Vaness: DNS for nomadic users in vehicular networks

Vehicular networks, also known as VANETs, are an ad-hoc network formed by vehicles and road-side units. Nowadays they have been attracting big interest both from researchers as from the automotive industry. With the upcoming of automotive specific operating systems and self-driving cars, the use of applications on vehicles and the integration with common mobile devices is becoming a big part of VANETs. Although many advances have been made on this field, there is still a big discrepancy between the communication layer services provided by VANETs and the user level services, namely those accessible through mobile applications on other networks and technologies. Users and developers are accustomed to user-to-user or user-tobusiness communication without explicit concerns related with the available communication transport layer. Such is not possible in VANETs since people may use more than one vehicle. However, to send a message to a specific user in these networks, there is a need to know the ID of the vehicle where the user is, meaning that there is a lack of services that map each individual user to VANETs endpoint (vehicle identification). This dissertation work proposes VANESS, a naming service as a resource to support user-to-user communication within a heterogeneous scenario comprising typical ISP scenario and VANETs focused on mobile devices. The proposed system is able to map the user to an end point either locally (i.e. there is not internet connection at all), online (i.e. system is not in a vehicular network but has direct internet connection) and using a gateway (i.e. the system is in a vehicular network where some of the nodes have internet access and will act as a gateway). VANESS was fully implemented on android OS with results proving his viability, and partially on iOS showing its multiplatform capabilities.

Error correcting codes for visible light communication systems

Over the past few years, the number of wireless networks users has been increasing. Until now, Radio-Frequency (RF) used to be the dominant technology. However, the electromagnetic spectrum in these region is being saturated, demanding for alternative wireless technologies. Recently, with the growing market of LED lighting, the Visible Light Communications has been drawing attentions from the research community. First, it is an eficient device for illumination. Second, because of its easy modulation and high bandwidth. Finally, it can combine illumination and communication in the same device, in other words, it allows to implement highly eficient wireless communication systems. One of the most important aspects in a communication system is its reliability when working in noisy channels. In these scenarios, the received data can be afected by errors. In order to proper system working, it is usually employed a Channel Encoder in the system. Its function is to code the data to be transmitted in order to increase system performance. It commonly uses ECC, which appends redundant information to the original data. At the receiver side, the redundant information is used to recover the erroneous data. This dissertation presents the implementation steps of a Channel Encoder for VLC. It was consider several techniques such as Reed-Solomon and Convolutional codes, Block and Convolutional Interleaving, CRC and Puncturing. A detailed analysis of each technique characteristics was made in order to choose the most appropriate ones. Simulink models were created in order to simulate how diferent codes behave in diferent scenarios. Later, the models were implemented in a FPGA and simulations were performed. Hardware co-simulations were also implemented to faster simulation results. At the end, diferent techniques were combined to create a complete Channel Encoder capable of detect and correct random and burst errors, due to the usage of a RS(255,213) code with a Block Interleaver. Furthermore, after the decoding process, the proposed system can identify uncorrectable errors in the decoded data due to the CRC-32 algorithm.

Forwarding and security in vehicular networks

The growing research in vehicular network solutions provided the rise of interaction in these highly dynamic environments in the market. The developed architectures do not usually focus, however, in security aspects. Common security strategies designed for the Internet require IP. Since nodes' addresses in a vehicular network are too dynamic, such solutions would require cumbersome negotiations, which would make them unsuitable to these environments. The objective of this dissertation is to develop, and test a scalable, lightweight, layer 3 security protocol for vehicular networks, in which nodes of the network are able to set up long-term security associations with a Home Network, avoiding session renegotiations due to lack of connectivity and reduce the protocol stacking. This protocol allows to provide security independent of the nodes (vehicles) position, of its addressing and of the established path to access the Internet, allowing the mobility of vehicles and of its active sessions seamlessly without communication failures.

On the application of contextual IoT service discovery in Information Centric Networks

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.