Time-varying fair queuing scheduling for multicode CDMA based on dynamic programming

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.

Scarcity of bandwidth for fixed allocation of frequency and also current growth trends in wireless communications shows that Cognitive Radio Networks (CRNs) are followed strictly. Fluctuating nature of the radio spectrum with a variety of quality services which needs causes some challenges in CRNs, such as spectrum sharing. In many previous works, the problem of performance loss is seen due to the sudden presence of primary user. In such a situation, secondary user has to vacate bandwidth at the moment. This often leads to long wait for secondary user on access the channel. However, Spectrum Pooling concept is used with the ability of secondary utility for licensed frequency band, without reducing quality of service and without requiring new hardware. In this paper, a fair queuing algorithm with weighting and prioritization between different users is recommended. This type of queuing model with weighted fair queuing policy is efficient to share the bandwidth among systems with different priority levels. The proposed algorithm offers shared use of spectrum to invest a fair sharing of bandwidth between cognitive users. The proposed model involves a different service rates for unlicensed users and can be used as an acceptable model in heterogeneous networks. By the use of analytical and simulation results, we can achieve a desirable level of performance and an improvement in fairness.

Fair queueing algorithms based on Generalized Processor Sharing (GPS) provide sessions with instantaneous fair sharing of server capacity, as well as guaranteed service rate and delay. The instantaneous fair sharing distributes server capacity to currently back-logged sessions in proportion to their weights regardless of the amount of service that the sessions received in the past. From a long-term perspective, however, this type of sharing leads to a different quality of service to sessions even if they have the same weight, since it provides only the instantaneous capacity sharing without considering the accumulated service delay and bandwidth. To minimize such long-term unfairness, we propose a delay and bandwidth normalized scheduling model in which the concept of Value of Service (VoS) is defined from the aspects of both delay and bandwidth. Performance comparisons between the proposed algorithm and traditional fair queueing algorithms show that the proposed algorithm provides better long-term fairness among sessions and is more adaptive to sessions with dynamic traffic patterns without compromising the guarantees of service rate and delay.

We present Start-time Fair Queuing (SFQ) algorithm that is computationally efficient, achieves fairness regardless of variation in a server capacity, and has the smallest fairness measure among all known fair scheduling algorithms. We analyze its throughput, single server delay, and end-to-end delay guarantee for variable rate Fluctuation Constrained (FC) and Exponentially Bounded Fluctuation (EBF) servers. We show that SFQ is better suited than Weighted Fair Queuing for integrated services networks and it is strictly better than Self Clocked Fair Queuing. To support heterogeneous services and multiple protocol families in integrated services networks, we present a hierarchical SFQ scheduler and derive its performance bounds. Our analysis demonstrates that SFQ is suitable for integrated services networks since it: (1) achieves low average as well as maximum delay for low-throughput applications (e.g., interactive audio, telnet, etc.); (2) provides fairness which is desirable for VBR video; (3) provides fairness, regardless of variation in a server capacity, for throughput-intensive, flow-controlled data applications; (4) enables hierarchical link sharing which is desirable for managing heterogeneity; and (5) is computationally efficient.

The Internet is facing two problems simultaneously: there is a need for a faster switching/routing infrastructure and a need to introduce guaranteed qualities-of-service (QoS). Each problem can be solved independently: high performance routers can be made faster by using input-queued crossbars instead of shared memory systems; QoS can be provided using packet fair queueing (PFQ) algorithms. Until now, however, the two solutions have been mutually exclusive-all of the work on PFQ algorithms has required that routers use output-queueing or centralized shared memory. In this paper, we design and implement a packet scheduling algorithm, DF/sup 2/Q (distributed feedback fair queueing), on the basis of CIOQ (combined input output queueing) architecture. The most important feature of this scheduling algorithm is the introduction of a feedback mechanism. We analyze and discuss the performance of DF/sup 2/Q, and the experimental results show that it can avoid internal congestion effectively and improve the efficiency of resource utilization.

