Design and stability analysis of high performance packet switches

With the rapid development of optical interconnection technology, high-performance packet switches are required to resolve contentions in a fast manner to satisfy the demand for high throughput and high speed rates. Combined input-crosspoint buffered (CICB) switches are an alternative to input-buffered (IB) packet switches to provide high-performance switching and to relax arbitration timing for packet switches with high-speed ports. A maximum weight matching (MWM) scheme can provide 100% throughput under admissible traffic for lB switches. However, the high complexity of MWM prohibits its implementation in high-speed switches. In this dissertation, a feedback-based arbitration scheme for CICB switches is studied, where cell selection is based on the provided service to virtual output queues (VOQs). The feedback-based scheme is named round-robin with adaptable frame size (RR-AF) arbitration. The frame size in RR-AF is adaptably changed by the serviced and unserviced traffic. If a switch is stable, the switch provides 100% throughput. Here, it is proved that RR-AF can achieve 100% throughput under uniform admissible traffic. Switches with crosspoint buffers need to consider the transmission delays, or round-trip times to define the crosspoint buffer size. As the buffered crossbar switch can be physically located far from the input ports, actual round-trip times can be non-negligible. To support non-negligible round-trip times in a buffered crossbar switch, the crosspoint buffer size needs to be increased. To satisfy this demand, this dissertation investigates how to select the crosspoint buffer size under non-negligible round trip times and under uniform traffic. With the analysis of stability margin, the relationship between the crosspoint buffer size and round-trip time is derived. Considering that CICB switches deliver higher performance than lB switches and require no speedup, this dissertation investigates the maximum throughput performance that these switches can achieve. It is shown that CICB switches without speedup achieve 100% throughput under any admissible traffic through a fluid model. In addition, a new hybrid scheme, based on longest queue-first (as input arbitration) and longest column occupancy first (as output arbitration) is proposed, which achieves 100% throughput under uniform and non-uniform traffic patterns. In order to give a better insight of the feedback nature of arbitration scheme for CICB switches, a frame-based round-robin arbitration scheme with explicit feedback control (FRE) is introduced. FRE dynamically sets the frame size according to the input load and to the accumulation of cells in a VOQ. FRE is used as the input arbitration scheme and it is combined with RR, PRR, and FRE as output arbitration schemes. These combined schemes deliver high performance under uniform and nonuniform traffic models using a buffered crossbar with one-cell crosspoint buffers. The novelty of FRE lies in that each VOQ sets the frame size by an adjustable parameter, Δ(i,j) which indicates the degree of service needed by VOQ(i, j). This value is adjusted according to the input loading and the accumulation of cells experienced in previous service cycles. This dissertation also explores an analysis technique based on feedback control theory. This methodology is proposed to study the stability of arbitration and matching schemes for packet switches. A continuous system is used and a control model is used to emulate a queuing system. The technique is applied to a matching scheme. In addition, the study shows that the dwell time, which is defined as the time a queue receives service in a service opportunity, is a factor that affects the stability of a queuing system. This feedback control model is an alternative approach to evaluate the stability of arbitration and matching schemes

Analysis of Error Control and Congestion Control Protocols

This thesis presents an analysis of a class of error control and congestion control protocols used in computer networks. We address two kinds of packet errors: (a) independent errors and (b) congestion-dependent errors. Our performance measure is the expected time and the standard deviation of the time to transmit a large message, consisting of N packets. The analysis of error control protocols. Assuming independent packet errors gives an insight on how the error control protocols should really work if buffer overflows are minimal. Some pertinent results on the performance of go-back-n, selective repeat, blast with full retransmission on error (BFRE) and a variant of BFRE, the Optimal BFRE that we propose, are obtained. We then analyze error control protocols in the presence of congestion-dependent errors. We study the selective repeat and go-back-n protocols and find that irrespective of retransmission strategy, the expected time as well as the standard deviation of the time to transmit N packets increases sharply the face of heavy congestion. However, if the congestion level is low, the two retransmission strategies perform similarly. We conclude that congestion control is a far more important issue when errors are caused by congestion. We next study the performance of a queue with dynamically changing input rates that are based on implicit or explicit feedback. This is motivated by recent proposals for adaptive congestion control algorithms where the sender\u27s window size is adjusted based on perceived congestion level of a bottleneck node. We develop a Fokker-Planck approximation for a simplified system; yet it is powerful enough to answer the important questions regarding stability, convergence (or oscillations), fairness and the significant effect that delayed feedback plays on performance. Specifically, we find that, in the absence of feedback delay, a linear increase/exponential decrease rate control algorithm is provably stable and fair. Delayed feedback, however, introduces cyclic behavior. This last result not only concurs with some recent simulation studies, it also expounds quantitatively on the real causes behind them

