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Selfish DTN capacity Experimental estimation

This seminar paper explores the capacity estimation challenges in Delay-Tolerant Networks (DTNs), emphasizing the effects of storage constraints, transmission constraints, and node selfishness on performance. It investigates the maximum achievable traffic demand before network saturation occurs, utilizing node contact traces and analyzing routing with Wardrop equilibrium. The findings indicate that delay-tolerance can significantly enhance network capacity, while node selfishness complicates network management and routing design. Key factors include packet delivery ratios and transmission costs, re-emphasizing the need for multidimensional routing protocols.

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Selfish DTN capacity Experimental estimation

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  1. Selfish DTN capacityExperimental estimation Dagstuhl Seminar DTN II February 2009 Joint work ofPU Tournoux, V. Conan, J. Crowcroft, J. Leguay, F. Benbadis, M De Amorim

  2. DTN performance • Measured in terms of packet delivery ratio, packet delay for non-congested networks • Performance is limited by: • Storage constraints • Transmission constraints • Node selfishness

  3. The problem For a given traffic pattern, what is the maximum total demand that can be achieved before the network becomes saturated, either in link capacity or in storage capacity?

  4. Capacity estimation • Use traces of node contacts as input • Consider fixed demands • One demand = transfer x Kbits from node s to node d injected at time t • Traffic is routedat Wardrop equilibrium • Increase x for all demands • Stop when storage/transmission overload increasesfaster than load

  5. Wardrop equilibrium • The journey times (or costs) in all routes actually used are equal and less than those which would be experienced by a single vehicle (or message) on any unused route. • For additive and separable positive and continuous cost functions the Wardrop equilibrium is a convex minimization problem. The equilibrium is unique, and may be obtained by running the Frank-Wolfe algorithm

  6. Time Discretized Graph

  7. Transmission capacities of connections Example

  8. Weight on delay = 1Weight on transmission cost = 1 Fastest route • Delay is costly: the fastest route is chosen

  9. Weight on delay = 1Weight on transmission cost = 30 Costly transmissions • Increasing transmission cost forces usage of slower routes

  10. Weight on delay << 1Weight on transmission cost = 30 More delay • Allowing for more delay forces usage of even more slow routes

  11. Infocom data set Weight on delay • Capacity increases with delay tolerance 0.10.0001 1 0.5

  12. Conclusions • Delay-tolerance helps increase capacity. • Routing protocols should be multi-dimensional. • Selfishness makes network engineering challenging.

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