Load distribution in weighted complex networks

We study the load distribution in weighted networks by measuring the effective number of optimal paths passing through a given vertex. The optimal path, along which the total cost is minimum, crucially depend on the cost distribution function $p_c(c)$. In the strong disorder limit, where $p_c(c)\sim c^{-1}$, the load distribution follows a power law both in the Erd\H{o}s-R\'enyi (ER) random graphs and in the scale-free (SF) networks, and its characteristics are determined by the structure of the minimum spanning tree. The distribution of loads at vertices with a given vertex degree also follows the SF nature similar to the whole load distribution, implying that the global transport property is not correlated to the local structural information. Finally, we measure the effect of disorder by the correlation coefficient between vertex degree and load, finding that it is larger for ER networks than for SF networks.Comment: 4 pages, 4 figures, final version published in PR

LOAD DISTRIBUTION AND RESOURCE SHARING

This paper will discuss about the system structure and system design philosophy for the large scale control systems. The design philosophy, the main theme of this article, is "load distribution and resource sharing", but also the following items will be discussed: - three level hierarchy control system philosophy; - coupling and optimal load sharing among SCC/DDC computers; - sharing of the process resources among computers.load distribution

Load distribution in small world networks

In this paper we introduce a new model of data packet transport, based on a stochastic approach with the aim of characterizing the load distribution on complex networks. Moreover we analyze the load standard deviation as an index of uniformity of the distribution of packets within the network, to characterize the effects of the network topology. We measure such index on the model proposed by Watts and Strogatz as the redirection probability is increased. We find that the uniformity of the load spread is maximized in the intermediate region, at which the small world effect is observed and both global and local efficiency are high. Moreover we analyze the relationship between load centrality and degree centrality as an approximate measure of the load at the edges. Analogous results are obtained for the load variance computed at the edges as well as at the vertices.Comment: 6 pages, 5 figures. Included in conference proceedings International Conference PhysCon 2005 August 24-26, 2005, Saint Petersburg, RUSSI

Efficient Load Flow Techniques Based on Holomorphic Embedding for Distribution Networks

The Holomorphic Embedding Load flow Method (HELM) employs complex analysis to solve the load flow problem. It guarantees finding the correct solution when it exists, and identifying when a solution does not exist. The method, however, is usually computationally less efficient than the traditional Newton-Raphson algorithm, which is generally considered to be a slow method in distribution networks. In this paper, we present two HELM modifications that exploit the radial and weakly meshed topology of distribution networks and significantly reduce computation time relative to the original HELM implementation. We also present comparisons with several popular load flow algorithms applied to various test distribution networks.Comment: Accepted for publication in the Proceedings of 2019 IEEE PES General Meeting, 5 Page

Universal Behavior of Load Distribution in Scale-free Networks

We study a problem of data packet transport in scale-free networks whose degree distribution follows a power-law with the exponent $\gamma$. We define load at each vertex as the accumulated total number of data packets passing through that vertex when every pair of vertices send and receive a data packet along the shortest path connecting the pair. It is found that the load distribution follows a power-law with the exponent $\delta \approx 2.2(1)$, insensitive to different values of $\gamma$ in the range, $2 < \gamma \le 3$, and different mean degrees, which is valid for both undirected and directed cases. Thus, we conjecture that the load exponent is a universal quantity to characterize scale-free networks.Comment: 5 pages, 5 figures, revised versio