Traffic control mechanisms with cell rate simulation for ATM networks.

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Performance analysis of an ATM network with multimedia traffic: a simulation study

Traffic and congestion control are important in enabling ATM networks to maintain the Quality of Service (QoS) required by end users. A Call Admission Control (CAC) strategy ensures that the network has sufficient resources available at the start of each call, but this does not prevent a traffic source from violating the negotiated contract. A policing strategy (User Parameter Control (UPC)) is also required to enforce the negotiated rates for a particular connection and to protect conforming users from network overload. The aim of this work is to investigate traffic policing and bandwidth management at the User to Network Interface (UNI). A policing function is proposed which is based on the leaky bucket (LB) which offers improved performance for both real time (RT) traffic such as speech and video and non-real time (non-RT) traffic, mainly data by taking into account the QoS requirements. A video cell in violation of the negotiated bit rate causes the remainder of the slice to be discarded. This 'tail clipping' provides protection for the decoder from damaged video slices. Speech cells are coded using a frequency domain coder, which places the most significant bits of a double speech sample into a high priority cell and the least significant bits into a high priority cell. In the case of congestion, the low priority cell can be discarded with little impact on the intelligibility of the received speech. However, data cells require loss-free delivery and are buffered rather than being discarded or tagged for subsequent deletion. This triple strategy is termed the super leaky bucket (SLB). Separate queues for RT and non-RT traffic, are also proposed at the multiplexer, with non pre-emptive priority service for RT traffic if the queue exceeds a predetermined threshold. If the RT queue continues to grow beyond a second threshold, then all low priority cells (mainly speech) are discarded. This scheme protects non-RT traffic from being tagged and subsequently discarded, by queueing the cells and also by throttling back non-RT sources during periods of congestion. It also prevents the RT cells from being delayed excessively in the multiplexer queue. A simulation model has been designed and implemented to test the proposal. Realistic sources have been incorporated into the model to simulate the types of traffic which could be expected on an ATM network. The results show that the S-LB outperforms the standard LB for video cells. The number of cells discarded and the resulting number of damaged video slices are significantly reduced. Dual queues with cyclic service at the multiplexer also reduce the delays experienced by RT cells. The QoS for all categories of traffic is preserved

Mathematical modelling of end-to-end packet delay in multi-hop wireless networks and their applications to qos provisioning

This thesis addresses the mathematical modelling of end-to-end packet delay for Quality of Service (QoS) provisioning in multi-hop wireless networks. The multi-hop wireless technology increases capacity and coverage in a cost-effective way and it has been standardised in the Fourth-Generation (4G) standards. The effective capacity model approximates end-to-end delay performances, including Complementary Cumulative Density Function (CCDF) of delay, average delay and jitter. This model is first tested using Internet traffic trace from a real gigabit Ethernet gateway. The effective capacity model is developed based on single-hop and continuous-time communication systems but a multi-hop wireless system is better described to be multi-hop and time-slotted. The thesis extends the effective capacity model by taking multi-hop and time-slotted concepts into account, resulting in two new mathematical models: the multi-hop effective capacity model for multi-hop networks and the mixed continuous/discrete-time effective capacity model for time-slotted networks. Two scenarios are considered to validate these two effective capacity-based models based on ideal wireless communications (the physical-layer instantaneous transmission rate is the Shannon channel capacity): 1) packets traverse multiple wireless network devices and 2) packets are transmitted to or received from a wireless network device every Transmission Time Interval (TTI). The results from these two scenarios consistently show that the new mathematical models developed in the thesis characterise end-to-end delay performances accurately. Accurate and efficient estimators for end-to-end packet delay play a key role in QoS provisioning in modern communication systems. The estimators from the new effective capacity-based models are directly tested in two systems, faithfully created using realistic simulation techniques: 1) the IEEE 802.16-2004 networks and 2) wireless tele-ultrasonography medical systems. The results show that the estimation and simulation results are in good agreement in terms of end-to-end delay performances

From burstiness characterisation to traffic control strategy : a unified approach to integrated broadbank networks

