Online Buffer Management Research Articles

Randomized two-valued bounded delay online buffer management

In the bounded delay buffer management problem unit size packets arrive online to be sent over a network link. The objective is to maximize the total weight of packets sent before their deadline. In this paper we are interested in the two-valued variant of the problem, where every packet has either low (1) or high priority weight (α>1). We show that the optimal randomized competitive ratio against an oblivious adversary is 1+(α−1)∕(α2+α).

Online buffer management for transmitting packets with processing cycles

We study an online buffer management problem under the model introduced by Azar and Gilon (2015) [5] recently. Unit-sized packets arrive and are kept in a First-In-First-Out buffer of size B in an online fashion at a network server. Each packet is associated with an arrival time, a value and a processing cycle time in the buffer. The density of a packet is defined to be the ratio of its value to processing time. It is assumed that every packet can be transmitted only after its processing cycle is completed and only the packet at the head of the buffer can be processed. A packet is allowed to be preempted and then discarded from the buffer. But, the value of a packet is attained only if it is successfully transmitted. Under the model, the objective of online buffer management is to maximize the total value of transmitted packets. This model finds applications to packet scheduling in communication networks.In this study, we consider the model with constant density from a theoretical perspective. We first propose some lower bounds for the problem. Azar and Gilon obtained a 4-competitive algorithm for the online buffer management problem for packets with constant density. Here, we present a (2+1B−1)-competitive algorithm for the case B>1 as well as its generalization to the multi-buffer model. Moreover, we prove that the competitive ratio of a deterministic online algorithm is at least four when the buffer size is one. We also conduct experiments to demonstrate the superior performance of the proposed online algorithm against the previous approach.

Competitive buffer management for multi-queue switches in QoS networks using packet buffering algorithms

In this paper, we consider the online buffer management problem, which formulates the problem of managing network switches supporting Quality of Service guarantee. We improve competitive ratios of the 2-value multi-queue switch model, where the value of a packet is restricted to 1 or α(≥1). We use a similar approach as Azar and Richter (STOC 2003 and Algorithmica 43(1-2), 2005) did for the multi-value multi-queue switch model. Namely, we show that the competitive ratio of “the relaxed model” of the 2-value multi-queue switch model is at most x=min⁡{c+2−cα(2−c)+c−1,cα}, if the competitive ratio of an online algorithm for the unit-value multi-queue switch model is at most c. Azar and Richter's technique implies that if the competitive ratio of the 2-value single-queue switch model is x′, then the competitive ratio of the 2-value multi-queue switch model is at most xx′. We obtain several results using known c and x′.

Better bounds for online k-frame throughput maximization in network switches

We consider a variant of the online buffer management problem in network switches, called the k-frame throughput maximization problem (k-FTM). This problem models the situation where a large frame is fragmented into k packets and transmitted through the Internet, and the receiver can reconstruct the frame only if he/she accepts all the k packets. Kesselman et al. introduced this problem and showed that its competitive ratio is unbounded even when k=2. They also introduced an “order-respecting” variant of k-FTM, called k-OFTM, where inputs are restricted in some natural way. They proposed an online algorithm and showed that its competitive ratio is at most 2kB⌊B/k⌋+k for any B≥k, where B is the size of the buffer. They also gave a lower bound of B⌊2B/k⌋ for deterministic online algorithms when 2B≥k and k is a power of 2.In this paper, we improve upper and lower bounds on the competitive ratio of k-OFTM. Our main result is to improve an upper bound of O(k2) by Kesselman et al. to 5B+⌊B/k⌋−4⌊B/2k⌋=O(k) for B≥2k. Note that this upper bound is tight up to a multiplicative constant factor since the lower bound given by Kesselman et al. is Ω(k). We also give two lower bounds. First we give a lower bound of 2B⌊B/(k−1)⌋+1 on the competitive ratio of deterministic online algorithms for any k≥2 and any B≥k−1, which improves the previous lower bound of B⌊2B/k⌋ by a factor of almost four. Next, we present the first nontrivial lower bound on the competitive ratio of randomized algorithms. Specifically, we give a lower bound of k−1 against an oblivious adversary for any k≥3 and any B. Since a deterministic algorithm, as mentioned above, achieves an upper bound of about 10k, this indicates that randomization does not help too much.

