Cache "less for more" in information-centric networks (extended version)

Ubiquitous in-network caching is one of the key aspects of information-centric networking (ICN) which has received widespread research interest in recent years. In one of the key relevant proposals known as Content-Centric Networking (CCN), the premise is that leveraging in-network caching to store content in every node along the delivery path can enhance content delivery. We question such an indiscriminate universal caching strategy and investigate whether caching less can actually achieve more. More specifically, we study the problem of en route caching and investigate if caching in only a subset of nodes along the delivery path can achieve better performance in terms of cache and server hit rates. We first study the behavior of CCN's ubiquitous caching and observe that even naïve random caching at a single intermediate node along the delivery path can achieve similar and, under certain conditions, even better caching gain. Motivated by this, we propose a centrality-based caching algorithm by exploiting the concept of (ego network) betweenness centrality to improve the caching gain and eliminate the uncertainty in the performance of the simplistic random caching strategy. Our results suggest that our solution can consistently achieve better gain across both synthetic and real network topologies that have different structural properties. We further find that the effectiveness of our solution is correlated to the precise structure of the network topology whereby the scheme is effective in topologies that exhibit power law betweenness distribution (as in Internet AS and WWW networks)

Self-organization of Nodes using Bio-Inspired Techniques for Achieving Small World Properties

In an autonomous wireless sensor network, self-organization of the nodes is essential to achieve network wide characteristics. We believe that connectivity in wireless autonomous networks can be increased and overall average path length can be reduced by using beamforming and bio-inspired algorithms. Recent works on the use of beamforming in wireless networks mostly assume the knowledge of the network in aggregation to either heterogeneous or hybrid deployment. We propose that without the global knowledge or the introduction of any special feature, the average path length can be reduced with the help of inspirations from the nature and simple interactions between neighboring nodes. Our algorithm also reduces the number of disconnected components within the network. Our results show that reduction in the average path length and the number of disconnected components can be achieved using very simple local rules and without the full network knowledge.Comment: Accepted to Joint workshop on complex networks and pervasive group communication (CCNet/PerGroup), in conjunction with IEEE Globecom 201

Zentralitäts- und Prestigemaße

Dieser Beitrag führt in die wichtigsten Zentralitätskonzepte ein - ohne Anspruch auf Vollständigkeit, aber in dem Bemühen, einen Katalog grundlegender, in der Netzwerkforschung gebräuchlicher Zentralitäts- und Prestigemaße zu liefern. Dabei wurde der Schwerpunkt auf die Darstellung der Konzepte gelegt. Kapitel 4 diskutiert die Maße im Hinblick auf ihre Interpretier- und Anwendbarkeit sowie einige Desiderate der Zentralitätsforschung. (Autorenreferat

Strategic Networking for Online Success

The growth of online social networks and the decreasing effectiveness of traditional marketing have lead to a large interest in social networks. For an appropriate application of new marketing approaches marketers have to understand the impact of interactions and relationships among network members on their individual outcome and network popularity in order to use online social networks effectively in marketing. In this study we analyze networking behavior of music artists for promoting their music. Our sample consists of a set of 480 music artists who actively operate online social networks for personal success on two independent online social network platforms at the same time. Personal network information on both platforms is tracked monthly over a period of six months. Applying a count data approach we relate well-established egocentric network measures to online success. Our results indicate that online success is determined by the social network structure and networking activities of the music artists rather than by their outside popularity. Most importantly, the drivers of online success are not limited to the size of the of the artist’s personal network. The findings of our study provide several insights into the use of personal online social networks for marketing products and services