Resource Contention Research Articles

Methods for Measuring the Impact of Sustainable Tourism Development on Climate and Environment

Climate and environmental change is a growing topic in the post-Covid-1, when tourism growth is recovering. Tourism is a significant polluter of the environment and a rapid response to climate change is needed. Methods for assessing the climate and environmental impact of sustainable tourism development help to measure and communicate the environmental impact of tourism activities, but they are difficult to select and often lack indicators. The aim of the study was to choose methods for assessing the climate and environmental impact of sustainable tourism development in the context of Latvia. The study was based on the analysis of scientific literature, the grouping of methods for assessing the climate and environmental impact of sustainable tourism development according to their functional characteristics i.e. "preventive", "protective", "estimating" and "carbon emission determining" methods. A multi-criteria decision-making method was used for the selection of evaluation methods - Analytical hierarchy process with empirical analysis (AHA) of the obtained weights. By summarising the environmental and climate indicators available for a specific region of Latvia regarding the impact of tourism and experts evaluating the obtained results, the most suitable method for evaluating the impact of tourism development on the climate and environment is the Tourism value chain for low carbon content and efficient use of resources. However, the authors' recommendation for researchers: 1) when evaluating the impact of tourism development on the climate and environment, the choice of method ought to be based on evaluation indicators available for a specific study; 2) in research combinations of sets of "evaluative" and "carbon emission determining” methods should be used.

CARIn: Constraint-Aware and Responsive Inference on Heterogeneous Devices for Single- and Multi-DNN Workloads

The relentless expansion of deep learning (DL) applications in recent years has prompted a pivotal shift towards on-device execution, driven by the urgent need for real-time processing, heightened privacy concerns, and reduced latency across diverse domains. This paper addresses the challenges inherent in optimising the execution of deep neural networks (DNNs) on mobile devices, with a focus on device heterogeneity, multi-DNN execution, and dynamic runtime adaptation. We introduce CARIn , a novel framework designed for the optimised deployment of both single- and multi-DNN applications under user-defined service-level objectives (SLOs). Leveraging an expressive multi-objective optimisation (MOO) framework and a runtime-aware sorting and search algorithm ( RASS ) as the MOO solver, CARIn facilitates efficient adaptation to dynamic conditions while addressing resource contention issues associated with multi-DNN execution. Notably, RASS generates a set of configurations, anticipating subsequent runtime adaptation, ensuring rapid, low-overhead adjustments in response to environmental fluctuations. Extensive evaluation across diverse tasks, including text classification, scene recognition, and face analysis, showcases the versatility of CARIn across various model architectures, such as Convolutional Neural Networks (CNNs) and Transformers, and realistic use cases. We observe a substantial enhancement in the fair treatment of the problem’s objectives, reaching 1.92 × when compared to single-model designs, and up to 10.69 × in contrast to the state-of-the-art OODIn framework. Additionally, we achieve a significant gain of up to 4.06 × over hardware-unaware designs in multi-DNN applications. Finally, our framework sustains its performance while effectively eliminating the time overhead associated with identifying the optimal design in response to environmental challenges.

Analysis and Research of Illustration Teaching Design in Applied Universities under Digital Environment

With the continuous development of digital technology, the field of education is also facing unprecedented challenges and opportunities. The purpose of this study is to explore the practice and application of illustration instructional design in applied colleges and universities under the digital environment. Firstly, through in-depth analysis of the impact of digital environment on education and the trend of digital education in applied colleges and universities, the importance and role of digital technology in teaching is highlighted. Then, combining with the characteristics and needs of illustration teaching, this paper puts forward the theoretical and practical framework of illustration instructional design adapted to the digital environment, and emphasizes that instructional design should be closely combined with practice and pay attention to the cultivation of students' practical application ability. Further, through the analysis of specific cases, the paper discusses the reform and construction of illustration course under the digital environment, including the optimization of course content, the development and utilization of digital teaching resources, etc. Finally, the relevant cases are evaluated, and the practical experience and enlightenment of illustration instructional design in the digital environment are summarized. The research results show that illustration instructional design under the digital environment should pay attention to innovation and practice, and actively use digital technology to provide students with more diversified learning experience, so as to cultivate their innovative ability and practical ability.

