Game theory based bio-inspired techniques for self-positioning autonomous MANET nodes
In this paper, we introduce a new node spreading bio-inspired game (NSBG) combining bio-inspired algorithms and traditional game theory to maximize the area covered by autonomous mobile ad hoc network nodes and to achieve a uniform node distribution while keeping the network connected. NSBG is a dis...
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creator | Kusyk, J. Uyar, M. U. Sahin, C. S. Urrea, E. Gundry, S. |
description | In this paper, we introduce a new node spreading bio-inspired game (NSBG) combining bio-inspired algorithms and traditional game theory to maximize the area covered by autonomous mobile ad hoc network nodes and to achieve a uniform node distribution while keeping the network connected. NSBG is a distributed and scalable game where each node's selfish actions lead the entire network toward a uniform and stable node distribution without a centralized controller. In NSBG, each mobile node autonomously makes movement decisions based on localized data while the movement probabilities of possible next locations are assigned by a force-based genetic algorithm (FGA). Because FGA takes only into account the current position of the neighboring nodes, our NSBG, combining FGA with traditional and evolutionary game theory, can find even better locations by setting up spatial games among neighbors. NSBG is a good candidate for the node spreading class of applications used in both military and commercial applications. We present a formal analysis of our NSBG to prove that an evolutionary stable state is its convergence point. Simulation experiments demonstrate that NSBG performs well with respect to network area coverage, uniform distribution of mobile nodes, and convergence speed. |
doi_str_mv | 10.1109/SARNOF.2011.5876440 |
format | Conference Proceeding |
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U.</creatorcontrib><creatorcontrib>Sahin, C. S.</creatorcontrib><creatorcontrib>Urrea, E.</creatorcontrib><creatorcontrib>Gundry, S.</creatorcontrib><title>Game theory based bio-inspired techniques for self-positioning autonomous MANET nodes</title><title>34th IEEE Sarnoff Symposium</title><addtitle>SARNOF</addtitle><description>In this paper, we introduce a new node spreading bio-inspired game (NSBG) combining bio-inspired algorithms and traditional game theory to maximize the area covered by autonomous mobile ad hoc network nodes and to achieve a uniform node distribution while keeping the network connected. NSBG is a distributed and scalable game where each node's selfish actions lead the entire network toward a uniform and stable node distribution without a centralized controller. In NSBG, each mobile node autonomously makes movement decisions based on localized data while the movement probabilities of possible next locations are assigned by a force-based genetic algorithm (FGA). Because FGA takes only into account the current position of the neighboring nodes, our NSBG, combining FGA with traditional and evolutionary game theory, can find even better locations by setting up spatial games among neighbors. NSBG is a good candidate for the node spreading class of applications used in both military and commercial applications. We present a formal analysis of our NSBG to prove that an evolutionary stable state is its convergence point. Simulation experiments demonstrate that NSBG performs well with respect to network area coverage, uniform distribution of mobile nodes, and convergence speed.</description><subject>bio-inspired algorithm</subject><subject>Force</subject><subject>Game theory</subject><subject>Games</subject><subject>Genetic algorithms</subject><subject>MANETs</subject><subject>Mobile ad hoc networks</subject><subject>Mobile communication</subject><subject>Network topology</subject><subject>node spreading</subject><subject>Topology control</subject><isbn>9781612846811</isbn><isbn>1612846815</isbn><isbn>9781612846804</isbn><isbn>1612846807</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVkM1Kw0AcxFdEUGqeoJd9gcTd7PcxlLYKtQVbz2WT_a9dabIxmx769gbsxbkMPxgGZhCaU1JQSszLvvrY7lZFSSgthFaSc3KHMqM0lbTUXGrC7_8xpY8oS-mbTJLSKGae0OfatoDHE8ThimubwOE6xDx0qQ_DBCM0py78XCBhHwec4OzzPqYwhtiF7gvbyxi72MZLwu_VdnnAXXSQntGDt-cE2c1naL9aHhav-Wa3fltUmzwYMuauASWIYh6cc-AdE5SXvPHGiLrhYAnzDpihVHDG9RQV1miomZJ-GgBshuZ_rQEAjv0QWjtcj7cr2C90yVN3</recordid><startdate>201105</startdate><enddate>201105</enddate><creator>Kusyk, J.</creator><creator>Uyar, M. 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S.</creatorcontrib><creatorcontrib>Urrea, E.</creatorcontrib><creatorcontrib>Gundry, S.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kusyk, J.</au><au>Uyar, M. U.</au><au>Sahin, C. S.</au><au>Urrea, E.</au><au>Gundry, S.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Game theory based bio-inspired techniques for self-positioning autonomous MANET nodes</atitle><btitle>34th IEEE Sarnoff Symposium</btitle><stitle>SARNOF</stitle><date>2011-05</date><risdate>2011</risdate><spage>1</spage><epage>5</epage><pages>1-5</pages><isbn>9781612846811</isbn><isbn>1612846815</isbn><eisbn>9781612846804</eisbn><eisbn>1612846807</eisbn><abstract>In this paper, we introduce a new node spreading bio-inspired game (NSBG) combining bio-inspired algorithms and traditional game theory to maximize the area covered by autonomous mobile ad hoc network nodes and to achieve a uniform node distribution while keeping the network connected. NSBG is a distributed and scalable game where each node's selfish actions lead the entire network toward a uniform and stable node distribution without a centralized controller. In NSBG, each mobile node autonomously makes movement decisions based on localized data while the movement probabilities of possible next locations are assigned by a force-based genetic algorithm (FGA). Because FGA takes only into account the current position of the neighboring nodes, our NSBG, combining FGA with traditional and evolutionary game theory, can find even better locations by setting up spatial games among neighbors. NSBG is a good candidate for the node spreading class of applications used in both military and commercial applications. We present a formal analysis of our NSBG to prove that an evolutionary stable state is its convergence point. Simulation experiments demonstrate that NSBG performs well with respect to network area coverage, uniform distribution of mobile nodes, and convergence speed.</abstract><pub>IEEE</pub><doi>10.1109/SARNOF.2011.5876440</doi><tpages>5</tpages></addata></record> |
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subjects | bio-inspired algorithm Force Game theory Games Genetic algorithms MANETs Mobile ad hoc networks Mobile communication Network topology node spreading Topology control |
title | Game theory based bio-inspired techniques for self-positioning autonomous MANET nodes |
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