Enhanced two-phase contention window MAC protocol for wireless sensor networks applications

This work was supported by the PhD FCT grant SFRH/BD/38356/2007 and IT grant PEst-OE/EEI/ LA0008/2011. I also acknowledge several projects where I was involved in: COST IC1004, COST 2100, MobileMAN, OPPORTUNISTIC-CR, PROENERGY-WSN, Smart-Clothing, and INSYSMNowadays, the user of Wireless Sensor Networks (WSNs) is becoming more and more demanding in terms of choice and diversity of applications. As a consequence, as the diversity of applications continues to grow there is a need to identify and classify the set of detailed characterization parameters that facilitates to sketch up a taxonomy for WSN applications. The proposed taxonomy identi es the services offered by each application makes a tool available to better understand the services and requirements of each application, along with a holistic overview of the WSN proposed application taxonomy. The research also involved the actual development of WSN applications within different research projects, namely in the elds of healthcare (Smart Clothing), civil engineering structure monitoring (INSYSM) and precision agriculture. Different medium access control mechanisms employ different collision avoidance schemes to cope with packet collision and retransmission, trading-off complexity, energy inef ciency and control of packet overhead. In particular, this PhD thesis addresses the study the packet collision probability for a MAC protocol that employs a collision avoidance mechanism with two contention window and consequent proposal of a model for the collision probability. Simulation results validate the model for saturated traf c. For unsaturated traf c and with a small number of nodes, the accuracy of the model is limited by numerical rounding. It is shown that, by using our analytical model, we have been able to obtain performance metrics such as network throughput and average service time for the successful transmissions. In addition, the Enhanced Reliability Decision Algorithm in the physical layer has been proposed. The frame capture effect (FC) feature has been implemented in the IEEE 802.15.4 compliant physical layer of the MiXiM framework. The proposed decision algorithm utilizes the Signal to Noise-plus-Interference ratio (SNIR) and the size of the packet to guarantee the delivery with certain reliability to the MAC layer, of a packet received at the PHY layer. A gain of more than 10 % has been achieved in the delivery ratio. Promising results have also been obtained for the SCP-MAC protocol with the FC effect enabled, for different values of reliability. As one of the main contributions of this thesis, an innovative ef cient multi-channel MAC protocol, based on SCP-MAC, was proposed, the so-called Multi-Channel Scheduled Channel Polling (MC-SCP-MAC) protocol. The in uential range concept, denial channel list (which considers the degradation metric of each slot channel), extra resolution phase algorithm and frame capture effect have been explored to achieve the maximum performance in terms of delivery ratio and energy consumption. It has been shown MC-SCP-MAC outperforms SCP-MAC and MC-LMAC in denser scenarios, with improved throughput fairness. Considering the in uential range concept reduces the redundancy level in the network facilitating to reduce the energy consumption whilst decreasing the latency. The conclusions from this research reveal the importance of an appropriate design for the MAC protocol for the desired WSN application. Depending on the objective or mission of the WSN application, different protocols are required. Therefore, the overall performance of a WSN application certainly depends on the appropriate development and application of the appropriate communication protocols (e.g., MAC, network layer)

Impact of using CSS PHY and RTS/CTS Combined with Frame Concatenation in the IEEE 802.15.4 Non-beacon Enabled Mode Performance

This paper studies the performance improvement of the IEEE 802.15.4 non-beacon-enabled mode originated by the inclusion of the Request-To-Send/Clear-To-Send (RTS/CTS) handshake mechanism resulting in frame concatenation. Under IEEE 802.15.4 employing RTS/CTS, the backoff procedure is not repeated for each data frame sent but only for each RTS/CTS set. The maximum throughput and minimum delay performance are mathematically derived for both the Chirp Spread Spectrum and Direct Sequence Spread Spectrum Physical layers for the 2.4 GHz band. Results show that the utilization of RTS/CTS significantly enhances the performance of IEEE 802.15.4 applied to healthcare in terms of bandwidth efficiency.This work was supported by FCT/MCTES through national funds and when applicable co-funded EU funds under the project UIDB/50008/2020, COST CA20120 INTERACT, Fundación Carolina and Grupo Tordesillas short stay grant in UC3M, SNF Scientific Exchange - AISpectrum (project 205842), ORCIP (22141- 01/SAICT/2016) and TeamUp5G. TeamUp5G project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie project number 813391.info:eu-repo/semantics/acceptedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Characterisation of microbial attack on archaeological bone

As part of an EU funded project to investigate the factors influencing bone preservation in the archaeological record, more than 250 bones from 41 archaeological sites in five countries spanning four climatic regions were studied for diagenetic alteration. Sites were selected to cover a range of environmental conditions and archaeological contexts. Microscopic and physical (mercury intrusion porosimetry) analyses of these bones revealed that the majority (68%) had suffered microbial attack. Furthermore, significant differences were found between animal and human bone in both the state of preservation and the type of microbial attack present. These differences in preservation might result from differences in early taphonomy of the bones. © 2003 Elsevier Science Ltd. All rights reserved