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

Efficient sharing mechanisms for virtualized multi-tenant heterogeneous networks

The explosion in data traffic, the physical resource constraints, and the insufficient financial incentives for deploying 5G networks, stress the need for a paradigm shift in network upgrades. Typically, operators are also the service providers, which charge the end users with low and flat tariffs, independently of the service enjoyed. A fine-scale management of the network resources is needed, both for optimizing costs and resource utilization, as well as for enabling new synergies among network owners and third-parties. In particular, operators could open their networks to third parties by means of fine-scale sharing agreements over customized networks for enhanced service provision, in exchange for an adequate return of investment for upgrading their infrastructures. The main objective of this thesis is to study the potential of fine-scale resource management and sharing mechanisms for enhancing service provision and for contributing to a sustainable road to 5G. More precisely, the state-of-the-art architectures and technologies for network programmability and scalability are studied, together with a novel paradigm for supporting service diversity and fine-scale sharing. We review the limits of conventional networks, we extend existing standardization efforts and define an enhanced architecture for enabling 5G networks' features (e.g., network-wide centralization and programmability). The potential of the proposed architecture is assessed in terms of flexible sharing and enhanced service provision, while the advantages of alternative business models are studied in terms of additional profits to the operators. We first study the data rate improvement achievable by means of spectrum and infrastructure sharing among operators and evaluate the profit increase justified by a better service provided. We present a scheme based on coalitional game theory for assessing the capability of accommodating more service requests when a cooperative approach is adopted, and for studying the conditions for beneficial sharing among coalitions of operators. Results show that: i) collaboration can be beneficial also in case of unbalanced cost redistribution within coalitions; ii) coalitions of equal-sized operators provide better profit opportunities and require lower tariffs. The second kind of sharing interaction that we consider is the one between operators and third-party service providers, in the form of fine-scale provision of customized portions of the network resources. We define a policy-based admission control mechanism, whose performance is compared with reference strategies. The proposed mechanism is based on auction theory and computes the optimal admission policy at a reduced complexity for different traffic loads and allocation frequencies. Because next-generation services include delay-critical services, we compare the admission control performances of conventional approaches with the proposed one, which proves to offer near real-time service provision and reduced complexity. Besides, it guarantees high revenues and low expenditures in exchange for negligible losses in terms of fairness towards service providers. To conclude, we study the case where adaptable timescales are adopted for the policy-based admission control, in order to promptly guarantee service requirements over traffic fluctuations. In order to reduce complexity, we consider the offline pre­computation of admission strategies with respect to reference network conditions, then we study the extension to unexplored conditions by means of computationally efficient methodologies. Performance is compared for different admission strategies by means of a proof of concept on real network traces. Results show that the proposed strategy provides a tradeoff in complexity and performance with respect to reference strategies, while reducing resource utilization and requirements on network awareness.La explosion del trafico de datos, los recursos limitados y la falta de incentivos para el desarrollo de 5G evidencian la necesidad de un cambio de paradigma en la gestion de las redes actuales. Los operadores de red suelen ser tambien proveedores de servicios, cobrando tarifas bajas y planas, independientemente del servicio ofrecido. Se necesita una gestion de recursos precisa para optimizar su utilizacion, y para permitir nuevas sinergias entre operadores y proveedores de servicios. Concretamente, los operadores podrian abrir sus redes a terceros compartiendolas de forma flexible y personalizada para mejorar la calidad de servicio a cambio de aumentar sus ganancias como incentivo para mejorar sus infraestructuras. El objetivo principal de esta tesis es estudiar el potencial de los mecanismos de gestion y comparticion de recursos a pequei\a escala para trazar un camino sostenible hacia el 5G. En concreto, se estudian las arquitecturas y tecnolog fas mas avanzadas de "programabilidad" y escalabilidad de las redes, junto a un nuevo paradigma para la diversificacion de servicios y la comparticion de recursos. Revisamos los limites de las redes convencionales, ampliamos los esfuerzos de estandarizacion existentes y definimos una arquitectura para habilitar la centralizacion y la programabilidad en toda la red. La arquitectura propuesta se evalua en terminos de flexibilidad en la comparticion de recursos, y de mejora en la prestacion de servicios, mientras que las ventajas de un modelo de negocio alternativo se estudian en terminos de ganancia para los operadores. En primer lugar, estudiamos el aumento en la tasa de datos gracias a un uso compartido del espectro y de las infraestructuras, y evaluamos la mejora en las ganancias de los operadores. Presentamos un esquema de admision basado en la teoria de juegos para acomodar mas solicitudes de servicio cuando se adopta un enfoque cooperativo, y para estudiar las condiciones para que la reparticion de recursos sea conveniente entre coaliciones de operadores. Los resultados ensei\an que: i) la colaboracion puede ser favorable tambien en caso de una redistribucion desigual de los costes en cada coalicion; ii) las coaliciones de operadores de igual tamai\o ofrecen mejores ganancias y requieren tarifas mas bajas. El segundo tipo de comparticion que consideramos se da entre operadores de red y proveedores de servicios, en forma de provision de recursos personalizada ya pequei\a escala. Definimos un mecanismo de control de trafico basado en polfticas de admision, cuyo rendimiento se compara con estrategias de referencia. El mecanismo propuesto se basa en la teoria de subastas y calcula la politica de admision optima con una complejidad reducida para diferentes cargas de trafico y tasa de asignacion. Con particular atencion a servicios 5G de baja latencia, comparamos las prestaciones de estrategias convencionales para el control de admision con las del metodo propuesto, que proporciona: i) un suministro de servicios casi en tiempo real; ii) una complejidad reducida; iii) unos ingresos elevados; y iv) unos gastos reducidos, a cambio de unas perdidas insignificantes en terminos de imparcialidad hacia los proveedores de servicios. Para concluir, estudiamos el caso en el que se adoptan escalas de tiempo adaptables para el control de admision, con el fin de garantizar puntualmente los requisitos de servicio bajo diferentes condiciones de trafico. Para reducir la complejidad, consideramos el calculo previo de las estrategias de admision con respecto a condiciones de red de referenda, adaptables a condiciones inexploradas por medio de metodologias computacionalmente eficientes. Se compara el rendimiento de diferentes estrategias de admision sobre trazas de trafico real. Los resultados muestran que la estrategia propuesta equilibra complejidad y ganancias, mientras se reduce la utilizacion de recursos y la necesidad de conocer el estado exacto de la red.Postprint (published version

