Wireless routing protocols in MANET are all flat routing protocols and are thus not suitable for ... more Wireless routing protocols in MANET are all flat routing protocols and are thus not suitable for large scale or very dense networks because of bandwidth and processing overheads they generate. A common solution to this scalability problem is to gather terminals into clusters and then to apply a hierarchical routing, which means, in most of the literature, using a proactive routing protocol inside the clusters and a reactive one between the clusters. We previously introduced a cluster organization to allow a hierarchical routing and scalability, which have shown very good properties. Nevertheless, it provides a constant number of clusters when the intensity of nodes increases. Therefore we apply a reactive routing protocol inside the clusters and a proactive routing protocol between the clusters. In this way, each cluster has O(1) routes to maintain toward other ones. When applying such a routing policy, a node u also needs to locate its correspondent v in order to pro-actively route toward the cluster owning v. In this paper, we describe our localization scheme based on Distributed Hashed Tables and Interval Routing which takes advantage of the underlying clustering structure. It only requires O(1) memory space size on each node.
We propose solutions to several multicast core management problems, including automatic core sele... more We propose solutions to several multicast core management problems, including automatic core selection, core failure handling, and core migration, for use in networks based on link-state routing. The proposed approach uses a central server, called the core binding server (CBS), to manage core-group bindings, accompanied by a network-level leader election protocol in order to achieve robustness. By modeling the selection of the CBS as a leader election problem, this approach can handle any combination of network component failures, including those that partition the network. Further, our simulation results reveal that the central server can sustain extremely high workloads, and demonstrate the effectiveness of our core selection and core migration methods
A core-based forwarding multicast protocol uses a core router as a traffic transit center: all mu... more A core-based forwarding multicast protocol uses a core router as a traffic transit center: all multicast packets are first sent to the core, then distributed to destinations on a multicast tree rooted at the core. The purpose of this paper is to evaluate, via simulation, the effect of various core selection methods on multicast performance. The main contribution of this work is the discovery of a simple yet effective core selection heuristic that can be implemented in a wide range of networks. Specifically, our results show that the tree center heuristic (using the center of the existing multicast tree as the new core node) significantly outperforms heuristics based on random selection, and performs as well as heuristics that are more computationally expensive
Wireless routing protocols in MANET are all flat routing protocols and are thus not suitable for ... more Wireless routing protocols in MANET are all flat routing protocols and are thus not suitable for large scale or very dense networks because of bandwidth and processing overheads they generate. A common solution to this scalability problem is to gather terminals into clusters and then to apply a hierarchical routing, which means, in most of the literature, using a proactive routing protocol inside the clusters and a reactive one between the clusters. We previously introduced a cluster organization to allow a hierarchical routing and scalability, which have shown very good properties. Nevertheless, it provides a constant number of clusters when the intensity of nodes increases. Therefore we apply a reactive routing protocol inside the clusters and a proactive routing protocol between the clusters. In this way, each cluster has O(1) routes to maintain toward other ones. When applying such a routing policy, a node u also needs to locate its correspondent v in order to pro-actively route toward the cluster owning v. In this paper, we describe our localization scheme based on Distributed Hashed Tables and Interval Routing which takes advantage of the underlying clustering structure. It only requires O(1) memory space size on each node.
We propose solutions to several multicast core management problems, including automatic core sele... more We propose solutions to several multicast core management problems, including automatic core selection, core failure handling, and core migration, for use in networks based on link-state routing. The proposed approach uses a central server, called the core binding server (CBS), to manage core-group bindings, accompanied by a network-level leader election protocol in order to achieve robustness. By modeling the selection of the CBS as a leader election problem, this approach can handle any combination of network component failures, including those that partition the network. Further, our simulation results reveal that the central server can sustain extremely high workloads, and demonstrate the effectiveness of our core selection and core migration methods
A core-based forwarding multicast protocol uses a core router as a traffic transit center: all mu... more A core-based forwarding multicast protocol uses a core router as a traffic transit center: all multicast packets are first sent to the core, then distributed to destinations on a multicast tree rooted at the core. The purpose of this paper is to evaluate, via simulation, the effect of various core selection methods on multicast performance. The main contribution of this work is the discovery of a simple yet effective core selection heuristic that can be implemented in a wide range of networks. Specifically, our results show that the tree center heuristic (using the center of the existing multicast tree as the new core node) significantly outperforms heuristics based on random selection, and performs as well as heuristics that are more computationally expensive
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Papers by Eric Fleury