Networking Large-Scale Virtual Environments

Proceedings of Computer Animation ‘96, 3- 4 June 1996, Geneva, Switzerland, IEEE Computer Society Press, pp. 1-4. (an earlier version of this paper also appeared in the Proceedings of the Second International Conference on the Military Applications of Synthetic Environments and Virtual Reality, Stockholm, Sweden, 6-8 December 1995, pp. 119-125.

A modelling and networking architecture for distributed virtual environments with multiple servers.

Virtual Environments (VEs) attempt to give people the illusion of immersion that they are in a computer generated world. VEs allow people to actively participate in a synthetic environment. They range from a single-person running on a single computer, to multiple-people running on several computers connected through a network. When VEs are distributed on multiple computers across a network, we call this a Distributed Virtual Environment (DVE). Virtual Environments can benefit greatly from distributed strategies.A networked VE system based on the Client-Server model is the most commonly used paradigm in constructing DVE systems. In a Client-Server model, data can be distributed on several server computers. The server computers provide services to their own clients via networks. In some client-server models, however, a powerful server is required, or it will become a bottleneck. To reduce the amount of data and traffic maintained by a single server, the servers themselves can be distributed, and the virtual environment can be divided over a network of servers.The system described in this thesis, therefore, is based on the client-server model with multiple servers. This grouping is called a Distributed Virtual Environment System with Multiple- Servers (DVM). A DVM system shows a new paradigm of distributed virtual environments based on shared 3D synthetic environments. A variety of network elements are required to support large scale DVM systems. The network is currently the most constrained resource of the DVM system. Development of networking architectures is the key to solving the DVM challenge. Therefore, a networking architecture for implementing a DVM model is proposed. Finally, a DVM prototype system is described to demonstrate the validity of the modelling and network architecture of a DVM model

Identifying immersive environments’ most relevant research topics: an instrument to query researchers and practitioners

This paper provides an instrument for ascertaining researchers’ perspectives on the relative relevance of technological challenges facing immersive environments in view of their adoption in learning contexts, along three dimensions: access, content production, and deployment. It described its theoretical grounding and expert-review process, from a set of previously-identified challenges and expert feedback cycles. The paper details the motivation, setup, and methods employed, as well as the issues detected in the cycles and how they were addressed while developing the instrument. As a research instrument, it aims to be employed across diverse communities of research and practice, helping direct research efforts and hence contribute to wider use of immersive environments in learning, and possibly contribute towards the development of news and more adequate systems.The work presented herein has been partially funded under the European H2020 program H2020-ICT-2015, BEACONING project, grant agreement nr. 687676.info:eu-repo/semantics/publishedVersio

VIoLET: A Large-scale Virtual Environment for Internet of Things

IoT deployments have been growing manifold, encompassing sensors, networks, edge, fog and cloud resources. Despite the intense interest from researchers and practitioners, most do not have access to large-scale IoT testbeds for validation. Simulation environments that allow analytical modeling are a poor substitute for evaluating software platforms or application workloads in realistic computing environments. Here, we propose VIoLET, a virtual environment for defining and launching large-scale IoT deployments within cloud VMs. It offers a declarative model to specify container-based compute resources that match the performance of the native edge, fog and cloud devices using Docker. These can be inter-connected by complex topologies on which private/public networks, and bandwidth and latency rules are enforced. Users can configure synthetic sensors for data generation on these devices as well. We validate VIoLET for deployments with > 400 devices and > 1500 device-cores, and show that the virtual IoT environment closely matches the expected compute and network performance at modest costs. This fills an important gap between IoT simulators and real deployments.Comment: To appear in the Proceedings of the 24TH International European Conference On Parallel and Distributed Computing (EURO-PAR), August 27-31, 2018, Turin, Italy, europar2018.org. Selected as a Distinguished Paper for presentation at the Plenary Session of the conferenc

Addressing the Challenges in Federating Edge Resources

This book chapter considers how Edge deployments can be brought to bear in a global context by federating them across multiple geographic regions to create a global Edge-based fabric that decentralizes data center computation. This is currently impractical, not only because of technical challenges, but is also shrouded by social, legal and geopolitical issues. In this chapter, we discuss two key challenges - networking and management in federating Edge deployments. Additionally, we consider resource and modeling challenges that will need to be addressed for a federated Edge.Comment: Book Chapter accepted to the Fog and Edge Computing: Principles and Paradigms; Editors Buyya, Sriram