Analytical controllability of deterministic scale-free networks and Cayley trees

According to the exact controllability theory, the controllability is investigated analytically for two typical types of self-similar bipartite networks, i.e., the classic deterministic scale-free networks and Cayley trees. Due to their self-similarity, the analytical results of the exact controllability are obtained, and the minimum sets of driver nodes (drivers) are also identified by elementary transformations on adjacency matrices. For these two types of undirected networks, no matter their links are unweighted or (nonzero) weighted, the controllability of networks and the configuration of drivers remain the same, showing a robustness to the link weights. These results have implications for the control of real networked systems with self-similarity.Comment: 7 pages, 4 figures, 1 table; revised manuscript; added discussion about the general case of DSFN; added 3 reference

Structural Analysis of Network Traffic Matrix via Relaxed Principal Component Pursuit

The network traffic matrix is widely used in network operation and management. It is therefore of crucial importance to analyze the components and the structure of the network traffic matrix, for which several mathematical approaches such as Principal Component Analysis (PCA) were proposed. In this paper, we first argue that PCA performs poorly for analyzing traffic matrix that is polluted by large volume anomalies, and then propose a new decomposition model for the network traffic matrix. According to this model, we carry out the structural analysis by decomposing the network traffic matrix into three sub-matrices, namely, the deterministic traffic, the anomaly traffic and the noise traffic matrix, which is similar to the Robust Principal Component Analysis (RPCA) problem previously studied in [13]. Based on the Relaxed Principal Component Pursuit (Relaxed PCP) method and the Accelerated Proximal Gradient (APG) algorithm, we present an iterative approach for decomposing a traffic matrix, and demonstrate its efficiency and flexibility by experimental results. Finally, we further discuss several features of the deterministic and noise traffic. Our study develops a novel method for the problem of structural analysis of the traffic matrix, which is robust against pollution of large volume anomalies.Comment: Accepted to Elsevier Computer Network

Design of Compact Planar Diplexer Based on Novel Spiral-Based Resonators

A miniaturized planar diplexer utilizing the novel spiral-based resonators is proposed. The given cell which is initially proposed in this article is composed of two separated rectangular spirals which are asymmetrical to each other and thus, it is called as ‘asymmetrical separated spirals resonator’ (ASSR). ASSR has more superior transmission property than the previous prototype and extremely compact dimension is also achieved. It is demonstrated that ASSR can exhibit bandpass performance with high frequency selectivity and good transmission property within the relatively low frequency band. Based on the given characteristic, one planar diplexer composed of T-junction and two ASSRs is synthesized and the fabricated prototype with compact dimension is achieved, thanks to ASSRs explored. Simultaneously, the transversal dimension of each channel is extremely compact because ASSRs are completely embedded in the feed lines. Both the simulated and measured results indicate that satisfactory impedance matching and high isolation between two channels are achieved. Furthermore, the proposed diplexer is uniplanar and no defected ground structure is introduced