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

Adaptive Hybrid Switching Technique for Parallel Computing System

Parallel processing accelerates computations by solving a single problem using multiple compute nodes interconnected by a network. The scalability of a parallel system is limited byits ability to communicate and coordinate processing. Circuit switching, packet switchingand wormhole routing are dominant switching techniques. Our simulation results show that wormhole routing and circuit switching each excel under different types of traffic.This dissertation presents a hybrid switching technique that combines wormhole routing with circuit switching in a single switch using vrtual channels and time division multiplexing. The performance of this hybrid switch is significantly impacted by the effciency of traffic scheduling and thus, this dissertation also explores the design and scalability of hardware scheduling for the hybrid switch. In particular, we introduce two schedulers for crossbar networks: a greedy scheduler and an optimal scheduler that improves upon the resultsprovided by the greedy scheduler. For the time division multiplexing portion of the hybrid switch, this dissertation presents three allocation methods that combine wormhole switching with predictive circuit switching. We further extend this research from crossbar networks to fat tree interconnected networks with virtual channels. The global "level-wise" scheduling algorithm is presented and improves network utilization by 30% when compared to a switch-level algorithm. The performance of the hybrid switching is evaluated on a cycle accurate simulation framework that is also part of this dissertation research. Our experimental results demonstrate that the hybrid switch is capable of transferring both predictable traffics and unpredictable traffics successfully. By dynamically selecting the proper switching technique based on the type of communication traffic, the hybrid switch improves communication for most types of traffic

On traffic classification and its applications in the Internet

In this work, the methods and applications of traffic classification in the Internet are examined in detail. First, we define and discuss the conceptual environment of traffic classification. We then discuss the performance issues of traffic classification and define a method of visualization to compare the performance of traffic classification implementations. Previously introduced methods of traffic classification: the static applications, the packet count and the list classifiers are compared with each other. We find these methods to perform quite well when analyzed as performing in an IP router, but to be rather ambiguous as to the effect they cause to the user. We introduce an implementation of dynamic traffic classification to two classes using learning vector quantization (LVQ) for flow analysis data and find it to perform well in a simulated environment using flow analysis made on traffic measurements. In comparison to the previous methods of traffic classification, we see that the LVQ classifier has adequate performance. We also study a method of traffic classification using consecutive flow analysis with varying values of the parameters of the flow and find that we are able to classify traffic to 2 or 3 different classes. Within the classes the applications are similar in measured behavior and thus may provide help in realizing some advanced Internet service architectures. Finally, we also observe the application of the dynamic classifier in an Internet router and in the Internet itself. We argue that the implementation of the dynamic classification method is feasible in the network.reviewe