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Distributed Virtual Circuit Switching protocol with auction pricing

This study focuses on establishing connections in networks using auction pricing to allocate resources and guarantee Quality of Service. Two auction models are proposed to maximize accepted requests and reduce congestion impact, considering deterministic and non-deterministic routing scenarios. The research explores stable link maximization and NP-Completeness in stable link problem-solving, with a heuristic approach showing promising results.

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Distributed Virtual Circuit Switching protocol with auction pricing

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  1. Distributed Virtual Circuit Switching protocol with auction pricing Loubna ECHABBI Dominique BARTH Laboratoire PRISM

  2. Framework • Virtuel circuit switching networks. • Goal: Ressource allocation to satisfy some QoS. • How : connection establishment. 2 3 5 4 3 D O

  3. Conflict : Congestion in a router Definition: the demand is greater than the available resource. Question : which criterions to choose accepted requests. • Maximize the number of accepted requests. • Minimize the remaining bandwidth. • for more fairness: Use auctions to charge accepted requests some congestion cost. These prices can be used to compute routing tables or in the service pricing.

  4. Auctions : local approach At each router we have the following information: • A set of requests (budget, demand, destination..) • A set of outgoing links ( capacities ) • A set of links obtained from the routing table which link each request to possible outgoing links. Two types of routing are studied : • Deterministic routing : 1 destination= 1 outgoing link. • Non deterministic routing : 1 destination= n outgoing links

  5. Auctions: first model • Requests submit their offer . • The router chooses a combination of traffic that maximizes its profit. • The non accepted requests increase their offer (by one unit). The stopping criteria : non accepted requests cannot increase their offer anymore. • At each step the problem is NP-complete (even in the deterministic case: contains the knapsack problem). • Auctions final result is difficult to be characterized .

  6. Auctions : second model • The main idea: each link fixes its cost. 43 43 3 1 3 1 1 4 2 4 2 3 2 3 11 *1 43 3 1 3 4 * 3 *1

  7. Second model : Deterministic case • Auctions on different links are independent • At each step the problem is polynomial. • The auction’s final result can be polynomialy obtained by sorting the requests in a decreasing order and accepting them in this order while keeping the capacity constraint held. • Note: When congestion occurs, the accepted requests are charged the first non accepted bid, else the cost is null.

  8. Second model: non deterministic case. • Auction on different links are not independent. 2 3 3 3 2 4 2 2 • Definition: The set of stable links, at a given step, is the set of links such that all requests that can be routed at least on one element of this set, is indeed accepted on a link in that set.

  9. Second model: non deterministic case 4 3 4 3 1 3 2 3 3 1 3 1 1 2 2 2 2 2 2 2 1 3 2 3 1 2 * 2 1 3 1 3 4 3 4 3 1 2 3 1 3 1 1 2 1 3 2 2 2 2 2 3 1 2 * 2

  10. Second model: non deterministic case • Process: At each step, we maximize the number of stable links. At the end of each step, non stable links increase their offer and eliminate requests that cannot bargain . • Property: With any configuration that maximizes the set of stable links , stable links are the same. • Conjecture: the stable link maximization problem is NP-Complete.

  11. A heuristic idea 6 2 3 5 5 2 4 4 * 3 3 2 1 3 2 0 1 1 * 1

  12. Previous work and perspectives • Previous work: • Complexity study. • Implementation of the exact problem in Cplex. • Implementation of a simulator with the virtual circuit protocol layered on a grid network. • Current work: • A comparison between the exact and the heuristic methods using the simulator. • Test of different auction strategies.

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