Controllable fair queuing for meeting performance goals

Although weighted fair queueing (WFQ) has been regarded as an ideal scheduling algorithm in terms of its combined delay bound and proportional fairness properties, its asymptotic time complexity increases linearly with the number of sessions serviced by the scheduler, thus limiting its use in high-speed networks. An algorithm that combines the delay and fairness bounds of WFQ with O(1) timestamp computations had remained elusive so far. In this paper we present two novel scheduling algorithms that have O(1) complexity for timestamp computations and provide the same bounds on end-to-end delay and buffer requirements as those of WFQ. The first algorithm, frame-based fair queueing (FFQ), uses a framing mechanism to periodically recalibrate a global variable tracking the progress of work in the system, limiting any short-term unfairness to within a frame period. The second algorithm, starting potential based fair queueing (SPFQ), performs the recalibration at packet boundaries, resulting in improved fairness while still maintaining the O(1) timestamp computations. Both algorithms are based on the general framework of rate-proportional servers (RPSs) introduced by Stiliadis and Varma (see ibid., vol.6, no.2, p.164-74, 1998). The algorithms may be used in both general packet networks with variable packet sizes and in asynchronous transfer mode (ATM) networks.

Weighted Fair Queuing (WFQ) is a packet scheduling technique allowing guaranteed bandwidth services. However, it is very difficult to implement the WFQ for a lot of queues, because the amount of required calculations for WFQ is proportional to the number of queues. Therefore we proposed the simplified WFQ (SWFQ) mechanism which can support a huge number of queues with guaranteeing the provisioned bandwidth for each queue while it requires fewer amounts of calculations by using approximation techniques. To compare the details of SWFQ and WFQ, a series of simulations are conducted. The result of the simulation shows that SWFQ can guarantee the bandwidth for each queue as same as WFQ and also shows that the difference between WFQ and SWFQ can be negligible when the granularity of the quantization for an approximation is sufficiently fine. In conclusion, these results clarify that SWFQ is an effective mechanism which can provide the same characteristics as WFQ.

We describe an efficient fair queuing scheme, leap forward virtual clock, that provides end-to-end delay bounds similar to weighted fair queuing (WFQ), along with throughput fairness. Our scheme can be implemented with a worst-case time O(loglogN) per packet (inclusive of sorting costs), which improves upon all previously known schemes that guarantee delay and throughput fairness similar to WFQ. Interestingly, both the classical virtual clock and the self-clocked fair queuing schemes can be thought of as special cases of our scheme, by setting the leap forward parameter appropriately.

Self-Clocked Fair Queueing (SCFQ) algorithm has been considered as an attractive packet scheduling algorithm because of its implementation simplicity, but it has unbounded delay property in some input traffic conditions. In this paper, we propose a Rate Proportional SCFQ (RP-SCFQ) algorithm which is a rate proportional version of SCFQ. If any fair queueing algorithm can be categorized into the rate proportional class and input is constrained by a leaky bucket, its delay is bounded and the same as that of Weighted Fair Queueing (WFQ) which is known as an optimal fair queueing algorithm. RP-SCFQ calculates the timestamps of packets arriving during the transmission of a packet using the current value of system potential updated at every packet departing instant and uses a starting potential when it updates the system potential. By doing so, RP-SCFQ can have the rate proportional property. RP-SCFQ is appropriate for high-speed packet-switched networks since its implementation complexity is low while it guarantees the bounded delay even in the worst-case input traffic conditions.

The ongoing evolution towards the generalization of wireless access to multi-service networks stresses on the need for optimizing the control of radio resources and in particular, for designing efficient scheduling approaches. The scheduling mechanisms proposed for wireline links do not carry over to wireless interfaces due to the variability of radio links capacity. Efficient schedulers for the radio channel have to take into account information relative to the channel state when allocating resources to the various connected equipments. For the case of delay tolerant traffic, the scheduler may take advantage of terminals diversity. We propose in this paper a modified version of the weighted fair queueing (WFQ) algorithm, termed OWFQ (opportunistic WFQ), that notably increases the average system performance through opportunistic scheduling while fulfilling users' QoS needs in terms of minimum realized throughput.

