Scheduling algorithms for high-speed switches

The virtual output queued (VOQ) switching architecture was adopted for high speed switch implementation owing to its scalability and high throughput. An ideal VOQ algorithm should provide Quality of Service (QoS) with low complexity. However, none of the existing algorithms can meet these requirements. Several algorithms for VOQ switches are introduced in this dissertation in order to improve upon existing algorithms in terms of implementation or QoS features. Initially, the earliest due date first matching (EDDFM) algorithm, which is stable for both uniform and non-uniform traffic patterns, is proposed. EDDFM has lower probability of cell overdue than other existing maximum weight matching algorithms. Then, the shadow departure time algorithm (SDTA) and iterative SDTA (ISDTA) are introduced. The QoS features of SDTA and ISDTA are better than other existing algorithms with the same computational complexity. Simulations show that the performance of a VOQ switch using ISDTA with a speedup of 1.5 is similar to that of an output queued (OQ) switch in terms of cell delay and throughput. Later, the enhanced Birkhoff-von Neumann decomposition (EBVND) algorithm based on the Birkhoff-von Neumann decomposition (BVND) algorithm, which can provide rate and cell delay guarantees, is introduced. Theoretical analysis shows that the performance of EBVND is better than BVND in terms of throughput and cell delay. Finally, the maximum credit first (MCF), the Enhanced MCF (EMCF), and the iterative MCF (IMCF) algorithms are presented. These new algorithms have the similar performance as BNVD, yet are easier to implement in practice

Joint buffer management and scheduling for input queued switches

Input queued (IQ) switches are highly scalable and they have been the focus of many studies from academia and industry. Many scheduling algorithms have been proposed for IQ switches. However, they do not consider the buffer space requirement inside an IQ switch that may render the scheduling algorithms inefficient in practical applications. In this dissertation, the Queue Length Proportional (QLP) algorithm is proposed for IQ switches. QLP considers both the buffer management and the scheduling mechanism to obtain the optimal allocation region for both bandwidth and buffer space according to real traffic load. In addition, this dissertation introduces the Queue Proportional Fairness (QPF) criterion, which employs the cell loss ratio as the fairness metric. The research in this dissertation will show that the utilization of network resources will be improved significantly with QPF. Furthermore, to support diverse Quality of Service (QoS) requirements of heterogeneous and bursty traffic, the Weighted Minmax algorithm (WMinmax) is proposed to efficiently and dynamically allocate network resources. Lastly, to support traffic with multiple priorities and also to handle the decouple problem in practice, this dissertation introduces the multiple dimension scheduling algorithm which aims to find the optimal scheduling region in the multiple Euclidean space

On scheduling input queued cell switches

Output-queued switching, though is able to offer high throughput, guaranteed delay and fairness, lacks scalability owing to the speed up problem. Input-queued switching, on the other hand, is scalable, and is thus becoming an attractive alternative. This dissertation presents three approaches toward resolving the major problem encountered in input-queued switching that has prohibited the provision of quality of service guarantees. First, we proposed a maximum size matching based algorithm, referred to as min-max fair input queueing (MFIQ), which minimizes the additional delay caused by back pressure, and at the same time provides fair service among competing sessions. Like any maximum size matching algorithm, MFIQ performs well for uniform traffic, in which the destinations of the incoming cells are uniformly distributed over all the outputs, but is not stable for non-uniform traffic. Subse-quently, we proposed two maximum weight matching based algorithms, longest normalized queue first (LNQF) and earliest due date first matching (EDDFM), which are stable for both uniform and non-uniform traffic. LNQF provides fairer service than longest queue first (LQF) and better traffic shaping than oldest cell first (OCF), and EDDEM has lower probability of delay overdue than LQF, LNQF, and OCF. Our third approach, referred to as store-sort-and-forward (SSF), is a frame based scheduling algorithm. SSF is proved to be able to achieve strict sense 100% throughput, and provide bounded delay and delay jitter for input-queued switches if the traffic conforms to the (r, T) model

High Performance Queueing and Scheduling in Support of Multicasting in Input-Queued Switches

Due to its mild requirement on the bandwidth of switching fabric and internal memory, the input-queued architecture is a practical solution for today\u27s very high-speed switches. One of the notoriously difficult problems in the design of input-queued switches with very high link rates is the high performance queueing and scheduling of multicast traffic. This dissertation focuses on proposing novel solutions for this problem. The design challenge stems from the nature of multicast traffic, i.e., a multicast packet typically has multiple destinations. On the one hand, this nature makes queueing and scheduling of multicast traffic much more difficult than that of unicast traffic. For example, virtual output queueing is widely used to completely avoid the head-of-line blocking and achieve 100% throughput for unicast traffic. Nevertheless, the exhaustive, multicast virtual output queueing is impractical and results in out-of-order delivery. On the other hand, in spite of extensive studies in the context of either pure unicast traffic or pure multicast traffic, the results from a study in one context are not applicable to the other context due to the difference between the natures of unicast and multicast traffic. The design of integrated scheduling for both types of traffic remains an open issue. The main contribution of this dissertation is twofold: firstly, the performance of an interesting approach to efficiently mitigate head-of-line blocking for multicast traffic is theoretically analyzed; secondly, two novel algorithms are proposed to efficiently integrate unicast and multicast scheduling within one switching fabric. The research work presented in this dissertation concludes that (1) a small number of queues are sufficient to maximize the saturation throughput and delay performances of a large multicast switch with multiple first-in-first-out queues per input port; (2) the theoretical analysis results are indeed valid for practical large-sized switches; (3) for a large M × N multicast switch, the final achievable saturation throughput decreases as the ratio of M/N decreases; (4) and the two proposed integration algorithms exhibit promising performances in terms of saturation throughput, delay, and packet loss ratio under both uniform Bernoulli and uniform bursty traffic