The major challenge in the design of an integrated network is the integration and support of a wide variety of applications. To provide the requested performance guarantees, a traffic control strategy has to allocate network resources according to the characteristics of input traffic. Specifically, the definition of traffic characterisation is significant in network conception. In this thesis, a traffic stream is characterised based on a virtual queue principle. This approach provides the necessary link between network resources allocation and traffic control. It is difficult to guarantee performance without prior knowledge of the worst behaviour in statistical multiplexing. Accordingly, we investigate the worst case scenarios in a statistical multiplexer. We evaluate the upper bounds on the probabilities of buffer overflow in a multiplexer, and data loss of an input stream. It is found that in networks without traffic control, simply controlling the utilisation of a multiplexer does not improve the ability to guarantee performance. Instead, the availability of buffer capacity and the degree of correlation among the input traffic dominate the effect on the performance of loss. The leaky bucket mechanism has been proposed to prevent ATM networks from performance degradation due to congestion. We study the leaky bucket mechanism as a regulation element that protects an input stream. We evaluate the optimal parameter settings and analyse the worst case performance. To investigate its effectiveness, we analyse the delay performance of a leaky bucket regulated multiplexer. Numerical results show that the leaky bucket mechanism can provide well-behaved traffic with guaranteed delay bound in the presence of misbehaving traffic. Using the leaky bucket mechanism, a general strategy based on burstiness characterisation, called the LB-Dynamic policy, is developed for packet scheduling. This traffic control strategy is closely related to the allocation of both bandwidth and buffer in each switching node. In addition, the LB-Dynamic policy 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 in integrated broadband networks

Numerical methods for queues with shared service

A queueing system is a mathematical abstraction of a situation where elements, called customers, arrive in a system and wait until they receive some kind of service. Queueing systems are omnipresent in real life. Prime examples include people waiting at a counter to be served, airplanes waiting to take off, traffic jams during rush hour etc. Queueing theory is the mathematical study of queueing phenomena. As often neither the arrival instants of the customers nor their service times are known in advance, queueing theory most often assumes that these processes are random variables. The queueing process itself is then a stochastic process and most often also a Markov process, provided a proper description of the state of the queueing process is introduced. This dissertation investigates numerical methods for a particular type of Markovian queueing systems, namely queueing systems with shared service. These queueing systems differ from traditional queueing systems in that there is simultaneous service of the head-of-line customers of all queues and in that there is no service if there are no customers in one of the queues. The absence of service whenever one of the queues is empty yields particular dynamics which are not found in traditional queueing systems. These queueing systems with shared service are not only beautiful mathematical objects in their own right, but are also motivated by an extensive range of applications. The original motivation for studying queueing systems with shared service came from a particular process in inventory management called kitting. A kitting process collects the necessary parts for an end product in a box prior to sending it to the assembly area. The parts and their inventories being the customers and queues, we get ``shared service'' as kitting cannot proceed if some parts are absent. Still in the area of inventory management, the decoupling inventory of a hybrid make-to-stock/make-to-order system exhibits shared service. The production process prior to the decoupling inventory is make-to-stock and driven by demand forecasts. In contrast, the production process after the decoupling inventory is make-to-order and driven by actual demand as items from the decoupling inventory are customised according to customer specifications. At the decoupling point, the decoupling inventory is complemented with a queue of outstanding orders. As customisation only starts when the decoupling inventory is nonempty and there is at least one order, there is again shared service. Moving to applications in telecommunications, shared service applies to energy harvesting sensor nodes. Such a sensor node scavenges energy from its environment to meet its energy expenditure or to prolong its lifetime. A rechargeable battery operates very much like a queue, customers being discretised as chunks of energy. As a sensor node requires both sensed data and energy for transmission, shared service can again be identified. In the Markovian framework, "solving" a queueing system corresponds to finding the steady-state solution of the Markov process that describes the queueing system at hand. Indeed, most performance measures of interest of the queueing system can be expressed in terms of the steady-state solution of the underlying Markov process. For a finite ergodic Markov process, the steady-state solution is the unique solution of $N-1$ balance equations complemented with the normalisation condition, $N$ being the size of the state space. For the queueing systems with shared service, the size of the state space of the Markov processes grows exponentially with the number of queues involved. Hence, even if only a moderate number of queues are considered, the size of the state space is huge. This is the state-space explosion problem. As direct solution methods for such Markov processes are computationally infeasible, this dissertation aims at exploiting structural properties of the Markov processes, as to speed up computation of the steady-state solution. The first property that can be exploited is sparsity of the generator matrix of the Markov process. Indeed, the number of events that can occur in any state --- or equivalently, the number of transitions to other states --- is far smaller than the size of the state space. This means that the generator matrix of the Markov process is mainly filled with zeroes. Iterative methods for sparse linear systems --- in particular the Krylov subspace solver GMRES --- were found to be computationally efficient for studying kitting processes only if the number of queues is limited. For more queues (or a larger state space), the methods cannot calculate the steady-state performance measures sufficiently fast. The applications related to the decoupling inventory and the energy harvesting sensor node involve only two queues. In this case, the generator matrix exhibits a homogene block-tridiagonal structure. Such Markov processes can be solved efficiently by means of matrix-geometric methods, both in the case that the process has finite size and --- even more efficiently --- in the case that it has an infinite size and a finite block size. Neither of the former exact solution methods allows for investigating systems with many queues. Therefore we developed an approximate numerical solution method, based on Maclaurin series expansions. Rather than focussing on structural properties of the Markov process for any parameter setting, the series expansion technique exploits structural properties of the Markov process when some parameter is sent to zero. For the queues with shared exponential service and the service rate sent to zero, the resulting process has a single absorbing state and the states can be ordered such that the generator matrix is upper-diagonal. In this case, the solution at zero is trivial and the calculation of the higher order terms in the series expansion around zero has a computational complexity proportional to the size of the state space. This is a case of regular perturbation of the parameter and contrasts to singular perturbation which is applied when the service times of the kitting process are phase-type distributed. For singular perturbation, the Markov process has no unique steady-state solution when the parameter is sent to zero. However, similar techniques still apply, albeit at a higher computational cost. Finally we note that the numerical series expansion technique is not limited to evaluating queues with shared service. Resembling shared queueing systems in that a Markov process with multidimensional state space is considered, it is shown that the regular series expansion technique can be applied on an epidemic model for opinion propagation in a social network. Interestingly, we find that the series expansion technique complements the usual fluid approach of the epidemic literature

