Network traffic characterisation, analysis, modelling and simulation for networked virtual environments

Networked virtual environment (NVE) refers to a distributed software system where a simulation, also known as virtual world, is shared over a data network between several users that can interact with each other and the simulation in real-time. NVE systems are omnipresent in the present globally interconnected world, from entertainment industry, where they are one of the foundations for many video games, to pervasive games that focus on e-learning, e-training or social studies. From this relevance derives the interest in better understanding the nature and internal dynamics of the network tra c that vertebrates these systems, useful in elds such as network infrastructure optimisation or the study of Quality of Service and Quality of Experience related to NVE-based services. The goal of the present work is to deepen into this understanding of NVE network tra c by helping to build network tra c models that accurately describe it and can be used as foundations for tools to assist in some of the research elds enumerated before. First contribution of the present work is a formal characterisation for NVE systems, which provides a tool to determine which systems can be considered as NVE. Based on this characterisation it has been possible to identify numerous systems, such as several video games, that qualify as NVE and have an important associated literature focused on network tra c analysis. The next contribution has been the study of this existing literature from a NVE perspective and the proposal of an analysis pipeline, a structured collection of processes and techniques to de ne microscale network models for NVE tra c. This analysis pipeline has been tested and validated against a study case focused on Open Wonderland (OWL), a framework to build NVE systems of di erent purpose. The analysis pipeline helped to de ned network models from experimental OWL tra c and assessed on their accuracy from a statistical perspective. The last contribution has been the design and implementation of simulation tools based on the above OWL models and the network simulation framework ns-3. The purpose of these simulations was to con rm the validity of the OWL models and the analysis pipeline, as well as providing potential tools to support studies related to NVE network tra c. As a result of this nal contribution, it has been proposed to exploit the parallelisation potential of these simulations through High Throughput Computing techniques and tools, aimed to coordinate massively parallel computing workloads over distributed resources

Interaktive latenzkritische Anwendungen in mobilen Ad-hoc Netzen

In this thesis we discuss the challenges that latency-sensitive interactive applications face in mobile ad-hoc networks. By using multi-player games as an example, we argue that the traditional client-server architecture is unsuitable for this new environment. We consequently create a novel communication architecture as well as quality of service mechanisms that can support the network requirements of such applications in mobile environments. By using a number of distributed zone servers that are selected and managed dynamically by our server selection algorithm, we provide a scalable approach that offers the necessary redundancy. Furthermore, we propose additional quality of service mechanisms to reduce latency and packet loss for interactive applications. We evaluate our approach through network simulation and realistic mobile gaming scenarios. The performance of our evaluation is checked against real-world measurements.In dieser Arbeit werden die Probleme und Herausforderungen von latenz-kritischen interactiven Computeranwendungen in mobilen Ad-hoc Netzen untersucht. Am Beispiel von Mehrbenutzercomputerspielen zeigen wir, dass traditionelle Client-Server Architekturen für diese neuen Umgebungen ungeeignet sind. Im Rahmen dieser Arbeit wird daher eine neue Kommunikationsarchitektur sowie verschiedene Mechanismen zur Erhöhung der Dienstgüte vorgeschlagen. Mit Hilfe von Zonenserver, die durch den Serverauswahlalgorithmus ausgesucht und verwaltet werden zeigen wir einen Ansatz auf, der sowohl bezüglich der Netzgröße skalierbar ist als auch die notwendige Redundanz bereitstellt. Wir zeigen die Funktionalität und die Leistung unseres Ansatzes mit Hilfe von Netzsimulationen bei denen realistische Szenarien für mobiles Spielen simuliert werden. Der hierbei benutze Netzsimulator wurde dafür auf Basis von eigenen Messungen verbessert und für das jeweilige Szenario passend eingestellt

Quality of service routing for real-time traffic

Imperial Users onl

Design, Implementation, and Evaluation of Join and Split Strategy for Transmission control protocol running on Software Defined Networks