On the Stability of Isolated and Interconnected Input-Queued Switches under Multiclass Traffic

In this correspondence, we discuss the stability of scheduling algorithms for input-queueing (IQ) and combined input/output queueing (CIOQ) packet switches. First, we show that a wide class of IQ schedulers operating on multiple traffic classes can achieve 100 % throughput. Then, we address the problem of the maximum throughput achievable in a network of interconnected IQ switches and CIOQ switches loaded by multiclass traffic, and we devise some simple scheduling policies that guarantee 100 % throughput. Both the Lyapunov function methodology and the fluid modeling approach are used to obtain our results

Configurable data center switch architectures

In this thesis, we explore alternative architectures for implementing con_gurable Data Center Switches along with the advantages that can be provided by such switches. Our first contribution centers around determining switch architectures that can be implemented on Field Programmable Gate Array (FPGA) to provide configurable switching protocols. In the process, we identify a gap in the availability of frameworks to realistically evaluate the performance of switch architectures in data centers and contribute a simulation framework that relies on realistic data center traffic patterns. Our framework is then used to evaluate the performance of currently existing as well as newly proposed FPGA-amenable switch designs. Through collaborative work with Meng and Papaphilippou, we establish that only small-medium range switches can be implemented on today's FPGAs. Our second contribution is a novel switch architecture that integrates a custom in-network hardware accelerator with a generic switch to accelerate Deep Neural Network training applications in data centers. Our proposed accelerator architecture is prototyped on an FPGA, and a scalability study is conducted to demonstrate the trade-offs of an FPGA implementation when compared to an ASIC implementation. In addition to the hardware prototype, we contribute a light weight load-balancing and congestion control protocol that leverages the unique communication patterns of ML data-parallel jobs to enable fair sharing of network resources across different jobs. Our large-scale simulations demonstrate the ability of our novel switch architecture and light weight congestion control protocol to both accelerate the training time of machine learning jobs by up to 1.34x and benefit other latency-sensitive applications by reducing their 99%-tile completion time by up to 4.5x. As for our final contribution, we identify the main requirements of in-network applications and propose a Network-on-Chip (NoC)-based architecture for supporting a heterogeneous set of applications. Observing the lack of tools to support such research, we provide a tool that can be used to evaluate NoC-based switch architectures.Open Acces

Deadline-ordered burst-based parallel scheduling strategy for IP-over-ATM with QoS support.

Siu Chun.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.Includes bibliographical references (leaves 66-68).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Thesis Overview --- p.3Chapter 2 --- Background and Related work --- p.4Chapter 2.1 --- Emergence of IP-over-ATM --- p.4Chapter 2.2 --- ATM architecture --- p.5Chapter 2.3 --- Scheduling issues in output-queued switch --- p.6Chapter 2.4 --- Scheduling issues in input-queued switch --- p.18Chapter 3 --- The Deadline-ordered Burst-based Parallel Scheduling Strategy --- p.23Chapter 3.1 --- Introduction --- p.23Chapter 3.2 --- Switch and queueing model --- p.24Chapter 3.2.1 --- Switch model --- p.24Chapter 3.2.2 --- Queueing model --- p.25Chapter 3.3 --- The DBPS Strategy --- p.26Chapter 3.3.1 --- Motivation --- p.26Chapter 3.3.2 --- Strategy --- p.31Chapter 3.4 --- The Deadline-ordered Burst-based Parallel Iterative Matching --- p.33Chapter 3.4.1 --- Algorithm --- p.34Chapter 3.4.2 --- An example of DBPIM --- p.35Chapter 3.5 --- Simulation results --- p.33Chapter 3.6 --- Discussions --- p.46Chapter 3.7 --- Future work --- p.47Chapter 4 --- The Quasi-static DBPIM Algorithm --- p.50Chapter 4.1 --- Introduction --- p.50Chapter 4.2 --- Quasi-static path scheduling principle --- p.51Chapter 4.3 --- Quasi-static DBPIM algorithm --- p.56Chapter 4.4 --- An example of Quasi-static DBPIM --- p.59Chapter 5 --- Conclusion --- p.63Bibliography --- p.6