Developing A Novel Load Balancing Approach for Mitigating Resource Contention in Multi-Cloud Environments

In the rapidly evolving landscape of cloud computing, the management of resources and load balancing across multiple cloud environments presents significant challenges. This paper proposes a novel approach to address resource contention issues in multi-cloud environments through the development of an innovative load-balancing mechanism. By leveraging advanced algorithms and dynamic resource allocation strategies, our approach aims to effectively distribute workloads across diverse cloud infrastructures, thereby optimizing resource utilization and mitigating contention. Through extensive experimentation and evaluation, we demonstrate the effectiveness and efficiency of our proposed solution in enhancing performance and resilience in multi-cloud deployments. Our findings underscore the importance of tailored load-balancing mechanisms in enabling scalable and reliable operations in complex cloud environments.

Divvying up the pie: Tissue nutrient content is related to its parasite load.

The nutrient content of host resources can influence the abundance of parasites within an ecosystem, but linking specific nutrients in a host to the abundance of different parasite taxa remains a challenge. Here, we work to forge this link by quantifying the relationship between the nutrient content of specific infection sites and the abundance of multiple parasite taxa within the digestive tract of largemouth bass (Micropterus salmoides) collected from the Mississippi River. To generate a mechanistic understanding of these relationships, we tested four basic predictions: (1) the nutrient content of different host tissues (infection sites) varies within and across hosts, (2) the nutrient content of parasite genera differs from that of their host tissue(s), (3) the nutrient content of parasite genera differ from one another and (4) the nutrient content of host tissues is related to the nutrient content and abundance of parasite genera. We found support for each of these predictions. We found stoichiometric differences between the digestive tissues we examined. We also found that across hosts, intestine and pyloric caeca C:N ratios increased and %N decreased with fish condition factor. Both of the actively feeding parasitic genera we measured had lower C:N ratios compared to both their host tissue and other encysted/non-reproductive genera, suggesting the potential for N limitation of these parasites in the intestines or pyloric caeca of hosts. Consistent with this possibility, we found that the total number of actively feeding parasitic worms in the pyloric caeca increased with that tissue's N:P ratio (but was not related to host condition factor). Our results suggest that parasites encounter significant variation in nutrient content within and across hosts and that this variation may influence the abundance of actively feeding parasites. This work highlights the need for additional empirical comparisons of parasite stoichiometry across tissues and individual hosts.

Online resources as a source of information for exercise and physical activity in solid organ transplant recipients.

Exercise training post-transplant has been shown to improve physical function and quality of life in solid organ transplant (SOT) recipients. Online resources in the form of websites and videos are commonly used to provide education and instruction on exercise and physical activity in SOT; however, the content and quality of these online resources has not been evaluated. The first 200 websites and videos identified on Google and YouTube using the English search term "exercise and physical activity in solid organ transplantation" were analyzed. Website and video content was evaluated based on 25 key components of exercise and physical activity in SOT as described in established exercise program recommendations. Website and video quality was determined using DISCERN, Global Quality Scale (GQS), and Patient Education Materials and Assessment Tool (PEMAT; threshold for which material is deemed understandable or actionable is >70%). Parametric and non-parametric tests were used to assess website and video characteristics, content, and quality metrics. Forty-nine unique SOT websites (n = 15) and videos (n = 34) were identified, with the two most common categories being foundation/advocacy organizations and scientific resources. The average reading grade level of websites was 13 ± 3. Website and video content scores varied significantly (websites 11.3 ± 6.4; videos 8.4 ± 5.3). DISCERN total score and GQS score were low (median range for DISCERN 2.5-3.0; median for GQS 2.0 for both websites and videos, out of 5). PEMAT understandability and actionability scores were also low across websites and videos (mean range 57%-67% and 47%-65%, respectively). Foundation/advocacy websites had higher content and quality scores compared to scientific organizations and news/media articles. To our knowledge, this is the first comprehensive assessment of online content and quality of website and video resources on physical activity and exercise in adult SOT recipients. There were a limited number of online English patient-directed resources related to physical activity in SOT, most of which only partly captured items outlined in consensus exercise program recommendations and were of low quality and understandability and actionability. This work provides important insight to the English-speaking transplant community on the current state of online exercise health information and provides future direction for resource development.

大学日语课程可持续发展路径探析

Along with the strengthening of globalization trend, the concern of the education sector for the sustainable development of higher education is gradually heating up. The foreign language education in colleges and universities represented by College Japanese has long been suffering from such problems as backward teaching concepts and teaching modes, outdated content of teaching resources, and imperfect assessment system, which affects the sustainable development of the course itself and talent cultivation. Aiming at the above problems, a blended teaching mode based on sustainable development goals was constructed and a one-year teaching practice was carried out. The results of the questionnaire survey and performance analysis show that the blended teaching mode is significantly better than the traditional teaching mode in improving students’ classroom satisfaction, interest and demand satisfaction, learning motivation, classroom participation, learning motivation continuity, learning interest, and teacher-student relationship, etc. At the same time, it significantly improves the students’ language application ability, which provides an empirical reference for the sustainable development of foreign language education in colleges and universities.

Understanding stoichiometric constraints on growth using resource use efficiency imbalances

Growth is a function of the net accrual of resources by an organism. Energy and elemental contents of organisms are dynamically linked through their uptake and allocation to biomass production, yet we lack a full understanding of how these dynamics regulate growth rate. Here, we develop a multivariate imbalance framework, the growth efficiency hypothesis, linking organismal resource contents to growth and metabolic use efficiencies, and demonstrate its effectiveness in predicting consumer growth rates under elemental and food quantity limitation. The relative proportions of carbon (%C), nitrogen (%N), phosphorus (%P), and adenosine triphosphate (%ATP) in consumers differed markedly across resource limitation treatments. Differences in their resource composition were linked to systematic changes in stoichiometric use efficiencies, which served to maintain relatively consistent relationships between elemental and ATP content in consumer tissues and optimize biomass production. Overall, these adjustments were quantitatively linked to growth, enabling highly accurate predictions of consumer growth rates.

ІННОВАЦІЙНІ ПІДХОДИ У ПІДГОТОВЦІ ПЕДАГОГІЧНИХ ТА КЕРІВНИХ КАДРІВ ОСВІТИ ЗАСОБАМИ ІНФОРМАЦІЙНИХ ТЕХНОЛОГІЙ

The article proves the importance of using modern information technologies in the training of pedagogical and management staff in the sphere of education. The meaning of information technologies in the process of forming the head’s of the educational institution information culture is defined. The analysis of the peculiarities of its formation is given. New applications of information technologies adapted to work in educational institutions and the possibility of their successful implementation are presented. The article suggests that information processes are aimed at forming a unique open educational environment, ensuring its accessibility, providing opportunities for updating, developing and improving the quality and efficiency of educational services. The use of the information technology approach is based on the LLL (lifelong learning) paradigm that implies the concept of continuous education, its internationalization and diversification. The efficiency of the educational process in the training of teachers and heads of educational institutions depends on the high-quality content of electronic educational resources. Electronic resources are components of the educational process and important parts of the information and educational environment. The most important directions of its development are content, technical support and maintenance of information sites, monitoring the level of information and professional competence of pedagogical workers, providing informational assistance to teachers in creating individual sites, improving their computer and technical literacy. The use of new models, information and communication technologies in educational institutions makes possible to create a unique information environment where educational regulatory documents, educational and methodical materials, monographs, tutorials are placed, which altogether can help pedagogical workers to improve the educational process and increase the level of pedagogical skills. The use of educational information and communication technologies in terms of innovative models implies the use of electronic lecturers, simulators, textbooks, encyclopedias; development of situational role-playing and intellectual games using artificial intelligence; modeling of different processes and phenomena; distance learning; conducting interactive educational teleconferences; construction of systems of control and verification of students' knowledge and skills (use of control test programs); creation and maintenance of educational institutions websites; creating presentations; carrying out design and research activities.

Functional Analysis of English Carriers and Related Resources of Cultural Communication in Internet Media

Abstract In the Internet intelligent teaching platform, students’ demand for English cultural content is increasingly obvious. To help students quickly locate the overall content of resources in online autonomous learning, this study constructs a video annotation model for online teaching. This method classifies text by designing an optimized Bidirectional Encoder Representation from the Transformers model and designs a Text Rank keyword extraction model that integrates external knowledge and semantic feature weights. The extraction of knowledge points contained in audio and video resources can be realized. In the experimental data set, a relatively complete video content summary could be obtained by combining the first three sentences with the last two sentences. The F1 value of the classification model was up to 91.3%. In addition, the BERT-T model proposed in this article had the best effect on the experiment. Compared with the original BERT model, the macro-F1 was 0.8% higher and 0.5% higher than the Ro BERTA model. In the keyword extraction experiment, B-Text Rank was 2.19 and 2.85% higher than the traditional Text Rank in the two datasets. The experiment shows that the BERT-Text Rank network resource annotation model has excellent application performance in English online autonomous teaching and could guide students to learn.

Data-driven modeling of reconfigurable multi-accelerator systems under dynamic workloads

Reconfigurable multi-accelerator systems used as computing offloading platforms in edge-cloud continuum scenarios usually have to deal with highly dynamic workloads and operating conditions. In order to properly take advantage of their parallel processing capabilities and increase execution performance for a given workload, these systems need to continuously adapt their configuration (i.e., number and type of accelerators) at run time. When working at the edge, additional requirements such as energy efficiency must be also met. In this paper, Machine Learning techniques are applied to extract predictive models of the execution of different combinations of hardware accelerators on a reconfigurable multi-accelerator platform, aiming at satisfying the previously mentioned continuous optimization needs. One of the key benefits of the proposed approach is that its data-driven models can transparently estimate the impact of the complex interactions between hardware accelerators due to run-time resource contention among them and with the rest of the system, as opposed to traditional modeling approaches that cannot include that information in an easy and scalable way (e.g., analytical models). The proposed models are complemented with a complete infrastructure to generate, execute and monitor dynamic workloads in FPGA-based systems. This infrastructure has been used to (i) quantitatively analyze resource contention in reconfigurable multi-accelerator systems and (ii) produce the training and evaluation datasets for the ML-based models using annotated power consumption and execution performance traces. Experimental results obtained with a reconfigurable multi-accelerator platform based on the ARTICo3 framework running the MachSuite benchmarks show that the proposed modeling approach is highly effective, with a relative prediction error of less than 5% on average for both power consumption and execution performance. Result also show that the ML-based models achieve high accuracy levels when predicting the impact of resource contention and accelerator interaction on both metrics, with a mean relative prediction error of less than 0.6% and a standard deviation below 4.7% for the worst case.

Investigation into the mechanical and thermal properties of lightweight mortar using commercial beads or recycled expanded polystyrene

Abstract The addition of recycled expanded polystyrene (EPS) in cement mortar is a key to enhancing buildings’ insulation and reducing energy consumption. The main objective of this study is to improve the thermal conductivity of lightweight mortar (LWM) by using the EPS. Also, to overcome the segregation problem when increasing the EPS proportion by more than 70% by volume, slurry sand was used. To achieve that, more EPS waste is required to produce an LWM with less cement and natural resources (sand) content. The effect of different percentages and particle sizes of the EPS either virgin or grated on the workability, density, compressive, flexural strength, and thermal conductivity were investigated by using the EPS with the range of 0, 75, 80, and 85% by mortar’s volume. The results exposed that LWM with grated EPS waste had greater physical and mechanical properties than with EPS beads because it has low void content and suitable distribution. In addition, mortar with 85% grated EPS had similar properties than that with 75% EPS beads. Accordingly, EPS should be grinded to increase its volumetric percentage in the mixture. Also, electron microscopy was used as an integral technique to study surface morphology between mortar components and the EPS.

