35 research outputs found

    Optimal Resource Allocation in Ultra-low Power Fog-computing SWIPT-based Networks

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    In this paper, we consider a fog computing system consisting of a multi-antenna access point (AP), an ultra-low power (ULP) single antenna device and a fog server. The ULP device is assumed to be capable of both energy harvesting (EH) and information decoding (ID) using a time-switching simultaneous wireless information and power transfer (SWIPT) scheme. The ULP device deploys the harvested energy for ID and either local computing or offloading the computations to the fog server depending on which strategy is most energy efficient. In this scenario, we optimize the time slots devoted to EH, ID and local computation as well as the time slot and power required for the offloading to minimize the energy cost of the ULP device. Numerical results are provided to study the effectiveness of the optimized fog computing system and the relevant challenges

    Hydrometeorological and climatic control over lake phytoplankton: the importance of time scales

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    [eng] In the present thesis we focus on the two extremes of the wind speed – storms and atmospheric stilling – and analyse their impacts on lake environments and phytoplankton dynamics over short and long periods. As we realised the importance of the time scale in the context of our wind effect studies, we decided to have a closer look at other environmental data in the Lake VĂ”rtsjĂ€rv database addressing the questions how the variability in environmental factors (thermal, wind, light- and water-level regimes) and phytoplankton variables is partitioned among different time scales from days to decades and whether matching shares can help to determine the leading factors responsible for phytoplankton dynamics

    Post-soviet changes in nitrogen and phosphorus stoichiometry in two large non-stratified lakes and the impact on phytoplankton

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    The post-soviet period in Eastern Europe brought about fast changes in economy, land use, and environmental protection, whereas legacy effects of the previous era of heavy contamination continued emerging in the status of water bodies. In this paper, we analysed the post-soviet (since 1992) changes in catchment nutrient loadings and stoichiometry of nitrogen (N) and phosphorus (P) in two large non-stratified lakes in Estonia – VĂ”rtsjĂ€rv and Peipsi. The drastic reduction in the application of P-fertilisers and P discharges with wastewaters since the early 1990s reduced P loadings and increased N/P loading ratio into both lakes. However, it was hard to find clear evidence of reduced in-lake nutrient concentrations and improved water quality. In both lakes, water transparency constantly decreased and phytoplankton biomass increased. Over the years, the difference in N/P ratio between the two lakes became smaller while the large differences in the cyanobacterial community composition remained. Although common thresholds in nutrient ratios favouring N2-fixing species could be revealed in both lakes, the phytoplankton in VĂ”rtsjĂ€rv, strongly dominated by Limnothrix spp., remained mostly light-limited and the relationship with N/P stoichiometry was indirect. Random Forest analysis indicated an important role of light limitation in both lakes. Constantly lower levels of N in the deeper Lake Peipsi favoured N2-fixing species, which, as a paradox, became P-limited. As climate warming reinforces eutrophication phenomena in lakes by increasing internal nutrient loading and favouring bloom-forming cyanobacteria, more stringent measures would be needed to further limit nutrient loads (especially that of P) to lakes through improved wastewater treatment and increased efficiency of fertiliser application.Main financial support for EMU: European Union’s Horizon 2020 research and innovation programme Under the Marie SkƂodowska-Curie Action, Innovative Training Networks, European Joint Doctorates.Project name, acronym and grant number: Management of climatic extreme events in lakes and reservoirs for the protection of ecosystem services, MANTEL, grant agreement No 722518.Publication date and, if applicable, length of embargo period: 20.11.2020, no embargo period

    Phytoplankton responses to meteorological and hydrological forcing at decadal to seasonal time scales

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    One of the challenges for predicting global change effects on aquatic ecosystems is the vague understanding of the mechanisms of multiple controlling factors affecting phytoplankton dynamics at different time scales. Here we distinguish between hydrometeorological forcing of phytoplankton dynamics at time scales from days to decades based on a 54-year monthly phytoplankton time series from a large shallow Lake VĂ”rtsjĂ€rv (58 160N, 26 020E) in Estonia, combined with daily data on forcing factors— thermal-, wind-, light- and water-level regimes. By using variance partitioning with linear mixed effect modelling (LME), we found a continuum from the large dominant K-selected filamentous cyanobacteria with strongest decadal scale variation (8–30%) to r-selected phytoflagellates with large stochastic variability (80–96%). External forcing revealed strong seasonal variation (up to 80%), while specifically water level and wind speed had a robust decadal variation (8% and 20%, respectively). The effect of external variables was proportionally manifested in the time scales of phytoplankton variation. Temperature, with a clear seasonal variation, had no impact on the dominant cold tolerant filamentous cyanobacteria in Lake VĂ”rtsjĂ€rv. We found the LME as a reliable method for resolving the temporal cross-scale problem. It yielded quantitative results that matched our intuitive understanding of the dynamics of different variables.Supplementary Information The online version of this article (https://doi.org/10.1007/s10750-021-04594-x) contains supplementary material, which is available to authorised users.This study was funded by MANTEL ITN (Management of climatic extreme events in lakes and reservoirs for the protection of ecosystem services) through European Union’s Horizon 2020 research and innovation programme under the Marie SkƂodowska-Curie grant agreement No 722518 and by the Estonian Research Council grants (PRG1266 and PRG1167). We would also like to thank Estonian Environment Agency for the long-term data used on this study.This study was funded by MANTEL ITN (Management of climatic extreme events in lakes and reservoirs for the protection of ecosystem services) through European Union’s Horizon 2020 research and innovation programme under the Marie SkƂodowska-Curie grant agreement No 722518 and by the Estonian Research Council grants (PRG1266 and PRG1167). We would also like to thank Estonian Environment Agency for the long-term data used on this study

    SWIPT-based Real-Time Mobile Computing Systems: A Stochastic Geometry Perspective

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    Driven by the Internet of Things vision, recent years have seen the rise of new horizons for the wireless ecosystem in which a very large number of mobile low power devices interact to run sophisticated applications. The main hindrance to the massive deployment of low power nodes is most probably the prohibitive maintenance cost of battery replacement and the ecotoxicity of the battery production/end-of-life. An emerging research direction to avoid battery replacement is the combination of radio frequency energy harvesting and mobile computing (MC). In this paper, we propose the use of simultaneous information and power transfer (SWIPT) to control the distributed computation process while delivering power to perform the computation tasks requested. A real-time MC system is considered, meaning that the trade-off between the information rate and the energy harvested must be carefully chosen to guarantee that the CPU may perform tasks of given complexity before receiving a new control signal. In order to provide a system-level perspective on the performance of SWIPT-MC networks, we propose a mathematical framework based on stochastic geometry to characterise the rate-energy trade-off of the system. The resulting achievable performance region is then put in relation with the CPU energy consumption to investigate the operating conditions of real-time computing systems. Finally, numerical results illustrate the joint effect of the network densification and the propagation environment on the optimisation of the CPU usage

    Minimization of Sum Inverse Energy Efficiency for Multiple Base Station Systems

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    A sum inverse energy efficiency (SIEE) minimization problem is solved. Compared with conventional sum energy efficiency (EE) maximization problems, minimizing SIEE achieves a better fairness. The paper begins by proposing a framework for solving sum-fraction minimization (SFMin) problems, then uses a novel transform to solve the SIEE minimization problem in a multiple base station (BS) system. After the reformulation into a multi-convex problem, the alternating direction method of multipliers (ADMM) is used to further simplify the problem. Numerical results confirm the efficiency of the transform and the fairness improvement of the SIEE minimization. Simulation results show that the algorithm convergences fast and the ADMM method is efficient

