Aubin Jarry

Optimal data gathering paths and energy-balance mechanisms in wireless networks

This paper studies the data gathering problem in wireless networks, where data generated at the nodes has to be collected at a single sink. We investigate the relationship between routing optimality and fair resource management. In particular, we prove that for energy-balanced data propagation, Pareto optimal routing and flow maximization are equivalent, and also prove that flow maximization is equivalent to maximizing the network lifetime. We algebraically characterize the network structures in which energy-balanced data flows are maximal. Moreover, we algebraically characterize communication links which are not used by an optimal flow. This leads to the characterization of minimal network structures supporting the maximal flows. We note that energy-balance, although implying global optimality, is a local property that can be computed efficiently and in a distributed manner. We suggest online distributed algorithms for energy-balance in different optimal network structures and numerically show their stability in particular setting. We remark that although the results obtained in this paper have a direct consequence in energy saving for wireless networks they do not limit themselves to this type of networks neither to energy as a resource. As a matter of fact, the results are much more general and can be used for any type of network and different types of resources.

Optimal data gathering paths and energy balance mechanisms in wireless networks

This paper studies the data gathering problem in wireless networks, where data generated at the nodes has to be collected at a single sink. We investigate the relationship between routing optimality and fair resource management. In particular, we prove that for energy balanced data propagation, Pareto optimal routing and flow maximization are equivalent, and also prove that flow maximization is equivalent to maximizing the network lifetime. We algebraically characterize the network structures in which energy balanced data flows are maximal. Moreover, we algebraically characterize communication links which are not used by an optimal flow. This leads to the characterization of minimal network structures supporting the maximal flows. We note that energy balance, although implying global optimality, is a local property that can be computed efficiently and in a distributed manner. We suggest online distributed algorithms for energy balance in different optimal network structures and numerically show their stability in particular setting. We remark that although the results obtained in this paper have a direct consequence in energy saving for wireless networks they do not limit themselves to this type of networks neither to energy as a resource. As a matter of fact, the results are much more general and can be used for any type of network and different type of resources.

Early Obstacle Detection and Avoidance for All to All Traffic Pattern in Wireless Sensor Networks

This paper deals with early obstacles recognition in wireless sensor networks under various traffic patterns. In the presence of obstacles, the efficiency of routing algorithms is increased by voluntarily avoiding some regions in the vicinity of obstacles, areas which we call dead-ends. In this paper, we first propose a fast convergent routing algorithm with proactive dead-end detection together with a formal definition and description of dead-ends. Secondly, we present a generalization of this algorithm which improves performances in all to many and all to all traffic patterns. In a third part we prove that this algorithm produces paths that are optimal up to a constant factor of 2? + 1. In a fourth part we consider the reactive version of the algorithm which is an extension of a previously known early obstacle detection algorithm. Finally we give experimental results to illustrate the efficiency of our algorithms in different scenarios.

Fast reroute paths algorithms

In order to keep services running despite link or node failure in MPLS networks, RSVP-TE fast reroute (FRR) schemes use precomputed backup label-switched path tunnels for local repair of LSP tunnels. In the event of failure, the redirection of traffic occurs onto backup LSP tunnels that have the same quality of service constraints as original paths. Local repair of LSP tunnels notably differ from traditional (1:1) dedicated path protection schemes in that traffic is diverted near the point of failure which speeds up the protection process by not having to notify the source and then resend the lost traffic. This gain in protection delay is crucial for MPLS networks which would otherwise suffer from an important recovery latency.In this paper, we investigate the algorithmic aspects of computing original paths along with their back-up so that they satisfy quality-of-service constraints (namely, delay) for single link or multiple link failure. In the case of single link failure, we propose an algorithm in O(nm+n2log(n)) that computes shortest guaranteed paths with their backup towards a single destination. In the case of directed graphs, we show that this algorithm is optimal by proving that computing shortest guaranteed paths is as hard as to compute multiple source shortest paths in directed graphs. In the case of undirected graphs, we propose a faster algorithm with time complexity O(mlog(n)+n2). We also provide a distributed algorithm based on Bellman-Ford distance computation which converges in 3n rounds at worst.

