Analysis domain model for shared virtual environments

The field of shared virtual environments, which also encompasses online games and social 3D environments, has a system landscape consisting of multiple solutions that share great functional overlap. However, there is little system interoperability between the different solutions. A shared virtual environment has an associated problem domain that is highly complex raising difficult challenges to the development process, starting with the architectural design of the underlying system. This paper has two main contributions. The first contribution is a broad domain analysis of shared virtual environments, which enables developers to have a better understanding of the whole rather than the part(s). The second contribution is a reference domain model for discussing and describing solutions - the Analysis Domain Model

An approach to enhance aggregated source specific multicast scheme

The Aggregated Source Specific Multicast (ASSM) scheme is proposed to overcome the limitations of Source Specific Multicast (SSM). It aims to handle the scalability issue of SSM. The key idea is that multiple groups are forced to share a single delivery tree. However, the ASSM scheme suffers from routers under utilization problem. In our previous work we have proposed an approach to overcome this problem. In this paper our proposed approach was presented and evaluated. It was shown that our proposed scheme results in achieving higher routers utilization

On forwarding state control in VPN multicast based on MPLS multipoint LSPs

This work is at: 2012 IEEE 13th International Conference on High Performance Switching and Routing took place June 24-27,2012 in Belgrade, Serbia. Web to event: http://hpsr2012.etf.bg.ac.rs/index.phpThe demand for multicast-capable VPN services, like Virtual Private LAN Service (VPLS), has grown quickly in the last years. In order to save bandwidth, MPLS point-to-multipoint LSPs could be used, but the VPN-specific state information to be handled inside the network may exceed the capacity of core nodes. A well-known solution for this is to aggregate the multicast/broadcast traffic of multiple VPNs into shared p2mp LSP trees. In shared trees, although some bandwidth is wasted because a fraction of the packets are delivered to non-member leaves (either not in the VPN broadcast or multicast group), there is wide working range where a good state vs. bandwidth trade-off is achieved. In this paper we enhance and improve previous works that analyze this trade-off. We propose new techniques for multicast traffic aggregation of VPNs in MPLS-based networks, with the objective of observing the behavior of the aggregation philosophy for different aggregation degrees, which should be very useful for network design and deployment purposes. We assess the aggregation heuristics over different reference networks and VPN geographic distributions. Simulations give a quantitative indication of the relevance of intelligent aggregation, of geographical distribution and group sizes.The work described in this paper was carried out with the support of MEDIANET PRICIT 2009/TIC-1468, from the Community of Madrid; and Fundación Carolina, Spain.Publicad

A Framework for Realistic and Systematic Multicast Performance Evaluation

Previous multicast research often makes commonly accepted but unverifed assumptions on network topologies and group member distribution in simulation studies. In this paper, we propose a framework to systematically evaluate multicast performance for different protocols. We identify a series of metrics, and carry out extensive simulation studies on these metrics with different topological models and group member distributions for three case studies. Our simulation results indicate that realistic topology and group membership models are crucial to accurate multicast performance evaluation. These results can provide guidance for multicast researchers to perform realistic simulations, and facilitate the design and development of multicast protocols

DISco: a Distributed Information Store for network Challenges and their Outcome

We present DISco, a storage and communication middleware designed to enable distributed and task-centric autonomic control of networks. DISco is designed to enable multi-agent identification of anomalous situations -- so-called "challenges" -- and assist coordinated remediation that maintains degraded -- but acceptable -- service level, while keeping a track of the challenge evolution in order to enable human-assisted diagnosis of flaws in the network. We propose to use state-of-art peer-to-peer publish/subscribe and distributed storage as core building blocks for the DISco service