Performance controls for distributed telecommunication services

As the Internet and Telecommunications domains merge, open telecommunication service architectures such as TINA, PARLAY and PINT are becoming prevalent. Distributed Computing is a common engineering component in these technologies and promises to bring improvements to the scalability, reliability and flexibility of telecommunications service delivery systems. This distributed approach to service delivery introduces new performance concerns. As service logic is decomposed into software components and distnbuted across network resources, significant additional resource loading is incurred due to inter-node communications. This fact makes the choice of distribution of components in the network and the distribution of load between these components critical design and operational issues which must be resolved to guarantee a high level of service for the customer and a profitable network for the service operator. Previous research in the computer science domain has addressed optimal placement of components from the perspectives of minimising run time, minimising communications costs or balancing of load between network resources. This thesis proposes a more extensive optimisation model, which we argue, is more useful for addressing concerns pertinent to the telecommunications domain. The model focuses on providing optimal throughput and profitability of network resources and on overload protection whilst allowing flexibility in terms of the cost of installation of component copies and differentiation in the treatment of service types, in terms of fairness to the customer and profitability to the operator. Both static (design-time) component distribution and dynamic (run-time) load distribution algorithms are developed using Linear and Mixed Integer Programming techniques. An efficient, but sub-optimal, run-time solution, employing Market-based control, is also proposed. The performance of these algorithms is investigated using a simulation model of a distributed service platform, which is based on TINA service components interacting with the Intelligent Network through gateways. Simulation results are verified using Layered Queuing Network analytic modelling Results show significant performance gains over simpler methods of performance control and demonstrate how trade-offs in network profitability, fairness and network cost are possible

