Heuristic method for working out a plurality of shortest simple routes in network under multiple constraints

Abstract

The invention discloses a heuristic method for working out a plurality of shortest simple routes in network under multiple constraints. The method uses improved route control rules and predication of lower price limit after extending the routes to destination nodes, and abandon the routes which contain rings, break the constraints and exceed the cost of the k obtained shortest simple route. In the reserved routes, front k shortest simple routes meeting constrain conditions are searched in the breadth-first way and adjustable precision. The method has strong adaptability on network types, scales and change of constrain degrees, and the complexity of the method is approaching to the traditional breadth-first searching method. The heuristic method for working out a plurality of shortest simple routes in network under multiple constraints can shown excellent and stable performances on the aspects like route quantity, quality and capacity for discovering routes by setting the probing depth of middle ring of route and retracting coefficients of controlled decision.

Description

technical field [0001] The heuristic method for obtaining multiple shortest simple paths in a network under multiple constraints belongs to the field of Internet routing technology, and in particular relates to the field of quality of service routing for quickly finding multiple simple paths under the constraints of multiple quality of service parameters. Background technique [0002] Providing routes that can guarantee Quality of Service (QoS) in the Internet has become a hot issue in today's network technology. QoS constraints are usually divided into two types of link constraints (such as bandwidth) and path constraints (such as delay): wherein the link constraint problem can be solved by pre-cutting the links that do not meet the constraints in the network; and the present invention focuses on The path constraint problem is relatively complicated, especially when the number of constraints m≥2, the problem is further transformed into finding the optimal path under multipl...

AI Technical Summary

Problems solved by technology

Obviously, the disadvantage of this approach is that many suboptimal paths that happen to be controlled in the cost comparison are deleted by mistake, so it is difficult to guarantee the quantity and quality of the found paths at the same time

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