2008
DOI: 10.1109/tnet.2007.897964
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Efficient Routing in Intermittently Connected Mobile Networks: The Multiple-Copy Case

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Cited by 677 publications
(567 citation statements)
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References 34 publications
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“…In the paper [12], the authors make use of a semi-Markov chain to analyze the contact probability of two nodes at equilibrium and also the probability that one node meets another at a specific location within certain time period. Spray and Wait protocol [24] derives the relationship between the number of nodes and the amount of copies in order to get the optimal number of copies to spread. By using the two-state Markov model and geometric distribution, the expected hitting time (to a location) and meeting time (of two nodes) are found for time-variant Community mobility model in [27].…”
Section: Related Workmentioning
confidence: 99%
“…In the paper [12], the authors make use of a semi-Markov chain to analyze the contact probability of two nodes at equilibrium and also the probability that one node meets another at a specific location within certain time period. Spray and Wait protocol [24] derives the relationship between the number of nodes and the amount of copies in order to get the optimal number of copies to spread. By using the two-state Markov model and geometric distribution, the expected hitting time (to a location) and meeting time (of two nodes) are found for time-variant Community mobility model in [27].…”
Section: Related Workmentioning
confidence: 99%
“…Spyropoulos et al [11] propose a multi-copy routing scheme to reduce the overhead of epidemic routing by restricting the number of message copies to L. To choose the minimum L value that meets the specific delay constraint, the global network information such as the number of nodes is required. Our approach in AMR uses a similar approach by restricting the number of messages while maintaining the end-to-end delay close to that of epidemic routing.…”
Section: Related Workmentioning
confidence: 99%
“…Otherwise, the multi-copy routing is used to exploit the multi-copy diversity gain. The parameter, α is a constraint that controls the tradeoff between end-to-end delay and overhead, which is a similar concept with the optimality control parameter used in [11]. We first describe the basic assumptions and ideas that AMR employs (Sect.…”
Section: Adaptive Multi-copy Routing (Amr) Protocolmentioning
confidence: 99%
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“…Analytical models can avoid these drawbacks providing a fast and broader performance evaluation. Two classes of analytical models have been proposed for modelling this network dynamics: Markovian models [5,6,7,8,9,10] and deterministic models based 35 on Ordinary Differential Equations (ODEs) [6,11,12,13]. Analytical models require anyway a precise and concise description of the mobility scenario, that usually assume that the inter-contact times distribution between pairs of nodes are exponentially distributed with a given contact rate [5].…”
mentioning
confidence: 99%