Reducing Internet Latency : A Survey of Techniques and their Merit

Bob Briscoe, Anna Brunstrom, Andreas Petlund, David Hayes, David Ros, Ing-Jyh Tsang, Stein Gjessing, Gorry Fairhurst, Carsten Griwodz, Michael WelzlPeer reviewedPreprin

Queueing networks: solutions and applications

During the pasttwo decades queueing network models have proven to be a versatile tool for computer system and computer communication system performance evaluation. This chapter provides a survey of th field with a particular emphasis on applications. We start with a brief historical retrospective which also servesto introduce the majr issues and application areas. Formal results for product form queuenig networks are reviewed with particular emphasis on the implications for computer systems modeling. Computation algorithms, sensitivity analysis and optimization techniques are among the topics covered. Many of the important applicationsof queueing networks are not amenableto exact analysis and an (often confusing) array of approximation methods have been developed over the years. A taxonomy of approximation methods is given and used as the basis for for surveing the major approximation methods that have been studied. The application of queueing network to a number of areas is surveyed, including computer system cpacity planning, packet switching networks, parallel processing, database systems and availability modeling.Durante as últimas duas décadas modelos de redes de filas provaram ser uma ferramenta versátil para avaliação de desempenho de sistemas de computação e sistemas de comunicação. Este capítulo faz um apanhado geral da área, com ênfase em aplicações. Começamos com uma breve retrospectiva histórica que serve também para introduzir os pontos mais importantes e as áreas de aplicação. Resultados formais para redes de filas em forma de produto são revisados com ênfase na modelagem de sistemas de computação. Algoritmos de computação, análise de sensibilidade e técnicas de otimização estão entre os tópicos revistos. Muitas dentre importantes aplicações de redes de filas não são tratáveis por análise exata e uma série (frequentemente confusa) de métodos de aproximação tem sido desenvolvida. Uma taxonomia de métodos de aproximação é dada e usada como base para revisão dos mais importantes métodos de aproximação propostos. Uma revisão das aplicações de redes de filas em um número de áreas é feita, incluindo planejamento de capacidade de sistemas de computação, redes de comunicação por chaveamento de pacotes, processamento paralelo, sistemas de bancos de dados e modelagem de confiabilidade

Energy-Efficient Interconnection Networks for High-Performance Computing

In recent years, energy has become one of the most important factors for de- signing and operating large scale computing systems. This is particularly true in high-performance computing, where systems often consist of thousands of nodes. Especially after the end of Dennard’s scaling, the demand for energy- proportionality in components, where energy is depending linearly on utilization, increases continuously. As the main contributor to the overall power consumption, processors have received the main attention so far. The increasing energy proportionality of processors, however, shifts the focus to other components such as interconnection networks. Their share of the overall power consumption is expected to increase to 20% or more while other components further increase their efficiency in the near future. Hence, it is crucial to improve energy proportionality in interconnection networks likewise to reduce overall power and energy consumption. To facilitate these attempts, this work provides comprehensive studies about energy saving in interconnection networks at different levels. First, interconnection networks differ fundamentally from other components in their underlying technology. To gain a deeper understanding of these differences and to identify targets for energy savings, this work provides a detailed power analysis of current network hardware. Furthermore, various applications at different scales are analyzed regarding their communication patterns and locality properties. The findings show that communication makes up only a small fraction of the execution time and networks are actually idling most of the time. Another observation is that point-to-point communication often only occurs within various small subsets of all participants, which indicates that a coordinated mapping could further decrease network traffic. Based on these studies, three different energy-saving policies are designed, which all differ in their implementation and focus. Then, these policies are evaluated in an event-based, power-aware network simulator. While two policies that operate completely local at link level, enable significant energy savings of more than 90% in most analyses, the hybrid one does not provide further benefits despite significant additional design effort. Additionally, these studies include network design parameters, such as transition time between different link configurations, as well as the three most common topologies in supercomputing systems. The final part of this work addresses the interactions of congestion management and energy-saving policies. Although both network management strategies aim for different goals and use opposite approaches, they complement each other and can increase energy efficiency in all studies as well as improve the performance overhead as opposed to plain energy saving

Taguchi approach for performance evaluation of service-oriented software systems.

Service-oriented software systems are becoming increasingly common in the world today as big companies such as Microsoft and IBM advocate approaches focusing on assembly of system from distributed services. Although performance of such systems is a big problem, there is surprisingly an obvious lack of attention for evaluating the performance of enterprise-scale, service-oriented software systems. This thesis investigates the application of statistical tools in performance engineering domain for total quality management. In particular, the Taguchi approach is used as an efficient and systematic way to optimize designs for performance, quality, and cost. The aim is to improve the performance of software systems and to reduce application development cost by assembling services from known vendors or intranet services. The focus of this thesis is on the response time of service-oriented systems. Nevertheless, the developed methodology also applies to other performance issues, such as memory management and caching. The interaction problems of those issues are preserved for future work.Dept. of Computer Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .L585. Source: Masters Abstracts International, Volume: 43-01, page: 0240. Adviser: Xiaobu Yuan. Thesis (M.Sc.)--University of Windsor (Canada), 2004

LoGPC: Modeling Network Contention in Message-Passing Programs

In many real applications, for example those with frequent and irregular communication patterns or those using large messages, network contention and contention for message processing resources can be a significant part of the total execution time. This paper presents a new cost model, called LoGPC, that extends the LogP [9] and LogGP [4] models to account for the impact of network contention and network interface DMA behavior on the performance of message-passing programs. We validate LoGPC by analyzing three applications implemented with Active Messages [11, 18] on the MIT Alewife multiprocessor. Our analysis shows that network contention accounts for up to 50% of the total execution time. In addition, we show that the impact of communication locality on the communication costs is at most a factor of two on Alewife. Finally, we use the model to identify tradeoffs between synchronous and asynchronous message passing styles. 1 Introduction Users of parallel machines need good performa..

