Solving key design issues for massively multiplayer online games on peer-to-peer architectures

Massively Multiplayer Online Games (MMOGs) are increasing in both popularity and scale on the Internet and are predominantly implemented by Client/Server architectures. While such a classical approach to distributed system design offers many benefits, it suffers from significant technical and commercial drawbacks, primarily reliability and scalability costs. This realisation has sparked recent research interest in adapting MMOGs to Peer-to-Peer (P2P) architectures. This thesis identifies six key design issues to be addressed by P2P MMOGs, namely interest management, event dissemination, task sharing, state persistency, cheating mitigation, and incentive mechanisms. Design alternatives for each issue are systematically compared, and their interrelationships discussed. How well representative P2P MMOG architectures fulfil the design criteria is also evaluated. It is argued that although P2P MMOG architectures are developing rapidly, their support for task sharing and incentive mechanisms still need to be improved. The design of a novel framework for P2P MMOGs, Mediator, is presented. It employs a self-organising super-peer network over a P2P overlay infrastructure, and addresses the six design issues in an integrated system. The Mediator framework is extensible, as it supports flexible policy plug-ins and can accommodate the introduction of new superpeer roles. Key components of this framework have been implemented and evaluated with a simulated P2P MMOG. As the Mediator framework relies on super-peers for computational and administrative tasks, membership management is crucial, e.g. to allow the system to recover from super-peer failures. A new technology for this, namely Membership-Aware Multicast with Bushiness Optimisation (MAMBO), has been designed, implemented and evaluated. It reuses the communication structure of a tree-based application-level multicast to track group membership efficiently. Evaluation of a demonstration application shows i that MAMBO is able to quickly detect and handle peers joining and leaving. Compared to a conventional supervision architecture, MAMBO is more scalable, and yet incurs less communication overheads. Besides MMOGs, MAMBO is suitable for other P2P applications, such as collaborative computing and multimedia streaming. This thesis also presents the design, implementation and evaluation of a novel task mapping infrastructure for heterogeneous P2P environments, Deadline-Driven Auctions (DDA). DDA is primarily designed to support NPC host allocation in P2P MMOGs, and specifically in the Mediator framework. However, it can also support the sharing of computational and interactive tasks with various deadlines in general P2P applications. Experimental and analytical results demonstrate that DDA efficiently allocates computing resources for large numbers of real-time NPC tasks in a simulated P2P MMOG with approximately 1000 players. Furthermore, DDA supports gaming interactivity by keeping the communication latency among NPC hosts and ordinary players low. It also supports flexible matchmaking policies, and can motivate application participants to contribute resources to the system

Simulation of Area of Interest Management for Massively Multiplayer Online Games Using OPNET

In recent years, there has been an important growth of online gaming. Today’s Massively Multiplayer Online Games (MMOGs) can contain millions of synchronous players scattered across the world and participating with each other within a single shared game. The increase in the number of players in MMOGs has led to some issues with the demand of server which generates a significant increase in costs for the game industry and impacts to the quality of service offered to players. With the number of players gradually increasing, servers still need to work efficiently under heavy load and, new researches are required to improve the established MMOG system architectures. In dealing with a considerable scale of massively multiplayer online games, several client-server and peer-to-peer solutions have been proposed. Although they have improved the scalability of MMOGs in different degrees, they faced new serious challenges in interest management. In this paper, we propose a novel static area of interest management in order to reduce the delay and traffic of Hybrid P2P MMOGs. We propose to use OPNET Modeler 18.0, and in particular the custom application to simulate the new architecture, which required the implementation of new nodes models and behaviors in the simulator to emulate correctly the new architecture. The scenarios include both client-server and hybrid P2P system to evaluate the communication of games with (125, 500, and 1000) peers. The simulation results show that area of interest management for MMOGs based on the hybrid P2P architectures have low delay and traffic received compared with MMOGs based on client-server system

Emerging Artificial Societies Through Learning

The NewTies project is implementing a simulation in which societies of agents are expected to de-velop autonomously as a result of individual, population and social learning. These societies are expected to be able to solve environmental challenges by acting collectively. The challenges are in-tended to be analogous to those faced by early, simple, small-scale human societies. This report on work in progress outlines the major features of the system as it is currently conceived within the project, including the design of the agents, the environment, the mechanism for the evolution of language and the peer-to-peer infrastructure on which the simulation runs.Artificial Societies, Evolution of Language, Decision Trees, Peer-To-Peer Networks, Social Learning

Storage systems for mobile-cloud applications

Mobile devices have become the major computing platform in todays world. However, some apps on mobile devices still suffer from insufficient computing and energy resources. A key solution is to offload resource-demanding computing tasks from mobile devices to the cloud. This leads to a scenario where computing tasks in the same application run concurrently on both the mobile device and the cloud. This dissertation aims to ensure that the tasks in a mobile app that employs offloading can access and share files concurrently on the mobile and the cloud in a manner that is efficient, consistent, and transparent to locations. Existing distributed file systems and network file systems do not satisfy these requirements. Furthermore, current offloading platforms either do not support efficient file access for offloaded tasks or do not offload tasks with file accesses. The first part of the dissertation addresses this issue by designing and implementing an application-level file system named Overlay File System (OFS). OFS assumes a cloud surrogate is paired with each mobile device for task and storage offloading. To achieve high efficiency, OFS maintains and buffers local copies of data sets on both the surrogate and the mobile device. OFS ensures consistency and guarantees that all the reads get the latest data. To effectively reduce the network traffic and the execution delay, OFS uses a delayed-update mechanism, which combines write-invalidate and write-update policies. To guarantee location transparency, OFS creates a unified view of file data. The research tests OFS on Android OS with a real mobile application and real mobile user traces. Extensive experiments show that OFS can effectively support consistent file accesses from computation tasks, no matter where they run. In addition, OFS can effectively reduce both file access latency and network traffic incurred by file accesses. While OFS allows offloaded tasks to access the required files in a consistent and transparent manner, file accesses by offloaded tasks can be further improved. Instead of retrieving the required files from its associated mobile device, a surrogate can discover and retrieve identical or similar file(s) from the surrogates belonging to other users to meet its needs. This is based on two observations: 1) multiple users have the same or similar files, e.g., shared files or images/videos of same object; 2) the need for a certain file content in mobile apps can usually be described by context features of the content, e.g., location, objects in an image, etc.; thus, any file with the required context features can be used to satisfy the need. Since files may be retrieved from surrogates, this solution improves latency and saves wireless bandwidth and power on mobile devices. The second part of the dissertation proposes and develops a Context-Aware File Discovery Service (CAFDS) that implements the idea described above. CAFDS uses a self-organizing map and k-means clustering to classify files into file groups based on file contexts. It then uses an enhanced decision tree to locate and retrieve files based on the file contexts defined by apps. To support diverse file discovery demands from various mobile apps, CAFDS allows apps to add new file contexts and to update existing file contexts dynamically, without affecting the discovery process. To evaluate the effectiveness of CAFDS, the research has implemented a prototype on Android and Linux. The performance of CAFDS was tested against Chord, a DHT based lookup scheme, and SPOON, a P2P file sharing system. The experiments show that CAFDS provides lower end-to-end latency for file search than Chord and SPOON, while providing similar scalability to Chord