Traffic Arrival Patterns Research Articles

On Sample-Path Optimal Dynamic Scheduling for Sum-Queue Minimization in Forests

We investigate the problem of minimizing the sum of the queue lengths of all the nodes in a wireless network with a forest topology. Each packet is destined to one of the roots (sinks) of the forest. We consider a time-slotted system and a primary (or one-hop) interference model. We characterize the existence of causal sample-path optimal scheduling policies for this network topology under this interference model. A causal sample-path optimal scheduling policy is one for which at each time-slot, and for any sample-path traffic arrival pattern, the sum of the queue lengths of all the nodes in the network is minimum among all policies. We show that such policies exist in restricted forest structures, and that for any other forest structure, there exists a traffic arrival pattern for which no causal sample-path optimal policy can exist. Surprisingly, we show that many forest structures for which such policies exist can be scheduled by converting the structure into an equivalent linear network and scheduling the equivalent linear network according to the one-hop interference model. The nonexistence of such policies in many forest structures underscores the inherent limitation of using sample-path optimality as a performance metric and necessitates the need to study other (relatively) weaker metrics of delay performance.

Optimal rate allocation in wireless networks with delay constraints

The optimal rate allocation problem with end-to-end delay constraints in wireless networks is highly challenging due to the dynamics incurred by delay related factors, such as traffic arrival pattern, queuing process, and wireless resource sharing mechanism. In this paper, we solve the problem through a utility maximization framework with two sets of constraints: (1) capacity and schedulability constraints and (2) end-to-end delay constraints. The end-to-end delay of a flow can be adjusted by controlling the per-link delays via a novel parameter called Virtual Link Capacity Margin (VLCM), which is the measurement of the gap between the schedulable link capacity and the maximum allowable flow rate over a link.This optimization problem can be solved via its dual decomposition through two prices derived with regard to the constraints: the link congestion price that reflects the relationship between the traffic load and the capacity of a link, and the flow delay price that reflects the margin between the average packet delay and the delay constraint of a flow. We prove that the algorithm converges to the optimal solution under the M/M/1 queuing model. We have also discussed using our algorithm under generalized traffic patterns, where we use link delay functions to formulate the relationship between VLCM and the average link delay. The algorithm is implemented distributedly via joint wireless link scheduling, VLCM adjustment and congestion control. Extensive experiments are conducted over diverse network topologies and traffic arrival models. The experimental results show that our algorithm is able to achieve optimal rate allocation while satisfying the end-to-end delay constraints.

Load-balanced differentiated services support switch

How to provide quality of service (QoS) guarantees in the routing and switching devices has become one of the key research topics in the areas of routing and switching technologies. Differentiated services architecture (DiffServ), which forwards packets based on their per-hop behaviours, is known as a promising way for supporting QoS in a high-speed backbone network scenario. Motivated by the load-balanced Birkhoff-von Neumann switch, which has received much attention recently because of its outstanding extensibility performance, in this study, the authors propose a new switch architecture called load-balanced DiffServ support switch (LBDS). LBDS consists of pipeline traffic bandwidth control, priority-based load balancing, and bandwidth-based priority scheduling to implement fast forwarding for expedited forwarding (EF) traffic and assured forwarding for AF classes of traffic. The authors evaluate LBDS by extensive theoretical analysis and comprehensive simulations. As expected, LBDS can provide bandwidth guarantees for both EF and AF traffic. We also show that under burst traffic arrivals, especially when the traffic arrival pattern is non-uniform and the load is above 0.6, LBDS performs much better delay performance than existing DiffServ support schemes.

Opportunistic spectrum scheduling for multiuser cognitive radio: a queueing analysis

We develop a queueing analytic framework to study the data link layer quality-of-service performance measures for cognitive radio users in an infrastructure-based dynamic spectrum access environment. In order to allocate the available spectrum white spaces among the cognitive radio users in a spectrum overlay scenario, an opportunistic scheduling scheme is considered. The queueing model considers bursty traffic arrival pattern at the cognitive radio user ends, finite buffer size, activity of primary users (i.e., dynamic channel availability), and correlated channel fading. We present a step-by-step procedure to derive the delay distribution, average throughput, and packet loss rate for the cognitive radio users. The proposed framework facilitates cross-layer design for improved QoS experience in cognitive radio networks. Usefulness of the developed analytical model is demonstrated through example applications.

