Delay-centric handover in SCTP

The introduction of the Stream Control Transmission Protocol (SCTP) has opened the possibility of a mobile aware transport protocol. The multihoming feature of SCTP negates the need for a solution such as Mobile IP and, as SCTP is a transport layer protocol, it adds no complexity to the network. Utilizing the handover procedure of SCTP, the large bandwidth of WLAN can be exploited whilst in the coverage of a hotspot, and still retain the 3G connection for when the user roams out of the hotspot’s range. All this functionality is provided at the transport layer and is transparent to the end user, something that is still important in non-mobile-aware legacy applications. However, there is one drawback to this scenario - the current handover scheme implemented in SCTP is failure-centric in nature. Handover is only performed in the presence of primary destination address failure. This dissertation proposes a new scheme for performing handover using SCTP. The handover scheme being proposed employs an aggressive polling of all destination addresses within an individual SCTP association in order to determine the round trip delay to each of these addresses. It then performs handover based on these measured path delays. This delay-centric approach does not incur the penalty associated with the current failover-based scheme, namely a number of timeouts before handover is performed. In some cases the proposed scheme can actually preempt the path failure, and perform handover before it occurs. The proposed scheme has been evaluated through simulation, emulation, and within the context of a wireless environment

The latest advances in wireless communication in aviation, wind turbines and bridges

Present-day technologies used in SHM (Structural Health Monitoring) systems in many implementations are based on wireless sensor networks (WSN). In the context of the continuous development of these systems, the costs of the elements that form the monitoring system are decreasing. In this situation, the challenge is to select the optimal number of sensors and the network architecture, depending on the wireless system’s other parameters and requirements. It is a challenging task for WSN to provide scalability to cover a large area, fault tolerance, transmission reliability, and energy efficiency when no events are detected. In this article, fundamental issues concerning wireless communication in structural health monitoring systems (SHM) in the context of non-destructive testing sensors (NDT) were presented. Wireless technology developments in several crucial areas were also presented, and these include engineering facilities such as aviation and wind turbine systems as well as bridges and associated engineering facilities

Delivering IoT Services in Smart Cities and Environmental Monitoring through Collective Awareness, Mobile Crowdsensing and Open Data

The Internet of Things (IoT) is the paradigm that allows us to interact with the real world by means of networking-enabled devices and convert physical phenomena into valuable digital knowledge. Such a rapidly evolving field leveraged the explosion of a number of technologies, standards and platforms. Consequently, different IoT ecosystems behave as closed islands and do not interoperate with each other, thus the potential of the number of connected objects in the world is far from being totally unleashed. Typically, research efforts in tackling such challenge tend to propose a new IoT platforms or standards, however, such solutions find obstacles in keeping up the pace at which the field is evolving. Our work is different, in that it originates from the following observation: in use cases that depend on common phenomena such as Smart Cities or environmental monitoring a lot of useful data for applications is already in place somewhere or devices capable of collecting such data are already deployed. For such scenarios, we propose and study the use of Collective Awareness Paradigms (CAP), which offload data collection to a crowd of participants. We bring three main contributions: we study the feasibility of using Open Data coming from heterogeneous sources, focusing particularly on crowdsourced and user-contributed data that has the drawback of being incomplete and we then propose a State-of-the-Art algorith that automatically classifies raw crowdsourced sensor data; we design a data collection framework that uses Mobile Crowdsensing (MCS) and puts the participants and the stakeholders in a coordinated interaction together with a distributed data collection algorithm that prevents the users from collecting too much or too less data; (3) we design a Service Oriented Architecture that constitutes a unique interface to the raw data collected through CAPs through their aggregation into ad-hoc services, moreover, we provide a prototype implementation

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts