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Mobile Agents for Clustering and Routing in Mobile Ad Hoc Networks 273mobile agent uses node mobility and link characteristic related parameters for clustering.A mobile agent is capable of migrating autonomously carrying code, data and statewith itself. It can even spawn off child agents anywhere in the network, merge thequery results and send back the final result to the source node. Mobile agents canimprove bandwidth utilization, reduce communication latency, minimize connectiontime, and reduce network traffic load.An attractive application of mobile agents is processing data over unreliable networks,such as MANETs. In such an environment, the low reliability network can beused to transfer agents, rather than a chunk of data, from one node to another. InMANETs, the agents can travel to the nodes of the cluster and collect or process clusteringand routing information, without the risk of network disconnection, and thenreturn to its originating node.In order to deploy mobile agents in MANETs, a suitable mobile agent platform isneeded. Conventional mobile agent platforms such as Aglets [16], Concordia [23],and D’Agent [8], to name a few, operate within high-end desktop environments suchas Windows and Unix. As a result some research projects have recently been proposedto develop mobile agent platforms for mobile devices. The Lightweight ExtensibleAgent Platform (LEAP) [18] aims to develop a FIPA-compliant mobile agentplatform for mobile devices with services in the area of knowledge and travel management.In our research, we hope to develop our own mobile agent platforms forMANETs.3 Mobile Agents for Clustering and RoutingIn a clustered network, a cluster may be organized into a multilevel hierarchy. A hierarchicalclustering architecture can reduce network routing overhead by hiding informationabout the content of the cluster. Route maintenance procedures and routingtable length can be significantly reduced [14]. Such architecture is relatively stableand scalable due to the localized nature of route computation and can be used inMANETs. Most previous works on clustering are based on the design of algorithmsthat form a 2-hop clustering architecture. These algorithms use a single parametersuch as node ID, connectivity, signal strength, mobility, power or some combinationof these for cluster formation. The cluster formation process can be slow since themethod of gathering the information necessary for cluster formation may not be efficientif clustering with more than 2-hop architecture is desired.Since mobile agents are autonomous and intelligent entities, they can be used forcreating dynamic and adaptive clustering in MANETs [22]. Distributed route computationcan be performed at each node. The clustering architecture consists of ordinarynodes, clusterheads and gateways. In our architecture, intra-cluster and inter-clusterrouting can be carried out using reactive, proactive or hybrid routing schemes. Since asingle criterion is not sufficient for a stable and efficient cluster formation, an aggregatemetric that includes node mobility, link quality, available bandwidth, etc. will bemaintained and used for cluster formation. This metric will also be used by the clusteringagent to assess the quality of the clusterhead periodically.
274 M.K. Denko and Q.H. Mahmoud3.1 Maintaining Routing and Clustering InformationIn our proposed architecture, each node has a Routing Mobile Agent (RMA) and aClustering Static Agent (CSA). These agents operate on top of an agent platformrunning on top of a Java virtual machine suitable for mobile devices such as the KiloVirtual Machine (KVM). The CSA maintains clustering information in a clusteringtable. The clustering table contains IDs of neighbors, the node role (ordinary node,gateway or clusterhead), mobility information, nodal degree and signal strength. Therouting mobile agent moves across the network to collect and maintain routing tableswhile the clustering agent gathers and maintains clustering information.All inter-cluster routing is performed via the clusterhead. On receiving a packetfrom a node, the clusterhead forwards the packet to the preferred gateway which inturn forwards it to the adjacent cluster. In the event that the clusterhead does not havethis information, it can deploy the mobile agent to get the route to the target destination.Routing and clustering table entries at the clusterheads are updated periodicallywith up-to-date values based on timestamps.To localize the agent mobility, the routing agent in a mobile node migrates onlywithin its cluster. The routing mobile agent also updates routing and clustering informationduring each visit. The agents at the clusterhead also maintain informationabout other clusterheads and gateways. The clustering agent elects a clusterheadbased on the clustering information maintained at each mobile node. Once the clusteringarchitecture stabilizes, each node will have a complete knowledge of itsneighbors.We have devised a migration strategy for routing mobile agents. To find a route,the Routing Mobile Agent (RMA) uses the following algorithm:IF the RMA does not have the routethenThe RMA moves to the Clusterheadin that Cluster;The RMA communicates with theClusterhead;IF the Clusterhead has the routing infothenThe RMA goes back and updates routes;ElseRMA in clusterhead continues route searchin other Clusters;END IFEND IF3.2 Mobile Nodes and Inter-agent CommunicationEach mobile agent will be given a temporary workspace to perform its functions andalso to allow multiple mobile agents to co-exist in a host. A hosting node can receivenew agents or transport them to other nodes without causing any interference. Theagent system hides details about the node and provides access to local resources withthe necessary security mechanisms.
