Lélia Blin

Bio: Lélia Blin is an academic researcher from University of Évry Val d'Essonne. The author has contributed to research in topics: Minimum spanning tree & Spanning tree. The author has an hindex of 15, co-authored 62 publications receiving 575 citations. Previous affiliations of Lélia Blin include Centre national de la recherche scientifique & University of Paris.

Exclusive perpetual ring exploration without chirality

Abstract: In this paper, we study the exclusive perpetual exploration problem with mobile anonymous and oblivious robots in a discrete space. Our results hold for the most generic settings: robots are asynchronous and are not given any sense of direction, so the left and right sense (i.e. chirality) is decided by the adversary that schedules robots for execution, and may change between invocations of a particular robots (as robots are oblivious). We investigate both the minimal and the maximal number of robots that are necessary and sufficient to solve the exclusive perpetual exploration problem. On the minimal side, we prove that three deterministic robots are necessary and sufficient, provided that the size n of the ring is at least 10, and show that no protocol with three robots can exclusively perpetually explore a ring of size less than 10. On the maximal side, we prove that k = n - 5 robots are necessary and sufficient to exclusively perpetually explore a ring of size n when n is coprime with k.

Distributed chasing of network intruders

Abstract: Graph searching is one of the most popular tools for analyzing the chase for a powerful and hostile software agent (called the ''intruder''), by a set of software agents (called the ''searchers'') in a network. The existing solutions for the graph searching problem suffer however from a serious drawback: they are mostly centralized and assume a global synchronization mechanism for the searchers. In particular: (1) the search strategy for every network is computed based on the knowledge of the entire topology of the network, and (2) the moves of the searchers are controlled by a centralized mechanism that decides at every step which searcher has to move, and what movement it has to perform. This paper addresses the graph searching problem in a distributed setting. We describe a distributed protocol that enables searchers with logarithmic size memory to clear any network, in a fully decentralized manner. The search strategy for the network in which the searchers are launched is computed online by the searchers themselves without knowing the topology of the network in advance. It performs in an asynchronous environment, i.e., it implements the necessary synchronization mechanism in a decentralized manner. In every network, our protocol performs a connected strategy using at most k+1 searchers, where k is the minimum number of searchers required to clear the network in a monotone connected way using a strategy computed in the centralized and synchronous setting.

On Proof-Labeling Schemes versus Silent Self-stabilizing Algorithms

Abstract: It follows from the definition of silent self-stabilization, and from the definition of proof-labeling scheme, that if there exists a silent self-stabilizing algorithm using l-bit registers for solving a task \({\mathcal{T}} \), then there exists a proof-labeling scheme for \({\mathcal{T}} \) using registers of at most l bits. The first result in this paper is the converse to this statement. We show that if there exists a proof-labeling scheme for a task \({\mathcal{T}} \), using l-bit registers, then there exists a silent self-stabilizing algorithm using registers of at most O(l + logn) bits for solving \({\mathcal{T}} \), where n is the number of processes in the system. Therefore, as far as memory space is concerned, the design of silent self-stabilizing algorithms essentially boils down to the design of compact proof-labeling schemes. The second result in this paper addresses time complexity. We show that, for every task \({\mathcal{T}} \) with k-bits output size in n-node networks, there exists a silent self-stabilizing algorithm solving \({\mathcal{T}} \) in O(n) rounds, using registers of O(n 2 + kn) bits. Therefore, as far as running time is concerned, every task has a silent self-stabilizing algorithm converging in a linear number of rounds.

An improved snap-stabilizing PIF algorithm

Abstract: A snap-stabilizing protocol, starting from any arbitrary initial configuration, always behaves according to its specification. In [10], Cournier and al. present the first snap-stabilizing Propagation of Information with Feedback (PIF) protocol in arbitrary networks. But, in order to achieve the desirable property of snap-stabilization, the algorithm needs the knowledge of the exact size of the network. This drawback prevents the protocol from working on dynamical systems. In this paper, we propose an original protocol which solves this drawback.

