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Random layout model with í µí±‰ = 50, where the numbers inside circles imply the cluster IDs.

Random layout model with í µí±‰ = 50, where the numbers inside circles imply the cluster IDs.

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Communication among isolated networks (clusters) in delay tolerant networks (DTNs) can be supported by a message ferry, which collects bundles from clusters and delivers them to a sink node. When there are lots of distant static clusters, multiple message ferries and sink nodes will be required. In this paper, we aim to make groups each of which co...

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... consider an area of 40 [km] × 30 [km], where fifty isolated clusters (í µí±‰ = 50) are randomly located, as illustrated in Fig. 1 and we then set í µí² = [í µí±‘ í µí±–í µí±— ] (í µí±–, í µí±— ∈ í µí²±) accordingly. For inter-cluster communications, we assume that each message ferry travels at a fixed speed of 10 m/s (i.e., 36 km/h). Table I illustrates two settings of í µí½† for heterogeneous and moderately loaded cases where í µí¼Œ í µí±– is assigned in an ...

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Communication among isolated networks (clusters) in delay tolerant networks (DTNs) can be supported by a message ferry, which collects bundles from clusters and delivers them to a sink node. When there are lots of distant static clusters, multiple message ferries and sink nodes will be required. In this paper, we aim to make groups, each of which c...

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Article
Full-text available
Communication among isolated networks (clusters) in delay tolerant networks (DTNs) can be supported by a message ferry, which collects bundles from clusters and delivers them to a sink node. When there are lots of distant static clusters, multiple message ferries and sink nodes will be required. In this paper, we aim to make groups, each of which consists of physically close clusters, a sink node, and a message ferry. Our objective is minimizing the overall mean delivery delay of bundles in consideration of both the offered load of clusters and distances between clusters and their sink nodes. Based on existing work, we first model this problem as a nonlinear integer programming. Using a commercial nonlinear solver, we obtain a quasi-optimal grouping. Through numerical evaluations, we show the fundamental characteristics of grouping, the impact of location limitation of base clusters, and the relationship between delivery delay and the number of base clusters.