The deployment of security services over Wireless Sensor Networks (WSN) and IoT devices brings significant processing and energy consumption overheads. These overheads are mainly determined by algorithmic efficiency, quality of implementation, and operating system. Benchmarks of symmetric primitives exist in the literature for WSN platforms but they are mostly focused on single platforms or single operating systems. Moreover, they are not up to date with respect to implementations and/or operating systems versions which had significant progress. Herein, we provide time and energy benchmarks of reference implementations for different platforms and operating systems and analyze their impact. Moreover, we not only give the first benchmark results of symmetric cryptography for the Intel Edison IoT platform but also describe a methodology of how to measure energy consumption on that platform.

Expanding involvement of the public in citizen science projects can benefit both volunteers and professional scientists alike. Recently, citizen science has come into focus as an important data source for reporting and monitoring United Nations Sustainable Development Goals (SDGs). Since bees play an essential role in the pollination ecosystem service, citizen science projects involving them have a high potential for attaining SDGs. By performing a systematic review of citizen science studies on bees, we assessed how these studies could contribute towards SDG reporting and monitoring, and also verified compliance with citizen science principles. Eighty eight studies published from 1992 to 2020 were collected. SDG 15 (Life on Land) and SDG 17 (Partnerships) were the most outstanding, potentially contributing to targets related to biodiversity protection, restoration and sustainable use, capacity building and establishing multi stakeholder partnerships. SDG 2 (Zero Hunger), SDG 4 (Quality Education), and SDG 11 (Sustainable Cities and Communities) were also addressed. Studies were found to produce new knowledge, apply methods to improve data quality, and invest in open access publishing. Notably, volunteer participation was mainly restricted to data collection. Further challenges include extending these initiatives to developing countries, where only a few citizen science projects are underway.

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The Software Defined Networking (SDN) paradigm can provide flexible routing and potentially support the different communication patterns that exist in Wireless Sensor Networks (WSN). However applying this paradigm to resource-constrained networks is not straightforward, especially if security services are a requirement. Existing SDN-based approaches for WSN evolved over time, addressing resource-constrained requirements. However, they do not integrate security services into their design and implementation. This work's main contribution is a secure-by-design SDN-based framework for Wireless Sensors Networks. Secure node admission and end-to-end key distribution to support secure communication are considered key services, which the framework must provide. We describe its specification, design, implementation, and experiments considering device and protocol constraints. The results indicate that our approach has achieved such goals with acceptable overheads up to medium sized networks.

Background Animal pollination is an important ecosystem function and service, ensuring both the integrity of natural systems and human well-being. Although many knowledge shortfalls remain, some high-quality data sets on biological interactions are now available. The development and adoption of standards for biodiversity data and metadata has promoted great advances in biological data sharing and aggregation, supporting large-scale studies and science-based public policies. However, these standards are currently not suitable to fully support interaction data sharing. Results Here we present a vocabulary of terms and a data model for sharing plant–pollinator interactions data based on the Darwin Core standard. The vocabulary introduces 48 new terms targeting several aspects of plant–pollinator interactions and can be used to capture information from different approaches and scales. Additionally, we provide solutions for data serialization using RDF, XML, and DwC-Archives and recommendations of existing controlled vocabularies for some of the terms. Our contribution supports open access to standardized data on plant–pollinator interactions. Conclusions The adoption of the vocabulary would facilitate data sharing to support studies ranging from the spatial and temporal distribution of interactions to the taxonomic, phenological, functional, and phylogenetic aspects of plant–pollinator interactions. We expect to fill data and knowledge gaps, thus further enabling scientific research on the ecology and evolution of plant–pollinator communities, biodiversity conservation, ecosystem services, and the development of public policies. The proposed data model is flexible and can be adapted for sharing other types of interactions data by developing discipline-specific vocabularies of terms.