Reactive traffic control mechanisms for communication networks with self-similar bandwidth demands

Communication network architectures are in the process of being redesigned so that many different services are integrated within the same network. Due to this integration, traffic management algorithms need to balance the requirements of the traffic which the algorithms are directly controlling with Quality of Service (QoS) requirements of other classes of traffic which will be encountered in the network. Of particular interest is one class of traffic, termed elastic traffic, that responds to dynamic feedback from the network regarding the amount of available resources within the network. Examples of this type of traffic include the Available Bit Rate (ABR) service in Asynchronous Transfer Mode (ATM) networks and connections using Transmission Control Protocol (TCP) in the Internet. Both examples aim to utilise available bandwidth within a network. Reactive traffic management, like that which occurs in the ABR service and TCP, depends explicitly on the dynamic bandwidth requirements of other traffic which is currently using the network. In particular, there is significant evidence that a wide range of network traffic, including Ethernet, World Wide Web, Varible Bit Rate video and signalling traffic, is self-similar. The term self-similar refers to the particular characteristic of network traffic to remain bursty over a wide range of time scales. A closely associated characteristic of self-similar traffic is its long-range dependence (LRD), which refers to the significant correlations that occur with the traffic. By utilising these correlations, greater predictability of network traffic can be achieved, and hence the performance of reactive traffic management algorithms can be enhanced. A predictive rate control algorithm, called PERC (Predictive Explicit Rate Control), is proposed in this thesis which is targeted to the ABR service in ATM networks. By incorporating the LRD stochastic structure of background traffic, measurements of the bandwidth requirements of background traffic, and the delay associated with a particular ABR connection, a predictive algorithm is defined which provides explicit rate information that is conveyed to ABR sources. An enhancement to PERC is also described. This algorithm, called PERC+, uses previous control information to correct prediction errors that occur for connections with larger round-trip delay. These algorithms have been extensively analysed with regards to their network performance, and simulation results show that queue lengths and cell loss rates are significantly reduced when these algorithms are deployed. An adaptive version of PERC has also been developed using real-time parameter estimates of self-similar traffic. This has excellent performance compared with standard ABR rate control algorithms such as ERICA. Since PERC and its enhancement PERC+ have explicitly utilised the index of self-similarity, known as the Hurst parameter, the sensitivity of these algorithms to this parameter can be determined analytically. Research work described in this thesis shows that the algorithms have an asymmetric sensitivity to the Hurst parameter, with significant sensitivity in the region where the parameter is underestimated as being close to 0.5. Simulation results reveal the same bias in the performance of the algorithm with regards to the Hurst parameter. In contrast, PERC is insensitive to estimates of the mean, using the sample mean estimator, and estimates of the traffic variance, which is due to the algorithm primarily utilising the correlation structure of the traffic to predict future bandwidth requirements. Sensitivity analysis falls into the area of investigative research, but it naturally leads to the area of robust control, where algorithms are designed so that uncertainty in traffic parameter estimation or modelling can be accommodated. An alternative robust design approach, to the standard maximum entropy approach, is proposed in this thesis that uses the maximum likelihood function to develop the predictive rate controller. The likelihood function defines the proximity of a specific traffic model to the traffic data, and hence gives a measure of the performance of a chosen model. Maximising the likelihood function leads to optimising robust performance, and it is shown, through simulations, that the system performance is close to the optimal performance as compared with maximising the spectral entropy. There is still debate regarding the influence of LRD on network performance. This thesis also considers the question of the influence of LRD on traffic predictability, and demonstrates that predictive rate control algorithms that only use short-term correlations have close performance to algorithms that utilise long-term correlations. It is noted that predictors based on LRD still out-perform ones which use short-term correlations, but that there is Potential simplification in the design of predictors, since traffic predictability can be achieved using short-term correlations. This thesis forms a substantial contribution to the understanding of control in the case where self-similar processes form part of the overall system. Rather than doggedly pursuing self-similar control, a broader view has been taken where the performance of algorithms have been considered from a number of perspectives. A number of different research avenues lead on from this work, and these are outlined

Explicit congestion control algorithms for available bit rate services in asynchronous transfer mode networks