Software Defined Networks (SDN)-enabled switches of today can be empowered to intelligently forward as well as elastically steer the network traffic. In this work, we focus on developing a SDN-based framework to provide improved delivery performance (of applications) in the network. This dissertation proposed a new TCP join and split proxy on SDN platform. The proposed framework allowed part of TCP (Transmission Control Protocol) optimization to migrate from the application server to the proxy. Therefore, with a control plane built between SDN controller and proxy, the SDN controller can further improve the TCP delivery performance. The proxy (join-proxy) joins all TCP flows at the beginning of the shared path into one long TCP flow. At the end of the shared path, the proxy (split-proxy) splits the long flow for each joined client with the same TCP session state. With the help of centralized controller of SDN and customized SDN switch, the new design simplifies the TCP session synchronization between proxies. Also, this dissertation developed Linked-ACK ((Acknowledgement) to maintain the end-to-end semantic and limit the buffer size in each proxy by coupling the ACK of three TCP flows separated by the join and split proxy. At the last, this dissertation shows that the proposed proxy can well integrate with wireless network and MPTCP (Multi-Path TCP) proxy [1] The extensions of the proposed TCP Join and Split platform are applied to Smart Grid network for improving fairness, WiFi network for reducing gaming traffic delay, and Data Center network for addressing Virtual Machine (VM) live migration problem. First, the proposed TCP Join and Split platform can be applied to Smart Grid network to provide better fairness on the application layer. The latest research in Smart Grid communications has advocated the aggregation of multiple traffic flows in order to achieve an improved throughput. While aggregation improves the overall throughput, the individual flows still suffer from unfair throughput performance. As a result, the enablers for time sensitive Smart Grid services, such as load-shedding which requires a timely report of data, are mostly affected. This dissertation proposed a novel SDN-based framework to provide fairness among smart-meters (SMs) through flow aggregation and scheduling. By exploring the SDN’s flow-level manageability features, for the first time in this paper, we present an implementation-based architecture to perform effective aggregation-and-scheduling of traffic flows. The proposed framework ensures fairness (among the smart-meters) as well as improve the throughput performance. Our extensive experimental results validate the efficacy of our proposed framework. Second, the proposed TCP Join and Split platform can be applied to WiFi network to reduce the gaming traffic delay. WiFi users typically expect different performance requirements for various types of applications. For instance, users expect 'better and consistent throughput' for Internet video consumption, and 'minimal delay' for local network gaming applications. The wireless access substrate (at the consumer-end), typically being the bottleneck in these networks, causes different users (in the same WiFi coverage) to experience unfair and fluctuating network performance. To combat such unfair situations, we need approaches to effectively control and steer the applications’ traffic in the shared WiFi medium. However, a network that deals with a crowd or private end-users (such as gaming multiplayers or the Internet content distributors), encounters a major challenge in controlling the traffic without involvement or modification at the end-host application devices. In this dissertation, we propose a SDN-based seamless traffic steering and control strategy in order to provide effective application-specific delivery services, such as reduced delay (for gaming traffic) and improved throughput (for video consumption). Unlike simulation-based solutions, our approach is production-ready, as we have implemented our framework on a real network testbed environment. With extensive performance study and sufficient mathematical insight, we demonstrate the prowess of our proposed framework. Last but not the least, the proposed TCP Join and Split platform can be applied to Data Center network to optimize the VM live migration. With the growth of data volumes and a variety of Internet applications, virtualization has become commonplace in modern data centers and an effective solution to provide better management flexibility, lower cost, scalability, better resources utilization, and energy efficiency. One of the powerful features provided by virtualization is Virtual Machine (VM) live migration, which facilitates moving workloads within the infrastructure with negligible downtime and minimal impact on workload. However, the performance of running applications is likely to be negatively affected during a live VM migration. The objective of this paper is to optimize the total performance degradation of concurrent VM live migration in the data center network by exploiting the SDN platform. The problem is modeled using mixed integer linear programming(MILP) for VM live migration with a fixed path and VM live migration with path selection. To provide a practical optimization, the greedy algorithm is proposed. Numerical study results show that a significant decrease occur in performance degradation in MILP model and greedy algorithm when the number of VMs increases. The proposed greedy algorithm cannot yield the optimum solution as the problem become harder, but it provides better solution than MILP model in terms of the time constrain exhibited in case of large problems

