Queue Weight Research Articles

Improving RED algorithm congestion control by using the Markov decision process

Congestion control plays an essential role on the internet to manage overload, which affects data transmission performance. The random early detection (RED) algorithm belongs to active queue management (AQM), which is used to manage internet traffic. The RED is used to eliminate weakness in default control of the Transport Control Protocol (TCP) drop-tail mechanism. The drawback of RED is parameter tuning, while adaptive RED (ARED) automatically adjusts these parameters. In this study, the suggested algorithm, the Markov decision process RED (MDPRED) uses the Markov decision process (MDP) to suitably adapt values for queue weight in the RED algorithm based on average queue length to enhance the performance of the traditional RED during TCP Slow Startup phase. This study is conducted based on fluctuations among the rate of service, queuing weight, and the mean queue length by using open-source network simulator NS3. The study shows efficient results by fluctuating end-to-end packet throughput and fast response to the inception of congestion in the network. The modified algorithm achieves a low level of drop packets by evaluating the results with other five algorithms, which is done by increasing the algorithm’s response when the average queue size becomes close to the maximum queue length threshold.

Active Queue Management in RED Considering Critical Point on Target Queue

The basic philosophy behind RED is to prevent congestion. When the average queue length exceeds the minimum threshold, packets are randomly dropped, or the explicit congestion notification bit is marked. Since network requirements differ significantly, it is not an optimal approach to establish RED parameters with constant value. There is a new algorithm we are proposing called Critical Point on Target Queue (AQM-RED-CPTQ), provide greater congestion management over the network while also preserving the value of RED. To overcome the problem in RED without changing queue weight parameter, we have proposed few models to control the congestion by introducing range parameter with probability and control mechanism which will belong between minimum and maximum threshold. The current queue size is controlled together with average queue size. A new range variable has been introduced to improve the performance of priority queue of existing RED based algorithm which improves the overall performance of networks. For each packet, minimum and maximum threshold has been updated and dropped with probability (Pa) for a special condition. Instead of multiplicative increase and decrease the maximum probability, the scheme uses additive-increase and multiplicative-decrease. Once the AVG queue length is close to the minimum threshold value, our approach automatically sets queue parameter according to queue conditions and handles queuing delay and improve throughput. The simulated results proof that our approaches are better than RED in terms of throughput, end to end delay, packet delivery ratio and goodput.

Weight Queue Dynamic Active Queue Management Algorithm

The current problem of packets generation and transformation around the world is router congestion, which then leads to a decline in the network performance in term of queuing delay (D) and packet loss (PL). The existing active queue management (AQM) algorithms do not optimize the network performance because these algorithms use static techniques for detecting and reacting to congestion at the router buffer. In this paper, a weight queue active queue management (WQDAQM) based on dynamic monitoring and reacting is proposed. Queue weight and the thresholds are dynamically adjusted based on the traffic load. WQDAQM controls the queue within the router buffer by stabilizing the queue weight between two thresholds dynamically. The WQDAQM algorithm is simulated and compared with the existing active queue management algorithms. The results reveal that the proposed method demonstrates better performance in terms mean queue length, D, PL, and dropping probability, compared to gentle random early detection (GRED), dynamic GRED, and stabilized dynamic GRED in both heavy or no-congestion cases. In detail, in a heavy congestion status, the proposed algorithm overperformed dynamic GRED (DGRED) by 13.3%, GRED by 19.2%, stabilized dynamic GRED (SDGRED) by 6.7% in term of mean queue length (mql). In terms of D in a heavy congestion status, the proposed algorithm overperformed DGRED by 13.3%, GRED by 19.3%, SDGRED by 6.3%. As for PL, the proposed algorithm overperformed DGRED by 15.5%, SDGRED by 19.8%, GRED by 86.3% in term of PL.

