
arXiv: 0704.1783
handle: 11568/144045 , 11391/121123
We present a formal model to represent and solve the unicast/multicast routing problem in networks withquality-of-service(QoS) requirements. To attain this, first we translate the network adapting it to a weighted graph (unicast) orand-orgraph (multicast), where the weight on a connector corresponds to the multidimensional cost of sending a packet on the related network link: each component of the weights vector represents a different QoS metric value (e.g., bandwidth). The second step consists in writing this graph as a program insoft-constraint logic programming(SCLP): the engine of this framework is then able to find the best paths/trees by optimizing their costs and solving the constraints imposed on them (e.g.delay≤ 40 ms), thus finding a solution to QoS routing problems.C-semiringstructures are a convenient tool to model QoS metrics. At last, we provide an implementation of the framework over scale-free networks and we suggest how the performance can be improved. The article highlights the expressivity of SCLP.
Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, Computer Science - Logic in Computer Science, D.3.2; D.3.3; C.2.3; F.4.1, Network design and communication in computer systems, quality of service (QoS), soft constraints, Computer Science - Artificial Intelligence, Constraints; soft constraints, Preferences, Quality of Service (QoS), Routing, Constraint logic programming (CLP), Soft constraint, D.3.2, D.3.3, Logic programming, Logic in Computer Science (cs.LO), Computer Science - Networking and Internet Architecture, C.2.3, Artificial Intelligence (cs.AI), routing, F.4.1, constraints, constraint logic programming (CLP), preferences
Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, Computer Science - Logic in Computer Science, D.3.2; D.3.3; C.2.3; F.4.1, Network design and communication in computer systems, quality of service (QoS), soft constraints, Computer Science - Artificial Intelligence, Constraints; soft constraints, Preferences, Quality of Service (QoS), Routing, Constraint logic programming (CLP), Soft constraint, D.3.2, D.3.3, Logic programming, Logic in Computer Science (cs.LO), Computer Science - Networking and Internet Architecture, C.2.3, Artificial Intelligence (cs.AI), routing, F.4.1, constraints, constraint logic programming (CLP), preferences
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