Reliability and Fault Tolerance based Topological Optimization of Computer Networks - Part II: Iterative Techniques

Abstract-Topological optimization of computer networks is concerned with the selection of a subset of the available links such that the reliability and fault-tolerance aspects are maxhized while meeting a cost constraint. In this case. the problem is stated as opthiring the reliability and fault-tolerance of a network subject to a maximum cost constraint. Existing iterative-based techniques consider the simple single-objective version of the problem by considering reliability as the only objective We consider fault-tolerance to be an important network design "ped We consider the use of three iterative techniques, namely Tabu Search, Simulated Anenling, and Genetic Algorithm, in solving the multi-objective topological optimization network design problem. Experimental results for a set of 10 randomly generated networks using the three iterative techniques are presented and compared. It is shown that improving the fault tolerance of a network can be achieved while optimizing its reliability however at the expense of a reasonable in- m the overall cost of the network. Keywords: Topological Optimization, Fault Tolerance, Reliability, Genetic Algorithm, Tabu Search, Simulated Annealing, Spanning tree

Reliability and fault tolerance based topological optimization of computer networks - part II: iterative techniques

Topological optimization of computer networks is concerned with the selection of a subset of the available links such that the reliability and fault-tolerance aspects are maximized while meeting a cost constraint. In this case, the problem is stated as optimizing the reliability and fault-tolerance of a network subject to a maximum cost constraint. Existing iterative-based techniques consider the simple single-objective version of the problem by considering reliability as the only objective. We consider fault-tolerance to be an important network design aspect. We consider the use of three iterative techniques, namely tabu search, simulated annealing, and genetic algorithms, in solving the multiobjective topological optimization network design problem. Experimental results for a set of 10 randomly generated networks using the three iterative techniques are presented and compared. It is shown that improving the fault tolerance of a network can be achieved while optimizing its reliability however at the expense of a reasonable increase in the overall cost of the network

The Use of Enumerative Techniques in Topological Optimization of Computer Networks Subject to Fault Tolerance and Reliability

Topological optimization of computer networks is concerned with the design of a network by selecting a subset of the available set of links such that the fault tolerance and reliability aspects are maximized while a cost constraint is met. A number of enumeration-based techniques were proposed to solve this problem. They are based on enumerating all the possible paths (for Terminal reliability) and all the spanning trees (for ��Network reliability). Existing enumeration-based techniques for solving this network optimization problem ignore the fault-tolerance aspect in their solution. Fault tolerance is an important network design aspect. A fault tolerant network is able to function even in the presence of some faults in the network. In this paper, we propose one algorithm for optimizing the terminal reliability and another for optimizing the network reliability while improving the fault tolerance aspects of the designed networks. Experimental results obtained from a set of randomly generated networks using the proposed algorithms are presented and compared to those obtained using the existing techniques [1], [2]. It is shown that improving the fault tolerance of a network can be achieved while optimizing its reliability however at the expense of a reasonable increase in the overall cost of the network while remaining within a maximum pre-specified cost constraint

The Use of Enumerative Techniques in Topological Optimization of Computer Networks Subject to Fault Tolerance and Reliability

Topological optimization of computer networks is concerned with the design of a network by selecting a subset of the available set of links such that the fault tolerance and reliability aspects are maximized while a cost constraint is met. A number of enumeration-based techniques were proposed to solve this problem. They are based on enumerating all the possible paths (for Terminal reliability) and all the spanning trees (for ��Network reliability). Existing enumeration-based techniques for solving this network optimization problem ignore the fault-tolerance aspect in their solution. Fault tolerance is an important network design aspect. A fault tolerant network is able to function even in the presence of some faults in the network. In this paper, we propose one algorithm for optimizing the terminal reliability and another for optimizing the network reliability while improving the fault tolerance aspects of the designed networks. Experimental results obtained from a set of randomly generated networks using the proposed algorithms are presented and compared to those obtained using the existing techniques [1], [2]. It is shown that improving the fault tolerance of a network can be achieved while optimizing its reliability however at the expense of a reasonable increase in the overall cost of the network while remaining within a maximum pre-specified cost constraint

The Use of Enumerative Techniques in Topological Optimization of Computer Networks Subject to Fault Tolerance and Reliability