Resource Allocation and Task Offloading for Heterogeneous Real-Time Tasks With Uncertain Duration Time in a Fog Queueing System

Fog computing has become the primary infrastructure on the Internet for improving the quality of service. We consider a fog queueing system with limited infrastructure resources to accommodate real-time tasks with heterogeneities in task types and execution deadlines. Owing to the uncertain execution duration, such a fog system should jointly consider fog resource allocation and a task offloading to satisfy the deadline requirements. To consider the task heterogeneity, a parallel virtual queue model is applied to buffer each type of task in a separate queue. Subsequently, we use a framework, including three parallel algorithms, namely, offloading, buffering, and resource allocation, to improve resource allocation balance, throughput, and task completion ratio. The task offloading is decided according to the task urgencies in terms of the laxity times, which accounts for the deadline, estimated execution time, and transmission delay to the cloud. The buffering process rearranges the arriving tasks based on their laxity time and the estimated task execution time at the fog tier. The resource allocation uses an adaptive queue weight based on the Lyapunov drift to avoid task starvation that may lead to a long queueing delay for tasks with long execution time. The simulation results indicate that our proposed policies can avoid task starvation and yields a tradeoff between high throughput and a high task completion ratio.

A generic controller for managing TCP transfers in IEEE 802.11 infrastructure WLANs

In this paper, we present a generic controller that ensures fair and efficient operation of IEEE 802.11 infrastructure wireless local area networks (WLANs) with multiple co-channel access points. Our controller addresses performance issues of long-lived TCP transfers in multi-AP WLANs, by overlaying a coarse time-slicing scheduler on top of a cascaded fair queuing scheduler. The time slices and queue weights, used in our controller, are obtained from the solution of a constrained utility optimization formulation. A study of the impact of coarse time-slicing on TCP is also presented in this paper. We also present a methodology to improve the performance of co-existing short-lived and interactive TCP flows. Finally, we report the results of experiments performed on a real testbed, demonstrating the efficacy of our controller.

The HSBQ Algorithm with Triple-play Services for Broadband Hybrid Satellite Constellation Communication System

The HSBQ algorithm is the one of active queue management algorithms, which orders to avoid high packet loss rates and control stable stream queue. That is the problem of calculation of the drop probability for both queue length stability and bandwidth fairness. This paper proposes the HSBQ, which drop the packets before the queues overflow at the gateways, so that the end nodes can respond to the congestion before queue overflow. This algorithm uses the change of the average queue length to adjust the amount by which the mark (or drop) probability is changed. Moreover it adjusts the queue weight, which is used to estimate the average queue length, based on the rate. The results show that HSBQ algorithm could maintain control stable stream queue better than group of congestion metric without flow information algorithm as the rate of hybrid satellite network changing dramatically, as well as the presented empiric evidences demonstrate that the use of HSBQ algorithm offers a better quality of service than the traditionally queue control mechanisms used in hybrid satellite network.

Indirect Load Shaping for CHP Systems Through Real-Time Price Signals

Direct or centralized loading shaping in smart grid has been heavily investigated. However, it is usually not clear how the users are compensated by providing load shaping services. In this paper, we will discuss indirect load shaping in a distributed manner. On one hand, we aim to reduce the users’ energy cost by investigating how to fully utilize the battery pack and the water tank for the combined heat and power (CHP) systems. We first formulate the queueing models for the CHP systems and then propose an algorithm based on the Lyapunov optimization technique, which does not need any statistical information about the system dynamics. The optimal control actions can be obtained by solving a nonconvex optimization problem. We then discuss when it can be converted into a convex optimization problem. Since the CHP battery pack queue and water tank queue are correlated, the capacity relationship between them is further explored considering different queue weights. On the other hand, based on the users’ reaction model, we propose an algorithm with a time complexity of ${O}$ (log ${n}$ ) to determine the real-time price for the power company to effectively coordinate all the CHP systems and provide distributed load shaping services.

