Enhancing the navigability in a social network of smart objects: a Shapley-value based approach

The Internet of Things (IoT) holds the promise to interconnect any possible object capable of providing useful information about the physical world for the benefit of humans' quality of life. The increasing number of heterogeneous objects that the IoT has to manage introduces crucial scalability issues that still need appropriate solutions. In this respect, one promising proposal is the Social IoT (SIoT) paradigm, whose main principle is to enable objects to autonomously establish social links with each other (adhering to rules set by their owners). "Friend" objects exchange data in a distributed manner and this avoids centralized solutions to implement major functions, such as: node discovery, information search, and trustworthiness management. However, the number and types of established friendships affect network navigability. This issue is the focus of this paper, which proposes an efficient, distributed and dynamic solution for the objects to select the right friends for the benefit of the overall network connectivity. The proposed friendship selection mechanism relies on a game theoretic model and a Shapley-value based algorithm. Two different utility functions are defined and evaluated based on either a group degree centrality and an average local clustering parameter. The comparison in terms of global navigability is measured in terms of average path length for the interconnection of any couple of nodes in the network. Results show that the group degree centrality brings to an enhanced degree of navigability thanks to the ability to create a suitable core of hubs

Node aggregation for enhancing PageRank

In this paper, we study the problem of node aggregation under different perspectives for increasing PageRank of some nodes of interest. PageRank is one of the parameters used by the search engine Google to determine the relevance of a web page. We focus our attention to the problem of nding the best nodes in the network from an aggregation viewpoint, i.e., what are the best nodes to merge with for the given nodes. This problem is studied from global and local perspectives. Approximations are proposed to reduce the computation burden and to overcome the limitations resulting from the lack of centralized information. Several examples are presented to illustrate the different approaches that we proposeFP7-ICT Project DYMASOS under Grant 611281Ministerio de Economía y Competitividad COOPERA Project Grant DPI2013-46912-C2-1-RMinisterio de Educación José Castillejo Grant (CAS14/00277)Grant-in-Aid for Scientific Research Grant 15H04020 and Fellowship PE1604