Named data networking (NDN) has emerged as a component of the Future Internet architecture to support scalable content distribution, mobility, security, and trust; as well as to provide access to information irrespective of its physical location. The NDN, and previously content-centric networking (CCN), has been considered as the enabler to address various Internet of Things (IoT) challenges, with the potential to outperform the current IP paradigm in many dimensions. The requirements and challenges of the IoT, imposed by constraints, such as limited memory and computational power, while requiring high energy efficiency in the face of unstable network connectivity, impose extra burdens on the IP paradigm. The named content, in-network caching and named-based routing approach in the CCN and NDN provide promising solutions to overcome these constraints and showcase alternative implementations. This paper aims to investigate and demonstrate the current incorporation of the NDN/CCN with the IoT in terms of innetwork caching management, naming scheme for devices and data, access control and policies, forwarding strategies, device configuration, and discovery. INDEX TERMS CCN, content-centric networking, ICN, information-centric networking, Internet of Things, named data networking, NDN.

This paper proposes an indoor positioning algorithm, WBI based on WiFi Received Signal Strength (RSS) technology in conjunction with trilateration techniques. The WBI algorithm estimates the location using RSS values previously collected from within the area of interest, determine whether it falls within the Min-Max bounding box, corrects for non-line-of-sight propagation effects on positioning errors using Kalman filtering, and finally update the location estimation using Least Square Estimation (LSE). The paper analyzes the complexity of the proposed algorithm and compares its performance against existing algorithms. Furthermore, the proposed WBI algorithm was able to achieve an average accuracy of 2.6 m.