Biblio

In recent time it has become very crucial for the data center networks (DCN) to broaden the system limit to be able to meet with the increasing need of cloud based applications. A decent DCN topology must comprise of numerous properties for low diameter, high bisection bandwidth, ease of organization and so on. In addition, a DCN topology should depict aptness in failure resiliency, scalability, construction and routing. In this paper, we introduce a new Data Center Network topology termed LevelTree built up with several modules grows as a tree topology and each module is constructed from a complete graph. LevelTree demonstrates great topological properties and it beats critical topologies like Jellyfish, VolvoxDC, and Fattree regarding providing a superior worthwhile plan with greater capacity.

In recent years, prodigious explosion of social network services may trigger new business models. However, it has negative aspects such as personal information spill or spamming, as well. Amongst conventional spam detection approaches, the studies which are based on vertex degrees or Local Clustering Coefficient have been caused false positive results so that normal vertices can be specified as spammers. In this paper, we propose a novel approach by employing the circuit structure in the social networks, which demonstrates the advantages of our work through the experiment.