Distributed game

Dissertação de mestrado em Engenharia InformáticaThe demand for online games has risen over the years, expanding multiplayer support for new and different game genres. Among them are Massively Multiplayer Online games, one of the most popular and successful game types in the industry. Nowadays, this industry is thriving, evolving alongside technological advancements and producing billions in revenue, making it an economic importance. However, as the complexity of these games grows, so do the challenges they face when constructing them. This dissertation aims to implement a distributed game, through a proof of concept or an existing game, using a distributed architecture to acquire knowledge in the construction of such complex systems and the effort involved in dealing with consistency, maintaining communication infrastructure, and managing data in a distributed way. It is also intended that this project implements multiple mechanisms capable of autonomously helping manage and maintain the correct state of the system. To evaluate the proposed solution, a detailed analysis is carried out with performance benchmark analysis, stress testing, followed by an examination of its security, scalability, and distribution’s resilience. Overall, the present research work allowed for a greater understanding of the technologies and approaches used in constructing a gaming system, establishing a new set of development opportunities to be further investi gated upon the constructed solution.A procura por jogos online aumentou ao longo dos anos, expandindo o suporte multiplayer para novos e diferentes géneros. Entre estes estão os jogos Massively Multiplayer Online, um dos tipos de jogos mais populares e bem-sucedidos na indústria. Atualmente, esta indústria está a prosperar, evoluindo com os avanços tecnológicos e gerando milhares de milhões em receita, tornando-se uma importância económica. Porém, à medida que a complexidade destes jogos aumenta, também aumenta os problemas encontrados durante a sua construção. Esta dissertação tem como objetivo implementar um jogo distribuído, através de uma prova de conceito ou um jogo existente, usando uma arquitetura distribuída a fim de adquirir conhecimento na construção destes sistemas complexos e o esforço envolvido em lidar com consistência, manter a infraestrutura de comunicação e gerir dados de maneira distribuída. Para isto, é pretendido que este projeto também implemente vários mecanismos capazes de, forma autônoma, ajudar a gerir e manter o correto estado do sistema. Para avaliar o solução proposta, uma análise detalhada é realizada sobre o desempenho, segurança, escalabilidade e resiliência da distribuição do sistema. De forma geral, o presente trabalho de pesquisa permitiu uma maior compreensão das tecnologias e abordagens utilizadas na construção de um sistema de jogos, estabelecendo um novo conjunto de oportunidades de desenvolvimento a serem investigadas sobre a solução construída

Pooling and polling : creation of pooling in inventory and queueing models

The subject of the present monograph is the ‘Creation of Pooling in Inventory and Queueing Models’. This research consists of the study of sharing a scarce resource (such as inventory, server capacity, or production capacity) between multiple customer classes. This is called pooling, where the goal is to achieve cost or waiting time reductions. For the queueing and inventory models studied, both theoretical, scientific insights, are generated, as well as strategies which are applicable in practice. This monograph consists of two parts: pooling and polling. In both research streams, a scarce resource (inventory or server capacity, respectively production capacity) has to be shared between multiple users. In the first part of the thesis, pooling is applied to multi-location inventory models. It is studied how cost reduction can be achieved by the use of stock transfers between local warehouses, so-called lateral transshipments. In this way, stock is pooled between the warehouses. The setting is motivated by a spare parts inventory network, where critical components of technically advanced machines are kept on stock, to reduce down time durations. We create insights into the question when lateral transshipments lead to cost reductions, by studying several models. Firstly, a system with two stock points is studied, for which we completely characterize the structure of the optimal policy, using dynamic programming. For this, we formulate the model as a Markov decision process. We also derived conditions under which simple, easy to implement, policies are always optimal, such as a hold back policy and a complete pooling policy. Furthermore, we identified the parameter settings under which cost savings can be achieved. Secondly, we characterize the optimal policy structure for a multi-location model where only one stock point issues lateral transshipments, a so-called quick response warehouse. Thirdly, we apply the insights generated to the general multi-location model with lateral transshipments. We propose the use of a hold back policy, and construct a new approximation algorithm for deriving the performance characteristics. It is based on the use of interrupted Poisson processes. The algorithm is shown to be very accurate, and can be used for the optimization of the hold back levels, the parameters of this class of policies. Also, we study related inventory models, where a single stock point servers multiple customers classes. Furthermore, the pooling of server capacity is studied. For a two queue model where the head-of-line processor sharing discipline is applied, we derive the optimal control policy for dividing the servers attention, as well as for accepting customers. Also, a server farm with an infinite number of servers is studied, where servers can be turned off after a service completion in order to save costs. We characterize the optimal policy for this model. In the second part of the thesis polling models are studied, which are queueing systems where multiple queues are served by a single server. An application is the production of multiple types of products on a single machine. In this way, the production capacity is pooled between the product types. For the classical polling model, we derive a closedform approximation for the mean waiting time at each of the queues. The approximation is based on the interpolation of light and heavy traffic results. Also, we study a system with so-called smart customers, where the arrival rate at a queue depends on the position of the server. Finally, we invent two new service disciplines (the gated/exhaustive and the ??-gated discipline) for polling models, designed to yield ’fairness and efficiency’ in the mean waiting times. That is, they result in almost equal mean waiting times at each of the queues, without increasing the weighted sum of the mean waiting times too much

