Stochastic Computer Network Research Articles

Data transmission reliability evaluation of a stochastic computer network through minimal paths with a retransmission mechanism

Multipath Transmission Control Protocol is a new networking protocol which can allow data transmission and retransmission across multiple minimal paths. It can reduce data transmission time and ensure data integrity. In computer networks, the capacity of each arc should be considered as stochastic because there are different situations such as failures, partial failures, and maintenance. This article focuses on a stochastic retransmission flow network to evaluate data transmission reliability that the data can be transmitted successfully through multiple minimal paths within transmission time threshold. We first propose an algorithm to generate all minimal capacity vectors satisfying both constraints and requirements and to obtain data transmission reliability. A numerical example and a large-scale case study of the Pan-European Research and Education Network are presented to illustrate the algorithm.

Reliability Evaluation of a Multi-state Network with Multiple Sinks under Individual Accuracy Rate Constraint

From the viewpoint of service level agreements (SLAs), Internet service providers and customers are gradually focusing on transmission accuracy. The Internet service provider should provide the specific bandwidth and individual accuracy rate requirement by their SLAs to each customer. This paper mainly evaluates the system reliability that a stochastic computer network can fulfill all requirements at all sinks. An efficient algorithm is proposed to generate the lower boundary points, minimal capacity vectors satisfying the demand and accuracy rate requirement for all sinks. The system reliability can be computed in terms of such points by applying recursive sum of disjoint products.

Considering retransmission mechanism and latency for network reliability evaluation in a stochastic computer network

Computer systems can be constructed as a network topology with arcs (transmission media) and nodes (data centers). Because ofconditions such as failure, partial failure, and maintenance, arc’s capacity should be considered stochastic. In order to sustain data quality, a data retransmission mechanism is necessary in practical computer networks. Such a mechanism can avoid data error during transmission procedure. Packet unreliability and latency are critical factors to assess the quality of service over the Internet. Therefore, this study focuses on a multistate retransmission flow network to evaluate network reliability that the data can be transmitted successfully with a retransmission mechanism under permitted latency. An algorithm is proposed to generate all lower boundary points satisfying requirements. Then, network reliability can be computed in terms of such boundary points. A numerical case of the China Education and Research Network is demonstrated to illustrate the utility of the proposed algorithm.

Stochastic computer network under accuracy rate constraint from QoS viewpoint

In the past, the main concerns for competitive enterprise environment of computer networks were data transmission delays and costs. However, from the viewpoint of quality of service (QoS), internet service providers and enterprise customers are increasingly focusing on data accuracy during transmission. This study extends a stochastic computer network (SCN) to evaluate the system reliability, where the system reliability is the probability that demand can be transmitted through the SCN under the total accuracy rate. In such an SCN, each arc has several capacities, and an accuracy rate. We can regard the system reliability as a measurable index for assessing the SCN performance. A lower boundary point for (d,K) is a minimal capacity vector, which allows the system to transmit demand d under the total accuracy rate K. Using the minimal paths, we propose an efficient algorithm to find all lower boundary points for (d,K). The system reliability can then be computed in terms of all lower boundary points for (d,K) by the recursive sum of disjoint products (RSDP) algorithm. Several numerical examples are demonstrated to illustrate the utility, efficiency, and effectiveness of the proposed algorithm.

Stochastic computer network with multiple terminals under total accuracy rate

From the viewpoint of service level agreements, data transmission accuracy is one of the critical performances for assessing Internet by service providers and enterprise customers. The stochastic computer network (SCN), in which each edge has several capacities and the accuracy rate, has multiple terminals. This paper is aimed mainly to evaluate the system reliability for an SCN, where system reliability is the probability that the demand can be fulfilled under the total accuracy rate. A minimal capacity vector allows the system to transmit demand to each terminal under the total accuracy rate. This study proposes an efficient algorithm to find all minimal capacity vectors by minimal paths. The system reliability can then be computed in terms of all minimal capacity vectors by the recursive sum of disjoint products (RSDP) algorithm.

Multi-objective optimization for stochastic computer networks using NSGA-II and TOPSIS

Network reliability is a performance indicator of computer/communication networks to measure the quality level. However, it is costly to improve or maximize network reliability. This study attempts to maximize network reliability with minimal cost by finding the optimal transmission line assignment. These two conflicting objectives frustrate decision makers. In this study, a set of transmission lines is ready to be assigned to the computer network, and the computer network associated with any transmission line assignment is regarded as a stochastic computer network (SCN) because of the multistate transmission lines. Therefore, network reliability means the probability to transmit a specified amount of data successfully through the SCN. To solve this multiple objectives programming problem, this study proposes an approach integrating Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). NSGA-II searches for the Pareto set where network reliability is evaluated in terms of minimal paths and Recursive Sum of Disjoint Products (RSDP). Subsequently, TOPSIS determines the best compromise solution. Several real computer networks serve to demonstrate the proposed approach.

Determining the optimal double-component assignment for a stochastic computer network

This study determines the optimal double-component assignment based on the system reliability criterion for a computer system, in which the computer system is represented as a network with a set of links and a set of vertices. The double-component assignment is to assign a set of transmission lines (resp. facilities) to the links (resp. vertices) of the network, in which each transmission line (resp. facility) has multiple states due to maintenance or failure. Thus, the computer system according to any double-component assignment is called a stochastic computer network. The system reliability is the probability that the specific units of data are successfully transmitted through the stochastic computer network. An optimization algorithm which integrates the genetic algorithm, minimal paths, and Recursive Sum of Disjoint Products is utilized to find the optimal double-component assignment with maximal system reliability. Several computer networks are utilized to demonstrate the efficiency of the proposed algorithm compared with other algorithms. By solving this problem, data can be more reliably transmitted and thus the organization operation is executed more smoothly.

Using minimal cuts to optimize network reliability for a stochastic computer network subject to assignment budget

In our modern society, information and data are usually transmitted through a computer network. Since the computer network's reliability has a great impact on the quality of data transmission, many organizations devote to evaluating or improving network reliability, especially for network reliability optimization. This study focuses on such a confronted problem that is to find the optimal transmission line assignment to the computer network such that network reliability is maximized subject to the budget constraint. Each transmission line owns several states due to failure, maintenance, etc., and thus the computer network associated with any transmission line assignment is called a stochastic computer network. Network reliability is the probability that the computer network can transmit the specified units of data successfully. Because the discussed problem is NP-hard, an optimization algorithm that integrates the genetic algorithm, minimal cuts and Recursive Sum of Disjoint Products is proposed. Experimental results illustrate the solution procedure and show that the proposed algorithm can be executed in a reasonable time.