Fair and Delay Adaptive Scheduler (FDAS) is a scheduling mechanism that dynamically adapts to the incoming traffic flows' requirements in term of bandwidth allocation, delay bounds and packet loss restrictions. It performs this utilizing both virtual finish time fluid scheduling along with schedulability and delay sensitive scheduling. The former ensures that the flows receive a fair share of the available output throughput while the later ensures that time critical flows that are about to expire will receive preferential treatment when needed to avoid getting garbled and dropped when possible. FDAS tries to maximize the satisfaction as perceived by incoming traffic flows through balancing between bandwidth fairness and delay bound accommodation. FDAS acts as a hybrid scheduler that tries to overcome fairness allocation problems due to preferential treatment for the soon-to-expire packets which happens in Earliest Deadline First (EDF) schedulers. Meanwhile, it tries to minimize the number of packets that violate their deadlines for transmission and get garbled accordingly that happens on Weighted Fair Queuing (WFQ) and its derivatives. In this paper, we try to answer the question of how many of the flows and how much of their traffic can be accommodated in terms of delay bound and throughput requirements given the incoming mixture of traffic with diverse QoS requirements. FDAS preliminary modeling and optimization is discussed in this paper to answer the above question in a manner that maximizes the overall performance satisfaction as perceived by incoming flows taking into consideration traffic priorities, if any.

In our previous work, we proposed the TNPOSS (To Next-hop Port Sequence Switch) network which can achieve scalable fast forwarding and is suitable for delivering multimedia flows. However, TNPOSS network has no Quality of Service (QoS) tools to provide better QoS guarantee for multimedia flows which often have long-range dependence (LRD) property. To enhance the QoS ability of TNPOSS network, this paper proposes a QoS-enhanced TNPOSS (QTNPOSS) network model by introducing Fractal Leak Bucket (FLB) shaper and Weighted Fair Queuing (WFQ) scheduler into the original TNPOSS network. In the new QTNPOSS network, each packet of multimedia flows is shaped by the FLB when arriving at a node and is scheduled by the WFQ before being outputted. Based on study above, we further analyze the end-to-end (E2E) delay bound of QTNPOSS network by means of the network calculus theory which is an effective mathematical tool on analyzing the worst-case QoS performances of networks. The service curve and the formulation of E2E delay bound of QTNPOSS network are presented and proved. Extensive numerical experiments show that both the LRD property of multimedia flows and the WFQ weight have influences on the E2E delay bound, and the WFQ weight influences the E2E delay bound more greatly than the LRD property does.

인터넷 전화, 인터넷 방송 VPN(Virtual Private Networks), 멀티미디어 서비스 등의 실시간 혹은 대역폭 요구 서비스 등의 실시간 혹은 대역폭 요구 서비스들이 늘어남에 따라 인터넷에서도 서비스 품질(QoS : Quality of Service)에 대한 요구가 중요한 문제가 되었다. 인터넷 응용 서비스의 품질을 보장하기 위하여 통합 서비스, 차등 서비스, 그리고 MIPLS(Multi-Protocol Label Switching) 등의 여러 가지 방안이 강구되고 있다. 본 논문에서는 차등 서비스(DiffServ : Diferentiated Service)를 이용한 QoS 보장 기법의 성능 해석에 대하여 기술하였다. 차등 서비스의 성능이 다양한 입력 트래픽 모델과 WFQ(Weighted Fair Queueing) 가중치에 의하여 어떻게 영향을 받는지 분석하기 위하여, 랜덤, 버스티, 자기유사 입력 트래픽 모델과 다양한 입력 파리미터에 대하여 모의실험과 성능평가를 수행하였다. 성능분석 결과, 사용된 입력 트래픽 모델에 따라 패킷 지연 rqkt과 손실 사이에 상당한 차이가 발생함을 확인할 수 있었다. 그러나, 모든 입력 트래픽 상황에서, EF(Expedited Forwarding)의 성능은 보장이 가능하고, EF와 BE(Best Effort) 클래스의 서비스가 분리가 가능한 것으로 나타났다. 다음으로 성능 합성(Performance Synthesis) 문제에 대하여 기술하였다. 차등 서비스 망에 대한 보존법칙을 유도하고, WFQ 방식에서 자원의 분배(즉, 가중치)에 따른 성능 변화와 동적 행위에 대하여 분석하였다. The requirement for QoS (Quality of Service) has become an important Issue as real-time or high bandwidth services are increasing, such as Internet Telephony, Internet broadcasting, and multimedia service etc. In order to guarantee the QoS of Internet application services, several approaches are being sought including IntServ (Integrated Service) DiffServ(Differentiated Srvices), and MPLS(Multi-Protocol Label Switching). In this paper, we describe the performance analysis of QoS guarantee mechanism using the DiffServ. To analyze how the DiffServ performance was affected by diverse input traffic models and the weight value in WFQ(Weighted Fair Queueing), we simulated and performed performance evaluation under a random, bursty, and self-similar input traffic models and for diverse input parameters. leased on the results of performance analysis, it was confirmed that significant difference exist in packet delay and loss depending on the input traffic models used. However, it was revealed that QoS guarantee is possible to the EF (expedited Forwarding) class and the service separation between RF and BE (Best Effort) classes may also be achieved. Next, we discussed the performance synthesis problem. (i. e. derived the conservation laws for a DiffServ networks, and analysed the performance variation and dynamic behavior based on the resource allocation (i.e., weight value) in WFQ.

