A Combined Low Latency and Weighted Fair Queuing Based Scheduling of an Input-Queued Switch

Abstract

Input queuing has become dominant and popular building blocks for high speed crossbar switches with many ports and fast line rates because they require minimum speed-up of memory bandwidth. Input Queued switches with finite Virtual Output Queues guarantees QoS performance in terms of throughput and average delay. A switch performs two functions Queuing and Scheduling. Queue Management algorithm manages the size of the queues and drops packets when necessary or appropriate. Scheduling algorithms determine next packet to transfer and solves conflicts with the switching fabric. Fairness and Starvation are another two properties of IQ switches and it is analyzed in finite VOQ in this works. Fairness performs fair allocation of bandwidth among flows and prevents flows from misbehaving flows. Starvation of VOQ prevents serving High priority queue. The motivation behind this study is to schedule the HoL packets queued in finite VOQs by Framing with Low Latency Queuing (LLQ) and Weighted Fair Queueing (WFQ). This queueing technique of VOQ is measured in terms of throughput and average delay by fair allocation of bandwidth with WFQ and Starvation-free queue with LLQ.

A Design of Packet Scheduling Algorithm to Enhance QoS in High-Speed Downlink Packet Access (HSDPA) Core Network

“…In previous work [12,14] to get QoS in end-to end HSDPA Network, focuses on customized mapping of video and voice communication but do not pay attention to other traffic classes of HSDPA. The scheduling algorithm Weighted Fair Queue (WFQ) and Priority Queue (PQ) have combined in the paper [9], resulting the video conferencing delay was reduced but www.ijacsa.thesai.org the voice traffic delay was increased. For provisioning of QoS in HSDPA network, a project of SEACORN [16] has contributed into implementation and development of Radio Resource Management (RRM).…”

Weighted Priority Queuing: A New Scheduling Strategy for Web Services

“…Then, WFQ arranges requests in the ascending order of the virtual finish time [4]. This can guarantee that each queue gets its shares of bandwidth in a proportional way to the allocated weights [14]. The WFQ algorithm is a little bit complex due to the necessary calculation procedure which requires the server to save a significant amount of data.…”