Analysis of a queue length aware and latency guaranteed fuzzy-based adaptive resource allocator for WiMAX networks

Escalation of multimedia devices in recent times has prompted human appetite for affluent multimedia applications. The QoS demands of these applications can only be satisfied by more and more powerful networks. WiMAX (Worldwide Interoperability for Microwave Access) networks are best suitable to serve these real-time applications; however, quantity of non-real time and best-effort traffic also cannot be neglected. Fair and efficient distribution of resources is always challenging in these networks and schedulers need to be adaptive and passable in order to guarantee appreciable performance levels. This paper introduces a quality of service mechanism based on concepts of fuzzy logic for scheduling different traffic classes in WiMAX networks. The proposed framework simplifies fair allocation of resources to real as well as non-real-time traffic classes. The scheduling ploy is developed by modifying weighted fair queuing algorithm to work adaptively by changing weights of queues serving real- and non-real-time traffic using fuzzy logic inferencing capabilities. New weights are calculated adaptively and these weights decide amount of bandwidth allocated to a particular traffic class. The proposed system works on three parameters: amount of real- and non-real-time traffic in queues, throughput requirement for non-real-time flows, and latency requirement of real-time data. Efficiency and fairness of proposed method is evaluated by performing versatile experiments and comparisons with established practices. The results obtained as implication of proposed work are quite promising.

Real-time network-wide traffic signal optimization considering long-term green ratios based on expected route flows

We propose a novel real-time network-wide traffic signal control scheme which is (1) applicable under modern data technologies, (2) flexible in response to variations of traffic flows due to its non-cyclic feature, (3) operable on a network-wide and real-time basis, and (4) capable of considering expected route flows in the form of long-term green time ratios for intersection movement. The proposed system has a two-level hierarchical architecture: (1) strategy level and (2) control level. Considering the optimal states for a long-term period found in the strategy level, the optimal signal timings for a short-term period are calculated in the control level which consists of two steps: (1) queue weight update and (2) signal optimization. Based on the ratio of the cumulative green time to the desired green time is the first step to update the queue weights, which are then used in the optimization to find signal timings for minimum total delay. A parametric queue weight function is developed, discussed and evaluated. Two numerical experiments were given. The first demonstrated that the proposed system performs effectively, and the second shows its capability in a real-world network.

A Register Allocation Algorithm Based on Regions Priority

Compiling speed and code quality are two key factors to evaluate the performance of register allocation. Modern Just In Time(JIT) compilers desire the best code in least time. Neither traditional graph coloring algorithm nor linear scan algorithm can satisfy the condition perfectly. A regions priority algorithm is proposed in this paper, which does not pursue the perfect register allocation in theory but takes greedy design method. The program is divided by loop region, on which physical register allocation is implemented by dealing lifetime length priority queue and spill weight priority queue. Then the allocation extends to the whole program. This algorithm creates high quality code in linear time and is applied to the compiler which compiles PTX instructions in SSA to traditional multicore platform. The experiment based on this compiler verifies the effectiveness of the algorithm.

Class-based weighted fair queuing scheduling on quad-priority Delta Networks

Contemporary networks support multiple priorities, aiming to differentiate the quality of service (QoS) levels offered to individual traffic classes. Support for multiple priorities necessitates the introduction of a scheduling algorithm, to select each time the next packet to transmit over the data link. Class-based weighted fair queuing (CBWFQ) scheduling and its variations are widely used as a scheduling technique since it is easy to implement and prevent the low-priority queues from starvation, i.e. receiving no service during periods of high-priority traffic. CBWFQ effectively thus offers low-priority queues, the opportunity to transmit packets even though the high-priority queues are not empty. In this paper, we present the modelling and performance evaluation of a single-buffered, four-priority multistage interconnection network (MIN) operating under the CBWFQ scheduling policy. Performance evaluation is conducted through simulation, and the performance metrics obtained can be used by MIN designers to set the appropriate queue weights according to the expected traffic and the desired QoS levels for each priority class, delivering efficient thus systems.