For pt.I see ibid., p.509-18 (1997). The total implementation complexity of cell schedulers which aim at approximating the generalized processor sharing (GPS) policy is the combination of the complexity of their system-potential function and the complexity involved in sorting the timestamps in order to select the cell with minimum timestamp for transmission. Given that several scheduling algorithms which use a system-potential function of O(1) complexity have been introduced (among them, the minimum-delay self-clocked fair queueing (MD-SCFQ) algorithm achieves optimal delay and excellent fairness properties), the major contribution to the total complexity comes from the task of sorting the timestamps every time a cell is transmitted or received, which is common to all GPS-related schedulers. In this paper, we present a technique, called the logarithmic calendar queue (LCQ), that can achieve a dramatic reduction of the implementation complexity of a GPS-related scheduler, at the cost of a very small and controllable degradation of the delay bounds. We then use the LCQ to implement MD-SCFQ with reduced complexity. By applying the general methodology for the delay analysis presented in the first part of this paper (Chiussi et al. 1997), we are able to provide a closed-form expression of the delay bounds as a function of the LCQ design parameters, which can be used to optimize the design. The LCQ is not exclusively related to MD-SCFQ, but can be applied to any GPS-related scheduler to simplify implementation complexity.

Fair scheduling or Fair Queueing (FQ) algorithms have received much attention in recent years because of their ability to provide a wide range of Quality-ofService (QoS) guarantees to end users. In this paper, we present a new analysis method that can statistically model such fair scheduling algorithms under Poisson arrivals and a general packet length distribution. We coin the new term M/G/FQ to describe this analysis method, which fits a broad range of scheduling policies including WFQ, SCFQ, SFQ and SPFQ.

In order to address the challenge of providing quality of service guarantees in today's network processing systems, the use of efficient scheduling algorithms is required. The efficiency of a scheduler is determined by several factors including its fairness, capability to operate at high speeds, as well as the resources required for its implementation. We present an architecture to support fair scheduling (gigabit FS) considering variable length packets (i. e. for packet forwarding/switching networks) over gigabit links. This high speed scheduler is designed to manage 32 K flows based on an algorithm that yields efficient implementation in hardware by avoiding the complexity of computing the system virtual time function that many packet fair queueing (PFQ) algorithms have proposed. Further, we demonstrate the critical factors in designing an effective scheduling engine at gigabit rates and we present several enhancements together with their associated cost.

Wireless planar networks have been used to model wireless networks in a tradition that dates back to 1961 to the work of E. N. Gilbert. Indeed, the study of connected components in wireless networks was the motivation for his pioneering work that spawned the modern field of continuum percolation theory. Given that node locations in wireless networks are not known, random planar modeling can be used to provide preliminary assessments of important quantities such as range, number of neighbors, power consumption, and connectivity, and issues such as spatial reuse and capacity. In this paper, the problem of connectivity based on nearest neighbors is addressed. The exact threshold function for /spl theta/-coverage is found for wireless networks modeled as n points uniformly distributed in a unit square, with every node connecting to its /spl phi//sub n/ nearest neighbors. A network is called /spl theta/-covered if every node, except those near the boundary, can find one of its /spl phi//sub n/ nearest neighbors in any sector of angle /spl theta/. For all /spl theta//spl isin/(0,2/spl pi/), if /spl phi//sub n/=(1+/spl delta/)log/sub 2/spl pi//2/spl pi/-/spl theta//n, it is shown that the probability of /spl theta/-coverage goes to one as n goes to infinity, for any /spl delta/>0; on the other hand, if /spl phi//sub n/=(1-/spl delta/)log/sub 2/spl pi//2/spl pi/-/spl theta//n, the probability of /spl theta/-coverage goes to zero. This sharp characterization of /spl theta/-coverage is used to show, via further geometric arguments, that the network will be connected with probability approaching one if /spl phi//sub n/=(1+/spl delta/)log/sub 2/n. Connections between these results and the performance analysis of wireless networks, especially for routing and topology control algorithms, are discussed.

