Gathering is a fundamental coordination problem in cooperative mobile robotics. In short, given a set of robots with arbitrary initial locations and no initial agreement on a global coordinate system, gathering requires that all robots, following their algorithm, reach the exact same but not predetermined location. Gathering is particularly challenging in networks where robots are oblivious (i.e., stateless) and direct communication is replaced by observations on their respective locations. Interestingly any algorithm that solves gathering with oblivious robots is inherently self-stabilizing if no specific assumption is made on the initial distribution of the robots.In this paper, we significantly extend the studies of deterministic gathering feasibility under different assumptions This manuscript considerably extends preliminary results presented as an extended abstract at the DISC 2006 conference [7]. The current version is under review at related to synchrony and faults (crash and Byzantine). Unlike prior work, we consider a larger set of scheduling strategies, such as bounded schedulers. In addition, we extend our study to the feasibility of probabilistic self-stabilizing gathering in both fault-free and fault-prone environments.
International audiencePublish/Subscribe systems provide a useful platform for delivering data (events) from publishers to subscribers in an anonymous fashion in distributed networks. In this pa-per, we promote a novel design principle for self-* dynamic and reliable content-based publish/subscribe systems and perform a comparative analysis of its probabilistic and de-terministic implementations. More specifically, we present a generic content-based publish/subscribe system, called DPS (Dynamic Publish/Subscribe). DPS combines classi-cal content-based filtering with self-* (self-organizing, self-configuring, and self-healing) subscription-driven cluster-ing of subscribers. DPS gracefully adapts to failures and changes in the system while achieving scalable events deliv-ery. DPS includes a variety of fault-tolerant deterministic and probabilistic content-based publication/subscription schemes. These schemes are targeted toward scalability, and aim at reducing and distributing the number of mes-sages exchanged. Reliability and scalability of our system are shown through analytical and experimental evaluation
We study the memory requirements of self-stabilizing leader election (SSLE) protocols. We are mainly interested in two types of systems: anonymous systems and id-based systems. We consider two classes of protocols: deterministic ones and randomized ones.We prove that a non-constant lower bound on the memory space is required by a SSLE protocol on unidirectional, anonymous rings (even if the protocol is randomized).We show that, if there is a deterministic protocol solving a problem on id-based systems where the processor memory space is constant and the id-values are not bounded then there is a deterministic protocol on anonymous systems using constant memory space that solves the same problem. Thus impossibility results on anonymous rings (i.e. one may design a deterministic SSLE protocol, only on prime size rings, under a centralized daemon) can be extended to those kinds of id-based rings. Nevertheless, it is possible to design a silent and deterministic SSLE protocol requiring constant memory space on unidirectional, id-based rings where the id-values are bounded. We present such a protocol.We also present a randomized SSLE protocol and a token circulation protocol under an unfair, distributed daemon on anonymous and unidirectional rings of any size. We give a lower bound on memory space requirement proving that these protocols are space optimal. The memory space required is constant on average.
We present a randomized self-stabilizing leader election protocol and a randomized self-stabilizing token circulation protocol under an arbitrary scheduler on anonymous and unidirectional rings of any size. These protocols are space optimal. We also give a formal and complete proof of these protocols. To this end, we develop a complete model for probabilistic self-stabilizing distributed systems which clearly separates the non deterministic behavior of the scheduler from the randomized behavior of the protocol. This framework includes all the necessary tools for proving the selfstabilization of a randomized distributed system: definition of a probabilistic space and definition of the self-stabilization of a randomized protocol. We also propose a new technique of scheduler management through a self-stabilizing protocol composition (cross-over composition). Roughly speaking, we force all computations to have a fairness property under any scheduler, even under an unfair one.
Caching Internet based services is a potentially important application for MANETs, as it can improve mobile users' perceived quality of service, reduce their energy consumption, and lower their air-time costs. This paper considers the problem of locating cache proxies in MANETs using several search techniques. The paper first examines several existing and a few novel search techniques including flooding, constrained flooding, a novel dynamic variation of probabilistic flooding, and BFS. These are superimposed on a Maximal Independent Set (MIS), a Connected Dominating Set (DS), and a novel adaptation of BFS-tree based overlays, where each of these overlays is maintained in a self stabilizing manner. The paper also includes a comparison of the performance of these search techniques and overlays by extensive simulations.
International audienceIn this paper, we specify the conflict manager abstraction. Informally, a conflict manager guarantees that any two nodes that are in conflict cannot enter their critical section simultaneously (safety), and that at least one node is able to execute its critical section (progress). The conflict manager problem is strictly weaker than the classical local mutual exclusion problem, where any node that requests to enter its critical section eventually does so (fairness). We argue that conflict managers are a useful mechanism to transform a large class of self-stabilizing algorithms that operate in an essentially sequential model, into self-stabilizing algorithm that operate in a completely asynchronous distributed model. We provide two implementations (one deterministic and one probabilistic) of our abstraction, and provide a composition mechanism to obtain a generic transformer. Our transformers have low overhead: the deterministic transformer requires one memory bit, and guarantees time overhead in order of the network degree, the probabilistic transformer does not require extra memory. While the probabilistic algorithm performs in anonymous networks, it only provides probabilistic stabilization guarantees. In contrast, the deterministic transformer requires initial symmetry breaking but preserves the original algorithm guarantees
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