Multiplexing regulated traffic streams: design and performance

The main network solutions for supporting QoS rely on traf- fic policing (conditioning, shaping). In particular, for IP networks the IETF has developed Intserv (individual flows regulated) and Diffserv (only ag- gregates regulated). The regulator proposed could be based on the (dual) leaky-bucket mechanism. This explains the interest in network element per- formance (loss, delay) for leaky-bucket regulated traffic. This paper describes a novel approach to the above problem. Explicitly using the correlation structure of the sources’ traffic, we derive approxi- mations for both small and large buffers. Importantly, for small (large) buffers the short-term (long-term) correlations are dominant. The large buffer result decomposes the traffic stream in a stream of constant rate and a periodic impulse stream, allowing direct application of the Brownian bridge approximation. Combining the small and large buffer results by a concave majorization, we propose a simple, fast and accurate technique to statistically multiplex homogeneous regulated sources. To address heterogeneous inputs, we present similarly efficient tech- niques to evaluate the performance of multiple classes of traffic, each with distinct characteristics and QoS requirements. These techniques, applica- ble under more general conditions, are based on optimal resource (band- width and buffer) partitioning. They can also be directly applied to set GPS (Generalized Processor Sharing) weights and buffer thresholds in a shared resource system

Multiplexing real time video services

Statistical Bit Rate (SBR) ATM capability is considered a good option for supporting Variable Bit Rate (VBR) services. However, its study is somewhat in lag compared with Deterministic Bit Rate (DBR) or Available Bit Rate (ABR) capabilities. The de nition of a general Call Acceptance Control (CAC) function is di cult to state for SBR. We present some results regarding the multiplexing of real time data streams, mainly from interactive video services, which are naturally VBR and therefore candidates to use the SBR capability. It is shown that image quality is improved by using SBR instead of DBR. The coder design does not become more complicated. In fact, it remains the same. We propose a statistical model for the tra c generated by such video sources. The delays introduced by a switch are studied following two approaches. Exact bounds are found for a worst case situation, indicating a very low statistical gain. However, simulations show that these bounds are too pessimistic since the worst case very rarely occurs. A very high mean load can be reached with acceptable delays. Indeed, the statistical gain is found to be signi cant. The CAC for this kind of service may be simple because, even assuming pessimistic gures, the burstiness for a real-time video data stream appears to be low.Eje: Procesamiento distribuido y paralelo. Tratamiento de señalesRed de Universidades con Carreras en Informática (RedUNCI

Dynamic bandwidth allocation in ATM networks

Includes bibliographical references.This thesis investigates bandwidth allocation methodologies to transport new emerging bursty traffic types in ATM networks. However, existing ATM traffic management solutions are not readily able to handle the inevitable problem of congestion as result of the bursty traffic from the new emerging services. This research basically addresses bandwidth allocation issues for bursty traffic by proposing and exploring the concept of dynamic bandwidth allocation and comparing it to the traditional static bandwidth allocation schemes

Design of traffic shaper / scheduler for packet switches and DiffServ networks : algorithms and architectures

The convergence of communications, information, commerce and computing are creating a significant demand and opportunity for multimedia and multi-class communication services. In such environments, controlling the network behavior and guaranteeing the user\u27s quality of service is required. A flexible hierarchical sorting architecture which can function either as a traffic shaper or a scheduler according to the requirement of the traffic load is presented to meet the requirement. The core structure can be implemented as a hierarchical traffic shaper which can support a large number of connections with a wide variety of rates and burstiness without the loss of the granularity in cells\u27 conforming departure time. The hierarchical traffic shaper can implement the exact sorting scheme with a substantial reduced memory size by using two stages of timing queues, and with substantial reduction in complexity, without introducing any sorting inaccuracy. By setting a suitable threshold to the length of the departure queue and using a lookahead algorithm, the core structure can be converted to a hierarchical rateadaptive scheduler. Based on the traffic load, it can work as an exact sorting traffic shaper or a Generic Cell Rate Algorithm (GCRA) scheduler. Such a rate-adaptive scheduler can reduce the Cell Transfer Delay and the Maximum Memory Occupancy greatly while keeping the fairness in the bandwidth assignment which is the inherent characteristic of GCRA. By introducing a best-effort queue to accommodate besteffort traffic, the hierarchical sorting architecture can be changed to a near workconserving scheduler. It assigns remaining bandwidth to the best-effort traffic so that it improves the utilization, of the outlink while it guarantees the quality of service requirements of those services which require quality of service guarantees. The inherent flexibility of the hierarchical sorting architecture combined with intelligent algorithms determines its multiple functions. Its implementation not only can manage buffer and bandwidth resources effectively, but also does not require no more than off-the-shelf hardware technology. The correlation of the extra shaping delay and the rate of the connections is revealed, and an improved fair traffic shaping algorithm, Departure Event Driven plus Completing Service Time Resorting algorithm, is presented. The proposed algorithm introduces a resorting process into Departure Event Driven Traffic Shaping Algorithm to resolve the contention of multiple cells which are all eligible for transmission in the traffic shaper. By using the resorting process based on each connection\u27s rate, better fairness and flexibility in the bandwidth assignment for connections with wide range of rates can be given. A Dual Level Leaky Bucket Traffic Shaper(DLLBTS) architecture is proposed to be implemented at the edge nodes of Differentiated Services Networks in order to facilitate the quality of service management process. The proposed architecture can guarantee not only the class-based Service Level Agreement, but also the fair resource sharing among flows belonging to the same class. A simplified DLLBTS architecture is also given, which can achieve the goals of DLLBTS while maintain a very low implementation complexity so that it can be implemented with the current VLSI technology. In summary, the shaping and scheduling algorithms in the high speed packet switches and DiffServ networks are studied, and the intelligent implementation schemes are proposed for them

Renegotiable VBR service

In this work we address the problem of supporting the QoS requirements for applications while efficiently allocating the network resources. We analyse this problem at the source node where the traffic profile is negotiated with the network and the traffic is shaped according to the contract. We advocate VBR renegotiation as an efficient mechanism to accommodate traffic fluctuations over the burst time-scale. This is in line with the Integrated Service of the IETF with the Resource reSerVation Protocol (RSVP), where the negotiated contract may be modified periodically. In this thesis, we analyse the fundamental elements needed for solving the VBR renegotiation. A source periodically estimates the needs based on: (1) its future traffic, (2) cost objective, (3) information from the past. The issues of this estimation are twofold: future traffic prediction given a prediction, the optimal change. In the case of a CBR specification the optimisation problem is trivial. But with a VBR specification this problem is complex because of the multidimensionality of the VBR traffic descriptor and the non zero condition of the system at the times where the parameter set is changed. We, therefore, focus on the problem of finding the optimal change for sources with pre-recorded or classified traffic. The prediction of the future traffic is out of the scope of this thesis. Traditional existing models are not suitable for modelling this dynamic situation because they do not take into account the non-zero conditions at the transient moments. To address the shortfalls of the traditional approaches, a new class of shapers, the time varying leaky bucket shaper class, has been introduced and characterised by network calculus. To our knowledge, this is the first model that takes into account non-zero conditions at the transient time. This innovative result forms the basis of Renegotiable VBR Service (RVBR). The application of our RVBR mathematical model to the initial problem of supporting the applications' QoS requirements while efficiently allocating the network resources results in simple, efficient algorithms. Through simulation, we first compare RVBR service versus VBR service and versus renegotiable CBR service. We show that RVBR service provides significant advantages in terms of resource costs and resource utilisation. Then, we illustrate that when the service assumes zero conditions at the transient time, the source could potentially experience losses in the case of policing because of the mismatch between the assumed bucket and buffer level and the policed bucket and buffer level. As an example of RVBR service usage, we describe the simulation of RVBR service in a scenario where a sender transmits a MPEG2 video over a network using RSVP reservation protocol with Controlled-Load service. We also describe the implementation design of a Video on Demand application, which is the first example of an RVBR-enabled application. The simulation and experimentation results lead us to believe that RVBR service provides an adequate service (in terms of QoS guaranteed and of efficient resource allocation) to sources with pre-recorded or classified traffic