Analyzing Data-center Application Performance Via Constraint-based Models

Hyperscale Data Centers (HDCs) are the largest distributed computing machines ever constructed. They serve as the backbone for many popular applications, such as YouTube, Netflix, Meta, and Airbnb, which involve millions of users and generate billions in revenue. As the networking infrastructure plays a pivotal role in determining the performance of HDC applications, understanding and optimizing their networking performance is critical. This thesis proposes and evaluates a constraint-based approach to characterize the networking performance of HDC applications. Through extensive evaluations conducted in both controlled settings and real-world case studies within a production HDC, I demonstrated the effectiveness of the constraint-based approach in handling the immense volume of performance data in HDCs, achieving tremendous dimension reduction, and providing very useful interpretability.Doctor of Philosoph

The Design and Implementation of Low-Latency Prediction Serving Systems

Machine learning is being deployed in a growing number of applications which demand real- time, accurate, and cost-efficient predictions under heavy query load. These applications employ a variety of machine learning frameworks and models, often composing several models within the same application. However, most machine learning frameworks and systems are optimized for model training and not deployment.In this thesis, I discuss three prediction serving systems designed to meet the needs of modern interactive machine learning applications. The key idea in this work is to utilize a decoupled, layered design that interposes systems on top of training frameworks to build low-latency, scalable serving systems. Velox introduced this decoupled architecture to enable fast online learning and model personalization in response to feedback. Clipper generalized this system architecture to be framework-agnostic and introduced a set of optimizations to reduce and bound prediction latency and improve prediction throughput, accuracy, and robustness without modifying the underlying machine learning frameworks. And InferLine provisions and manages the individual stages of prediction pipelines to minimize cost while meeting end-to-end tail latency constraints

Greediness control algorithm for multimedia streaming in wireless local area networks

This work investigates the interaction between the application and transport layers while streaming multimedia in a residential Wireless Local Area Network (WLAN). Inconsistencies have been identified that can have a severe impact on the Quality of Experience (QoE) experienced by end users. This problem arises as a result of the streaming processes reliance on rate adaptation engines based on congestion avoidance mechanisms, that try to obtain as much bandwidth as possible from the limited network resources. These upper transport layer mechanisms have no knowledge of the media which they are carrying and as a result treat all traffic equally. This lack of knowledge of the media carried and the characteristics of the target devices results in fair bandwidth distribution at the transport layer but creates unfairness at the application layer. This unfairness mostly affects user perceived quality when streaming high quality multimedia. Essentially, bandwidth that is distributed fairly between competing video streams at the transport layer results in unfair application layer video quality distribution. Therefore, there is a need to allow application layer streaming solutions, tune the aggressiveness of transport layer congestion control mechanisms, in order to create application layer QoE fairness between competing media streams, by taking their device characteristics into account. This thesis proposes the Greediness Control Algorithm (GCA), an upper transport layer mechanism that eliminates quality inconsistencies caused by rate / congestion control mechanisms while streaming multimedia in wireless networks. GCA extends an existing solution (i.e. TCP Friendly Rate Control (TFRC)) by introducing two parameters that allow the streaming application to tune the aggressiveness of the rate estimation and as a result, introduce fair distribution of quality at the application layer. The thesis shows that this rate adaptation technique, combined with a scalable video format allows increased overall system QoE. Extensive simulation analysis demonstrate that this form of rate adaptation increases the overall user QoE achieved via a number of devices operating within the same home WLAN

Expressive Policy-Based Access Control for Resource-Constrained Devices

Upcoming smart scenarios enabled by the Internet of Things envision smart objects that expose services that can adapt to user behavior or be managed with the goal of achieving higher productivity, often in multi-stakeholder applications. In such environments, smart things are cheap sensors (and actuators) and, therefore, constrained devices. However, they are also critical components because of the importance of the provided information. Therefore, strong security is a must. Nevertheless, existing feasible approaches do not cope well with the principle of least privilege; they lack both expressiveness and the ability to update the policy to be enforced in the sensors. In this paper, we propose an access control model that comprises a policy language that provides dynamic fine-grained policy enforcement in the sensors based on local context conditions. This dynamic policy cycle requires a secure, efficient, and traceable message exchange protocol. For that purpose, a security protocol called Hidra is also proposed. A security and performance evaluation demonstrates the feasibility and adequacy of the proposed protocol and access control model.This work was supported in part by the Training and Research Unit through UPV/EHU under Grant UFI11/16 and in part by the Department of Economic Development and Competitiveness of the Basque Government through the Security Technologies SEKUTEK Collaborative Research Projec