Performance analysis of adaptive multipath load balancing in WDM–LOBS networks

The rapid advances in optical transmission technology have led to a wide deployment of WDM-based networks, and OBS is considered as a promising switching technology in the optical domain. A major problem in OBS is undoubtedly burst contention. Different mechanisms to reduce burst loss probability have been proposed, but multipath routing has many advantages and it is a relatively little explored alternative in the scope of OBS networks. Two interesting adaptive multipath mechanisms for OBS (AARA and GPMR) have been proposed in the literature, but both of them assume that all the interfaces have total wavelength conversion capacity. However, it is expected this feature to be gradually introduced, giving rise to heterogeneous scenarios where different types of interfaces coexist. Although AARA is applicable to heterogeneous scenarios, GPMR must be slightly modified. We propose this modification and an interesting practical implementation for GPMR. Finally, it is shown that both solutions work satisfactorily well for homogeneous scenarios, but the modified GPMR works clearly better than AARA for heterogeneous scenarios. On the other hand, by means of a general traffic model at the burst level, and through exhaustive simulation experiments, we study the effect of the correlation structure and of the marginal distribution of the traffic arrival pattern on the burst losses.

A Dynamic Mobile Terminal Sleep Mode Operation Scheme Considering Packet Queue Length

Due to the discontinuity of packet based traffic, the user terminals in next generation mobile telecommunications systems will be equipped with sleep mode operation functions for power saving purpose. The sleep mode parameters should be appropriately configured so that power consumption can be sufficiently decreased while packet queue length and packet delay are restricted within a demanded level. This paper proposes an adaptive sleep mode parameter configuration scheme which is able to jointly optimize the inactivity timer and sleep period in response to the variation of user traffic arrival pattern. The optimization target of this scheme is to minimize mobile terminal power consumption while ensuring that the mean downlink packet queue length do not exceed a certain threshold. Results of computer simulations prove that, the presented approach perfectly manages packet queue length restriction, packet delay control and power saving in a wide range of user packet inter-arrival rates both in single- and dual-service scenarios.

Analysis of effect of load-based excess bandwidth reservation on performances of differentiated services in E-PON

Performances of differentiated services in the upstream transmission of Ethernet passive optical network (E-PON) are affected by bandwidth reservation algorithm of an optical network unit, since data packets can be transmitted to an optical line termination only during the reserved transmission window. The effects of time-slot reservation on differentiated services are analysed and an adaptive class-based excess bandwidth reservation algorithm, called service quality pre-engagement (SQP), which reserves a time-slot based on the backlog queue and traffic arrival pattern of class is proposed. SQP applies the prediction-based bandwidth reservation to selected forward reservation classes (FRCs) which are determined by the introduced dynamic FRC selection. The proposed short-term service work-based time-slot reservation and long-term adaptive FRC selection optimise time-slot reservation according to traffic load of class. Analytic and simulation results show that this approach improves the performance of differentiated services, especially in terms of system buffer size, light-load penalty and service fairness, while guaranteeing high link utilisation and throughput.

Intelligent parking systems

The basic concepts of the parking reservation system and parking revenue management system are discussed in this paper. The proposed “intelligent” parking space inventory control system that is based on a combination of fuzzy logic and integer programming techniques makes “on line” decisions whether to accept or reject a new driver’s request for parking. In the first step of the proposed model, the best parking strategies are developed for many different patterns of vehicle arrivals. These parking strategies are developed using integer programming approach. In the second step, learning from the best strategies, specific rules are defined. The uniqueness of the proposed approach is that the rules are derived from the set of chosen examples assuming that the future traffic arrival patterns are known. The results were found to be close to the best solution assuming that the future arrival pattern is known.

Adaptive Fair Subcarrier/Rate Allocation in Multirate OFDMA Networks: Radio Link Level Queuing Performance Analysis

This paper presents a semi-analytical methodology for radio link level performance analysis in a multirate "orthogonal frequency-division multiple-access" (OFDMA) network with adaptive fair rate allocation. Multirate transmission is assumed to be achieved through adaptive modulation, and fair rate allocation is based on the principle of generalized processor sharing to allocate the subcarriers adaptively among the users. The fair rate allocation problem is formulated as an optimization problem with the objective of maximizing system throughput while maintaining fairness (in terms of transmission rate) among the users. The "optimal" fair rate allocation is obtained by using the "Hungarian method." A heuristic-based approach, namely the "iterative approach," that is more implementation friendly is also presented. The throughput performance of the iterative fair rate allocation is observed to be as good as that of optimal fair rate allocation and is better than that of the static subcarrier allocation scheme. Also, the iterative fair allocation provides better fairness compared to that for each of the optimal and the static subcarrier allocation schemes. To this end, a queuing model is formulated to analyze radio link level performance measures such as packet dropping probability and packet transmission delay under the above rate allocation schemes. In this formulation, packet arrivals are modeled by the discrete Markov modulated Poisson process, which is flexible to model different types of traffic arrival patterns. The proposed framework for radio link level performance analysis of multirate OFDMA networks is validated by extensive simulations. Also, examples on the application of the proposed model for connection admission control and quality-of-service provisioning are illustrated

