This paper proposes a self-stabilizing distributed algorithm for deploying mobile nodes with loaded energy to the stationary nodes by considering the energy those stationary nodes need. The goal is to deploy mobile no...
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This paper proposes a self-stabilizing distributed algorithm for deploying mobile nodes with loaded energy to the stationary nodes by considering the energy those stationary nodes need. The goal is to deploy mobile nodes to appropriate locations for energy supplements such that the network lifetime can be extended. The problem of maximizing the lifetime is NP-hard. Therefore, it is unrealistic to search for an optimal solution in sensor networks. In this paper, we design several simple rules for mobile nodes and stationary nodes separately in order to find a feasible solution. Simple rules are especially suitable and necessary for low computability sensor networks. Our algorithm is simple and distributed. We prove that our method is stable and has good performance. Simulations show its efficiency too. Copyright (c) 2010 John Wiley & Sons, Ltd.
This paper presents distributed self-stabilizing algorithms for the maximal independent and the minimal dominating set problems. Using an unfair distributed scheduler the algorithms stabilizes in at most max{3n - 5, 2...
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This paper presents distributed self-stabilizing algorithms for the maximal independent and the minimal dominating set problems. Using an unfair distributed scheduler the algorithms stabilizes in at most max{3n - 5, 2n} resp. 9n moves. All previously known algorithms required O(n(2)) moves. (c) 2007 Elsevier B.V. All rights reserved.
The maximum weight matching problem is a fundamental problem in graph theory with a variety of important applications. Recently Manne and Mjelde presented the first self-stabilizing algorithm computing a 2-approximati...
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The maximum weight matching problem is a fundamental problem in graph theory with a variety of important applications. Recently Manne and Mjelde presented the first self-stabilizing algorithm computing a 2-approximation of the optimal solution. They established that their algorithm stabilizes after 0(2(n)) (resp. 0(3")) moves under a central (resp. distributed) scheduler. This paper contributes a new analysis, improving these bounds considerably. In particular it is shown that the algorithm stabilizes after 0(nm) moves under the central scheduler and that a modified version of the algorithm also stabilizes after 0(nm) moves under the distributed scheduler. The paper presents a new proof technique based on graph reduction for analyzing the complexity of self-stabilizing algorithms. (C) 2010 Elsevier B.V. All rights reserved.
The non-computability of many distributed tasks in anonymous networks is well known. This paper presents a deterministic self-stabilizing algorithm to compute a (3 - 2/Delta+1)-approximation of a minimum vertex cover ...
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The non-computability of many distributed tasks in anonymous networks is well known. This paper presents a deterministic self-stabilizing algorithm to compute a (3 - 2/Delta+1)-approximation of a minimum vertex cover in anonymous networks. The algorithm operates under the distributed unfair scheduler, stabilizes after O(n + m) moves respectively O(Delta) rounds, and requires O(log n) storage per node. Recovery from a single fault is reached within a constant time and the contamination number is O(Delta). For trees the algorithm computes a 2-approximation of a minimum vertex cover. (C) 2010 Elsevier B.V. All rights reserved.
The non-computability of many distributed tasks in anonymous networks is well known. This paper presents a deterministic self-stabilizing algorithm to compute a (3 - 2/Delta+1)-approximation of a minimum vertex cover ...
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The non-computability of many distributed tasks in anonymous networks is well known. This paper presents a deterministic self-stabilizing algorithm to compute a (3 - 2/Delta+1)-approximation of a minimum vertex cover in anonymous networks. The algorithm operates under the distributed unfair scheduler, stabilizes after O(n + m) moves respectively O(Delta) rounds, and requires O(log n) storage per node. Recovery from a single fault is reached within a constant time and the contamination number is O(Delta). For trees the algorithm computes a 2-approximation of a minimum vertex cover. (C) 2010 Elsevier B.V. All rights reserved.
The maximum weight matching problem is a fundamental problem in graph theory with a variety of important applications. Recently Manne and Mjelde presented the first self-stabilizing algorithm computing a 2-approximati...
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The maximum weight matching problem is a fundamental problem in graph theory with a variety of important applications. Recently Manne and Mjelde presented the first self-stabilizing algorithm computing a 2-approximation of the optimal solution. They established that their algorithm stabilizes after 0(2(n)) (resp. 0(3")) moves under a central (resp. distributed) scheduler. This paper contributes a new analysis, improving these bounds considerably. In particular it is shown that the algorithm stabilizes after 0(nm) moves under the central scheduler and that a modified version of the algorithm also stabilizes after 0(nm) moves under the distributed scheduler. The paper presents a new proof technique based on graph reduction for analyzing the complexity of self-stabilizing algorithms. (C) 2010 Elsevier B.V. All rights reserved.
A leader node is defined to be any node of the network unambiguously identified by some characteristics. In this paper, we first present a distributed algorithm for finding a leader node of a directed split-star. More...
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A leader node is defined to be any node of the network unambiguously identified by some characteristics. In this paper, we first present a distributed algorithm for finding a leader node of a directed split-star. Moreover, an efficient self-stabilizing leader election algorithm that converges with linear rounds is proposed for directed split-stars. Actually, the distributed algorithm and the self-stabilizing algorithm are also applicable to the problem of directed alternating group graphs. As far as we know, no self-stabilizing leader election algorithm was known for the two graphs.
The maximal matching problem has received considerable attention in the self-stabilizing community. Previous work has given several self-stabilizing algorithms that solve the problem for both the adversarial and the f...
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The maximal matching problem has received considerable attention in the self-stabilizing community. Previous work has given several self-stabilizing algorithms that solve the problem for both the adversarial and the fair distributed daemon, the sequential adversarial daemon, as well as the synchronous daemon. In the following we present a single self-stabilizing algorithm for this problem that unites all of these algorithms in that it has the same time complexity as the previous best algorithms for the sequential adversarial. the distributed fair, and the synchronous daemon. In addition, the algorithm improves the previous best time complexities for the distributed adversarial daemon from O(n(2)) and O(delta m) to O(m) where n is the number of processes, m is the number of edges, and delta is the maximum degree in the graph. (C) 2008 Elsevier B.V. All rights reserved.
This paper presents a new distributed self-stabilizing algorithm for the weakly connected minimal dominating set problem. It assumes a self-stabilizing algorithm to compute a breadth-first tree. Using an unfair distri...
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This paper presents a new distributed self-stabilizing algorithm for the weakly connected minimal dominating set problem. It assumes a self-stabilizing algorithm to compute a breadth-first tree. Using an unfair distributed scheduler the algorithm stabilizes in at most O (nmA) moves, where A is the number of moves to construct a breadth-first tree. All previously known algorithms required an exponential number of moves. (C) 2009 Elsevier B.V. All rights reserved.
This paper presents a deterministic self-stabilizing algorithm that computes a 3-approximation vertex cover in anonymous networks. It reaches a legal state after O(n + m) moves or 2n + 1 rounds respectively and recove...
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ISBN:
(纸本)9783642051173
This paper presents a deterministic self-stabilizing algorithm that computes a 3-approximation vertex cover in anonymous networks. It reaches a legal state after O(n + m) moves or 2n + 1 rounds respectively and recovers from a single fault within a constant containment time. The contamination number is 2 Delta + 1. An enhanced version of this algorithm achieves a 2-approximation on trees
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