Self-stabilizing neighborhood synchronizer in tree networks

Johnen, Colette; Alima, Luc Onana; Datta, Ajoy K.; Tixeuil, Sébastien

doi:10.1109/icdcs.1999.776551

Cited by 8 publications

(5 citation statements)

References 22 publications

(23 reference statements)

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“…Global self-stabilizing synchronizers for tree networks are also proposed in [13,3,11]. A self-stabilizing local synchronizer, that synchronizes each node in a tree network with its neighbours is presented in [18]. In the recent literature, several communication problems in the message-passing model have been addressed.…”

Section: Related Work and Resultsmentioning

confidence: 99%

Reliable Self-Stabilizing Communication for Quasi Rendezvous

Johnen,

Lavallee,

Lavault

2010

Preprint

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The paper presents three self-stabilizing protocols for basic fair and reliable link communication primitives. We assume a link-register communication model under read/write atomicity, where every process can read from but cannot write into its neighbours' registers. The first primitive guarantees that any process writes a new value in its register(s) only after all its neighbours have read the previous value, whatever the initial scheduling of processes' actions. The second primitive implements a "weak rendezvous" communication mechanism by using an alternating bit protocol: whenever a process consecutively writes n values (possibly the same ones) in a register, each neighbour is guaranteed to read each value from the register at least once. On the basis of the previous protocol, the third primitive implements a "quasi rendezvous": in words, this primitive ensures furthermore that there exists exactly one reading between two writing operations All protocols are self-stabilizing and run in asynchronous arbitrary networks. The goal of the paper is in handling each primitive by a separate procedure, which can be used as a "black box" in more involved self-stabilizing protocols.

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Section: Related Work and Resultsmentioning

confidence: 99%

Reliable Self-Stabilizing Communication for Quasi Rendezvous

Johnen,

Lavallee,

Lavault

2010

Preprint

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“…Let E be an execution. If the value of in i does not change in E, then the value of out i does not change, and the following conditions are satisfied: Figure 1 shows the neighborhood synchronizer protocol N SP [4] in a tree network. Each process i has a logical-type variable col i .…”

Section: [Definition 25] Protocol Request Hpmentioning

confidence: 93%

“…Johnen and colleagues proposed a self-stabilizing neighborhood synchronizer protocol in a tree network [4]. This protocol achieves synchronization between neighboring processes in a tree network.…”

Section: Introductionmentioning

confidence: 98%

“…1 and 2 are large because global synchronization protocols (the root, which is the mediator of the entire system, synchronizes the processes) are being used. Therefore, in this paper, we use a neighborhood synchronizer protocol [4], which only achieves synchronization between neighboring processes, to design a self-stabilizing protocol for configuring a heap-ordered tree.…”

Section: Introductionmentioning

confidence: 99%

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A self‐stabilizing max‐heap protocol in tree networks

Ukena

Hasegawa

Katayama

et al. 2003

Electron Comm Jpn Pt III

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SUMMARYA fault-tolerant protocol is important in a distributed system consisting of processes that are interconnected in a network. One prominent technique used for implementing fault tolerance is a self-stabilizing protocol. A self-stabilizing protocol stabilizes in obtaining a solution regardless of the network status from which execution begins. This property enables a self-stabilizing protocol to tolerate arbitrary transient faults. This paper uses a self-stabilizing protocol for implementing interprocess synchronization in a tree network to propose a self-stabilizing protocol for configuring a heap-ordered tree. The proposed protocol for configuring the heap-ordered tree, which has stabilizing time O(h) and space complexity of each process O(K), has improved both the stabilizing time and space complexity compared with other known results (where h is the height of the tree and K is the input size).

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“…Using a snap-stabilizing PI, as in [24], the protocol ensures that any message broadcast by the root is received by every processor of the system.…”

Section: Snap-stabilizationmentioning

confidence: 99%

Snap-stabilization and PIF in tree networks

et al. 2007

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The contribution of this paper is threefold. First, we present the paradigm of snap-stabilization. A snapstabilizing protocol guarantees that, starting from an arbitrary system configuration, the protocol always behaves according to its specification. So, a snap-stabilizing protocol is a time optimal self-stabilizing protocol (because it stabilizes in 0 rounds). Second, we propose a new Propagation of Information with Feedback (PIF) cycle, called Propagation of Information with Feedback and Cleaning (PFC). We show three different implementations of this new PIF. The first one is a basic PFC cycle which is inherently snap-stabilizing. However, the first PIF cycle can be delayed O(h 2 ) rounds (where h is the height of the tree) due to some undesirable local states. WARNING:The concept of snap-stabilization was first introduced in [12]. The concept evolved over the last eight years. We take this evolution in consideration in this paper, which includes the early results published in [10] and [12]. In particular, infinite repetition of computation cycles is a requirement of self -stabilizing systems. This is not required in snap-stabilization because snap-stabilization ensures that the first completed computation cycle is executed according to the specification of the problem. The correctness proofs conform to this basic property.The second algorithm improves the worst delay of the basic PFC algorithm from O(h 2 ) to 1 round. The state requirement for the above two algorithms is 3 states per processor, except for the root and leaf processors that use only 2 states. Also, they work on oriented trees. We then propose a third snap-stabilizing PIF algorithm on un-oriented tree networks. The state requirement of the third algorithm depends on the degree of the processors, and the delay is at most h rounds. Next, we analyze the maximum waiting time before a PIF cycle can be initiated whether the PIF cycle is infinitely and sequentially repeated or launch as an isolated PIF cycle. The analysis is made for both oriented and un-oriented trees. We show or conjecture that the two best of the above algorithms produce optimal waiting time. Finally, we compute the minimal number of states the processors require to implement a single PIF cycle, and show that both algorithms for oriented trees are also (in addition to being time optimal) optimal in terms of the number of states.

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Self-stabilizing neighborhood synchronizer in tree networks

Cited by 8 publications

References 22 publications

Reliable Self-Stabilizing Communication for Quasi Rendezvous

Reliable Self-Stabilizing Communication for Quasi Rendezvous

A self‐stabilizing max‐heap protocol in tree networks

Snap-stabilization and PIF in tree networks

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