Evolving Random Geometric Graph Models for Mobile Wireless Networks
We consider evolving exponential RGGs in one dimension and characterize the time dependent behavior of some of their topological properties. We consider two evolution models and study one of them detail while providing a summary of the results for the other. In the first model, the inter-nodal gaps...
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creator | Karamchandani, N. Manjunath, D. Yogeshwaran, D. Iyer, S.K. |
description | We consider evolving exponential RGGs in one dimension and characterize the time dependent behavior of some of their topological properties. We consider two evolution models and study one of them detail while providing a summary of the results for the other. In the first model, the inter-nodal gaps evolve according to an exponential AR(1) process that makes the stationary distribution of the node locations exponential. For this model we obtain the one-step conditional connectivity probabilities and extend it to the k-step case. Finite and asymptotic analysis are given. We then obtain the k-step connectivity probability conditioned on the network being disconnected. We also derive the pmf of the first passage time for a connected network to become disconnected. We then describe a random birth-death model where at each instant, the node locations evolve according to an AR(1) process. In addition, a random node is allowed to die while giving birth to a node at another location. We derive properties similar to those above. |
doi_str_mv | 10.1109/WIOPT.2006.1666441 |
format | Conference Proceeding |
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We consider two evolution models and study one of them detail while providing a summary of the results for the other. In the first model, the inter-nodal gaps evolve according to an exponential AR(1) process that makes the stationary distribution of the node locations exponential. For this model we obtain the one-step conditional connectivity probabilities and extend it to the k-step case. Finite and asymptotic analysis are given. We then obtain the k-step connectivity probability conditioned on the network being disconnected. We also derive the pmf of the first passage time for a connected network to become disconnected. We then describe a random birth-death model where at each instant, the node locations evolve according to an AR(1) process. In addition, a random node is allowed to die while giving birth to a node at another location. 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We derive properties similar to those above.</description><subject>Ad hoc networks</subject><subject>Context modeling</subject><subject>Mathematics</subject><subject>Mobile ad hoc networks</subject><subject>Probability distribution</subject><subject>Solid modeling</subject><subject>Stochastic processes</subject><subject>Throughput</subject><subject>Wireless networks</subject><subject>Wireless sensor networks</subject><isbn>0780395492</isbn><isbn>9780780395497</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2006</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj11LwzAYhQMiqNv-gN7kD7S--WiaXEqZdTDd0MEuR9u80Wi7jKRM_PdO3Lk5z7l54BByyyBnDMz9drFab3IOoHKmlJKSXZAbKDUIU0jDr8gspU845W-X8ppU82Poj37_Tl-bvQ0DrTEMOEbf0To2hw_6HCz2iboQT9j6HunWR-wxJfqC43eIX2lKLl3TJ5yde0LeHueb6ilbrupF9bDMvIExs8xpYw0g107oljFhBIC0JUpdcM061E5h65gVumsMBy0Kozh2rSukYGJC7v6tHhF3h-iHJv7szi_FL4BDSAI</recordid><startdate>2006</startdate><enddate>2006</enddate><creator>Karamchandani, N.</creator><creator>Manjunath, D.</creator><creator>Yogeshwaran, D.</creator><creator>Iyer, S.K.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>2006</creationdate><title>Evolving Random Geometric Graph Models for Mobile Wireless Networks</title><author>Karamchandani, N. ; Manjunath, D. ; Yogeshwaran, D. ; Iyer, S.K.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-d1f89d90e28f38b11393004d7e485281ce8f6ebf1d38ca920835962ecbf54313</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Ad hoc networks</topic><topic>Context modeling</topic><topic>Mathematics</topic><topic>Mobile ad hoc networks</topic><topic>Probability distribution</topic><topic>Solid modeling</topic><topic>Stochastic processes</topic><topic>Throughput</topic><topic>Wireless networks</topic><topic>Wireless sensor networks</topic><toplevel>online_resources</toplevel><creatorcontrib>Karamchandani, N.</creatorcontrib><creatorcontrib>Manjunath, D.</creatorcontrib><creatorcontrib>Yogeshwaran, D.</creatorcontrib><creatorcontrib>Iyer, S.K.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Karamchandani, N.</au><au>Manjunath, D.</au><au>Yogeshwaran, D.</au><au>Iyer, S.K.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Evolving Random Geometric Graph Models for Mobile Wireless Networks</atitle><btitle>2006 4th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks</btitle><stitle>WIOPT</stitle><date>2006</date><risdate>2006</risdate><spage>1</spage><epage>7</epage><pages>1-7</pages><isbn>0780395492</isbn><isbn>9780780395497</isbn><abstract>We consider evolving exponential RGGs in one dimension and characterize the time dependent behavior of some of their topological properties. We consider two evolution models and study one of them detail while providing a summary of the results for the other. In the first model, the inter-nodal gaps evolve according to an exponential AR(1) process that makes the stationary distribution of the node locations exponential. For this model we obtain the one-step conditional connectivity probabilities and extend it to the k-step case. Finite and asymptotic analysis are given. We then obtain the k-step connectivity probability conditioned on the network being disconnected. We also derive the pmf of the first passage time for a connected network to become disconnected. We then describe a random birth-death model where at each instant, the node locations evolve according to an AR(1) process. In addition, a random node is allowed to die while giving birth to a node at another location. We derive properties similar to those above.</abstract><pub>IEEE</pub><doi>10.1109/WIOPT.2006.1666441</doi><tpages>7</tpages></addata></record> |
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subjects | Ad hoc networks Context modeling Mathematics Mobile ad hoc networks Probability distribution Solid modeling Stochastic processes Throughput Wireless networks Wireless sensor networks |
title | Evolving Random Geometric Graph Models for Mobile Wireless Networks |
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