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Architecture and Algorithms for Real-Time Mobility Management 51Location management operations include agent discovery, movement detection,forming care-of-address, and location update. Handover operations include routingand tunneling.Figure 1 illustrates Mobile IP network architecture.MNHACNIP NetworkMNFAFig. 1. Mobile IP network architecture3 Architecture and Algorithms ProposedThis section presents a new Mobile IP network architecture and new algorithms supportingreal-time features as well as performance analysis.3.1 Proposed ArchitectureFigure 2 shows the proposed Mobile IP network architecture.MNCN1HACNnFAIP NetworkMNFA2MNnFAFig. 2. Proposed architecture of Mobile IP networkThe architecture introduces the following main features:1. Real-time algorithms support.2. Connection of MNs and CNs to an FA or HA with different arrival rates in thenetwork.
52 M. Diha and S. Pierre3. All procedures associated with an MN (registration, discovery, tunneling and routing)represent different tasks with a specific priority.4. Multiprocessor agent (HA or FA). In this paper the emphasis is put on the HA.Also the Home Agent is redundant to allow failure recovery.5. A main processor dispatching the different tasks arriving on an agent.6. A set of faster processors is defined to process high-priority tasks.7. Architecture allowing different speeds for the processors.3.2 Proposed AlgorithmsBased on the architecture described above, a set of new algorithms has been definedfor mobility management. These algorithms are derived from Mobile IPv4 algorithms[6]. They introduce the notion of priority management in a real-time context. The newdiscovery algorithm adds the ranging concept in addition to the lifetime used in MobileIPv4. Also it allows the MN to initiate Foreign Agents search at startup in steadof waiting advertisements. In addition, this algorithm allows the MN to keep a list ofthe most recent Foreign Agents that it tries to contact first before initiating any broadcastsearch.3.2.1 Tasks Scheduling and Assignment Algorithm-Given i counter of tasks and j counter of processors.-Given n tasks TSK 1, …,TSK i, …, TSK nwith the priorities p 1, … p i, … p n.-Given S a set of faster processors and p sthreshold of a critical task.-Given u(i) the utilization rate of the task TSK iand U(j) a vector of u(i) on P j.BEGIN-i= 1, U(j)= 0, S =1.-Sort the n tasks based on u(i) on P 0.WHILE i ≤ n DOj = min{k|U(k) + u(i) = 1}IF ( (p i> p s) && ( ∃ P R∈S | ∑ U(P R) < 1)) ) THEN TSK i→ P RELSE TSK i→ Pji ← i + 1END WHILEEND BEGINFig. 3. Task scheduling and assignment algorithmThe scheduling part of the algorithm is based on the EDF algorithm [2] while theassignment part is a totally new concept since it based on a multiprocessor architecture.The tasks are sorted based on the deadline and assigned to the processors. If atask is critical (short deadline), it is assigned to a faster processor. If not it is assignedto a normal processor. A task is assigned to a processor only if its current utilization
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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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108 G. Alonso et al.frequency alloc
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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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118 F. Gamba, J.-F. Wagen, and D. R
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142 J. Zhen and S. SrinivasTraffic
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144 J. Zhen and S. SrinivasFig. 2.
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A New Framework for Building Secure
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166 H.-P. Bischof, A. Kaminsky, and
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176 G. Calinescuof the UDG 2-hops a
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184 G. Calinescu< nodeID, pieceID,
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186 G. Calinescu7. Heinz Breu and D
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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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198 S.O. Krumke et al.for any given
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200 S. PatilIDEA uses the concept o
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206 S. PatilAvg. Aggregate Energy C
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208 S. PatilTable 1. Probability of
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3BerlinHeidelbergNew YorkHong KongL
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Series EditorsGerhard Goos, Karlsru
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Organizing CommitteeConference Co-c
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Table of ContentsSpace-Time Routing
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Author IndexAlonso, G. 104Bachir, A
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