Prediction of the impact of network switch utilization on application performance via active measurement

Although one of the key characteristics of High Performance Computing (HPC) infrastructures are their fast interconnecting networks, the increasingly large computational capacity of HPC nodes and the subsequent growth of data exchanges between them constitute a potential performance bottleneck. To achieve high performance in parallel executions despite network limitations, application developers require tools to measure their codes’ network utilization and to correlate the network’s communication capacity with the performance of their applications. This paper presents a new methodology to measure and understand network behavior. The approach is based in two different techniques that inject extra network communication. The first technique aims to measure the fraction of the network that is utilized by a software component (an application or an individual task) to determine the existence and severity of network contention. The second injects large amounts of network traffic to study how applications behave on less capable or fully utilized networks. The measurements obtained by these techniques are combined to predict the performance slowdown suffered by a particular software component when it shares the network with others. Predictions are obtained by considering several training sets that use raw data from the two measurement techniques. The sensitivity of the training set size is evaluated by considering 12 different scenarios. Our results find the optimum training set size to be around 200 training points. When optimal data sets are used, the proposed methodology provides predictions with an average error of 9.6% considering 36 scenarios.With the support of the Secretary for Universities and Research of the Ministry of Economy and Knowledge of the Government of Catalonia and the Cofund programme of the Marie Curie Actions of the 7th R&D Framework Programme of the European Union (Expedient 2013BP_B00243). The research leading to these results has received funding from the European Research Council under the European Union’s 7th FP (FP/2007-2013) /ERC GA n. 321253. Work partially supported by the Spanish Ministry of Science and Innovation (TIN2012-34557)Peer ReviewedPostprint (author's final draft

Simple network management protocol co- existence with hydrocarbon process automation communication real-time network

Hydrocarbon Process Automation Applications (HPAA) utilizes Real-time network connecting process instrumentations, controllers, and real-time logic control applications. Conventional practice is to dedicate a real-time network for process automation applications and prevent other applications from utilizing the same infrastructure. An important application that can help optimize, improve network performance, and provide rapid response time in network diagnostics and mitigation is Simple Network Management Protocol (SNMP). This paper addresses the co-existence of SNMP traffic with real-time applications. The impacts of activating this protocol with the real-time HPAA utilizing high speed Ethernet network design will be examined. Empirical data for an implemented Hydrocarbon process automation system will be used to illustrate the interdependency of application performance, traffic mix, and potential areas of improvements. The outcomes of this effort demonstrate the co-existence of SNMP with HPPA, given special considerations (i.e., bandwidth, number of applications, etc.)

A Survey of Green Networking Research

Reduction of unnecessary energy consumption is becoming a major concern in wired networking, because of the potential economical benefits and of its expected environmental impact. These issues, usually referred to as "green networking", relate to embedding energy-awareness in the design, in the devices and in the protocols of networks. In this work, we first formulate a more precise definition of the "green" attribute. We furthermore identify a few paradigms that are the key enablers of energy-aware networking research. We then overview the current state of the art and provide a taxonomy of the relevant work, with a special focus on wired networking. At a high level, we identify four branches of green networking research that stem from different observations on the root causes of energy waste, namely (i) Adaptive Link Rate, (ii) Interface proxying, (iii) Energy-aware infrastructures and (iv) Energy-aware applications. In this work, we do not only explore specific proposals pertaining to each of the above branches, but also offer a perspective for research.Comment: Index Terms: Green Networking; Wired Networks; Adaptive Link Rate; Interface Proxying; Energy-aware Infrastructures; Energy-aware Applications. 18 pages, 6 figures, 2 table