Loop-free super-stabilizing spanning tree construction

Abstract: We propose an univesal scheme to design loop-free and super-stabilizing protocols for constructing spanning trees optimizing any tree metrics (not only those that are isomorphic to a shortest path tree). Our scheme combines a novel super-stabilizing loop-free BFS with an existing self-stabilizing spanning tree that optimizes a given metric. The composition result preserves the best properties of both worlds: super-stabilization, loop-freedom, and optimization of the original metric without any stabilization time penalty. As case study we apply our composition mechanism to two well known metric-dependent spanning trees: the maximum-flow tree and the minimum degree spanning tree.

Construction of Tree Network with Limited Delivery Latency in Homogeneous Wireless Sensor Networks

Abstract: In this paper we propose an approximation algorithm, which is called ADCMCST (algorithm with the minimum number of child nodes when the depth is restricted), to construct a tree network for homogeneous wireless sensor network, so as to reduce and balance the payload of each node, and consequently prolong the network lifetime. When the monitoring node obtains the neighbor graph, ADCMCST tries to find a tree topology with a minimum number of child nodes, and then broadcast the topology to every node, and finally a tree network is constructed. Simulation results show that ADCMCST could greatly reduce the topology formation time, and achieve good approximation results; when the compression ratio is less than 70 %, the network lifetime of ADCMCST will be larger than that of energy driven tree construction.

Distributed Computing by Oblivious Mobile Robots

Abstract: The study of what can be computed by a team of autonomous mobile robots, originally started in robotics and AI, has become increasingly popular in theoretical computer science (especially in distributed computing), where it is now an integral part of the investigations on computability by mobile entities. The robots are identical computational entities located and able to move in a spatial universe; they operate without explicit communication and are usually unable to remember the past; they are extremely simple, with limited resources, and individually quite weak. However, collectively the robots are capable of performing complex tasks, and form a system with desirable fault-tolerant and self-stabilizing properties. The research has been concerned with the computational aspects of such systems. In particular, the focus has been on the minimal capabilities that the robots should have in order to solve a problem. This book focuses on the recent algorithmic results in the field of distributed computing by oblivious mobile robots (unable to remember the past). After introducing the computational model with its nuances, we focus on basic coordination problems: pattern formation, gathering, scattering, leader election, as well as on dynamic tasks such as flocking. For each of these problems, we provide a snapshot of the state of the art, reviewing the existing algorithmic results. In doing so, we outline solution techniques, and we analyze the impact of the different assumptions on the robots' computability power. Table of Contents: Introduction / Computational Models / Gathering and Convergence / Pattern Formation / Scatterings and Coverings / Flocking / Other Directions

Challenging the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL): A Survey

Abstract: RPL is the IPv6 routing protocol for low-power and lossy networks, standardized by IETF in 2012 as RFC6550. Specifically, RPL is designed to be a simple and inter-operable networking protocol for resource-constrained devices in industrial, home, and urban environments, intended to support the vision of the Internet of Things with thousands of devices interconnected through multihop mesh networks. More than four-years have passed since the standardization of RPL, and we believe that it is time to examine and understand its current state. In this paper, we review the history of research efforts in RPL; what aspects have been (and have not been) investigated and evaluated, how they have been studied, what was (and was not) implemented, and what remains for future investigation. We reviewed over 97 RPL-related academic research papers published by major academic publishers and present a topic-oriented survey for these research efforts. Our survey shows that only 40.2% of the papers evaluate RPL through experiments using implementations on real embedded devices, ContikiOS and TinyOS are the two most popular implementations (92.3%), and TelosB was the most frequently used hardware platform (69%) on testbeds that have average and median size of 49.4 and 30.5 nodes, respectively. Furthermore, unfortunately, despite it being approximately four years since its initial standardization, we are yet to see wide adoption of RPL as part of real-world systems and applications. We present our observations on the reasons behind this and suggest directions on which RPL should evolve.