    Storm impacts on phytoplankton community dynamics in lakes

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    In many regions across the globe, extreme weather events, such as storms, have increased in frequency, intensity and duration. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. For lake ecosystems, high winds and rainfall associated with storms are linked by short term runoff events from catchments and physical mixing of the water column. Although we have a well-developed understanding of how such wind and precipitation events alter lake physical processes, our mechanistic understanding of how these short-term disturbances 48 translate from physical forcing to changes in phytoplankton communities is poor. Here, we provide a conceptual model that identifies how key storm features (i.e., the frequency, intensity, and duration of wind and precipitation) interact with attributes of lakes and their watersheds to generate changes in a lake’s physical and chemical environment and subsequently phytoplankton community structure and dynamics. We summarize the current understanding of storm-phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions by generating testable hypotheses across a global gradient of lake types and environmental conditions.Fil: Stockwell, Jason D.. University of Vermont; Estados UnidosFil: Adrian, Rita. Leibniz Institute of Freshwater Ecology and Inland Fisheries; AlemaniaFil: Andersen, Mikkel. Dundalk Institute of Technology; IrlandaFil: Anneville, Orlane. Institut National de la Recherche Agronomique; FranciaFil: Bhattacharya, Ruchi. University of Missouri; Estados UnidosFil: Burns, Wilton G.. University of Vermont; Estados UnidosFil: Carey, Cayelan C.. Virginia Tech University; Estados UnidosFil: Carvalho, Laurence. Freshwater Restoration & Sustainability Group; Reino UnidoFil: Chang, ChunWei. National Taiwan University; RepĂșblica de ChinaFil: De Senerpont Domis, Lisette N.. Netherlands Institute of Ecology; PaĂ­ses BajosFil: Doubek, Jonathan P.. University of Vermont; Estados UnidosFil: Dur, GaĂ«l. Shizuoka University; JapĂłnFil: Frassl, Marieke A.. Griffith University; AustraliaFil: Gessner, Mark O.. Leibniz Institute of Freshwater Ecology and Inland Fisheries; AlemaniaFil: Hejzlar, Josef. Biology Centre of the Czech Academy of Sciences; RepĂșblica ChecaFil: Ibelings, Bas W.. University of Geneva; SuizaFil: Janatian, Nasim. Estonian University of Life Sciences; EstoniaFil: Kpodonu, Alfred T. N. K.. City University of New York; Estados UnidosFil: Lajeunesse, Marc J.. University of South Florida; Estados UnidosFil: Lewandowska, Aleksandra M.. Tvarminne Zoological Station; FinlandiaFil: Llames, Maria Eugenia del Rosario. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de Investigaciones BiotecnolĂłgicas. Universidad Nacional de San MartĂ­n. Instituto de Investigaciones BiotecnolĂłgicas; ArgentinaFil: Matsuzaki, Shin-ichiro S.. National Institute for Environmental Studies; JapĂłnFil: Nodine, Emily R.. Rollins College; Estados UnidosFil: NĂ”ges, Peeter. Estonian University of Life Sciences; EstoniaFil: Park, Ho-Dong. Shinshu University; JapĂłnFil: Patil, Vijay P.. US Geological Survey; Estados UnidosFil: Pomati, Francesco. Swiss Federal Institute of Water Science and Technology; SuizaFil: Rimmer, Alon. Kinneret Limnological Laboratory; IsraelFil: Rinke, Karsten. Helmholtz-Centre for Environmental Research; AlemaniaFil: Rudstam, Lars G.. Cornell University; Estados UnidosFil: Rusak, James A.. Ontario Ministry of the Environment and Climate Change; CanadĂĄFil: Salmaso, Nico. Research and Innovation Centre - Fondazione Mach; ItaliaFil: Schmitt, François. Laboratoire d’OcĂ©anologie et de GĂ©osciences; FranciaFil: Seltmann, Christian T.. Dundalk Institute of Technology; IrlandaFil: Souissi, Sami. Universite Lille; FranciaFil: Straile, Dietmar. University of Konstanz; AlemaniaFil: Thackeray, Stephen J.. Lancaster Environment Centre; Reino UnidoFil: Thiery, Wim. Vrije Unviversiteit Brussel; BĂ©lgica. Institute for Atmospheric and Climate Science; SuizaFil: Urrutia Cordero, Pablo. Uppsala University; SueciaFil: Venail, Patrick. Universidad de Ginebra; SuizaFil: Verburg, Piet. 8National Institute of Water and Atmospheric Research; Nueva ZelandaFil: Williamson, Tanner J.. Miami University; Estados UnidosFil: Wilson, Harriet L.. Dundalk Institute of Technology; IrlandaFil: Zohary, Tamar. Israel Oceanographic & Limnological Research; IsraelGLEON 20: All Hands' MeetingRottnest IslandAustraliaUniversity of Western AustraliaUniversity of AdelaideGlobal Lake Ecological Observatory Networ

