Internet growth has generated new types of services where the use of sensors and actuators is especially remarkable. These services compose what is known as the Internet of Things (IoT). One of the biggest current challenges is obtaining a safe and easy access control scheme for the data managed in these services. We propose integrating IoT devices in an access control system designed for Web-based services by modelling certain IoT communication elements as resources. This would allow us to obtain a unified access control scheme between heterogeneous devices (IoT devices, Internet-based services, etc.). To achieve this, we have analysed the most relevant communication protocols for these kinds of environments and then we have proposed a methodology which allows the modelling of communication actions as resources. Then, we can protect these resources using access control mechanisms. The validation of our proposal has been carried out by selecting a communication protocol based on message exchange, specifically Message Queuing Telemetry Transport (MQTT). As an access control scheme, we have selected User-Managed Access (UMA), an existing Open Authorization (OAuth) 2.0 profile originally developed for the protection of Internet services. We have performed tests focused on validating the proposed solution in terms of the correctness of the access control system. Finally, we have evaluated the energy consumption overhead when using our proposal.

We introduce and explore a family of vertex-coloring problems, which, surprisingly enough, have not been considered before despite stemming from the problem of Wi-Fi channel assignment. Given a spectrum of colors, endowed with a matrix of interferences between each pair of colors, the Threshold Spectrum Coloring problem fixes the number of colors available and aims to minimize the interference threshold, i.e., the maximum of the interferences at the vertices. Conversely, the Chromatic Spectrum Coloring problem fixes a threshold and aims to minimize the number of colors for which respecting that threshold is possible. As the main theoretical results, we prove tight upper bounds for the solutions to each problem. Since both problems turn out to be NP-hard, we complete the scene with experimental results. We propose a DSATUR-based heuristic and study its performance to minimize the maximum vertex interference in Wi-Fi channel assignment, both for randomly-generated graphs and for a real-world scenario. Further, for all these graphs, we experimentally check the goodness of the theoretical bounds.

Due to the low cost of CMOS IP-based cameras, wireless surveillance sensor networks have emerged as a new application of sensor networks able to monitor public or private areas or even country borders. Since these networks are bandwidth intensive and the radioelectric spectrum is limited, especially in unlicensed bands, it is mandatory to assign frequency channels in a smart manner. In this work, we propose the application of automated negotiation techniques for frequency assignment. Results show that these techniques are very suitable for the problem, being able to obtain the best solutions among the techniques with which we have compared them.

The rise of the Internet of Things (IoT) paradigm has allowed the design and development of new services interconnecting heterogeneous devices. However, the complexity of these new systems hasn't been followed by the increase of intelligence and reasoning of the devices connected. On the other hand, intelligent agent systems have developed precisely these characteristics so the combination of both paradigms by modelling intelligent agents in IoT devices is a very promising approach that will enable a more powerful and smart IoT. The interconnection of agents through a Internet-based network implies addressing critical issues that affect all network communications, such as security, privacy and access control, specially given the sensitivity of the information exchanged by agents. In this paper, we propose the application of User-Managed Access (UMA) to provide an unified access control schema for an heterogeneous hybrid architecture of IoT devices and intelligent agents.

Nonmonotonic utility spaces are found in multi‐issue negotiations where the preferences on the issues yield multiple local optima. These negotiations are specially challenging because of the inherent complexity of the search space and the difficulty of learning the opponent’s preferences. Most current solutions successfully address moderately complex preference scenarios, while solutions intended to operate in highly complex spaces are constrained by very specific preference structures. To overcome these problems, we propose the Region‐Based Multi‐issue Negotiation Protocol (RBNP) for bilateral automated negotiation. RBNP is built upon a nonmediated recursive bargaining mechanism which efficiently modulates a region‐based joint exploration of the solution space. We empirically show that RBNP produces outcomes close to the Pareto frontier in reasonable negotiation times, and show that it provides a significantly better performance when compared to a generic Similarity‐Based Multi‐issue Negotiation Protocol (SBNP), which has been successfully used in many negotiation models. We have paid attention to the strategic issues, proposing and evaluating several concession mechanisms, and analyzing the equilibrium conditions. Results suggest that RBNP may be used as a basis to develop negotiation mechanisms in nonmonotonic utility spaces.