Some aspects of traffic control and performance evaluation of ATM networks

The emerging high-speed Asynchronous Transfer Mode (ATM) networks are expected to integrate through statistical multiplexing large numbers of traffic sources having a broad range of statistical characteristics and different Quality of Service (QOS) requirements. To achieve high utilisation of network resources while maintaining the QOS, efficient traffic management strategies have to be developed. This thesis considers the problem of traffic control for ATM networks. The thesis studies the application of neural networks to various ATM traffic control issues such as feedback congestion control, traffic characterization, bandwidth estimation, and Call Admission Control (CAC). A novel adaptive congestion control approach based on a neural network that uses reinforcement learning is developed. It is shown that the neural controller is very effective in providing general QOS control. A Finite Impulse Response (FIR) neural network is proposed to adaptively predict the traffic arrival process by learning the relationship between the past and future traffic variations. On the basis of this prediction, a feedback flow control scheme at input access nodes of the network is presented. Simulation results demonstrate significant performance improvement over conventional control mechanisms. In addition, an accurate yet computationally efficient approach to effective bandwidth estimation for multiplexed connections is investigated. In this method, a feed forward neural network is employed to model the nonlinear relationship between the effective bandwidth and the traffic situations and a QOS measure. Applications of this approach to admission control, bandwidth allocation and dynamic routing are also discussed. A detailed investigation has indicated that CAC schemes based on effective bandwidth approximation can be very conservative and prevent optimal use of network resources. A modified effective bandwidth CAC approach is therefore proposed to overcome the drawback of conventional methods. Considering statistical multiplexing between traffic sources, we directly calculate the effective bandwidth of the aggregate traffic which is modelled by a two-state Markov modulated Poisson process via matching four important statistics. We use the theory of large deviations to provide a unified description of effective bandwidths for various traffic sources and the associated ATM multiplexer queueing performance approximations, illustrating their strengths and limitations. In addition, a more accurate estimation method for ATM QOS parameters based on the Bahadur-Rao theorem is proposed, which is a refinement of the original effective bandwidth approximation and can lead to higher link utilisation

Worst case traffic from sources constrained by leaky buckets

This thesis investigates the worst possible behaviour of a source if the traffic emanating from it is constrained to pass through a selection of leaky buckets. Various criteria for judging the worst ease arc considered, including the average queue length when the traffic is passed through an infinite buffer served at a constant rate and the rate of loss when the traffic is passed through a finite buffer, again served at a constant rate. Both of these criteria may be used when the source traffic is buffered alone or in combination with other traffic. Another functional considered is the effective bandwidth function which governs the asymptotic loss rate when the number of sources becomes infinite. This functional turns out to be the most tractable and we concentrate our attention on it. In all cases considered it is found that the functional to be maximised is convex in the space of traffic processes. This leads to the use of convex optimisation methods to characterise the worst case traffic process. In addition, Optimal Control Theory is used to show that the worst case traffic exhibits periodic behaviour

Multiplexing real time video services

Statistical Bit Rate (SBR) ATM capability is considered a good option for supporting Variable Bit Rate (VBR) services. However, its study is somewhat in lag compared with Deterministic Bit Rate (DBR) or Available Bit Rate (ABR) capabilities. The de nition of a general Call Acceptance Control (CAC) function is di cult to state for SBR. We present some results regarding the multiplexing of real time data streams, mainly from interactive video services, which are naturally VBR and therefore candidates to use the SBR capability. It is shown that image quality is improved by using SBR instead of DBR. The coder design does not become more complicated. In fact, it remains the same. We propose a statistical model for the tra c generated by such video sources. The delays introduced by a switch are studied following two approaches. Exact bounds are found for a worst case situation, indicating a very low statistical gain. However, simulations show that these bounds are too pessimistic since the worst case very rarely occurs. A very high mean load can be reached with acceptable delays. Indeed, the statistical gain is found to be signi cant. The CAC for this kind of service may be simple because, even assuming pessimistic gures, the burstiness for a real-time video data stream appears to be low.Eje: Procesamiento distribuido y paralelo. Tratamiento de señalesRed de Universidades con Carreras en Informática (RedUNCI