A rate-based drop policy for punishing unresponsive flows

This paper proposes a drop policy for punishing unresponsive flows. The proposed drop policy uses the difference in traffic arrival patterns of responsive and unresponsive flows, and discards more packets from unresponsive flows. The drop probability of an arriving packet at a router is determined only by the temporal arrival rate of the router at that time, and the router does not need to identify the flow to which the packet belongs. The main advantage of this policy is that it performs well even in the presence of a large number of unresponsive flows since it does not attempt to distinguish high-bandwidth flows. Extensive simulations are presented to show that the proposed policy effectively punishes unresponsive flows by dropping more packets from them in various network situations.

A proportional-delay diffserv-enabled web server: admission control and dynamic adaptation

We consider a Web server that can provide differentiated services to clients with different quality of service (QoS) requirements. The Web server can provide N/spl ges/1 classes of proportional-delay differentiated services (PDDS) to heterogeneous clients. An operator can specify fixed performance spacings between classes, namely, r/sub i,i+1/>1, for i=1,..., N-1. Requests in class i+1 are guaranteed to have an average waiting time which is 1/r/sub i,i+1/ of the average waiting time of class i requests. With PDDS, we can provide consistent performance spacings over a wide range of system loading and this simplifies many pricing issues. In addition, each client can specify a maximum average waiting time requirement to be guaranteed by the PDDS-enabled Web server. We show that, in general, the problem of assigning clients to service classes in order to optimize system efficacy is NP-complete. We propose two efficient admission control algorithms so that a Web server can provide the QoS guarantees and, at the same time, classify each client to its "lowest" admissible class, resulting in lowest usage cost for the admitted client. We also consider how to perform end-point dynamic adaptation such that admitted clients can submit requests at a lower class and further reduce their usage costs without violating their QoS requirements. We propose two dynamic adaptation algorithms: one is server-based and the other is client-based. The client-based adaptation is distributed and is based on a noncooperative game technique. We carry out experiments to illustrate the effectiveness of these algorithms under different utility functions and traffic arrival patterns (e.g., Poisson, MMPP, and Pareto). We report extensive experimental results to illustrate the effectiveness of our proposed algorithms.

Matching output queueing with a combined input/output-queued switch

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: switches and routers can be made faster by using input-queued crossbars instead of shared memory systems; QoS can be provided using weighted-fair queueing (WFQ)-based packet scheduling. Until now, however, the two solutions have been mutually exclusive-all of the work on WFQ-based scheduling algorithms has required that switches/routers use output-queueing or centralized shared memory. This paper demonstrates that a combined input/output-queueing (CIOQ) switch running twice as fast as an input-queued switch can provide precise emulation of a broad class of packet-scheduling algorithms, including WFQ and strict priorities. More precisely, we show that for an N/spl times/N switch, a "speedup" of 2-1/N is necessary, and a speedup of two is sufficient for this exact emulation. Perhaps most interestingly, this result holds for all traffic arrival patterns. On its own, the result is primarily a theoretical observation; it shows that it is possible to emulate purely OQ switches with CIOQ switches running at approximately twice the line rate. To make the result more practical, we introduce several scheduling algorithms that with a speedup of two can emulate an OQ switch. We focus our attention on the simplest of these algorithms, critical cells first (CCF), and consider its running time and implementation complexity. We conclude that additional techniques are required to make the scheduling algorithms implementable at a high speed and propose two specific strategies.

A unified approach to traffic control strategy in integrated broadband networks

In integrated networks, a traffic control strategy has to allocate network resources according to the characteristics of input traffic. In this paper, a traffic control strategy using a burstiness characterization based on a virtual queue principle is examined. This approach provides the necessary link between network resources allocation and traffic control. Using the leaky bucket mechanism, a general strategy based on the burstiness characterization, called the LB-Dynamic policy, is developed for packet scheduling. This traffic control strategy monitors the allocated network resources and guarantees the network performance of each established connection, irrespective of the traffic intensity and arrival patterns of incoming packets. Simulation studies demonstrate that the LB-Dynamic policy is able to provide the requested service quality for heterogeneous traffic.

