Efficient Fair Queueing using Deficit Round Robin

Fair queuing is a technique that allows each flow passing through a network device to have fair share of network resources. previous schemes for fair queuing that achieved nearly perfect fairness were expensive to implement: specifically, the work required to process a packet in these schemes was O(log(n)), where n is the number of active flows. This is expensive at high speeds. On the other hand, cheaper approximations of fair queuing that have been reported in the literature exhibit unfair behavior. In this paper, we describe a new approximation of fair queuing, that we call Deficit Round Robin. Our scheme achieves nearly perfect fairness in terms of throughput, requires only O(1) work to process a packet, and is simple enough to implement in hardware. Deficit Round Robin is also applicable to other scheduling problems where servicing cannot be broken up into smaller units

Heart-like fair queuing algorithms (HLFQA)

We propose a new family of fair, work conserving traffic scheduling mechanisms that imitate the behavior of the human heart in the cardiovascular system. The algorithms have MAX (where MAX is the maximum packet size) fairness and O(log N) complexity and thus compare favorably with existing algorithms. The algorithms are simple enough to be implemented in hardwar

Performance Analysis of QoS in PMP Mode WiMax Networks

IEEE 802.16 standard supports two different topologies: point to multipoint (PMP) and Mesh. In this paper, a QoS mechanism for point to multipoint of IEEE 802.16 and BS scheduler for PMP Mode is proposed. This paper also describes quality of service over WiMAX networks. Average WiMAX delay, Average WiMAX load and Average WiMAX throughput at base station is analyzed and compared by applying different scheduler at Base station and at fixed nodes

Just Queuing: Policy-Based Scheduling Mechanism for Packet Switching Networks

The pervasiveness of the Internet and its applications lead to the potential increment of the users’ demands for more services with economical prices. The diversity of Internet traffic requires some classification and prioritisation since some traffic deserve much attention with less delay and loss compared to others. Current scheduling mechanisms are exposed to the trade-off between three major properties namely fairness, complexity and protection. Therefore, the question remains about how to improve the fairness and protection with less complex implementation. This research is designed to enhance scheduling mechanism by providing sustainability to the fairness and protection properties with simplicity in implementation; and hence higher service quality particularly for real-time applications. Extra elements are applied to the main fairness equation to improve the fairness property. This research adopts the restricted charge policy which imposes the protection of normal user. In terms of the complexity property, genetic algorithm has an advantage in holding the fitness score of the queue in separate storage space which potentially minimises the complexity of the algorithm. The integrity between conceptual, analytical and experimental approach verifies the efficiency of the proposed mechanism. The proposed mechanism is validated by using the emulation and the validation experiments involve real router flow data. The results of the evaluation showed fair bandwidth distribution similar to the popular Weighted Fair Queuing (WFQ) mechanism. Furthermore, better protection was exhibited in the results compared with the WFQ and two other scheduling mechanisms. The complexity of the proposed mechanism reached O(log(n)) which is considered as potentially low. Furthermore, this mechanism is limited to the wired networks and hence future works could improve the mechanism to be adopted in mobile ad-hoc networks or any other wireless networks. Moreover, more improvements could be applied to the proposed mechanism to enhance its deployment in the virtual circuits switching network such as the asynchronous transfer mode networks

Multi-Channel Deficit Round-Robin Scheduling for Hybrid TDM/WDM Optical Networks

In this paper we propose and investigate the performance of a multi-channel scheduling algorithm based on the well-known deficit round-robin (DRR), which we call multi-channel DRR (MCDRR). We extend the original DRR to the case of multiple channels with tunable transmitters and fixed receivers to provide efficient fair queueing in hybrid time division multiplexing (TDM)/wavelength division multiplexing (WDM) optical networks. We take into account the availability of channels and tunable transmitters in extending the DRR and allow the overlap of `rounds' in scheduling to efficiently utilize channels and tunable transmitters. Simulation results show that the proposed MCDRR can provide nearly perfect fairness with ill-behaved flows for different sets of conditions for inter-frame times and frame sizes in hybrid TDM/WDM optical networks with tunable transmitters and fixed receivers

Achieving per-flow Queueing Performance without a per-flow Queue

Recent studies have shown that suitably-designed packet discard policies can dramatically improve the performance of fair queueing mechanisms in internet routers. The Queue State Deficit Round Robin algorithm (QSDRR) preferentially discards from long queues, but in-troduces hysteresis into the discard policy to minimize synchronization among TCP flows. QSDRR provides higher throughput and much better fairness than simpler queueing mech-anisms, such as Tail-Drop, RED and Blue. However, since QSDRR needs to maintain a separate queue for each active flow, there is a legitimate concern that it may be too costly for the highest speed links. In previous studies, we have shown that QSDRR can deliver almost the same performance with one-tenth the number queues as flows, if the flows are evenly distributed across the queues. In this paper, we develop and evaluate a flow dis-tribution algorithm using a Bloom filter architecture with dynamic rebalancing. We show that our algorithm significantly reduces the memory requirement compared to maintaining per-flow state and can achieve near optimal flow distribution. Thus, using this algorithm in conjunction with QSDRR, we can achieve the performance of per-flow queueing at a significantly reduced cost

Multi-resource fairness: Objectives, algorithms and performance

Designing efficient and fair algorithms for sharing multiple resources between heterogeneous demands is becoming increasingly important. Applications include compute clusters shared by multi-task jobs and routers equipped with middleboxes shared by flows of different types. We show that the currently preferred objective of Dominant Resource Fairness has a significantly less favorable efficiency-fairness tradeoff than alternatives like Proportional Fairness and our proposal, Bottleneck Max Fairness. In addition to other desirable properties, these objectives are equally strategyproof in any realistic scenario with dynamic demand