Research on Dynamic Weight WFQ Algorithm of Wireless Networks

Excellent scheduling algorithms can optimize allocation and improve utilization of wireless resources. To improve QoS of wireless networks, this paper presents a Dynamic Weight-Weight Fair Queuing (DW-WFQ) algorithm with differentiated service that is suited to characteristics of wireless networks based on WFQ algorithm. The proposed algorithm adaptively adjusts the weights of queues according to the dynamical measurement of link state. It can fully make use of limited wireless network resources and improve the overall throughput of network.The simulation experiment results using OPNET software tool demonstrate that the proposed algorithm can improve the network throughput and reduce the average end-to-end delay, compared with WFQ algorithm.

PFWRR: An Enhanced WRR Scheduling Realizing the Proportion Fairness Principle

To realize proportion fairness principle,a scheduling based on Weighted Round Robin(WRR)is proposed,whose name is Proportion Fairness WRR(PFWRR).PFWRR adjusts each queue's weight in terms of the average packet arrival rate to guarantee that the proportion of average queuing delay accords with the differentiation parameters when each queue's length is smaller than or equals to its buffer length and the proportion of average packet loss rate accords with the differentiation parameters when the system begins to drop packets.The computation load of PFWRR is reasonable because it renews each queue's weight only when the system is overloaded and the average packet arrival rate changes.The experiment shows that PFWRR can realize the average queuing delay proportion fairness principle when the system is overloaded but do not drop packets and the average packet loss rate proportion fairness principle when packet loss happens in the system.

Multi-scale analysis of generalised processor sharing queues with long-range-dependent traffic inputs and variable service rates

An analytical technique is provided to estimate queue-length and delay distributions for multi-queue systems using generalised processor sharing discipline with time-correlated variable service rates, based on two-dimensional multi-level decoupling. First, temporal decomposition is used to convert the time-correlated queuing problem into a set of sub-problems over several timescales. Subsequently, queue decomposition exploits the queue weight dependencies to convert a multi-queue problem into a set of single-queue problems. The core of the analysis lies in estimating the multi-scale service rate models for each of these queues. The authors show the hierarchy of this estimation and the dependency of the queue service rate on the unused capacity of the other queues and their weights. Simulation and analytical results on queue and delay survivor functions are in good agreement.

DESIGN AND PERFORMANCE EVALUATION OF A FUZZY-BASED TRAFFIC CONDITIONER FOR MOBILE AD HOC NETWORKS

A mobile ad hoc network is a collection of mobile hosts forming a temporary network on the fly, without using any fixed infrastructure. Characteristics of mobile ad hoc networks such as lack of central coordination, mobility of hosts, dynamically varying network topology, and limited availability of resources make QoS provisioning very challenging in such networks. In this paper, we introduce a fuzzy QoS traffic conditioner for mobile ad hoc networks. The proposed traffic conditioner consists of fuzzy admission control (FAC), fuzzy traffic rate controller (FTRC), and fuzzy scheduler (FS). The proposed FAC monitors the delay and available bandwidth and decides whether to accept or reject the request. The FTRC uses the additive increase multiplicative decrease (AIMD) rate control algorithm as a base, in which a node increments its transmission rate when the observed delay is below the predefined threshold, with an increment rate of c Kbps and decreases its transmission rate by r% when the delay passes the threshold. FTRC accepts the packet delay and the "delay-threshold d" as inputs and calculates c and r by using a set of fuzzy rules. The third part of the proposed traffic conditioner is FS, which is based on the traditional weighted round robin (WRR) mechanism. FS monitors the packet drop and delay of each queue and adjusts the queue weights by using a fuzzy inference engine.

A probabilistic constrained nonlinear optimization framework to optimize RED parameters

The random early detection (RED) technique has seen a lot of research over the years. However, the functional relationship between RED performance and its parameters viz., queue weight ( w q ), marking probability ( max p ), minimum threshold ( min t h ) and maximum threshold ( max t h ) is not analytically available. In this paper, we formulate a probabilistic constrained optimization problem by assuming a nonlinear relationship between the RED average queue length and its parameters. This problem involves all the RED parameters as the variables of the optimization problem. We use the barrier and the penalty function approaches for its solution. However (as above), the exact functional relationship between the barrier and penalty objective functions and the optimization variable is not known, but noisy samples of these are available for different parameter values. Thus, for obtaining the gradient and Hessian of the objective, we use certain recently developed simultaneous perturbation stochastic approximation (SPSA) based estimates of these. We propose two four-timescale stochastic approximation algorithms based on certain modified second-order SPSA updates for finding the optimum RED parameters. We present the results of detailed simulation experiments conducted over different network topologies and network/traffic conditions/settings, comparing the performance of our algorithms with variants of RED and a few other well known adaptive queue management (AQM) techniques discussed in the literature.

