Two Algorithms for Network Size Estimation for Master/Slave Ad Hoc Networks

This paper proposes an adaptation of two network size estimation methods: random tour and gossip-based aggregation to suit master/slave mobile ad hoc networks. We show that it is feasible to accurately estimate the size of ad hoc networks when topology changes due to mobility using both methods. The algorithms were modified to account for the specific constraints of master/slave ad hoc networks and the results show that the proposed modifications perform better on these networks than the original protocols. Each of the two algorithms presents strengths and weaknesses and these are outlined in this paper.Comment: 3 pages, 2 figures, submitted to ANTS'09 - Corrected typos and definition

Self-Stabilizing Supervised Publish-Subscribe Systems

In this paper we present two major results: First, we introduce the first self-stabilizing version of a supervised overlay network by presenting a self-stabilizing supervised skip ring. Secondly, we show how to use the self-stabilizing supervised skip ring to construct an efficient self-stabilizing publish-subscribe system. That is, in addition to stabilizing the overlay network, every subscriber of a topic will eventually know all of the publications that have been issued so far for that topic. The communication work needed to processes a subscribe or unsubscribe operation is just a constant in a legitimate state, and the communication work of checking whether the system is still in a legitimate state is just a constant on expectation for the supervisor as well as any process in the system

Design and analysis of adaptive hierarchical low-power long-range networks

A new phase of evolution of Machine-to-Machine (M2M) communication has started where vertical Internet of Things (IoT) deployments dedicated to a single application domain gradually change to multi-purpose IoT infrastructures that service different applications across multiple industries. New networking technologies are being deployed operating over sub-GHz frequency bands that enable multi-tenant connectivity over long distances and increase network capacity by enforcing low transmission rates to increase network capacity. Such networking technologies allow cloud-based platforms to be connected with large numbers of IoT devices deployed several kilometres from the edges of the network. Despite the rapid uptake of Long-power Wide-area Networks (LPWANs), it remains unclear how to organize the wireless sensor network in a scaleable and adaptive way. This paper introduces a hierarchical communication scheme that utilizes the new capabilities of Long-Range Wireless Sensor Networking technologies by combining them with broadly used 802.11.4-based low-range low-power technologies. The design of the hierarchical scheme is presented in detail along with the technical details on the implementation in real-world hardware platforms. A platform-agnostic software firmware is produced that is evaluated in real-world large-scale testbeds. The performance of the networking scheme is evaluated through a series of experimental scenarios that generate environments with varying channel quality, failing nodes, and mobile nodes. The performance is evaluated in terms of the overall time required to organize the network and setup a hierarchy, the energy consumption and the overall lifetime of the network, as well as the ability to adapt to channel failures. The experimental analysis indicate that the combination of long-range and short-range networking technologies can lead to scalable solutions that can service concurrently multiple applications

Algorithme de gestion de groupe pour réseaux ad hoc fortement dynamiques

National audienceNous proposons un service de gestion de groupe adapté aux réseaux ad hoc fortement dynamiques tels que les réseaux de véhicules. Ce service maintient un groupe restreint dans un certain diamètre Dmax dépendant de critères applicatifs. Notre solution fonctionne dans un environnement asynchrone et ne requiert pas que les communications soient fiables. L'algorithme que nous proposons est auto-stabilisant, c'est-à-dire qu'il construit des groupes satisfaisant les contraintes quelque soit la configuration initiale. De plus, lorsqu'un noeud s'ajoute ou se retire d'un groupe stable, l'effet de cette modification est corrigé sur tous les noeuds du groupe en un temps optimal, soit O(Dmax) unités de temps

Resource location based on precomputed partial random walks in dynamic networks

The problem of finding a resource residing in a network node (the \emph{resource location problem}) is a challenge in complex networks due to aspects as network size, unknown network topology, and network dynamics. The problem is especially difficult if no requirements on the resource placement strategy or the network structure are to be imposed, assuming of course that keeping centralized resource information is not feasible or appropriate. Under these conditions, random algorithms are useful to search the network. A possible strategy for static networks, proposed in previous work, uses short random walks precomputed at each network node as partial walks to construct longer random walks with associated resource information. In this work, we adapt the previous mechanisms to dynamic networks, where resource instances may appear in, and disappear from, network nodes, and the nodes themselves may leave and join the network, resembling realistic scenarios. We analyze the resulting resource location mechanisms, providing expressions that accurately predict average search lengths, which are validated using simulation experiments. Reduction of average search lengths compared to simple random walk searches are found to be very large, even in the face of high network volatility. We also study the cost of the mechanisms, focusing on the overhead implied by the periodic recomputation of partial walks to refresh the information on resources, concluding that the proposed mechanisms behave efficiently and robustly in dynamic networks.Comment: 39 pages, 25 figure