Performance Management in ATM Networks

ATM is representative of the connection-oriented resource provisioning classof protocols. The ATM network is expected to provide end-to-end QoS guaranteesto connections in the form of bounds on delays, errors and/or losses. Performancemanagement involves measurement of QoS parameters, and application of controlmeasures (if required) to improve the QoS provided to connections, or to improvethe resource utilization at switches. QoS provisioning is very important for realtimeconnections in which losses are irrecoverable and delays cause interruptionsin service. QoS of connections on a node is a direct function of the queueing andscheduling on the switch. Most scheduling architectures provide static allocationof resources (scheduling priority, maximum buffer) at connection setup time. Endto-end bounds are obtainable for some schedulers, however these are precluded forheterogeneously composed networks. The resource allocation does not adapt to theQoS provided on connections in real time. In addition, mechanisms to measurethe QoS of a connection in real-time are scarce.In this thesis, a novel framework for performance management is proposed. Itprovides QoS guarantees to real time connections. It comprises of in-service QoSmonitoring mechanisms, a hierarchical scheduling algorithm based on dynamicpriorities that are adaptive to measurements, and methods to tune the schedulers atindividual nodes based on the end-to-end measurements. Also, a novel scheduler isintroduced for scheduling maximum delay sensitive traffic. The worst case analysisfor the leaky bucket constrained traffic arrivals is presented for this scheduler. Thisscheduler is also implemented on a switch and its practical aspects are analyzed.In order to understand the implementability of complex scheduling mechanisms,a comprehensive survey of the state-of-the-art technology used in the industry isperformed. The thesis also introduces a method of measuring the one-way delayand jitter in a connection using in-service monitoring by special cells

Learning algorithms for the control of routing in integrated service communication networks

There is a high degree of uncertainty regarding the nature of traffic on future integrated service networks. This uncertainty motivates the use of adaptive resource allocation policies that can take advantage of the statistical fluctuations in the traffic demands. The adaptive control mechanisms must be 'lightweight', in terms of their overheads, and scale to potentially large networks with many traffic flows. Adaptive routing is one form of adaptive resource allocation, and this thesis considers the application of Stochastic Learning Automata (SLA) for distributed, lightweight adaptive routing in future integrated service communication networks. The thesis begins with a broad critical review of the use of Artificial Intelligence (AI) techniques applied to the control of communication networks. Detailed simulation models of integrated service networks are then constructed, and learning automata based routing is compared with traditional techniques on large scale networks. Learning automata are examined for the 'Quality-of-Service' (QoS) routing problem in realistic network topologies, where flows may be routed in the network subject to multiple QoS metrics, such as bandwidth and delay. It is found that learning automata based routing gives considerable blocking probability improvements over shortest path routing, despite only using local connectivity information and a simple probabilistic updating strategy. Furthermore, automata are considered for routing in more complex environments spanning issues such as multi-rate traffic, trunk reservation, routing over multiple domains, routing in high bandwidth-delay product networks and the use of learning automata as a background learning process. Automata are also examined for routing of both 'real-time' and 'non-real-time' traffics in an integrated traffic environment, where the non-real-time traffic has access to the bandwidth 'left over' by the real-time traffic. It is found that adopting learning automata for the routing of the real-time traffic may improve the performance to both real and non-real-time traffics under certain conditions. In addition, it is found that one set of learning automata may route both traffic types satisfactorily. Automata are considered for the routing of multicast connections in receiver-oriented, dynamic environments, where receivers may join and leave the multicast sessions dynamically. Automata are shown to be able to minimise the average delay or the total cost of the resulting trees using the appropriate feedback from the environment. Automata provide a distributed solution to the dynamic multicast problem, requiring purely local connectivity information and a simple updating strategy. Finally, automata are considered for the routing of multicast connections that require QoS guarantees, again in receiver-oriented dynamic environments. It is found that the distributed application of learning automata leads to considerably lower blocking probabilities than a shortest path tree approach, due to a combination of load balancing and minimum cost behaviour