Distributed Multicast Tree Aggregation

Multicast is not scalable mainly due to the number of forwarding states and control overhead required to maintain trees. Tree aggregation reduces the number of multicast forwarding states and the tree maintenance overhead by allowing several multicast groups to share the same delivery tree. In this paper, we exhibit several drawbacks of the existing protocols: the latency to manage group dynamics is high, the managers are critical points of failures and some group-specific entries are stored unnecessarily. Then, we propose a new distributed protocol that significantly reduces the number of control messages and limits the number of trees within a domain. By simulations, we show that our protocol achieves good performance and outperforms the previous known distributed algorithm. // Le Multicast n'est pas encore bien déployé dans Internet. Les deux raisons principales qui freinent son déploiement sont : le nombre d'états de routage important qui dépend du nombre de groupes et le nombre de messages de contrôle nécessaires pour maintenir les arbres multicast dans un domaine de routage. L'agrégation d'arbres multicast est un protocole qui permet de résoudre ces deux problèmes en permettant à plusieurs groupes multicast d'utiliser le même arbre de routage. Dans ce papier, nous détaillons plusieurs inconvénients concernant les protocoles rééalisant l'agrégation d'arbres. En effet, dans ces protocoles, la latence pour gérer la dynamicité des groupes est grande, les gestionnaires d'agrégation sont des points critiques dans le cas de pannes et des entrées spécifiques aux groupes sont stoquées inutilement. Nous proposons un nouveau protocole distribué qui réduit le nombre de messages de contrôle envoyés et qui limite le nombre d'arbres dans un domaine. Par des simulations, nous prouvons que notre protocole a de bien meilleures performances que le tout dernier protocole distribué connu

Dealing with Heterogeneity in a Fully Reliable Multicast Protocol

Many of the proposed multicast congestion avoidance algorithms are single-rate where heterogeneity is accommodated by adjusting the transmission rate as a response to the worst receiver in the group. Due to the Internet heterogeneity, a single-rate congestion co ntrol affects the overall satisfaction of the receivers in a multicast session. In this paper, we propose a multi-rate replicated scheme where some receivers (instead of the source) are designated to perform data replication for other receivers with lower capacity. To be more scalable and to minimize the bandwidth consumption due to data replication, the partitioning algorithm is per- formed on-the-fly by the routers depending on the feedback they receive. Neither a prior estimation of the receivers capacity is necessary nor a complex computation is required to execute our partitioning algorithm

Learning algorithms for the control of routing in integrated service communication networks

There is a high degree of uncertainty regarding the nature of traffic on future integrated service networks. This uncertainty motivates the use of adaptive resource allocation policies that can take advantage of the statistical fluctuations in the traffic demands. The adaptive control mechanisms must be 'lightweight', in terms of their overheads, and scale to potentially large networks with many traffic flows. Adaptive routing is one form of adaptive resource allocation, and this thesis considers the application of Stochastic Learning Automata (SLA) for distributed, lightweight adaptive routing in future integrated service communication networks. The thesis begins with a broad critical review of the use of Artificial Intelligence (AI) techniques applied to the control of communication networks. Detailed simulation models of integrated service networks are then constructed, and learning automata based routing is compared with traditional techniques on large scale networks. Learning automata are examined for the 'Quality-of-Service' (QoS) routing problem in realistic network topologies, where flows may be routed in the network subject to multiple QoS metrics, such as bandwidth and delay. It is found that learning automata based routing gives considerable blocking probability improvements over shortest path routing, despite only using local connectivity information and a simple probabilistic updating strategy. Furthermore, automata are considered for routing in more complex environments spanning issues such as multi-rate traffic, trunk reservation, routing over multiple domains, routing in high bandwidth-delay product networks and the use of learning automata as a background learning process. Automata are also examined for routing of both 'real-time' and 'non-real-time' traffics in an integrated traffic environment, where the non-real-time traffic has access to the bandwidth 'left over' by the real-time traffic. It is found that adopting learning automata for the routing of the real-time traffic may improve the performance to both real and non-real-time traffics under certain conditions. In addition, it is found that one set of learning automata may route both traffic types satisfactorily. Automata are considered for the routing of multicast connections in receiver-oriented, dynamic environments, where receivers may join and leave the multicast sessions dynamically. Automata are shown to be able to minimise the average delay or the total cost of the resulting trees using the appropriate feedback from the environment. Automata provide a distributed solution to the dynamic multicast problem, requiring purely local connectivity information and a simple updating strategy. Finally, automata are considered for the routing of multicast connections that require QoS guarantees, again in receiver-oriented dynamic environments. It is found that the distributed application of learning automata leads to considerably lower blocking probabilities than a shortest path tree approach, due to a combination of load balancing and minimum cost behaviour