The paper presents the simulation results of the comparison of two Fair Queuing (FQ) based QSD (Queue scheduling discipline) algorithms with Weighted Round Robin (WRR). We propose the comparison of Weighted Fair Queuing (WFQ), Worst-case Fair Weighted Fair Queuing+ (WF2Q+) with WRR from the point of their usage in modern convergated telecommunication networks.

Low latency and efficient packet scheduling for streaming applications

Design and performance evaluation of a fuzzy based traffic conditioner for differentiated services

Chapter 14 - Scheduling packets

In this paper, we study fair scheduling in ad hoc networks, accounting for channel errors. Since wireless channels are susceptible to failures, to ensure fairness it may be necessary to compensate those flows with error-prone channels. Existing compensation mechanisms need the support of base stations and only work for one-hop wireless channels. Therefore, they are not suitable for multihop wireless networks. Existing fair scheduling protocols for ad hoc networks can be classified into timestamp-based and credit-based approaches. None of them takes channel errors into account. In this paper, we investigate the compensation issue of fair scheduling and propose a timestamp-based fair scheduling mechanism for multihop mobile ad hoc networks, called timestamp-based compensation protocol (TBCP). We evaluate the performance of the proposed mechanism by simulation and also analyze its long-term throughput. The results show that our analytical result provides accurate approximation for the proposed mechanism.

Wireless Sensor Networks (WSNs) comprise sensor and actuator nodes that either generate or consume data. These end devices typically have limited memory, energy, and computational capacity, making them ill-suited for intensive processing tasks. Edge computing addresses this limitation by offloading data collection, processing, and forwarding to edge nodes with greater resources. This architecture aligns well with WSNs, but efficient allocation of edge resources remains a significant challenge, particularly under node mobility and fluctuating traffic. The resource allocation problem at the edge is NP-hard, and while static solutions exist, they often fail under dynamic network conditions. Memory management for packet queues is especially critical. The scheduling and dropping policies at edge nodes directly influence Quality of Service (QoS). Weighted Fair Queuing (WFQ), a popular scheduling method, assigns different weights to traffic classes, affecting uplink bandwidth distribution. However, bursty data, varying packet sizes, and node mobility complicate fair and efficient weight assignment. This study proposes a federated learning-based framework for dynamic queue and bandwidth allocation in mobile WSNs. The model adapts to real-time changes in traffic and topology while reducing communication overhead. Simulation outcomes demonstrate improved resource utilization and network performance, validating the effectiveness of the proposed approach in dynamic WSN environments.

The paper considers both the basic mechanisms of queue management on the router and the principle of their operation. A comparative analysis of the following queuing mechanisms: FIFO (First-In First-Out), CQ (Custom Queuing), PQ (Priority Queuing), WFQ (Weighted Fair Queuing), CBWFQ (Class Based Weighted Fair Queuing) and LLQ (Low Latency Queuing) based on a number of parameters such as traffic volume, traffic type, service of mixed traffic, enable on router and number of queues was made. The results of analysis showed that each of the queuing mechanisms has its advantages when dealing with certain types of traffic. Whereas in the process of load balancing several interfaces of the router are involved simultaneously the choice of queuing mechanism on each of them will depend on QoS for real-time traffic. Thus in this work the effect of various queue management mechanisms (such as FIFO, PQ, CQ, WFQ, LLQ) to QoS for real-time traffic in the process of load balancing on the router in an IP network was also investigated. The simulation results showed that most of queuing mechanisms (except FIFO and CQ) in the process of load balancing allowed to provide high QoS for real time traffic by reducing the values of delays and jitter and a significant reduction of lost packets for such traffic flows. At the same time the results showed that in the load balancing process, the most efficient queues servicing mechanism is LLQ, which provides the lowest delay for VoIP and the end to-end delay commensurable with the PQ mechanism for video traffic.