The smart management of freshwater for precision irrigation in agriculture is essential for increasing crop yield and decreasing costs, while contributing to environmental sustainability. The intense use of technologies offers a means for providing the exact amount of water needed by plants. The Internet of Things (IoT) is the natural choice for smart water management applications, even though the integration of different technologies required for making it work seamlessly in practice is still not fully accomplished. The SWAMP project develops an IoT-based smart water management platform for precision irrigation in agriculture with a hands-on approach based on four pilots in Brazil and Europe. This paper presents the SWAMP architecture, platform, and system deployments that highlight the replicability of the platform, and, as scalability is a major concern for IoT applications, it includes a performance analysis of FIWARE components used in the Platform. Results show that it is able to provide adequate performance for the SWAMP pilots, but requires specially designed configurations and the re-engineering of some components to provide higher scalability using less computational resources.

The area of Internet traffic measurement has advanced enormously over the last couple of years. This was mostly due to the increase in network access speeds, due to the appearance of bandwidth-hungry applications, due to the ISPs' increased interest in precise user traffic profile information and also a response to the enormous growth in the number of connected users. These changes greatly affected the work of Internet service providers and network administrators, which have to deal with increasing resource demands and abrupt traffic changes brought by new applications. This survey explains the main techniques and problems known in the field of IP traffic analysis and focuses on application detection. First, it separates traffic analysis into packet-based and flow-based categories and details the advantages and problems for each approach. Second, this work cites the techniques for traffic analysis accessible in the literature, along with the analysis performed by the authors. Relevant techniques include signature-matching, sampling and inference. Third, this work shows the trends in application classification analysis and presents important and recent references in the subject. Lastly, this survey draws the readers' interest to open research topics in the area of traffic analysis and application detection and makes some final remarks.

Irrigation for agriculture is the biggest consumer of freshwater in the world, which makes a case for the intensive use of technology to optimize the use of water, reduce the consumption of energy and improve the quality of crops. While the Internet of Things (IoT) and other associated technologies are the natural choice for smart water management applications, their appropriateness is still to be proven in real settings with the deployment of on-site pilots. Also, IoT-based application development platforms should be generic enough to be adapted to different crops, climates, and countries. The SWAMP project develops IoT based methods and approaches for smart water management in precision irrigation domain and pilots them in Italy, Spain, and Brazil. In this paper, we present the SWAMP view, architecture, pilots and the scenario-based development process adopted in the project.

Layered internet of things (IoT) architectures have been proposed over the last years as they facilitate understanding the roles of different networking, hardware, and software components of smart applications. These are inherently distributed, spanning from devices installed in the field up to a cloud datacenter and further to a user smartphone, passing by intermediary stages at different levels of fog computing infrastructure. However, IoT architectures provide almost no hints on where components should be deployed. IoT Software Platforms derived from the layered architectures are expected to adapt to scenarios with different characteristics, requirements, and constraints from stakeholders and applications. In such a complex environment, a one-size-fits-all approach does not adapt well to varying demands and may hinder the adoption of IoT Smart Applications. In this paper, we propose a 5-layer IoT Architecture and a 5-stage IoT Computing Continuum, as well as provide insights on the mapping of software components of the former into physical locations of the latter. Also, we conduct a performance analysis study with six configurations where components are deployed into different stages. Our results show that different deployment configurations of layered components into staged locations generate bottlenecks that affect system performance and scalability. Based on that, policies for static deployment and dynamic migration of layered components into staged locations can be identified.

IoT systems use sensors to collect data from smart environments and manage resources through data analysis. An IoT system deals with many connected devices with different network and hardware constraints in a real-world scenario. An IoT system needs to handle low-latency data analysis, security threats, internal vulnerabilities, and network disconnections, which cause data loss and incorrect decisions. Trustworthiness (also known as dependability) provides various features for an IoT end-to-end data flow, such as resilience, security, availability, reliability, scalability, maintainability, heterogeneity, hardware resources management, fault management policies, and data quality. This paper presents a survey on trustworthiness and dependability in IoT systems and proposes the Trustworthiness for IoT Framework (TW-IoT) to provide trustworthiness at the data level for mist and fog-based IoT systems. The TW-IoT framework provides data trustworthiness to ensure a continuous and uninterrupted operation of IoT data flow. We also discuss challenges and trade-offs related to data trustworthiness in IoT.