Topological optimization of computer networks is concerned with the design of a network by selecting a subset of the available set of links such that the fault tolerance and reliability aspects are maximized while a cost constraint is met. A number of enumeration-based techniques were proposed to solve this problem. They are based on enumerating all the possible paths (for Terminal reliability) and all the spanning trees (for ��Network reliability). Existing enumeration-based techniques for solving this network optimization problem ignore the fault-tolerance aspect in their solution. Fault tolerance is an important network design aspect. A fault tolerant network is able to function even in the presence of some faults in the network. In this paper, we propose one algorithm for optimizing the terminal reliability and another for optimizing the network reliability while improving the fault tolerance aspects of the designed networks. Experimental results obtained from a set of randomly generated networks using the proposed algorithms are presented and compared to those obtained using the existing techniques [1], [2]. It is shown that improving the fault tolerance of a network can be achieved while optimizing its reliability however at the expense of a reasonable increase in the overall cost of the network while remaining within a maximum pre-specified cost constraint

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

Optimal design of water distribution systems based on entropy and topology

A new multi-objective evolutionary optimization approach for joint topology and pipe size design of water distribution systems is presented. The algorithm proposed considers simultaneously the adequacy of flow and pressure at the demand nodes; the initial construction cost; the network topology; and a measure of hydraulic capacity reliability. The optimization procedure is based on a general measure of hydraulic performance that combines statistical entropy, network connectivity and hydraulic feasibility. The topological properties of the solutions are accounted for and arbitrary assumptions regarding the quality of infeasible solutions are not applied. In other words, both feasible and infeasible solutions participate in the evolutionary processes; solutions survive and reproduce or perish strictly according to their Pareto-optimality. Removing artificial barriers in this way frees the algorithm to evolve optimal solutions quickly. Furthermore, any redundant binary codes that result from crossover or mutation are eliminated gradually in a seamless and generic way that avoids the arbitrary loss of potentially useful genetic material and preserves the quality of the information that is transmitted from one generation to the next. The approach proposed is entirely generic: we have not introduced any additional parameters that require calibration on a case-by-case basis. Detailed and extensive results for two test problems are included that suggest the approach is highly effective. In general, the frontier-optimal solutions achieved include topologies that are fully branched, partially- and fully-looped and, for networks with multiple sources, completely separate sub-networks

Reliability and fault tolerance based topological optimization of computer networks - part I: enumerative techniques

Topological optimization of computer networks is concerned with the design of a network by selecting a subset of the available set of links such that the fault tolerance and reliability aspects are maximized while a cost constraint is met. A number of enumeration-based techniques were proposed to solve this problem. They are based on enumerating all possible paths (for terminal reliability) and all the spanning trees (for network reliability). Existing enumeration-based techniques for solving this network optimization problem ignore the fault-tolerance aspect in their solution. We consider fault tolerance to be an important network design aspect In this paper, we propose one algorithm for optimizing the terminal reliability and another for optimizing the network reliability while improving the fault tolerance aspects of the designed networks. Experimental results obtained from a set of randomly generated networks using the proposed algorithms are presented and compared to those obtained using existing techniques. It is shown that improving the fault tolerance of a network can be achieved while optimizing its reliability however at the expense of a reasonable increase in the overall cost of the network

Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependency

Increased coupling between critical infrastructure networks, such as power and communication systems, will have important implications for the reliability and security of these systems. To understand the effects of power-communication coupling, several have studied interdependent network models and reported that increased coupling can increase system vulnerability. However, these results come from models that have substantially different mechanisms of cascading, relative to those found in actual power and communication networks. This paper reports on two sets of experiments that compare the network vulnerability implications resulting from simple topological models and models that more accurately capture the dynamics of cascading in power systems. First, we compare a simple model of topological contagion to a model of cascading in power systems and find that the power grid shows a much higher level of vulnerability, relative to the contagion model. Second, we compare a model of topological cascades in coupled networks to three different physics-based models of power grids coupled to communication networks. Again, the more accurate models suggest very different conclusions. In all but the most extreme case, the physics-based power grid models indicate that increased power-communication coupling decreases vulnerability. This is opposite from what one would conclude from the coupled topological model, in which zero coupling is optimal. Finally, an extreme case in which communication failures immediately cause grid failures, suggests that if systems are poorly designed, increased coupling can be harmful. Together these results suggest design strategies for reducing the risk of cascades in interdependent infrastructure systems