Over the past decade, many approaches have been introduced for traffic speed prediction. However, providing fine-grained, accurate, time-efficient, and adaptive traffic speed prediction for a growing transportation network where the size of the network keeps increasing and new traffic detectors are constantly deployed has not been well studied. To address this issue, this paper presents DistTune based on long short-term memory (LSTM) and the Nelder-Mead method. When encountering an unprocessed detector, DistTune decides if it should customize an LSTM model for this detector by comparing the detector with other processed detectors in the normalized traffic speed patterns they have observed. If a similarity is found, DistTune directly shares an existing LSTM model with this detector to achieve time-efficient processing. Otherwise, DistTune customizes an LSTM model for the detector to achieve fine-grained prediction. To make DistTune even more time-efficient, DisTune performs on a cluster of computing nodes in parallel. To achieve adaptive traffic speed prediction, DistTune also provides LSTM re-customization for detectors that suffer from unsatisfactory prediction accuracy due to, for instance, changes in traffic speed patterns. Extensive experiments based on traffic data collected from freeway I5-N in California are conducted to evaluate the performance of DistTune. The results demonstrate that DistTune provides fine-grained, accurate, time-efficient, and adaptive traffic speed prediction for a growing transportation network.

The research on network optimization in InfiniBand (IB) networks has been evolved in several directions, e.g. increasing network utilization, fault-tolerance, congestion control, and energy-aware systems. However, for efficient HPC clouds based on IB, the optimization problem becomes both complex and multi-dimensional, while individually proposed solutions often yield contradictory management decisions. We believe that a holistic closed-loop control system is required to effectively incorporate multidimensional objective function in future IB systems. Based on control theory, a self-adaptive model for the IB subnet system, may help acheiving better network utilization while effectively keeping user level SLAs in HPC clouds.

Interconnection networks are key components in High-Performance Computing (HPC) systems, their performance having a strong influence on the overall system one. However, at high load, congestion and its negative effects (e.g. Head-of-line blocking) threaten the performance of the network, and so the one of the entire system. Congestion control (CC) is crucial to ensure an efficient utilization of the interconnection network during congestion situations. As one major trend is to reduce the effective wiring in interconnection networks to reduce cost and power consumption, the network will operate very close to its capacity. Thus, congestion control becomes essential. Existing CC techniques can be divided into two general approaches. One is to throttle traffic injection at the sources that contribute to congestion, and the other is to isolate the congested traffic in specially designated resources. However, both approaches have different, but non-overlapping weaknesses: injection throttling techniques have a slow reaction against congestion, while isolating traffic in special resources may lead the system to run out of those resources. In this paper we propose EcoCC, a new Efficient and Cost-Effective CC technique, that combines injection throttling and congested-flow isolation to minimize their respective drawbacks and maximize overall system performance. This new strategy is suitable for current commercial switch architectures, where it could be implemented without requiring significant complexity. Experimental results, using simulations under synthetic and real tracebased traffic patterns, show that this technique improves by up to 55% over some of the most successful congestion control techniques.

This short abstract describes a demonstration proposal for the NorNet Core testbed for multi-homed systems.

In supercomputers and modern data center clusters lossless interconnection networks are frequently used to achieve high throughput and low latency. It has been known for three decades however, that congestion and congestion spreading in such networks can lead to severe performance degradation if no countermeasure is taken. Nevertheless, for a long time, the challenges related to network-wide congestion in lossless interconnection networks received little attention. A combination of tuning and tailoring of network characteristics for a given application, together with overprovisioning of network resources, kept congestion and congestion spreading from occurring in practice. To be able to dynamically manage congestion was then not really needed. During the last decade, however, we have seen a renewed interest in congestion management for lossless interconnection networks. The use of virtualization together with an increased focus on cost-efficient green computing have spawned a desire to operate networks with dynamic and unpredictable traffic patterns closer to saturation. As such, proper congestion management is needed. In this thesis, we study congestion management in lossless interconnection networks in general, while giving special attention to the congestion control mechanism specified for InfiniBand, currently one of the most popular interconnection network standards. The contributions of the thesis include guidelines on how to implement congestion detection in switches facilitating injection throttling at the source nodes to avoid unfair treatment of contributors to congestion; an exploration of the rich InfiniBand congestion control parameter space and the corresponding influence on the performance of the congestion control mechanism; a study of the scope of an injection throttling based congestion management mechanism, like the one specified for InfiniBand; an abstract classification scheme for congestion trees of varying degree of dynamics; and finally, two novel congestion management mechanisms for input buffered switches and switches utilizing virtual output queuing, respectively, to overcome the weaknesses of current congestion management mechanisms based on injection throttling or hot-flow dynamic isolation.

The Internet has made it possible to communicate and to use services over large geographical distances. While it has originally been built for less critical services like e-mail and file transfer, it is nowadays also increasingly often used for availability-critical services like e.g. e-commerce or healthcare. Clearly, the reachability of such services must be ensured by so-called multi-homing of endpoints. That is, endpoints are simultaneously connected to multiple Internet Service Providers (ISP) to provide redundancy. If one ISP has problems, it is intended that the connection to another one still works. However, such assumptions have never been verified in real, large-scale setups. The intention of the NorNet project is to build up a realistic Internet testbed for multi-homing. In this paper, we describe the design of NorNet with focus on the implementation of its fixed-line part: NorNet Core. This paper is intended to give researchers an overview of its mode of operation, its capabilities as well as its interesting feature realisations. The knowledge about these items is very useful to plan own experiments in the NorNet testbed.