STUDY OF MOBILITY AND QoS OF 802.11 AND 802.11e WIRELESS LAN STANDARDS

Quality of service (QoS) is a key problem in wireless environments where bandwidth is scarce and channel conditions are time varying and sometimes implies highly packet losses. IEEE 802.11b/g/a wireless LAN (WLAN) are the most widely used WLAN standards today, and the IEEE 802.11e QoS enhancement standard exists and introduces QoS support for multimedia applications. This paper presents a class based admission control algorithm for 802.11e based wireless local area networks . The strengths of our admission control is dynamicity and flexibility of the algorithm, which adapts to the situation of the BSS, like global load, number of best effort AC, and position of QSTA by report of QAP. Thus it achieves higher throughput than other admission control for 802.11 e. A summary of many good solutions on admission control for 802.11e is be done, and the model of our admission control is presented. The 802.11e standard starves the low priority traffic in case of high load, and leads to higher collision rates, and did not make a good estimate of weight of queues, so there is an unbalance enters the flows with high priorities. A discussion is presented in detail using simulation-based evaluations, with an aim of comparing results of our admission control algorithm, with the 802.11e standard and the FHCF algorithm. Results reveal an improvement of the network load and a decrease of the number of collisions.

Stability of a frame-based oldest-cell-first maximal weight matching algorithm

Input-queued cell switches employing the oldest-cell-first (OCF) policy have been shown to yield low mean delay characteristics. Moreover, it has been proven that OCF is stable for admissible traffic conditions when executed with a scheduling speedup of 2. However, as link speeds increase, the computational complexity of these algorithms limits their applicability in high port-density switches and routers. To address the scalability issue, we describe a Frame-Based Maximal Weight Matching (FMWM) algorithm, employing OCF as queue weights, in which a new scheduling decision is issued once every several cell times. Between scheduling decisions, the configuration of the crossbar switch remains unchanged. We further extend the analysis to address the case of multiple classes of service, and prove that the algorithm is stable with an internal buffer transfer speedup of 2, thereby significantly relaxing the timing constraints imposed on the scheduling process.

A weightiest Scheduling Based on Queue Length and Queue Delay Restriction for Asynchronous Optical Packet Switch

Packet scheduling plays an important role in the asynchronous optical switched node. An intelligence scheduling algorithm can reduce packet loss probability and increase the throughput to guarantee the quality of service. A weighted scheduling algorithm based on the queue length associated with waiting delay restriction was proposed to solve the problem of packet queue starvation and time delay. The work has contributed with a much powerful scheduling mechanism which reduces resource contention at the asynchronous OPS core nodes and guarantees a reasonable packet delay thanks to its weighted scheduling algorithm based on queue length and waiting delay for variable length OPS network. The scheduler calculates every input port with NxK virtual output queue (VOQ) weight and schedules the maximal weight queue packets to available output channel. The analysis and simulation results show that the proposed scheduling has high throughput and low packet loss ratio.

A State Dependent RED: An Enhanced Active Queue Management Scheme for Real-Time Internet Services

This paper introduces a State Dependent Random Early Detection (SDRED) scheme that can improve delay and jitter performances by adjusting RED parameters such as max th and w q according to queue status. The SDRED is designed to adapt to traffic conditions by adjusting the maximum threshold and queue weight to four different levels. From the simulation results, we show that the SDRED decreases queuing delay and has more stable jitter characteristics than the existing RED, BLUE, ARED and DSRED schemes.