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Lecture Notes in Computer Science 2
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Samuel Pierre Michel BarbeauEvangel
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PrefaceAd Hoc Networks are wireless
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Program CommitteeG. Alonso, ETHZ, S
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XTable of ContentsResisting Malicio
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2 H. Dubois-Ferrière, M. Grossglau
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10 H. Dubois-Ferrière, M. Grossgla
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SAFAR: An Adaptive Bandwidth-Effici
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14 J. Doshi and P. Kilambiour proto
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16 J. Doshi and P. Kilambipacket th
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18 J. Doshi and P. Kilambibandwidth
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20 J. Doshi and P. Kilambi5 Simulat
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22 J. Doshi and P. Kilambiquery its
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24 J. Doshi and P. Kilambi4. David
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26 P. Narayan and V.R. SyrotiukThe
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28 P. Narayan and V.R. Syrotiuk2.2
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30 P. Narayan and V.R. Syrotiukrand
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32 P. Narayan and V.R. Syrotiukenti
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34 P. Narayan and V.R. SyrotiukDSRA
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36 P. Narayan and V.R. Syrotiuk7. A
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38 L. Qin and T. Kunzthese two prot
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40 L. Qin and T. Kunzsidered broken
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42 L. Qin and T. KunzP = Prdlog( )
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46 L. Qin and T. KunzFig. 5. Averag
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48 L. Qin and T. Kunz6. J. Broch et
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50 M. Diha and S. Pierrethe propose
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52 M. Diha and S. Pierre3. All proc
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54 M. Diha and S. Pierre3.3 Perform
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56 M. Diha and S. PierreCmip/Cprop0
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58 M. Diha and S. PierreThe tunneli
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Proactive QoS Routing in Ad Hoc Net
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62 Y. Ge, T. Kunz, and L. LamontFig
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64 Y. Ge, T. Kunz, and L. Lamontits
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Delivering Messagesin Disconnected
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Extending Seamless IP Multicast Edg
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94 P.M. Ruiz et al.10.90.81-hop-750
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A Uniform Continuum Model for Scali
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102 E.W. Grundke and A.N. Zincir-He
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Probabilistic Protocols for Node Di
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106 G. Alonso et al.A node discover
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108 G. Alonso et al.frequency alloc
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110 G. Alonso et al.- D is a diagon
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112 G. Alonso et al.and therefore,
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114 G. Alonso et al.complicated. Fo
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Towards Adaptive WLAN Frequency Man
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Analyzing Split Channel Medium Acce
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A New Framework for Building Secure
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176 G. Calinescuof the UDG 2-hops a
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178 G. CalinescuSection 3 describe
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182 G. CalinescuRyvxFig. 3. The unn
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184 G. Calinescu< nodeID, pieceID,
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188 S.O. Krumke et al.desirable in
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192 S.O. Krumke et al.1. From the g
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194 S.O. Krumke et al.The following
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196 S.O. Krumke et al.1. Let α =6l
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208 S. PatilTable 1. Probability of
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Page 305 and 306: 3BerlinHeidelbergNew YorkHong KongL
Page 307 and 308: Series EditorsGerhard Goos, Karlsru
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Page 312 and 313: Table of ContentsSpace-Time Routing
Page 314: Author IndexAlonso, G. 104Bachir, A
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