Packet scheduling constitutes the core problem in efficient fair allocation of bandwidth to competing flows. To date, numerous algorithms for packet scheduling have been suggested and tested. However, only a few of them are currently deployed. One of the key reasons for rarity of applied packet scheduling methods lies in the complexity of their implementation. This paper describes a family of randomized algorithms for packet scheduling. These algorithms are simple to implement and require small amounts of computation time. Specifically we present an O(1) probabilistic weighted fair queuing algorithm that emits packets from flows with an improved delay jitter. Experimental results of the proposed randomized algorithms suggest that the randomized approach is a viable alternative to the currently deployed deterministic fair queuing algorithms.

Admission control in Flow-Aware Networking (FAN) architectures under GridFTP traffic

Fair scheduling algorithms have been proposed to tackle the problem of bursty and location-dependent errors in wireless packet networks. Most of those algorithms ensure the fairness property and guarantee the QoS of all sessions in a large-scale cellular network such as GSM or GPRS. In this paper, we propose the Weighted-Sacrificing Fair Queueing (WSFQ) scheduling algorithm for small-area and device-limited wireless networks. WSFQ slows down the growth of queue length in limited-buffer devices, still maintains the properties of fairness, and guarantees the throughputs of the system. Moreover, WSFQ can easily adapt itself to various kinds of traffic load. We also implement a packet-based scheduling algorithm, the Packetized Weighted Sacrificing Fair Queueing (PWSFQ), to approach the WSFQ. WSFQ and PWSFQ are evaluated by comparing with other algorithms by mathematical analysis and simulations.

Below the Media Access Control (MAC) layer is the Physical (PHY) layer which deals with the actual transmission of the bits received from the MAC layer above into electromagnetic signals. This layer is optimized to implore power management in wireless networks. Power management is a crucial issue in wireless and mobile networks. In this paper, we propose an Adaptive Context-Aware Rate Selection (ACARS) algorithm to handle the issue of power consumption in wireless networks. This algorithm is implemented by optimizing the PHY layer to transmit efficiently as the number of nodes changes and we estimate the Signal-to-Noise Ratio (SNR) to the PHY layer. Results show that by using the appropriate power management technique, ACARS is reliable and efficient for power consumption in wireless networks which is a high demand for vehicular networks.

Distributed fair queueing in shared-medium ad hoc wireless networks is non-trivial because of the unique design challenges in such networks, such as location-dependent contention, distributed nature of ad hoc fair queueing, channel spatial reuse, and scalability in the presence of node mobility. In this paper, we seek to devise new distributed, localized, scalable and efficient solutions to this problem. We first analyze an ideal centralized fair queueing algorithm developed for ad hoc networks, and extract the desired global properties that the localized algorithms should possess. We then propose three localized fair queueing models, in which local schedulers self-coordinate their local interactions and collectively achieve the desired global properties. We further describe a novel implementation of the proposed models within the framework of the popular CSMA/CA paradigm and address several practical issues. Our simulations and analysis demonstrate the effectiveness of our proposed design.

In the paper, we propose a media access framework for supporting integrated including the real-time service, the controlled load service, and the best effort in wireless networks. Three medium access mechanisms, the Multi-classes fair scheduling, the Single-class fair scheduling + DCF, and the Single-class fair scheduling + DCF with threshold for controlled load service are proposed in the paper to manage the traffic within a piconet. Moreover, a measurement based admission control algorithm is proposed to guarantee the QoS requirements for the requests. We compare the performance of the proposed access mechanisms by conducting simulations. The simulation results show that the Multi-classes fair scheduling mechanism is the best choice for the networks occupied by the real-time service; the Single-class fair scheduling + DCF with threshold for controlled service mechanism is the best for controlled in general case.