Non-asymptotic performance evaluation and sampling-based parameter estimation for communication networks with long memory traffic

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Bits of Internet traffic control

In this work, we consider four problems in the context of Internet traffic control. The first problem is to understand when and why a sender that implements an equation-based rate control would be TCP-friendly, or not—a sender is said to be TCP-friendly if, under the same operating conditions, its long-term average send rate does not exceed that of a TCP sender. It is an established axiom that some senders in the Internet would need to be TCP-friendly. An equation-based rate control sender plugs-in some on-line estimates of the loss-event rate and an expected round-trip time in a TCP throughput formula, and then at some points in time sets its send rate to such computed values. Conventional wisdom held that if a sender adjusts its send rate as just described, then it would be TCP-friendly. We show exact analysis that tells us when we should expect an equation-based rate control to be TCP-friendly, and in some cases excessively so. We show experimental evidence and identify the causes that, in a realistic scenario, make an equation-based rate control grossly non-TCP-friendly. Our second problem is to understand the throughput achieved by another family of send rate controls—we termed these "increase-decrease controls," with additive-increase/multiplicative-decrease as a special case. One issue that we consider is the allocation of long-term average send rates among senders that adjust their send rates by an additive-increase/multiplicative-decrease control, in a network of links with arbitrary fixed routes, and arbitrary round-trip times. We show what the resulting send rate allocation is. This result advances the state-of-the-art in understanding the fairness of the rate allocation in presence of arbitrary round-trip times. We also consider the design of an increase-decrease control to achieve a given target loss-throughput function. We show that if we design some increase-decrease controls under a commonly used reference loss process—a sequence of constant inter-loss event times—then we know that these controls would overshoot their target loss-throughput function, for some more general loss processes. A reason to study the design problem is to construct an increase-decrease control that would be friendly to some other control, TCP, for instance. The third problem that we consider is how to obtain probabilistic bounds on performance for nodes that conform to the per-hop-behavior of Expedited Forwarding, a service of differentiated services Internet. Under the assumption that the arrival process to a node consists of flows that are individually regulated (as it is commonplace with Expedited Forwarding) and the flows are stochastically independent, we obtained probabilistic bounds on backlog, delay, and loss. We apply our single-node performance bounds to a network of nodes. Having good probabilistic bounds on the performance of nodes that conform to the per-hop-behavior of Expedited Forwarding, would enable a dimensioning of those networks more effectively, than by using some deterministic worst-case performance bounds. Our last problem is on the latency of an input-queued switch that implements a decomposition-based scheduler. With decomposition-based schedulers, we are given a rate demand matrix to be offered by a switch in the long-term between the switch input/output port pairs. A given rate demand matrix is, by some standard techniques, decomposed into a set of permutation matrices that define the connectivity of the input/output port pairs. The problem is how to construct a schedule of the permutation matrices such that the schedule offers a small latency for each input/output port pair of the switch. We obtain bounds on the latency for some schedulers that are in many situations smaller than a best-known bound. It is important to be able to design switches with bounds on their latencies in order to provide guarantees on delay-jitter