Enhancing Identifier/Locator Splitting Through Social Internet of Things

Abstract

In recent years identifier/locator splitting (ILS) has been proposed as a promising future Internet solution to the so-called “semantic overload of addresses” problem. It is currently under debate whether the ILS approach, which entails identifier-to-locator resolution procedures, could ensure scalability, session continuity, and mobility across heterogeneous multiaccess networks as demanded by Internet of Things (IoT). In this paper, it is proposed to exploit the Social IoT concept to address the above issues. More specifically, a scheme is introduced that browses the social graph of devices to find information about the locator of the intended destination. Results show that the proposed solution outperforms the alternative ILS approaches in terms of number of hops and latency incurred to accomplish the resolution procedure, at the cost of a slight increase in the storage demands to track social relationships.