Decision-aided evaluation of paths for routing on multi-attribute computer network consisting of encoded paths under uncertainty

Abstract

The network users need to evaluate the alternative transmission pathways to avoid some routing problems such as possible network attacks, data traffic, etc. in computer networks. In order to provide a mathematical solution to this situation, in this paper the computer network system is considered as a graph, and a random data structure denoted by Bloom filter is used to forward data between computers in the network. The Bloom filter has been used for encoding the routes minimises the query response time, although it has a significant risk of producing errors indicated by false positives (FP). The study aims to assess all paths between two distinct computers on a multi-attribute computer network considering risk and FP values regarding paths. These considerations are inherently vagueness. That being the case, a novel two-stage research methodology is presented to determine the desired pathways during message transmission on a multi-attribute computer network under uncertainty. At this point, the values of the possible risks and the probability of FP of the transmission edges are defined by employing triangular fuzzy numbers to reach the theoretical solutions. The novelty of the study is proposing a research methodology based on fuzzy Multi-Criteria Decision Making (MCDM) techniques to offer alternative routes during data transmission on any multi-attribute computer network under uncertainty for the first time. Further, a sensitivity analysis is implemented. In all computational analyses, the most appropriate and reliable transmission pathways are listed, and some managerial insights and main findings are provided for the network users.