Self-Stabilizing TDMA Algorithms for Dynamic Wireless Ad-hoc Networks

In dynamic wireless ad-hoc networks (DynWANs), autonomous computing devices set up a network for the communication needs of the moment. These networks require the implementation of a medium access control (MAC) layer. We consider MAC protocols for DynWANs that need to be autonomous and robust as well as have high bandwidth utilization, high predictability degree of bandwidth allocation, and low communication delay in the presence of frequent topological changes to the communication network. Recent studies have shown that existing implementations cannot guarantee the necessary satisfaction of these timing requirements. We propose a self-stabilizing MAC algorithm for DynWANs that guarantees a short convergence period, and by that, it can facilitate the satisfaction of severe timing requirements, such as the above. Besides the contribution in the algorithmic front of research, we expect that our proposal can enable quicker adoption by practitioners and faster deployment of DynWANs that are subject changes in the network topology

A Radio Link Quality Model and Simulation Framework for Improving the Design of Embedded Wireless Systems

Despite the increasing application of embedded wireless systems, developers face numerous challenges during the design phase of the application life cycle. One of the critical challenges is ensuring performance reliability with respect to radio link quality. Specifically, embedded links experience exaggerated link quality variation, which results in undesirable wireless performance characteristics. Unfortunately, the resulting post-deployment behaviors often necessitate network redeployment. Another challenge is recovering from faults that commonly occur in embedded wireless systems, including node failure and state corruption. Self-stabilizing algorithms can provide recovery in the presence of such faults. These algorithms guarantee the eventual satisfaction of a given state legitimacy predicate regardless of the initial state of the network. Their practical behavior is often different from theoretical analyses. Unfortunately, there is little tool support for facilitating the experimental analysis of self-stabilizing systems. We present two contributions to support the design phase of embedded wireless system development. First, we provide two empirical models that predict radio-link quality within specific deployment environments. These models predict link performance as a function of inter-node distance and radio power level. The models are culled from extensive experimentation in open grass field and dense forest environments using all radio power levels and covering up to the maximum distances reachable by the radio. Second, we provide a simulation framework for simulating self-stabilizing algorithms. The framework provides three feature extensions: (i) fault injection to study algorithm behavior under various fault scenarios, (ii) automated detection of non-stabilizing behavior; and (iii) integration of the link quality models described above. Our contributions aim at avoiding problems that could result in the need for network redeployment

Etude de la fiabilité des algorithmes self-convergeants face aux soft-erreurs

This thesis is devoted to the study of the robustness/sensitivity of a self-converging algorithm with respect to SEU's. These phenomenon also called bit-flips which may modify the content of memory elements as the result of the silicon ionization resulting from the impact of a charged particles. This study may have a significant impact given the conditions of miniaturization that will soon have circuits with hundreds to thousands of processing cores on a single chip, this will require make the cores communicate effectively and robust manner. In this context the so-called self-converging algorithm can be used to ensure that communication between cores is reliable and without external intervention. A fault injection study of the robustness of the algorithm was performed, this algorithm was initially executed by a processor LEON3 implemented in the FPGA embedded in a specific platform test. Preliminary fault injection from a method the state of the art called CEU showed some sensitivity to SEUs of algorithm. To cope with the software changes were made and techniques for fault tolerance have been implemented in software in the program implementing the self-converging algorithm. The fault injection experiments were made to demonstrate the robustness to SEU's and potential problems of the modified algorithm. The impact of SEUs was explored on a hardware-implemented self-converging algorithm in a FPGA. The evaluation of this method was performed by fault injection at RTL level circuit. These results obtained with this method have shown a significant improvement of the robustness of the algorithm in comparison with its software version.Cette thèse est consacrée à l'étude de la robustesse/sensibilité d'un algorithme auto-convergeant face aux SEU's. Ces phénomènes appelés aussi bit-flips qui se traduit par le basculement intempestif du contenu d'un élément mémoire comme conséquence de l'ionisation produite par le passage d'une particule chargée avec le matériel. Cette étude pourra avoir un impact important vu la conjoncture de miniaturisation qui permettra bientôt de disposer de circuits avec des centaines à des milliers de cœurs de traitement sur une seule puce, pour cela il faudra faire les cœurs communiquer de manière efficace et robustes. Dans ce contexte les algorithme dits auto-convergeants peuvent être utilis afin que la communication entre les cœurs soit fiable et sans intervention extérieure. Une étude par injection de fautes de la robustesse de l'algorithme étudié a été effectuée, cet algorithme a été initialement exécuté par un processeur LEON3 implémenté dans un FPGA embarqué dans une plateforme de test spécifique. Les campagnes préliminaires d'injection de fautes issus d'une méthode de l'état de l'art appelée CEU (Code Emulated Upset) ont mis en évidence une certaine sensibilité aux SEUs de l'algorithme. Pour y faire face des modifications du logiciel ont été effectuées et des techniques de tolérance aux fautes ont été implémentés au niveau logiciel dans le programme implémentant l'algorithme. Des expériences d'injection de fautes ont été effectués pour mettre en évidence la robustesse face aux SEUs et ses potentiels « Tallons d'Achille » de l'algorithme modifié. L'impact des SEUs a été aussi exploré sur l'algorithme auto-convergeant implémenté dans une version hardware dans un FPGA. L'évaluation de cette méthodologie a été effectuée par des expériences d'injection de fautes au niveau RTL du circuit. Ces résultats obtenus avec cette méthode ont montré une amélioration significative de la robustesse de l'algorithme en comparaison avec sa version logicielle

Self-stabilizing deterministic TDMA for sensor networks

An algorithm for time division multiple access (TDMA) is found to be applicable in converting existing distributed algorithms into a model that is consistent with sensor networks. Such a TDMA service needs to be self-stabilizing so that in the event of corruption of assigned slots and clock drift, it recovers to states from where TDMA slots are consistent. Previous self-stabilizing solutions for TDMA are either randomized or assume that the topology is known upfront and cannot change. Thus, the question of feasibility of self-stabilizing deterministic TDMA algorithm where topology is unknown remains open. In this paper, we present a self-stabilizing, deterministic algorithm for TDMA in networks where a sensor is aware of only its neighbors. This is the first such algorithm that achieves these properties. Moreover, this is the first algorithm that demonstrates the feasibility of stabilization-preserving, deterministic transformation of a shared memory distributed program on an arbitrary topology into a program that is consistent with the sensor network model

Fast Abstract: Self-Stabilizing Deterministic TDMA for Sensor Networks ⋆

Abstract. In this paper, we present a self-stabilizing, deterministic algorithm for TDMA in sensor networks where a sensor is aware of only its neighbors. We derive this algorithm by systematically reusing a distance 2 coloring algorithm. Keywords: Self-stabilization, TDMA, Determinism, Sensor networks