Natarajan Meghanathan

Assortative index (A. Index) of a network graph is a measure of the similarity of the end vertices of the edges with respect to a node-level metric. Networks were classified as assortative, dissortative or neutral depending on the proximity of the A. index values to 1, -1 or 0 respectively. Degree centrality (DegC) has been traditionally the node-level metric used for assortativity analysis in the literature. In this paper, we propose to analyse assortativity of real-world networks using the local clustering coefficient (LCC) metric: a measure of the probability with which any two neighbours of a vertex are connected. Though DegC and LCC are inversely related, we observe 80% of the 50 real-world network graphs analysed to exhibit similar levels of assortativity. We also observe a real-world network graph to be neutral (i.e., assortative or dissortative) with a probability of 0.6 or above with respect to both DegC and LCC.]]>

Dhafer Ben Khedher; Jehad S. Alomari

The basic use of virtualisation is the optimisation of technical resources, improved service and reduce the cost. Server consolidation based on virtualisation technology that implement redundancy to achieve consolidation of computing resources and provide usability, flexibility, simplify system administration, reduce the cost physical infrastructure. This technology improves utilisation in today's internet service-oriented industry data centres. This service relies on performance of different hardware subsystems. Vendor's researches have shown that performance can be achieved with virtualisation as on physical hardware. Most work done on applications performance testing in virtual solutions is conducted by vendors. In this paper, we present a critical analysis and comparison on virtual solution performance using telecommunication applications to meet high quality of service. We have mainly used in this experiment a real data in a real-time network application. ]]>

Natarajan Meghanathan

We propose a centrality and topological sort-based formulation to quantify the relative contribution of courses in a curriculum network graph (CNG). We normalise the values obtained for each centrality metric as well as the level numbers of the vertices in a topological sort of the CNG. The contribution score for a vertex is the weighted sum of the normalised values for the vertex. The relative contribution scores of the vertices could be used as a measure of the weights to be given to the courses for curriculum assessment and student ranking as well as to cluster courses with similar contribution. ]]>

Dimitrios Tsiotas

This article studies the topology of four urban road networks (URNs) in the region of Thessaly, Greece, comparatively with some aspects of their socioeconomic environment. The purpose of the study is to enlighten the interrelation between network structure and traffic, as defined in the case of URNs submitted to spatial constraints, and to reveal the topological patterns describing the concept of urban mobility. The methodological approach examines whether some fundamental measures of complex network analysis are related to socioeconomic indices of urban mobility in the socioeconomic framework of the URNs of Thessaly. Overall, the analysis provides interesting insights about the effects of spatial constraints on the network topology, the magnitude of the examined URNs comparatively with global cases, the growth patterns between connectivity and distance, and how the network topology is related to urban mobility, population, and market information.]]>