Congestion control of available bit rate (ABR) services in asynchronous transfer mode (ATM) networks has been the recent focus of the ATM Forum. The focus of this dissertation is to study the impact of queueing disciplines on ABR service congestion control, and to develop an explicit rate control algorithm. Two queueing disciplines, namely, First-In-First-Out (FIFO) and per-VC (virtual connection) queueing, are examined. Performance in terms of fairness, throughput, cell loss rate, buffer size and network utilization are benchmarked via extensive simulations. Implementation complexity analysis and trade-offs associated with each queueing implementation are addressed. Contrary to the common belief, our investigation demonstrates that per-VC queueing, which is costlier and more complex, does not necessarily provide any significant improvement over simple FIFO queueing. A new ATM switch algorithm is proposed to complement the ABR congestion control standard. The algorithm is designed to work with the rate-based congestion control framework recently recommended by the ATM Forum for ABR services. The algorithm\u27s primary merits are fast convergence, high throughput, high link utilization, and small buffer requirements. Mathematical analysis is done to show that the algorithm converges to the max-min fair allocation rates in finite time, and the convergence time is proportional to the distinct number of fair allocations and the round-trip delays in the network. At the steady state, the algorithm operates without causing any oscillations in rates. The algorithm does not require any parameter tuning, and proves to be very robust in a large ATM network. The impact of ATM switching and ATM layer congestion control on the performance of TCP/IP traffic is studied and the results are presented. The study shows that ATM layer congestion control improves the performance of TCP/IP traffic over ATM, and implementing the proposed switch algorithm drastically reduces the required switch buffer requirements. In order to validate claims, many benchmark ATM networks are simulated, and the performance of the switch is evaluated in terms of fairness, link utilization, response time, and buffer size requirements. In terms of performance and complexity, the algorithm proposed here offers many advantages over other proposed algorithms in the literature

Self-similar traffic and network dynamics

Copyright © 2002 IEEEOne of the most significant findings of traffic measurement studies over the last decade has been the observed self-similarity in packet network traffic. Subsequent research has focused on the origins of this self-similarity, and the network engineering significance of this phenomenon. This paper reviews what is currently known about network traffic self-similarity and its significance. We then consider a matter of current research, namely, the manner in which network dynamics (specifically, the dynamics of transmission control protocol (TCP), the predominant transport protocol used in today's Internet) can affect the observed self-similarity. To this end, we first discuss some of the pitfalls associated with applying traditional performance evaluation techniques to highly-interacting, large-scale networks such as the Internet. We then present one promising approach based on chaotic maps to capture and model the dynamics of TCP-type feedback control in such networks. Not only can appropriately chosen chaotic map models capture a range of realistic source characteristics, but by coupling these to network state equations, one can study the effects of network dynamics on the observed scaling behavior. We consider several aspects of TCP feedback, and illustrate by examples that while TCP-type feedback can modify the self-similar scaling behavior of network traffic, it neither generates it nor eliminates it.Ashok Erramilli, Matthew Roughan, Darryl Veitch and Walter Willinge