In a lossless interconnection network, network congestion needs to be detected and resolved to ensure high performance and good utilization of network resources at high network load. If no countermeasure is taken, congestion at a node in the network will stimulate the growth of a congestion tree that not only affects contributors to congestion, but also other traffic flows in the network. Left untouched, the congestion tree will block traffic flows, lead to underutilization of network resources and result in a severe drop in network performance. The InfiniBand standard specifies a congestion control (CC) mechanism to detect and resolve congestion before a congestion tree is able to grow and, by that, hamper the network performance. The InfiniBand CC mechanism includes a rich set of parameters that can be tuned in order to achieve effective CC. Even though it has been shown that the CC mechanism, properly tuned, is able to improve both throughput and fairness in an interconnection network, it has been questioned whether the mechanism is fast enough to keep up with dynamic network traffic, and if a given set of parameter values for a topology is robust when it comes to different traffic patterns, or if the parameters need to be tuned depending on the applications in use. In this paper we address both these questions. Using the three-stage fat-tree topology from the Sun Datacenter InfiniBand Switch 648 as a basis, and a simulator tuned against CC capable InfiniBand hardware, we conduct a systematic study of the efficiency of the InfiniBand CC mechanism as the network traffic becomes increasingly more dynamic. Our studies show that the InfiniBand CC, even when using a single set of parameter values, performs very well as the traffic patterns becomes increasingly more dynamic, outperforming a network without CC in all cases. Our results show throughput increases varying from a few percent, to a seventeen-fold increase.

Existing fat-tree routing algorithms fully exploit the path diversity of a fat-tree topology in the context of compute node traffic, but they lack support for deadlock free and fully connected switch-to-switch communication. Such support is crucial for efficient system management, for example in InfiniBand (IB) systems. With the general increase in system management capabilities found in modern InfiniBand switches, the lack of deadlock free switch-to-switch communication is a problem for fat-tree based IB installations because management traffic might cause routing deadlocks that bring the whole system down. This lack of deadlock free communication affects all system management and diagnostic tools using LID routing. In this paper, we propose the sFtree routing algorithm that guarantees deadlock free and fully connected switch-to-switch communication in fat-trees while maintaining the properties of the current fat-tree algorithm. We prove that the algorithm is deadlock free and we implement it in OpenSM for evaluation. We evaluate the performance of the sFtree algorithm experimentally on a small cluster and we do a large-scale evaluation through simulations. The results confirm that the sFtree routing algorithm is deadlock free and show that the impact of switch-to-switch management traffic on the end-node traffic is negligible.

In InfiniBand networks congestion control (CC) can be an effective mechanism to achieve high performance and high utilisation of network resources. Without CC, congestion in one node may severely degrade overall performance. In this talk we introduce the problem of congestion and how it can be avoided with InfiniBand congestion control.

In lossless interconnection networks congestion control (CC) can be an effective mechanism to achieve high performance and good utilization of network resources. Without CC, congestion on one link may grow into a congestion tree that can degrade the performance severely. This degradation can affect not only contributors to the congestion, but also throttles innocent traffic flows in the network. The InfiniBand standard describes CC functionality for detecting and resolving congestion. The InfiniBand CC concept is rich in the way that it specifies a set of parameters that can be tuned in order to achieve effective CC. There is, however, limited experience with the InfiniBand CC mechanism. To the best of our knowledge, only a few simulation studies exist. Recently, InfiniBand CC has been implemented in hardware, and in this paper we present the first experiences with such equipment. We show that the implemented InfiniBand CC mechanism effectively resolves congestion and improves fairness by solving the parking lot problem, if the CC parameters are appropriately set. By conducting extensive testing on a selection of the CC parameters, we have explored the parameter space and found a subset of parameter values that leads to efficient CC for our test scenarios. Furthermore, we show that the InfiniBand CC increases the performance of the well known HPC Challenge benchmark in a congested network.

In InfiniBand networks congestion control (CC) can be an effective mechanism to achieve high performance and high utilisation of network resources. Without CC, congestion in one node may severely degrade overall performance. In this talk we introduce the problem of congestion and how it can be avoided with InfiniBand congestion control.

Invited talk about early experiences with InfiniBand Congestion Control implemented in Mellanox hardware. Held at the Mellanox booth at Supercomputing 2009, Portland, USA

One of the major reasons for playing Massive Multiplayer Online Role Playing Games (MMORPGs) is the possibility to show off your abilities to other players. The more rare your equipment is, the higher is the show off value of your character. And because rare items are hard to find cooperation between several players is often required. This introduces a conflict between the players, and a way to distribute loot is necessary. We introduce the problem of loot distribution in MMORPG, and we suggest and give a preliminary evaluation of a new and improved Dragon Kill Points system.