Virtual raw anchor coordinates: A new localization paradigm

A wide range of applications in wireless sensor networks rely on the location information of the sensing nodes. However, traditional localization techniques are dependent on hardware that is sometimes unavailable (e.g. GPS), or on sophisticated virtual localization calculus which have a costly overhead. Instead of actually localizing nodes in the physical two-dimensional Euclidean space, we use directly the raw distance to a set of anchors to produce multi-dimensional coordinates. We prove that the image of the physical two-dimensional Euclidean space is a two-dimensional surface, and we show how to adapt geographic routing strategies on this surface in a simple and efficient manner.

Virtual raw anchor coordinates: a new localization paradigm

A wide range of applications in wireless sensor networks rely on the location information of the sensing nodes. However, traditional localization techniques are dependent on hardware that is sometimes unavailable (e.g. GPS), or on sophisticated virtual localization calculus which have a costly overhead. Instead of actually localizing nodes in the physical two-dimensional Euclidean space, we use directly the raw distance to a set of anchors to produce multi-dimensional coordinates. We prove that the image of the physical two-dimensional Euclidean space is a two-dimensional surface, and we show that it is possible to adapt geographic routing strategies on this surface, simply, efficiently and successfully.

Efficient Graph Planarization in Sensor Networks and Local Routing Algorithm

In this paper, we propose an efficient planarization algorithm and a routing algorithm dedicated to Unit Disk Graphs whose nodes are localized using the Virtual Raw Anchor Coordinate system (VRAC).Our first algorithm computes a planar 2-spanner under light constraints on the edge lengths and induces a total exchange of at most 6n node identifiers. Its total complexity is O(nΔ), with Δ the maximum degree of the communication graph. The second algorithm that we present is a simple and efficient algorithm to route messages in this planar graph that requires routing tables with only three entries. We support these theoretical results by simulations showing the robustness of our algorithms when the coordinates are inaccurate.

VRAC: Virtual raw anchor coordinate routing in sensor networks

Geographic routing has been widely recognized as one of the most efficient approach to generally scalable wireless routing. However, in order to use geographic routing algorithms, nodes must be localized with Euclidean coordinates. Current localization techniques are dependent either on expensive hardware (e.g. GPS) or on costly virtual localization and this is a problem in sensor networks where resources are scarce. In this paper we directly use the raw distance to a set of anchors to route messages in a multi-dimensional space. This original approach enables us to completely bypass the localization phase while retaining useful geographic properties of the network. To prove this concept, we implemented two typical geographic routing algorithms using both traditional coordinates and multidimensional raw anchor coordinates. Simulation results show that using only the raw coordinates does not decrease routing efficiency.

Brief announcement: routing with obstacle avoidance mechanism with constant approximation ratio

We study the problem of routing messages in sensor networks where the energy saving issue is essential. In this paper, we propose ROAM2, an improvement of ROAM (Routing protocol with Obstacle Avoidance Mechanism) proposed in [HJL+09]. This distributed protocol has a light obstacle detection and avoidance component with low message and computation overhead and a routing component which sends messages along short paths, thus saving energy. We improved it so that is has an 100% delivery rate and we prove that ROAM finds with high probability paths whose lengths are comparable to the length of the shortest paths. Furthermore, we prove a general result on the length of any path computed in a greedy way. Whereas ROAM uses one bit of memory in nodes (even if there are several destinations), in [KWZ08], it was shown that no geographic routing algorithm not using any sensor memory can compute a path whose length is guaranteed to be of order less than O(l2), where l is the length of the shortest path. Finally, we compare the energy efficiency of ROAM against GPSR (or GFG) [KK00], the algorithm proposed in [MLNR08] and SLGF [JMLW08], by running simulations which validates our theoretical results

On the efficiency of routing in sensor networks

In sensor networks, a key efficiency measure for routing protocols is the stretch of the computed paths, where the stretch is the ratio of the path length and the Euclidean distance covered. In the literature, many protocols have been evaluated via extensive simulations, and often come without any theoretical guarantees. For those whose performances are theoretically guaranteed there is an important gap between the theoretical predictions and the experimental results. The contribution of this paper is twofold. First, we give theoretical results that explain the observed efficiency of many of the algorithms proposed in the literature. Second, we propose ROAM2, a deterministic routing protocol, that requires a single bit of memory at each node and that ensures, with high probability (depending on the node distribution), that the paths have a constant stretch.