Online computation and competitive analysis
Online computation and competitive analysis
Loss-bounded analysis for differentiated services
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Competitve buffer management for shared-memory switches
Proceedings of the thirteenth annual ACM symposium on Parallel algorithms and architectures
Nearly optimal FIFO buffer management for DiffServ
Proceedings of the twenty-first annual symposium on Principles of distributed computing
Competitive queueing policies for QoS switches
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Management of multi-queue switches in QoS networks
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Buffer Overflow Management in QoS Switches
SIAM Journal on Computing
The zero-one principle for switching networks
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Packet buffering: randomization beats deterministic algorithms
STACS'05 Proceedings of the 22nd annual conference on Theoretical Aspects of Computer Science
An improved algorithm for CIOQ switches
ACM Transactions on Algorithms (TALG)
Lower and upper bounds on FIFO buffer management in QoS switches
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
Proceedings of the twenty-first annual symposium on Parallelism in algorithms and architectures
A survey of buffer management policies for packet switches
ACM SIGACT News
An optimal lower bound for buffer management in multi-queue switches
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
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We focus on the online problem of queue management in networks providing differentiated services. As in DiffServ, packets are divided into two priority groups. Low priority packets are assigned the value of 1 and high priority packets are assigned the value of α 1. The goal is to maximize the total value of packets that are sent. Restricted to FIFO queues, the packets must be sent by the order of their arrival, however we are allowed to preempt packets from the queue.Several deterministic online algorithms for this model have been presented in previous papers. Currently, the best online algorithm known for this problem has a competitive ratio of 1.304 for the worst case α [17]. In this work we consider randomized online algorithms. Our main result is an online policy that outperforms any deterministic policy and achieves a competitive ratio of 1.25, by using a single random bit. This result is lower than the deterministic lower bound of 1.281 [19]. We then derive a general lower bound for randomized algorithms of 1.197.A natural extension of this model is to assign arbitrary packet values to the input packets. Currently, the best competitive ratio achieved for a deterministic policy is 1.75 [7]. We present a randomized comparison based online policy with the same competitive ratio. Since no deterministic comparison based policy is known to have a competitive ratio better than 2, we believe that this result demonstrates the potential of using randomization to outperform deterministic policies, as in the two value model.