"uuid","repository link","title","author","contributor","publication year","abstract","subject topic","language","publication type","publisher","isbn","issn","patent","patent status","bibliographic note","access restriction","embargo date","faculty","department","research group","programme","project","coordinates"
"uuid:5c80616a-87ba-478d-8428-45f807f473f3","http://resolver.tudelft.nl/uuid:5c80616a-87ba-478d-8428-45f807f473f3","A network approach for power grid robustness against cascading failures","Wang, X.; Koc, Y.; Kooij, R.E.; Van Mieghem, P.","","2015","Cascading failures are one of the main reasons for blackouts in electrical power grids. Stable power supply requires a robust design of the power grid topology. Currently, the impact of the grid structure on the grid robustness is mainly assessed by purely topological metrics, that fail to capture the fundamental properties of the electrical power grids such as power flow allocation according to Kirchhoff’s laws. This paper deploys the effective graph resistance as a metric to relate the topology of a grid to its robustness against cascading failures. Specifically, the effective graph resistance is deployed as a metric for network expansions (by means of transmission line additions) of an existing power grid. Four strategies based on network properties are investigated to optimize the effective graph resistance, accordingly to improve the robustness, of a given power grid at a low computational complexity. Experimental results suggest the existence of Braess’s paradox in power grids: bringing an additional line into the system occasionally results in decrease of the grid robustness. This paper further investigates the impact of the topology on the Braess’s paradox, and identifies specific sub-structures whose existence results in Braess’s paradox in power grids. Careful assessment of the design and expansion choices of grid topologies incorporating the insights provided by this paper optimizes the robustness of a power grid, while avoiding the Braess’s paradox in the system.","","en","conference paper","RNDM","","","","","","","","Electrical Engineering, Mathematics and Computer Science","Network Architectures and Services","","","",""
"uuid:5ef03603-9045-4bdf-a1db-4842f2f82def","http://resolver.tudelft.nl/uuid:5ef03603-9045-4bdf-a1db-4842f2f82def","Do greedy assortativity optimization algorithms produce good results?","Winterbach, W.; De Ridder, D.; Wang, H.J.; Reinders, M.; Van Mieghem, P.","","2012","","","en","conference paper","EDP sciences","","","","","","","","Electrical Engineering, Mathematics and Computer Science","Network Architectures and Services (NAS) Group","","","",""
"uuid:184d1254-2bb2-4205-818e-7824de728c59","http://resolver.tudelft.nl/uuid:184d1254-2bb2-4205-818e-7824de728c59","Correlating the topology of a metabolic network with its growth capacity","Winterbach, W.; Wang, H.; Reinders, M.; Van Mieghem, P.; De Ridder, D.","","2010","","","en","conference paper","ICST","","","","","","","","Electrical Engineering, Mathematics and Computer Science","Network Architectures & Services (NAS)","","","",""
"uuid:a5e4ab47-eed4-4180-b346-da086e826a02","http://resolver.tudelft.nl/uuid:a5e4ab47-eed4-4180-b346-da086e826a02","Metabolic network destruction: Relating topology to robustness","Winterbach, W.; Wang, H.; Reinders, M.; Van Mieghem, P.; De Ridder, D.","","2010","Biological networks exhibit intriguing topological properties such as small-worldness. In this paper, we investigate whether the topology of a metabolic network is related to its robustness. We do so by perturbing a metabolic system in silico, one reaction at a time and studying the correlations between growth, as predicted by flux balance analysis, and a number of topological metrics, as computed from three network representations of the metabolic system. We find that a small number of metrics correlate with growth and that only one of the network representations stands out in terms of correlated metrics. The most correlated metrics point to the importance of hub nodes in this network: so-called ""currency metabolites"". Since they are responsible for interconnecting distant functional modules in the network, they are important points in the networks for predicting if reaction removal affects growth. Source code and data are available upon request.","metabolic networks; ux balance analysis; network topology; robustness","en","conference paper","","","","","","","","","Electrical Engineering, Mathematics and Computer Science","Network Architectures and Services","","","",""
"uuid:ff66e490-db59-4e3c-b6e2-926da4f074df","http://resolver.tudelft.nl/uuid:ff66e490-db59-4e3c-b6e2-926da4f074df","Algebraic Connectivity Optimization via Link Addition","Wang, H.; Van Mieghem, P.","","2008","","algebraic connectivity; synchronization; optimization; link addition","en","conference paper","ICST","","","","","","","","Electrical Engineering, Mathematics and Computer Science","","","","",""
"uuid:9426fb39-a92e-41e0-9a82-5075d08a7b35","http://resolver.tudelft.nl/uuid:9426fb39-a92e-41e0-9a82-5075d08a7b35","The Effect of Peer Selection with Hopcount or Delay Constraint on Peer-to-Peer Networking","Tang, S.; Wang, H.; Van Mieghem, P.","","2008","","","en","conference paper","","","","","","","","","Electrical Engineering, Mathematics and Computer Science","","","","",""
"uuid:abb66a4a-4d08-4652-9f16-ae697c85f6cf","http://resolver.tudelft.nl/uuid:abb66a4a-4d08-4652-9f16-ae697c85f6cf","Shifting the Link Weights in Networks","Wang, H.; Van Mieghem, P.","","2007","","","en","conference paper","","","","","","","","","Electrical Engineering, Mathematics and Computer Science","","","","",""
"uuid:ee8d18fb-b846-4009-baa2-67a65ffc32d3","http://resolver.tudelft.nl/uuid:ee8d18fb-b846-4009-baa2-67a65ffc32d3","A Qualitative Comparison of Power Law Generators","Martin Hernandez, J.; Kleiberg, T.; Wang, H.; Van Mieghem, P.","","2007","","network topology; internet; power law; graphs; algorithms","en","conference paper","","","","","","","","","Electrical Engineering, Mathematics and Computer Science","","","","",""
"uuid:50689b82-502c-49b6-b265-311a592f1642","http://resolver.tudelft.nl/uuid:50689b82-502c-49b6-b265-311a592f1642","Constructing the Overlay Network by Tuning Link Weights","Wang, H.; Van Mieghem, P.","","2007","","","en","conference paper","","","","","","","","","Electrical Engineering, Mathematics and Computer Science","","","","",""
"uuid:357b3fb5-8dfc-4d75-973b-4c1b6dc2d49d","http://resolver.tudelft.nl/uuid:357b3fb5-8dfc-4d75-973b-4c1b6dc2d49d","Topological Characteristics of the Dutch Road Infrastructure","Jamakovic, A.; Wang, H.; Van Mieghem, P.","","2006","","","en","conference paper","","","","","","","","","Electrical Engineering, Mathematics and Computer Science","","","","",""
"uuid:2b1acb2a-d4db-40ab-8cb3-d57033a47e57","http://resolver.tudelft.nl/uuid:2b1acb2a-d4db-40ab-8cb3-d57033a47e57","The Stability of Paths in a Dynamic Network","Kuipers, F.A.; Wang, H.; Van Mieghem, P.","","2005","","network dynamics; link-state update policy; shortest path; link weight perturbation; quality of service","en","conference paper","","","","","","","","","Electrical Engineering, Mathematics and Computer Science","","","","",""
"uuid:055f7afd-22bf-4bc5-b841-dddf31b66217","http://resolver.tudelft.nl/uuid:055f7afd-22bf-4bc5-b841-dddf31b66217","Degree and Principal Eigenvectors in Complex Networks","Li, C.; Wang, H.; Van Mieghem, P.","","","The largest eigenvalue ? 1 of the adjacency matrix powerfully characterizes dynamic processes on networks, such as virus spread and synchronization. The minimization of the spectral radius by removing a set of links (or nodes) has been shown to be an NP-complete problem. So far, the best heuristic strategy is to remove links/nodes based on the principal eigenvector corresponding to the largest eigenvalue ? 1. This motivates us to investigate properties of the principal eigenvector x 1 and its relation with the degree vector. (a) We illustrate and explain why the average E[x 1] decreases with the linear degree correlation coefficient ? D in a network with a given degree vector; (b) The difference between the principal eigenvector and the scaled degree vector is proved to be the smallest, when ?1=N2N1 , where N k is the total number walks in the network with k hops; (c) The correlation between the principal eigenvector and the degree vector decreases when the degree correlation ? D is decreased.","networks; spectral radius; principal eigenvector; degree; as-sortativity","en","conference paper","Springer","","","","","","","","Electrical Engineering, Mathematics and Computer Science","Network Architectures and Services Group (NAS)","","","",""