithm. In particular, our algorithm achieves a competitive ratio of approximately 11.123 for κ = 1, which improves upon the previous best-known upper bound for this problem [17].…”

“…For κ = 1, the competitive ratio of our algorithm is approximately 11.123, which improves upon the previous bestknown upper bound of 11.656 due to [17]. The work in [17] also gives a lower bound of 8 − on the competitive ratio of any online scheduling algorithm for the continuous time model for κ = 1. This lower bound can be also transformed to our model.…”

“…For the case of arbitrary length jobs, they derive a 11.656-competitive algorithm and show a lower bound of 8 − under the continuous time model. In the present paper we extend their work to the case of variable value density, but in contrast to [17], we consider only the slotted time model. Some of our algorithms are in the spirit of [17], however, we try to maximize the total value rather than the total length of the successfully transmitted packets.…”

“…The present paper is most closely related to the work of Lee and Chwa [17], where they study the parallel communication problem assuming the uniform value density (i.e. the value of a packet is proportional to its length).…”