Towards a Scalable Dynamic Spatial Database System

With the rise of GPS-enabled smartphones and other similar mobile devices, massive amounts of location data are available. However, no scalable solutions for soft real-time spatial queries on large sets of moving objects have yet emerged. In this paper we explore and measure the limits of actual algorithms and implementations regarding different application scenarios. And finally we propose a novel distributed architecture to solve the scalability issues.Comment: (2012

Towards a Framework for DHT Distributed Computing

Distributed Hash Tables (DHTs) are protocols and frameworks used by peer-to-peer (P2P) systems. They are used as the organizational backbone for many P2P file-sharing systems due to their scalability, fault-tolerance, and load-balancing properties. These same properties are highly desirable in a distributed computing environment, especially one that wants to use heterogeneous components. We show that DHTs can be used not only as the framework to build a P2P file-sharing service, but as a P2P distributed computing platform. We propose creating a P2P distributed computing framework using distributed hash tables, based on our prototype system ChordReduce. This framework would make it simple and efficient for developers to create their own distributed computing applications. Unlike Hadoop and similar MapReduce frameworks, our framework can be used both in both the context of a datacenter or as part of a P2P computing platform. This opens up new possibilities for building platforms to distributed computing problems. One advantage our system will have is an autonomous load-balancing mechanism. Nodes will be able to independently acquire work from other nodes in the network, rather than sitting idle. More powerful nodes in the network will be able use the mechanism to acquire more work, exploiting the heterogeneity of the network. By utilizing the load-balancing algorithm, a datacenter could easily leverage additional P2P resources at runtime on an as needed basis. Our framework will allow MapReduce-like or distributed machine learning platforms to be easily deployed in a greater variety of contexts

Re-engineering jake2 to work on a grid using the GridGain Middleware

With the advent of Massively Multiplayer Online Games (MMOGs), engineers and designers of games came across with many questions that needed to be answered such as, for example, "how to allow a large amount of clients to play simultaneously on the same server?", "how to guarantee a good quality of service (QoS) to a great number of clients?", "how many resources will be necessary?", "how to optimize these resources to the maximum?". A possible answer to these questions relies on the usage of grid computing. Taking into account the parallel and distributed nature of grid computing, we can say that grid computing allows for more scalability in terms of a growing number of players, guarantees shorter communication time between clients and servers, and allows for a better resource management and usage (e.g., memory, CPU, core balancing usage, etc.) than the traditional serial computing model. However, the main focus of this thesis is not about grid computing. Instead, this thesis describes the re-engineering process of an existing multiplayer computer game, called Jake2, by transforming it into a MMOG, which is then put to run on a grid

Building Robust Distributed Infrastructure Networks

Many competing designs for Distributed Hash Tables exist exploring multiple models of addressing, routing and network maintenance. Designing a general theoretical model and implementation of a Distributed Hash Table allows exploration of the possible properties of Distributed Hash Tables. We will propose a generalized model of DHT behavior, centered on utilizing Delaunay triangulation in a given metric space to maintain the networks topology. We will show that utilizing this model we can produce network topologies that approximate existing DHT methods and provide a starting point for further exploration. We will use our generalized model of DHT construction to design and implement more efficient Distributed Hash Table protocols, and discuss the qualities of potential successors to existing DHT technologies

The use of computational geometry techniques to resolve the issues of coverage and connectivity in wireless sensor networks

Wireless Sensor Networks (WSNs) enhance the ability to sense and control the physical environment in various applications. The functionality of WSNs depends on various aspects like the localization of nodes, the strategies of node deployment, and a lifetime of nodes and routing techniques, etc. Coverage is an essential part of WSNs wherein the targeted area is covered by at least one node. Computational Geometry (CG) -based techniques significantly improve the coverage and connectivity of WSNs. This paper is a step towards employing some of the popular techniques in WSNs in a productive manner. Furthermore, this paper attempts to survey the existing research conducted using Computational Geometry-based methods in WSNs. In order to address coverage and connectivity issues in WSNs, the use of the Voronoi Diagram, Delaunay Triangulation, Voronoi Tessellation, and the Convex Hull have played a prominent role. Finally, the paper concludes by discussing various research challenges and proposed solutions using Computational Geometry-based techniques.Web of Science2218art. no. 700

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

Update propagation for peer-to-peer-based massively multi-user virtual environments

Over the last decade Massively Multi-user Virtual Environments (MMVEs) have become an integral part of modern culture and business. Applications for these large-scale virtual environments range from gaming to business and scientific research. Some MMVEs reach a user base in the tens of millions and the total number of users is estimated in the billions. Despite this success, launching an MMVEs is still a risky proposition. This is in large part due to the high cost associated with setting up and maintaining the necessary server infrastructure. One way of reducing the costs of operating MMVEs is to switch their system architecture from the current client/server-based model to one based on peer-to-peer (P2P) technologies. This has the potential to significantly reduce the infrastructure costs of MMVEs, as users bring their own resources into the P2P system and servers are no longer required, thus decreasing expenses and market entry barriers. This thesis describes a scalable and low-latency update propagation system for P2P-based MMVEs. Update propagation refers to the exchange of information about changes in the virtual environment between users and is one of the key components of MMVEs. Thus, the described system represents a key step towards operating MMVEs as fully distributed peer-to-peer systems

Collaborative visualization environment using P2P technology and ellipsoidal mesh partitioning

Ph.DDOCTOR OF PHILOSOPH

A Map-algebra-inspired Approach for Interacting With Wireless Sensor Networks, Cyber-physical Systems or Internet of Things

The typical approach for consuming data from wireless sensor networks (WSN) and Internet of Things (IoT) has been to send data back to central servers for processing and analysis. This thesis develops an alternative strategy for processing and acting on data directly in the environment referred to as Active embedded Map Algebra (AeMA). Active refers to the near real time production of data, and embedded refers to the architecture of distributed embedded sensor nodes. Network macroprogramming, a style of programming adopted for wireless sensor networks and IoT, addresses the challenges of coordinating the behavior of multiple connected devices through a high-level programming model. Several macroprogramming models have been proposed, but none to date has adopted a comprehensive spatial model. This thesis takes the unique approach of adapting the well-known Map Algebra model from Geographic Information Science to extend the functionality of WSN/IoT and the opportunities for user interaction with WSN/IoT. As an inherently spatial model, the Map Algebra-inspired metaphor supports the types of computation desired from a network of geographically dispersed WSN nodes. The AeMA data model aligns with the conceptual model of GIS layers and specific layer operations from Map Algebra. A declarative query and network tasking language, based on Map Algebra operations, provides the basis for operations and interactions. The model adds functionality to calculate and store time series and specific temporal summary-type composite objects as an extension to traditional Map Algebra. The AeMA encodes Map Algebra-inspired operations into an extensible Virtual Machine Runtime system, called MARS (Map Algebra Runtime System) that supports Map Algebra in an efficient and extensible way. Map algebra-like operations are performed in a distributed manner. Data do not leave the network but are analyzed and consumed in place. As a consequence, collected information is available in-situ to drive local actions. The conceptual model and tasking language are designed to direct nodes as active entities, able to perform some actions on their environment. This Map Algebra inspired network macroprogramming model has many potential applications for spatially deployed WSN/IoT networks. In particular the thesis notes its utility for precision agriculture applications