A knowledge-based system with learning for computer communication network design

Computer communication network design is well-known as complex and hard. For that reason, the most effective methods used to solve it are heuristic. Weaknesses of these techniques are listed and a new approach based on artificial intelligence for solving this problem is presented. This approach is particularly recommended for large packet switched communication networks, in the sense that it permits a high degree of reliability and offers a very flexible environment dealing with many relevant design parameters such as link cost, link capacity, and message delay

Comparing the reliability of networks by spectral analysis

We provide a method for the ranking of the reliability of two networks with the same connectance. Our method is based on the Cheeger constant linking the topological property of a network with its spectrum. We first analyze a set of twisted rings with the same connectance and degree distribution, and obtain the ranking of their reliability using their eigenvalue gaps. The results are generalized to general networks using the method of rewiring. The success of our ranking method is verified numerically for the IEEE57, the Erd\H{o}s-R\'enyi, and the Small-World networks.Comment: 7 pages, 3 figure

A Neural-Net Gaussian Machine for Optimal Local Access Network Design

Local access network design often involves the solution of a capacitated concentrator location problem (CCLP). In contrast to the conventional single-capacitated CCLP, this paper presents a generalized CCLP (GCCLP) in which n given end-user nodes are to be connected to concentrators located at m available sites, and each concentrator is subject to two capacity constraints - its effective data processing rate (Kbits/sec) and the available number of circuit ports. The objective of GCCLP is to ensure that each end-user node is connected to exactly one concentrator such that neither of its capacity constraints is violated while the total communication costs are minimized. Since GCCLP is combinatorially explosive, large problems may not be practically solved by an exact method. In this paper, rather, an artificial intelligence solution engine, a Gaussian Machine, is developed for solving GCCLP. Our preliminary computational results indicate that this AI-based solution algorithm is a feasible alternative for solving GCCLP

A Genetic Algorithm based Approach for Topological Optimization of Interconnection Networks

AbstractThe paper addresses the two terminal reliability while designing the interconnection networks. Thus a topological optimization problem is defined as the existence of at least a reliable path between a pair of nodes satisfying the predefined cost of the network. A new method based on Genetic Algorithm is proposed to solve the above said problem. In the proposed method the chromosome as well as the genes are efficiently encoded so that the cross over provides the optimal solution with better convergence rate. The reliability of some benchmark interconnection networks are evaluated by the proposed method. The population size and the computational time of the said networks as reported in this paper ensures that the proposed method converges to it's optimal solution in very few cpu secondss, while maximizing the value of the reliability of the said network to a greater extent

TOPOLOGICAL PLANNING OF COMMUNICATION NETWORKS

In this paper, we concentrate on topological planning process of large-scale communication networks such as those used by telecom operators. Such networks are usually spread over large geographical area, and finding an optimal topology is very important part of the planning process. Network equipment used in such network is very expensive, and two connection points can be hundreds of kilometers apart. These networks, in most cases, form a backbone network of telecom operator, meaning that majority of traffic is carried through high-speed communication links of such network. Any cable cuts or equipment malfunctions could result in huge data losses. Therefore, such networks require high degree of availability and fault resistance, which must be considered during the planning process. Network topology providing fault resistance should offer at least two separate communication paths between any pair of network nodes. Most important issue in network topology planning is finding topology with lowest possible overall network price, while keeping all requirements (such as fault tolerance, availability, maximal number of hops, maximal blocking probability etc.) satisfied. Network design process can be divided into three stages. First step is making decisions about which network elements (nodes, existing edges) should be included in a backbone network (for instance, one of sub-problems appearing in this phase is facility location problem). Second step includes selection of network topology, so that all elements selected in first step will be interconnected satisfying given requirements. Last phase is used to determine node and link capacities needed for successful traffic transport as well as routings of traffic demands, including protection. Depending on technologies used in network, different routing and protection mechanisms, as well as specific topology models, can be used (e.g. SDH/WDM SHR, mesh, dual-homing etc.)

Inter-domain router placement and traffic engineering

The Internet is organized as an interconnection of separate administrative domains called Autonomous Systems (AS). The Border Gateway Protocol (BGP) is the de facto standard for controlling the routing of traffic across different ASs. It supports scalable distribution of reachability and routing policy information among different ASs. In this paper, we study a network design problem which determines (1) the optimal placement of border router(s) within a domain and (2) the corresponding inter-and intra-domain traffic patterns within an AS. Practical constraints imposed by BGP and other standard shortest-path-based intra-domain routing protocols are considered. The problem is formulated as a variant of the uncapacitated network design problem (UNDP). While it is feasible to use a brute-force, integer-programming-based approach for tackling small instances of this problem, we have resorted to a dual-ascent approximation approach for mid/large-scale instances. The quality of the approximation approach is evaluated in terms of its computational efficiency and network cost sub-optimality. Sensitivity analysis w.r.t. various network/traffic parameters are also conducted. We then describe how one can apply our optimization results to better configure BGP as well as other intra-domain routing protocols. This serves as a first-step towards the auto-configuration of Internet routing protocols, BGP in particular, which is "well-known" for its tedious and error-prone configuration needs.published_or_final_versio

Hierarchical Network Design Using Simulated Annealing

The hierarchical network problem is the problem of nding the least cost net-work, with nodes divided into groups, edges connecting nodes in each groups and groups ordered in a hierarchy. The idea of hierarchical networks comes from telecommunication networks where hierarchies exist. Hierarchical net-works are described and a mathematical model is proposed for a two level version of the hierarchical network problem. The problem is to determine which edges should connect nodes, and how demand is routed in the net-work. The problem is solved heuristically using simulated annealing which as a sub-algorithm uses a construction algorithm to determine edges and route the demand. Performance for dierent versions of the algorithm are reported in terms of runtime and quality of the solutions. The algorithm is able to nd solutions of reasonable quality in approximately 1 hour for networks with 100 nodes

TOPOLOGICAL PLANNING OF COMMUNICATION NETWORKS

In this paper, we concentrate on topological planning process of large-scale communication networks such as those used by telecom operators. Such networks are usually spread over large geographical area, and finding an optimal topology is very important part of the planning process. Network equipment used in such network is very expensive, and two connection points can be hundreds of kilometers apart. These networks, in most cases, form a backbone network of telecom operator, meaning that majority of traffic is carried through high-speed communication links of such network. Any cable cuts or equipment malfunctions could result in huge data losses. Therefore, such networks require high degree of availability and fault resistance, which must be considered during the planning process. Network topology providing fault resistance should offer at least two separate communication paths between any pair of network nodes. Most important issue in network topology planning is finding topology with lowest possible overall network price, while keeping all requirements (such as fault tolerance, availability, maximal number of hops, maximal blocking probability etc.) satisfied. Network design process can be divided into three stages. First step is making decisions about which network elements (nodes, existing edges) should be included in a backbone network (for instance, one of sub-problems appearing in this phase is facility location problem). Second step includes selection of network topology, so that all elements selected in first step will be interconnected satisfying given requirements. Last phase is used to determine node and link capacities needed for successful traffic transport as well as routings of traffic demands, including protection. Depending on technologies used in network, different routing and protection mechanisms, as well as specific topology models, can be used (e.g. SDH/WDM SHR, mesh, dual-homing etc.)