2006
DOI: 10.1109/lcn.2006.322105
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Clustered Mobility Model for Scale-Free Wireless Networks

Abstract: Recently, researchers have discovered that many of social, natural and biological networks are characterized by scale-free power-law connectivity distribution and a few densely populated nodes, known as hubs. We envision that wireless communication or sensor networks are directly deployed over such real-world networks to facilitate communication among participating entities. Here nodes move in such a way that they exhibit scale-free connectivity distribution at any instance, which cannot be modeled by most of … Show more

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Cited by 43 publications
(39 citation statements)
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“…All edges represent movement paths of nodes in the grid map. We designed the node mobility model on the basis of the Manhattan model [19,20]. The dotted circles in the figure represent the coverage area of each base station.…”
Section: Simulation Design and Resultsmentioning
confidence: 99%
“…All edges represent movement paths of nodes in the grid map. We designed the node mobility model on the basis of the Manhattan model [19,20]. The dotted circles in the figure represent the coverage area of each base station.…”
Section: Simulation Design and Resultsmentioning
confidence: 99%
“…We have integrated the knowledge of human mobility patterns into our deletion mechanism as we introduce the static helper nodes (static H-nodes) based on the idea of Human Gathering Points". These static H-nodes will play the role in expediting the distribution of ACK messages Human Gathering Points: The hotspot model is one of the commonly found characteristics of human mobility in various studies [8,9,10,11]. This model suggests that there are locations where many people naturally meet in space.…”
Section: Mobility Patterns and Helper Nodesmentioning
confidence: 99%
“…Although sparse networks are extensively modeled and studied, not much attention is paid to clustered networks. In fact, we are aware of only few mobility models that, by tuning their parameters, may lead to such networks [13,20,23,30].…”
Section: Introductionmentioning
confidence: 99%