Carry-over round robin: a simple cell scheduling mechanism for ATM networks

We propose a simple mechanism named carry-over round robin (CORR) for scheduling cells in asynchronous transfer mode networks. We quantify the operational complexity of CORR scheduling and show that it is comparable to that of a simple round-robin scheduler. We then show that, albeit its simplicity, CORR is very competitive with much more sophisticated and significantly more complex scheduling disciplines in terms of performance. We evaluate the performance of CORR using both analysis and simulation, We derive analytical bounds on the worst case end-to-end delay achieved by a CORR scheduler for different traffic arrival patterns. Using traffic traces from MPEG video streams, we compare the delay performance of CORR with that of packet-by-packet generalized processor sharing (PGPS) and stop-and-go (SG). Our results show that, in terms of delay performance, CORR compares favorably with both PGPS and SG. We also analyze the fairness properties of CORR and show that it achieves near perfect fairness.

Access flow control scheme for ATM networks using neural-network-based traffic prediction

The authors propose a new approach to the problem of congestion control arising at the user network interface (UNI) of ATM-based broadband networks. The access flow control mechanism operates on the principle of feedback control. It uses a finite impulse response (FIR) neural network to accurately predict the traffic arrival patterns. The predicted output in conjunction with the current queue information of the buffer can be used as a measure of congestion. When the congestion level is reached, a control signal is generated to throttle the input arrival rate. The FIR multilayer perceptron model and its training algorithm are discussed. Simulation results presented in the paper suggest that the scheme provides a simple and efficient traffic management for ATM networks.

A Frame-Oriented Queueing Control Policy for Real- and Non-Real-Time Traffic in ATM Switches

The need to carry various real-time and non-real-time applications involving diverse traffic arrival pattern and a wide range of QoS requirements in ATM-based BISDN has spurred research activity on queueing control in ATM switches. Frame-oriented queueing policies have drawn much attention recently, which alleviates the high-speed processing requirement of the slot-oriented policies. In this paper, we propose a frame-oriented queueing control policy based on Golden-Ratio hashed slot assignment for real-time and non-real-time traffic in the output queue of ATM switches. The buffer is shared by the two types of traffic. The proposed policy updates the transmission schedule at every frame according to the buffer state instead of the arrival traffic pattern. The enqueueing priority assignment will also be updated at every frame or slot according to the transmission schedule of the current frame and the buffer state at the current frame or slot. Under the proposed policy, the minimum aggregate time-cumulative cell loss (subject to the system parameters) can always be guaranteed for any arrival traffic pattern. The system parameters need to be changed only when the traffic load and profile change (due to setup and tear-down of connections). To exploit the potential of the proposed policy, the performance of the theoretically optimal discipline R* is used to benchmark the performance of the proposed policy under a wide variety of cases.

Traffic arrival patterns on a cross section of a multilane highway

The dependence of vehicle arrival patterns in adjacent lanes of a multilane, one-directional highway necessitates the use of models which simultaneously describe vehicle arrivals on the roadway (defined as a number of parallel lanes in the same direction). The assumption of independent vehicle arrivals may lead to inaccuracies in a number of important design applications. The model presented describes the sequence of vehicle arrivals in adjacent lanes as a Markov renewal process. Markovian properties provide adequate expression of the dependence of vehicle arrivals on the roadway. After a vehicle arrives in a certain lane, the tendency for the next vehicle to appear in the adjacent lane is greater than is the unconditional probability for such a vehicle in that lane. These arrival patterns indicate that the distribution of vehicles in road lanes is different from that achieved by splitting total flow into independent streams.

Further Aspects of Traffic Arrival Patterns on a Multilane Highway

The model presented in this study describes the arrival pattern of vehicles on a multilane unidirectional highway. It is based on the assumption that in discrete time intervals, the vehicle arrival patterns can be described as a Markov chain process. The Markov properties conveniently enable the expression of interdependence of vehicle arrivals within and among lanes. From the empirical data collected, it was found that in the fast lane, the arrival process is overdispersed and the tendency for bunching is greater than under Poisson distribution conditions. The arrival process in the slow lane is underdispersed and the vehicles tend to distribute themselves deterministically along the lane. The cross-correlation function between the arrival processes in two adjacent lanes indicates a clear dependence between the two processes. This dependence might limit the number of potential overtakings, increases the friction between lanes and increases the probability for a side collision.