Proceedings of the Twenty-First Annual Symposium on Principles of Distributed Computing - PODC '02 2002
DOI: 10.1145/571865.571872
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Cited by 51 publications
(67 citation statements)
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“…In fact, as discussed in Section 7.4 we consider a dynamic upper bound. Figure 12 illustrates the percentage of FPs that are not involved in the protocol in cases the node speed is contained in [5,7] m/sec and it is contained in [3,9] m/sec. This percentage indicates the reduction of message transmissions.…”
Section: Mdq Systemsmentioning
confidence: 99%
“…In fact, as discussed in Section 7.4 we consider a dynamic upper bound. Figure 12 illustrates the percentage of FPs that are not involved in the protocol in cases the node speed is contained in [5,7] m/sec and it is contained in [3,9] m/sec. This percentage indicates the reduction of message transmissions.…”
Section: Mdq Systemsmentioning
confidence: 99%
“…The high dynamicity and the sheer size of such networking topologies ask for the adoption of decentralized approaches to information dissemination [1][2][3][4]. In this paper, the problem of efficiently disseminating information (or queries) across a large-scale, resource-limited, ad hoc-structured wireless network, such as a wireless sensor network, is considered.…”
Section: Introductionmentioning
confidence: 99%
“…in [17,18,6,12], but the implicit model is completely different from ours. In the aforementioned works, agents are software entities that are exchanged through messages between processes (that are located in the nodes of the network), and thus can be destroyed, duplicated, and created at will.…”
Section: Introductionmentioning
confidence: 82%
“…In [18], exactly n agents are supposed to traverse a n sized tree network infinitely often, by means of a swap primitive that swaps agents located at two neighboring nodes. In [12], the authors consider dynamic evolving networks and rely on random walks to ensure proper agent traversal; again, the purpose of the agent protocol is to ensure that a single agent stabilizes the system. By contrast, in this paper, we focus on the self-stabilization of the agents themselves, and our model keeps the number of agents fixed for the whole life of the network.…”
Section: Introductionmentioning
confidence: 99%