Scalable download protocols

Scalable on-demand content delivery systems, designed to effectively handle increasing request rates, typically use service aggregation or content replication techniques. Service aggregation relies on one-to-many communication techniques, such as multicast, to efficiently deliver content from a single sender to multiple receivers. With replication, multiple geographically distributed replicas of the service or content share the load of processing client requests and enable delivery from a nearby server.Previous scalable protocols for downloading large, popular files from a single server include batching and cyclic multicast. Analytic lower bounds developed in this thesis show that neither of these protocols consistently yields performance close to optimal. New hybrid protocols are proposed that achieve within 20% of the optimal delay in homogeneous systems, as well as within 25% of the optimal maximum client delay in all heterogeneous scenarios considered.In systems utilizing both service aggregation and replication, well-designed policies determining which replica serves each request must balance the objectives of achieving high locality of service, and high efficiency of service aggregation. By comparing classes of policies, using both analysis and simulations, this thesis shows that there are significant performance advantages in using current system state information (rather than only proximities and average loads) and in deferring selection decisions when possible. Most of these performance gains can be achieved using only “local” (rather than global) request information.Finally, this thesis proposes adaptations of already proposed peer-assisted download techniques to support a streaming (rather than download) service, enabling playback to begin well before the entire media file is received. These protocols split each file into pieces, which can be downloaded from multiple sources, including other clients downloading the same file. Using simulations, a candidate protocol is presented and evaluated. The protocol includes both a piece selection technique that effectively mediates the conflict between achieving high piece diversity and the in-order requirements of media file playback, as well as a simple on-line rule for deciding when playback can safely commence

Climbing Up Cloud Nine: Performance Enhancement Techniques for Cloud Computing Environments

With the transformation of cloud computing technologies from an attractive trend to a business reality, the need is more pressing than ever for efficient cloud service management tools and techniques. As cloud technologies continue to mature, the service model, resource allocation methodologies, energy efficiency models and general service management schemes are not yet saturated. The burden of making this all tick perfectly falls on cloud providers. Surely, economy of scale revenues and leveraging existing infrastructure and giant workforce are there as positives, but it is far from straightforward operation from that point. Performance and service delivery will still depend on the providers’ algorithms and policies which affect all operational areas. With that in mind, this thesis tackles a set of the more critical challenges faced by cloud providers with the purpose of enhancing cloud service performance and saving on providers’ cost. This is done by exploring innovative resource allocation techniques and developing novel tools and methodologies in the context of cloud resource management, power efficiency, high availability and solution evaluation. Optimal and suboptimal solutions to the resource allocation problem in cloud data centers from both the computational and the network sides are proposed. Next, a deep dive into the energy efficiency challenge in cloud data centers is presented. Consolidation-based and non-consolidation-based solutions containing a novel dynamic virtual machine idleness prediction technique are proposed and evaluated. An investigation of the problem of simulating cloud environments follows. Available simulation solutions are comprehensively evaluated and a novel design framework for cloud simulators covering multiple variations of the problem is presented. Moreover, the challenge of evaluating cloud resource management solutions performance in terms of high availability is addressed. An extensive framework is introduced to design high availability-aware cloud simulators and a prominent cloud simulator (GreenCloud) is extended to implement it. Finally, real cloud application scenarios evaluation is demonstrated using the new tool. The primary argument made in this thesis is that the proposed resource allocation and simulation techniques can serve as basis for effective solutions that mitigate performance and cost challenges faced by cloud providers pertaining to resource utilization, energy efficiency, and client satisfaction

Final report on the evaluation of RRM/CRRM algorithms

Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin