(Archived) - Context Information

On the application of Contextual IoT Service Discovery in Information Centric Networks

jquevedo — Wed, 09 Mar 2016 13:28:48 +0000

The continuous flow of technological developments in communications and electronic industries has led to the growing expansion of the Internet of Things (IoT). By leveraging the capabilities of smart networked devices and integrating them into existing industrial, leisure and communication applications, the IoT is expected to positively impact both economy and society, reducing the gap between the physical and digital worlds. Therefore, several efforts have been dedicated to the development of networking solutions addressing the diversity of challenges associated with such a vision. In this context, the integration of Information Centric Networking (ICN) concepts into the core of IoT is a research area gaining momentum and involving both research and industry actors. The massive amount of heterogeneous devices, as well as the data they produce, is a significant challenge for a wide-scale adoption of the IoT. In this paper we propose a service discovery mechanism, based on Named Data Networking (NDN), that leverages the use of a semantic matching mechanism for achieving a flexible discovery process. The development of appropriate service discovery mechanisms enriched with semantic capabilities for understanding and processing context information is a key feature for turning raw data into useful knowledge and ensuring the interoperability among different devices and applications. We assessed the performance of our solution through the implementation and deployment of a proof-of-concept prototype. Obtained results illustrate the potential of integrating semantic and ICN mechanisms to enable a flexible service discovery in IoT scenarios.

Semantic features for context organization

mantunes — Mon, 21 Sep 2015 16:43:35 +0000

In recent years the technological world has grown by incorporating billions of small sensing devices, collecting and sharing real-world information. As the number of such devices grows, it becomes increasingly difficult to manage all these new information sources. There is no uniform way to share, process and understand context information. In previous publications we discussed efficient ways to organize context information that is independent of structure and representation. However, our previous solution suffers from semantic sensitivity. In this paper we review semantic methods that can be used to minimize this issue, and propose an unsupervised semantic similarity solution that combines distributional profiles with public web services. Our solution was evaluated against Miller-Charles dataset, achieving a correlation of 0.6.

Semantic-based Publish/Subscribe for M2M

mantunes — Tue, 09 Sep 2014 13:54:58 +0000

The number of connected devices is expected to soar in the coming years, each one of them collects and distributes real-world information though various systems. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several context representation schemes try to standardize this informa-tion, however none of them have been widely adopted. Publish/ subscribe paradigm has proven to be an adequate abstraction for large scale information dissemination, but none of current variations is well suited for context information. In a previous publication we addressed these challenges, however our solution has some drawbacks: poor scalability and semantic extraction. The aim of this paper is twofold. First, we discuss an efficient way to deal with representation schemes diversity and propose a d-dimensional context organization model. Second, we propose a semantic-based publish/subscribe system that is well suited for M2M scenarios. Our evaluation shows that d-dimensional organization model outperforms our previous solution in both speed and space requirements.