    Storm impacts on phytoplankton community dynamics in lakes

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    In many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short-term runoff events from watersheds and physical mixing of the water column. In addition, lakes connected to rivers and streams will also experience flushing due to high flow rates. Although we have a well-developed understanding of how wind and precipitation events can alter lake physical processes and some aspects of biogeochemical cycling, our mechanistic understanding of the emergent responses of phytoplankton communities is poor. Here we provide a comprehensive synthesis that identifies how storms interact with lake and watershed attributes and their antecedent conditions to generate changes in lake physical and chemical environments. Such changes can restructure phytoplankton communities and their dynamics, as well as result in altered ecological function (e.g., carbon, nutrient and energy cycling) in the short- and long-term. We summarize the current understanding of storm-induced phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions across a gradient of lake types and environmental conditions.Peer reviewe

    HĂŒdrometeoroloogiliste ja kliimategurite mĂ”ju jĂ€rvede fĂŒtoplanktonile : ajaskaalade olulisus

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    A Thesis for applying for the degree of Doctor of Philosophy in Environmental Sciences and Applied Biology.VĂ€itekiri filosoofiadoktori kraadi taotlemiseks rakendusbioloogia erialal.Phytoplankton reflects changes in the environment and plays a vital role in biogeochemical cycles and the climate system. The thesis attempts to link the phytoplankton dynamics with the timing, intensity, and duration of the local forcing factors at different time scales. We highlight the influence of two extremes of the wind gradient – storms and atmospheric stilling, on lake environments and phytoplankton dynamics over short and long periods, several aspects of which are poorly understood. Until recently, atmospheric stilling as a climatic phenomenon has been largely overlooked in lakes studies. To fill this research gap, we focussed on a large shallow polymictic lake (VĂ”rtsjĂ€rv, Estonia), that was affected by a 30% decrease in average wind speed since 1996, and for which a long-term (54 years) phytoplankton and hydrometeorological database was available. Further, a contradiction between the continuous decrease in the lake’s nutrient loading and an increasing trend in phytoplankton biomass emerged as a topic of interest for this thesis. We summarise how storms interact with and alter the dynamic of phytoplankton communities. Further, we highlight to what extent this impact can change the ecological processes (e.g., nutrient, carbon, and energy cycling) within lakes and their environmental conditions in the short and long term. Using Nonmetric Multidimensional Scaling ordination of phytoplankton community composition for the years 1964–2017, we revealed three distinct periods with breaking points coinciding with abrupt changes in the wind and/or water level. We introduced a concept of "light niche," a newly discovered mechanism of meteorological control over phytoplankton in light-limited shallow lakes. Combining the monthly phytoplankton data with daily data on hydrometeorological forcing factors — thermal, light, wind, and water-level regimes and using variance partitioning with linear mixed effect modelling (LME), we found that (i) the external forcing factors relevant for each phytoplankton variable could be individualised by having a similar variance partitioning among time scales as the particular phytoplankton variable; (ii) with the largest seasonal variation component, the dominant shade-tolerant filamentous cyanobacteria were most affected by seasonal factors such as solar irradiance and water level; (iii) the LME was proven appropriate for resolving the temporal cross-scale issues.HĂŒdrometeoroloogiliste ja kliimategurite mĂ”ju jĂ€rvede fĂŒtoplanktonile: ajaskaalade olulisus FĂŒtoplankton peegeldab muutusi keskkonnas ja mĂ€ngib olulist rolli biogeokeemilises aineringes ning kliimasĂŒsteemis. Doktoritöö uurib seoseid fĂŒtoplanktoni dĂŒnaamika ning erinevates ajaskaalades (pĂ€evane, sesoonne, aastatevaheline) toimivate tegurite ajastuse, intensiivsuse ja kestusega. Töös tuuakse esile kahe vastandliku tuulte olukorra – tormide ja tuulevaikuse mĂ”ju jĂ€rvekeskkonnale ja fĂŒtoplanktoni dĂŒnaamikale, mille mitmed aspektid on seni vĂ€he uuritud. Kuni viimase ajani on jĂ€rveuuringutes suuresti tĂ€helepanuta jÀÀnud tuulte nĂ”rgenemise kui kliimanĂ€htuse mĂ”ju. Selle uurimislĂŒnga tĂ€itmiseks keskendusime suurele madalale polĂŒmiktilisele VĂ”rtsjĂ€rvele, mida mĂ”jutavate tuulte keskmine kiirus on alates 1996. aastast vĂ€henenud 30% ning mille kohta on olemas pikaajaline (54 aastat) fĂŒtoplanktoni ja hĂŒdrometeoroloogia andmebaas. Tuulte mĂ”ju uurimine vĂ”imaldas selgitada ka nĂ€ilist vastuolu jĂ€rve toiteainete hulga pideva vĂ€henemise ja fĂŒtoplanktoni biomassi kasvutrendi vahel. Töö esimene osa vĂ”tab kokku teadmised tormide mĂ”ju kohta jĂ€rvede fĂŒtoplanktonikoosluste dĂŒnaamikale. Tuuakse vĂ€lja, kuidas tormid mĂ”jutavad ökoloogilisi protsesse jĂ€rvedes (nt toiteainete kĂ€ttesaadavust, sĂŒsiniku- ja energiaringet) ning nende kaudu fĂŒtoplanktoni elutingimusi lĂŒhi- ja pikaajalises lĂ”ikes. Aastate 1964–2017 VĂ”rtsjĂ€rve fĂŒtoplanktonikoosluse mitmemÔÔtmeline analĂŒĂŒs eristas koosluse muutustes kolm perioodi, mille murdepunktid langesid kokku tuule ja/vĂ”i veetaseme jĂ€rskude muutustega. Nende seoste pĂ”hjal sĂ”nastati nn "valgusniĆĄi" kontseptsioon, mis kirjeldab varem tundmatut fĂŒtoplanktoni meteoroloogilise kontrolli mehhanismi hĂ€guse veega madalates jĂ€rvedes. Kasutades enam kui poole sajandi vĂ€ltel kogutud igakuiseid fĂŒtoplanktoni andmeid ja kombineerides neid igapĂ€evaste andmetega hĂŒdrometeoroloogiliste tegurite (temperatuur, valgus, tuul ja veetase) kohta uuriti lineaarsete segamudelite abil muutlikkuse jaotumise erinevate ajaskaalade vahel. Leiti, et fĂŒtoplanktoni erinevate rĂŒhmade jaoks olulisi vĂ€listegureid saab kindlaks teha selle jĂ€rgi, et vastava rĂŒhma ja seda mĂ”jutavate tegurite muutlikkus jaotub erinevate ajaskaalade vahel sarnastes proportsioonides. Nii mĂ”jutasid suurima sesoonse muutlikkuse komponendiga tsĂŒanobaktereid enim sesoonsed tegurid, flagellaatide puhul, sarnaselt tuulega, ulatus aga juhusliku ja lĂŒhiajalise varieeruvuse komponent 80%-ni. KokkuvĂ”ttes osutusid lineaarsed segamudelid sobivaks tööriistaks erinevates ajaskaalades toimivate tegurite mĂ”ju uurimiseks.Publication of this thesis is supported by the Estonian University of Life Sciences
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