Optimal buffer management for 2-frame throughput maximization

We consider a variant of the online buffer management problem in network switches, called the k-frame throughput maximization problem (k-FTM). Large data, called frames, carried on the Internet are split into small k packets by a sender, and the receiver can reconstruct each frame only if he/she accepts all the k constituent packets of the frame. Packets pass through network switches on the Internet, and each switch is equipped with a FIFO buffer to temporarily store arriving packets. Since the size of the buffer is bounded, some packets must be discarded if it is full. It is impossible to reconstruct frames including discarded packets any more. Our goal is to maximize the number of reconstructed frames. Kesselman et al. proposed this problem, and showed that any online algorithm has an unbounded competitive ratio even when k=2. Hence, they considered the “order-respecting” variant of k-FTM. They showed that the competitive ratio of their algorithm is at most (2kB⌊B/k⌋+k) for any B ≥ k, where B is the size of the buffer. Also, they gave a lower bound of B⌊2B/k⌋ on the competitive ratio when 2B ≥ k and k is a power of 2. Furthermore, they proved that the competitive ratio of a greedy algorithm is at most (11+8B−1) for any B ≥ 2 and k=2.We analyze a greedy algorithm for k=2, and show that its competitive ratio is at most 3 for any B, improving the previous upper bound of 4B⌊B/2⌋+2(≥10). Moreover, we show that the competitive ratio of any deterministic algorithm is at least 3 for any B if k=2, which matches our upper bound.

Randomized competitive algorithms for online buffer management in the adaptive adversary model

In the problem of buffer management with bounded delay, packets with weights and deadlines arrive at a network switch over time, and the goal is to send those packets on the outgoing link while maximizing the total weight of the packets that are sent before their deadlines. We present a study of randomized algorithms that are competitive against an adaptive adversary. Previous studies considered only the oblivious adversary model that does not capture dependency of network traffic on the packet scheduling algorithm. We give a new analysis of a previously known algorithm, which shows that it remains e / ( e − 1 ) -competitive even against an adaptive adversary. We complement this with a 4/3 lower bound on the competitive ratio on 2-bounded instances, in which each packet has a lifespan of one or two steps. We also study more restricted 2-uniform instances, in which every packet has a lifespan of exactly two steps. For such instances we give a 1.2 lower bound on the competitive ratio of arbitrary algorithms and 4/3 lower bound on the competitive ratio of memoryless scale-invariant algorithms. Finally, we devise a 4/3-competitive memoryless scale-invariant algorithm for 2-bounded instances, matching two of these lower bounds.

A Tight Upper Bound on Online Buffer Management for Multi-Queue Switches with Bicodal Buffers

The online buffer management problem formulates the problem of queuing policies of network switches supporting QoS (Quality of Service) guarantee. In this paper, we consider one of the most standard models, called multi-queue switches model. In this model, Albers et al. gave a lower bound $\frac{e}{e-1}$, and Azar et al. gave an upper bound $\frac{e}{e-1}$ on the competitive ratio when m, the number of input ports, is large. They are tight, but there still remains a gap for small m. In this paper, we consider the case where m = 2, namely, a switch is equipped with two ports, which is called a bicordal buffer model. We propose an online algorithm called Segmental Greedy Algorithm (SG) and show that its competitive ratio is at most $\frac{16}{13} (\simeq 1.231)$, improving the previous upper bound by $\frac{9}{7} (\simeq 1.286)$. This matches the lower bound given by Schmidt.

A Tight Bound on Online Buffer Management for Two-Port Shared-Memory Switches

The online buffer management problem formulates the problem of queueing policies of network switches supporting QoS (Quality of Service) guarantee. For this problem, several models are considered. In this paper, we focus on shared memory switches with preemption. We prove that the competitive ratio of the Longest Queue Drop (LQD) policy is 4M-4/3M-2 in the case of N = 2, where N is the number of output ports in a switch and M is the size of the buffer. This matches the lower bound given by Hahne, Kesselman and Mansour. Also, in the case of arbitrary N, we improve the competitive ratio of LQD from 2 to 2-1/M minK = 1, 2, ₀, N { ⌊M/K⌋ + K-1}.

An Online Buffer Management Algorithm for QoS-Sensitive Multimedia Networks

In this letter, we propose a new online buffer management algorithm to simultaneously provide diverse multimedia traffic services and enhance network performance. Our online approach exhibits dynamic adaptability and responsiveness to the current traffic conditions in multimedia networks. This approach can provide high buffer utilization and thereby improve packet loss performance at the time of congestion.