Universal Loop-Free Super-Stabilization

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

Stabilisation progressive

International audienceCet article est un résumé étendu de (Altisen et al., Euro-Par 2016) dans lequel nous nous intéressons à des réseaux pouvant subir des changements topologiques transitoires. Nous proposons une nouvelle spécialisation de l'autostabilisation adaptée à ce type de réseau : la stabilisation progressive. Un algorithme est progressivement stabilisant sous hypothèse de (τ, ρ)-dynamicité s'il est autostabilisant et satisfait la propriété supplémentaire suivante : après au plus τ pas dynamiques vérifiant la condition ρ et se produisant à partir d'une configuration légitime, l'algorithme converge rapidement vers une configuration où une spécification plus faible est satisfaite ; puis il continue à converger progressivement vers des configurations où des spécifications de plus en plus fortes sont vérifiées, et ce, jusqu'à retrouver une configuration légitime vérifiant la spécification initiale du problème. Nous illustrons cette nouvelle propriété en proposant un algorithme progressivement stabilisant de synchronisation d'horloges

Adaptive Stabilization of Reactive Protocols

Abstract. A self-stabilizing distributed protocol can recover from any state-corrupting fault. A self-stabilizing protocol is called adaptive if its recovery time is proportional to the number of processors hit by the fault. General adaptive protocols are known for the special case of function computations: these are tasks that map static distributed inputs to static distributed outputs. In reactive distributed systems, input values at each node change on-line, and dynamic distributed outputs are to be generated in response in an on-line fashion. To date, only some specific reactive tasks have had an adaptive implementation. In this paper we outline the first proof that all reactive tasks admit adaptive protocols. The key ingredient of the proof is an algorithm for distributing input values in an adaptive fashion. Our algorithm is optimal, up to a constant factor, in its fault resilience, response time, and recovery time.

Self-* distributed query region covering in sensor networks

Wireless distributed sensor networks are used to monitor a multitude of environments for both civil and military applications. Sensors may be deployed to unreachable or inhospitable areas. Thus, they cannot be replaced easily. However, due to various factors, sensors\u27 internal memory, or the sensors themselves, can become corrupted. Hence, there is a need for more robust sensor networks. Sensors are most commonly densely deployed, but keeping all sensors continually active is not energy efficient. Our aim is to select the minimum number of sensors which can entirely cover a particular monitored area, while remaining strongly connected. This concept is called a Minimum Connected Cover of a query region in a sensor network. In this research, we have designed two fully distributed, robust, self-* solutions to the minimum connected cover of query regions that can cope with both transient faults and sensor crashes. We considered the most general case in which every sensor has a different sensing and communication radius. We have also designed extended versions of the algorithms that use multi-hop information to obtain better results utilizing small atomicity (i.e., each sensor reads only one of its neighbors\u27 variables at a time, instead of reading all neighbors\u27 variables). With this, we have proven self-* (self-configuration, self-stabilization, and self-healing) properties of our solutions, both analytically and experimentally. The simulation results show that our solutions provide better performance in terms of coverage than pre-existing self-stabilizing algorithms