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A Message Ferrying Approach for Data Delivery in Sparse Mobile Ad Hoc Networks Wenrui Zhao, Mostafa Ammar and Ellen Zegura Presentation by: Carlos Castillo
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Message Ferrying Routing in ad hoc networks Sparse networks General approach: Store-Carry-Forward –Reactive Approaches: Epidemic Routing –Proactive Approaches: MF
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Approaches to MF The paper studies two approaches to MF –Node-initiated MF –Ferry-initiated MF
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Message Ferrying Applications Crisis-driven: battlefield and disaster applications Geography-driven: for example ZebraNet Cost-driven: for example DakNet Service-driven: to provide privacy or anonymity
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Node-Initiated MF The ferry moves according to a specific route Nodes make proactive movement to meet up with ferry There are two types of drops: buffer overflow or message time out
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Node Trajectory Control Balance between meeting with ferry and performing tasks. The paper describes a policy which allows a node to move to the ferry only when: where D i (t d ) = D i n (t d )+D i f (t d )
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Node Trajectory Control Message drop rate:
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State Transitions Mode transition diagram for NIMF nodes:
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Message Drop Rate
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Ferry-Initiated MF In this scheme the ferry takes proactive movement to meet up with nodes. Long range radios in nodes are used to transmit control messages. Message forwarding, device discovery and message drop computation are the same in both schemes.
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Ferry-Initiated MF Operations A node can be in two states DISSASOCIATED and ASSOCIATED. The ferry can be in two states: IDLE and WORKING.
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Node Notification Control The goal of notification control is to minimize message drops while considering energy constraints. The paper describes a criteria when to actually send notification control messages. Nodes send notification messages to request communication service from the ferry. Notification messages can be: –Service_Request –Location_Update
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Ferry Trajectory Control The expected message drops for a route P is: The ferry route problem can be stated as finding the route that minimizes D p When D i n (t)+D i f (t)=1 for all i and t, this problem becomes a Minimum Latency Problem (MLP).
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Heuristics for Ferry Control To overcome the intractability of the initial formulation, the authors study two heuristics: –Nearest neighbor (NN) –Traffic aware (TA)
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Performance Evaluation The performance evaluation was done through simulations in the ns simulator. Metrics: message delivery rate, message delay, delivered messages per unit of energy.
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Impact of Node Buffer Size
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Impact of Node Mobility Random waypoint, limited random waypoint and area based:
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Impact of Range on FIMF performance
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Impact of the Avg. Notification Rate in FIMF Performance
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Closing Remarks The paper studies the problem of data delivery in sparse ad hoc networks The work is limited to one ferry Contention and resources
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