A General Framework for Motion Sensor Based Web Services

With the development of motion sensing technology, motion sensor based services have been put into a wide range of applications in recent years. Demand of consuming such service on mobile devices has already emerged. However, as most motion sensors are specifically designed for some heavyweight clients such as PCs or game consoles, there are several technical challenges prohibiting motion sensor from being used by lightweight clients such as mobile devices, for example: There is no direct approach to connect the motion sensor with mobile devices. Most mobile devices don't have enough computational power to consume the motion sensor outputs. To address these problems, I have designed and implemented a framework for publishing general motion sensor functionalities as a RESTful web service that is accessible to mobile devices via HTTP connections. In the framework, a pure HTML5 based interface is delivered to the clients to ensure good accessibility, a websocket based data transferring scheme is adopted to guarantee data transferring efficiency, a server side gesture pipeline is proposed to reduce the client side computational burden and a distributed architecture is designed to make the service scalable. Finally, I conducted three experiments to evaluate the framework's compatibility, scalability and data transferring performance

Imitation learning through games: theory, implementation and evaluation

Despite a history of games-based research, academia has generally regarded commercial games as a distraction from the serious business of AI, rather than as an opportunity to leverage this existing domain to the advancement of our knowledge. Similarly, the computer game industry still relies on techniques that were developed several decades ago, and has shown little interest in adopting more progressive academic approaches. In recent times, however, these attitudes have begun to change; under- and post-graduate games development courses are increasingly common, while the industry itself is slowly but surely beginning to recognise the potential offered by modern machine-learning approaches, though games which actually implement said approaches on more than a token scale remain scarce. One area which has not yet received much attention from either academia or industry is imitation learning, which seeks to expedite the learning process by exploiting data harvested from demonstrations of a given task. While substantial work has been done in developing imitation techniques for humanoid robot movement, there has been very little exploration of the challenges posed by interactive computer games. Given that such games generally encode reasoning and decision-making behaviours which are inherently more complex and potentially more interesting than limb motion data, that they often provide inbuilt facilities for recording human play, that the generation and collection of training samples is therefore far easier than in robotics, and that many games have vast pre-existing libraries of these recorded demonstrations, it is fair to say that computer games represent an extremely fertile domain for imitation learning research. In this thesis, we argue in favour of using modern, commercial computer games to study, model and reproduce humanlike behaviour. We provide an overview of the biological and robotic imitation literature as well as the current status of game AI, highlighting techniques which may be adapted for the purposes of game-based imitation. We then proceed to describe our contributions to the field of imitation learning itself, which encompass three distinct categories: theory, implementation and evaluation. We first describe the development of a fully-featured Java API - the Quake2 Agent Simulation Environment (QASE) - designed to facilitate both research and education in imitation and general machine-learning, using the game Quake 2 as a testbed. We outline our motivation for developing QASE, discussing the shortcomings of existing APIs and the steps which we have taken to circumvent them. We describe QASE’s network layer, which acts as an interface between the local AI routines and the Quake 2 server on which the game environment is maintained, before detailing the API’s agent architecture, which includes an interface to the MatLab programming environment and the ability to parse and analyse full recordings of game sessions. We conclude the chapter with a discussion of QASE’s adoption by numerous universities as both an undergraduate teaching tool and research platform. We then proceed to describe the various imitative mechanisms which we have developed using QASE and its MatLab integration facilities. We first outline a behaviour model based on a well-known psychological model of human planning. Drawing upon previous research, we also identify a set of believability criteria - elements of agent behaviour which are of particular importance in determining the “humanness” of its in-game appearance. We then detail a reinforcement-learning approach to imitating the human player’s navigation of his environment, centred upon his pursuit of items as strategic goals. In the subsequent section, we describe the integration of this strategic system with a Bayesian mechanism for the imitation of tactical and motion-modelling behaviours. Finally, we outline a model for the imitation of reactive combat behaviours; specifically, weapon-selection and aiming. Experiments are presented in each case to demonstrate the imitative mechanisms’ ability to accurately reproduce observed behaviours. Finally, we criticise the lack of any existing methodology to formally gauge the believability of game agents, and observe that the few previous attempts have been extremely ad-hoc and informal. We therefore propose a generalised approach to such testing; the Bot-Oriented Turing Test (BOTT). This takes the form of an anonymous online questionnaire, an accompanying protocol to which examiners should adhere, and the formulation of a believability index which numerically expresses each agent’s humanness as indicated by its observers, weighted by their experience and the accuracy with which the agents were identified. To both validate the survey approach and to determine the efficacy of our imitative models, we present a series of experiments which use the believability test to evaluate our own imitation agents against both human players and traditional artificial bots. We demonstrate that our imitation agents perform substantially better than even a highly-regarded rule-based agent, and indeed approach the believability of actual human players. Some suggestions for future directions in our research, as well as a broader discussion of open questions, conclude this thesis