Quantitative approaches for optimization of user experience based on network resilience for wireless service provider networks

Novel binary-addition tree algorithm (BAT) for binary-state network reliability problem

“…𝑇𝑇 � for different δ and Nsim. δ 2 11 2 13 2 15 2 17 2 19 avg 0 0.002833 0.011600 0.063967 0.254467 1.015033 0.269580 1 0.002667 0.010400 0.044767 0.181633 0.693600 0.186613 3 0.002733 0.010467 0.037900 0.151933 0.605367 0.161680 5 0.002300 0.008533 0.034133 0.133967 0.535000 0.142787 7 0.002000 0.007733 0.030933 0.122467 0.486300 0.129887 9 0.006667 0.011500 0.027167 0.105967 0.421967 0.114653 11 0.002500 0.006867 0.029933 0.098467 0.369567 0.101467 13 0.012233 0.016467 0.032533 0.092667 0.327867 0.096353 15 0.047200 0.050167 0.068433 0.121233 0.318800 0.121167 17 0.212833 0.214800 0.223800 0.271433 0.431600 0.270893 19 0.792700 0.794067 0.863100 0.886267 1.010367 0.869300 avg 0.098788 0.103873 0.132424 0.220045 0.565042…”

“…Standard deviations for different δ and Nsim. δ 2 11 2 13 2 15 2 17 2 19 avg 0 0.023924 0.013523 0.006838 0.003665 0.001624 0.009915 1 0.028306 0.012346 0.006542 0.003244 0.001613 0.010410 3 0.019739 0.011419 0.005203 0.002863 0.001412 0.008127 5 0.020445 0.011356 0.005272 0.002925 0.001478 0.008295 7 0.021986 0.010834 0.005591 0.002498 0.001401 0.008462 9 0.020792 0.009916 0.005446 0.002470 0.001342 0.007993 11 0.019218 0.009958 0.005171 0.002681 0.001325 0.007671 13 0.006552 0.009215 0.005373 0.002681 0.001421 0.005049 15 0.003724 0.004374 0.004180 0.002607 0.001475 0.003272 17 0.001410 0.002153 0.001750 0.002556 0.001272 0.001828 19 0.000693 0.001143 0.001165 0.000835 0.001089 0.000985 avg 0.015163 0.008749 0.004776 0.002639 0.001405…”

“…The binary-state network is a vital network model; each of its components is binary-state, either functioning or failed to communicate to send power [5], liquids [6], gases [6], data [7], topology design [8], signals [8,9], resilience [10,11], and multimedia [12]. Hence, the binary-state network has been applied to a variety of real applications, including communication [5,8], transportation [6,13], transformation [14], transmission [15], distribution [16], recovery [17], backup [18,19], and allocation [20].…”

“…However, the two-subset reliability is not sufficient to measure the network performance and the roles of components in making a correct decision. For example, a decision-maker is always needed to find which of the four locations is the most reliable for building a supply chain in the transportation system [13]; which five bases have the best reliable connection after considering network resiliency in telecom systems [10,11]; which three nodes have less reliable communication in the wireless sensor network [8,9,10,16], which six grids need to enhance their connection to have a better reliable smart grid [5,20]; and which five points have the weakest signal transmission in the Internet of Things systems [15,38].…”

“…Various binary-state networks are used in real-world applications such network resilience [11], wireless sensor network [12], pipe networks [13], the internet of things [14], and social networks [15], and such networks are constantly growing. For example, social networks have more than 27 billion users [16].…”