Performance Evaluation of Classical and Quantum Communication Systems

The Transmission Control Protocol (TCP) is a robust and reliable method used to transport data across a network. Many variants of TCP exist, e.g., Scalable TCP, CUBIC, and H-TCP. While some of them have been studied from empirical and theoretical perspectives, others have been less amenable to a thorough mathematical analysis. Moreover, some of the more popular variants had not been analyzed in the context of the high-speed environments for which they were designed. To address this issue, we develop a generalized modeling technique for TCP congestion control under the assumption of high bandwidth-delay product. In a separate contribution, we develop a versatile fluid model for congestion-window-based and rate-based congestion controllers that can be used to analyze a protocol’s stability. We apply this model to CUBIC – the default implementation of TCP in Linux systems – and discover that under a certain loss probability model, CUBIC is locally asymptotically stable. The contribution of this work is twofold: (i) the first formal stability analysis of CUBIC, and (ii) the fluid model can be easily adapted to other protocols whose window or rate functions are difficult to model. We demonstrate another application of this model by analyzing the stability of H-TCP, another popular variant used in data science networks. On a different front, a wide range of quantum distributed applications, which either promise to improve on existing classical applications or offer functionality that is entirely unobtainable via classical means, are helping to fuel rapid technological advances in the area of quantum communication. In view of this, it is prudent to model and analyze quantum networks, whose applications range from quantum cryptography to quantum sensing. Several types of quantum distributed applications, such as the E91 protocol for quantum key distribution, make use of entanglement to meet their objectives. Thus, being able to distribute entanglement efficiently is one of the most important and fundamental tasks that must be performed in a quantum network – without this functionality, many quantum distributed applications would be rendered infeasible. Modeling such systems is vital in order to better conceptualize their operation, and more importantly, to discover and address the challenges involved in actualizing them. To this end, we explore the limits of star-topology entanglement switching networks and introduce methods to model the process of entanglement generation, a set of switching policies, memory constraints, link heterogeneity, and quantum state decoherence for a switch that can serve bipartite (and in a specific case, tripartite) entangled states. In one part of this work, we compare two modeling techniques: discrete time Markov chains (DTMCs) and continuous-time Markov chains (CTMCs). We find that while DTMCs are a more accurate way to model the operation of an entanglement distribution switch, they quickly become intractable when one introduces link heterogeneity or state decoherence into the model. In terms of accuracy, we show that not much is lost for the case of homogeneous links, infinite buffer and no decoherence when CTMCs are employed. We then use CTMCs to model more complex systems. In another part of this work, we analyze a switch that can store one or two qubits per link and can serve both bipartite and tripartite entangled states. Through analysis, we discover that randomized policies allow the switch to achieve a better capacity than time-division multiplexing between bipartite and tripartite entangling measurements, but the advantage decreases as the number of links grows

Stable and scalable congestion control for high-speed heterogeneous networks

For any congestion control mechanisms, the most fundamental design objectives are stability and scalability. However, achieving both properties are very challenging in such a heterogeneous environment as the Internet. From the end-users' perspective, heterogeneity is due to the fact that different flows have different routing paths and therefore different communication delays, which can significantly affect stability of the entire system. In this work, we successfully address this problem by first proving a sufficient and necessary condition for a system to be stable under arbitrary delay. Utilizing this result, we design a series of practical congestion control protocols (MKC and JetMax) that achieve stability regardless of delay as well as many additional appealing properties. From the routers' perspective, the system is heterogeneous because the incoming traffic is a mixture of short- and long-lived, TCP and non-TCP flows. This imposes a severe challenge on traditional buffer sizing mechanisms, which are derived using the simplistic model of a single or multiple synchronized long-lived TCP flows. To overcome this problem, we take a control-theoretic approach and design a new intelligent buffer sizing scheme called Adaptive Buffer Sizing (ABS), which based on the current incoming traffic, dynamically sets the optimal buffer size under the target performance constraints. Our extensive simulation results demonstrate that ABS exhibits quick responses to changes of traffic load, scalability to a large number of incoming flows, and robustness to generic Internet traffic

Extreme Temperature Switch Mode Power Supply Based on Vee-square Control Using Silicon Carbide, Silicon on Sapphire, Hybrid Technology

Switch mode power supplies, commonly known as SMPS are basic building blocks of the electronic systems. SMPS performs power regulation by accepting a raw input voltage and transforming it to required voltage at output with desired characteristics. Electronic systems used in applications such as deep well oil drilling, geothermal wells and deep space explorations is expected to operate under extremely harsh conditions like elevated temperature, high pressure and radiation prone environments. To support the onboard electronics in these applications, SMPS capable of operating at extreme temperatures are of high interest.This research work deals with the design and development of a switch mode power supply capable of operating over the temperature range of 300 degree centigrade (�C). Silicon carbide field effect transistors are used as power devices in the design to tolerate these extreme high ambient temperatures without compromising power handling capability. The simplest yet robust vee square control architecture is adopted for control mechanism. The control electronics are implemented as an integrated circuit in 0.5 �m silicon on sapphire process. The supporting components like high temperature tolerant inductors and capacitors are identified by evaluating various samples at elevated temperature. This is the first demonstration of SMPS capable of operating at 275�C as a standalone component. Also for the first time, a gate drive mechanism based on planar transformer architecture is studied and presented for high temperature operation. A low cost packaging technique suited for harsh environment operation is proposed based on gold on aluminum nitride thin film technology. The basic analog building blocks of the system, such as comparator, voltage reference and rail-to-rail amplifiers are made available in discrete packages for use at temperatures above 275�C. A SMPS prototype on a 1.8 square inches substrate is developed and tested. Test results indicate that the system is capable of operating continuously at 275�C for extended period of time, providing the desired performance characteristics.School of Electrical & Computer Engineerin