D 2 Comp: Efficient Offload of LSM-tree Compaction with Data Processing Units on Disaggregated Storage

LSM-based key-value stores suffer from sub-optimal performance due to their slow and heavy background compactions. The compaction brings severe CPU and network overhead on high-speed disaggregated storage. This paper further reveals that data-intensive compression in compaction consumes a significant portion of CPU power. Moreover, the multi-threaded compactions cause substantial CPU contention and network traffic during high-load periods. Based on the above observations, we propose fine-grained dynamical compaction offloading by leveraging the modern Data Processing Unit (DPU) to alleviate the CPU and network overhead. To achieve this, we first customized a file system to enable efficient data access for DPU. We then leverage the Arm cores on the DPU to meet the burst CPU and network requirements to reduce resource contention and data movement. We further employ dedicated hardware-based accelerators on the DPU to speed up the compression in compactions. We integrate our DPU-offloaded compaction with RocksDB and evaluate it with NVIDIA’s latest Bluefield-2 DPU on a real system. The evaluation shows that the DPU is an effective solution to solve the CPU bottleneck and reduce data traffic of compaction. The results show that compaction performance is accelerated by 2.86 to 4.03 times, system write and read throughput is improved by up to 3.2 times and 1.4 times respectively, and host CPU contention and network traffic are effectively reduced compared to the fine-tuned CPU-only baseline.

Assessing the Cloud-RAN in the Linux Kernel: Sharing Computing and Network Resources.

Cloud-based Radio Access Network (Cloud-RAN) leverages virtualization to enable the coexistence of multiple virtual Base Band Units (vBBUs) with collocated workloads on a single edge computer, aiming for economic and operational efficiency. However, this coexistence can cause performance degradation in vBBUs due to resource contention. In this paper, we conduct an empirical analysis of vBBU performance on a Linux RT-Kernel, highlighting the impact of resource sharing with user-space tasks and Kernel threads. Furthermore, we evaluate CPU management strategies such as CPU affinity and CPU isolation as potential solutions to these performance challenges. Our results highlight that the implementation of CPU affinity can significantly reduce throughput variability by up to 40%, decrease vBBU's NACK ratios, and reduce vBBU scheduling latency within the Linux RT-Kernel. Collectively, these findings underscore the potential of CPU management strategies to enhance vBBU performance in Cloud-RAN environments, enabling more efficient and stable network operations. The paper concludes with a discussion on the efficient realization of Cloud-RAN, elucidating the benefits of implementing proposed CPU affinity allocations. The demonstrated enhancements, including reduced scheduling latency and improved end-to-end throughput, affirm the practicality and efficacy of the proposed strategies for optimizing Cloud-RAN deployments.

The Spatiotemporal Variation Characteristics and Influencing Factors of Green Vegetation in China

Green vegetation is one of the main objects of ecological environment restoration and protection, objectively reflecting the quality of regional ecological environments. Studying its spatial distribution characteristics is of great significance to the formulation of ecological environment restoration policies. Based on data on urban green vegetation in China from 2000 to 2022, this study attempts to analyze the destruction and protection patterns of urban green vegetation in China from the perspectives of total changes in green vegetation contraction and growth and spatial evolution characteristics and trends, and it explores the driving factors affecting the change in green vegetation area. The results show the following: (1) Green vegetation growth and contraction occurred alternately in China from 2000 to 2022. Vegetation contraction showed a “point–line–plane” evolution pattern, forming a contraction stage of point-like aggregation, linear series, and planar spread. Vegetation growth has always presented a frontal pattern. (2) The growth and contraction of green vegetation in China showed a north–south differentiation phenomenon. The vegetation contraction phenomenon spread in the Central Plains urban agglomeration and its surrounding areas and showed an expanding trend. The growth trend is obviously moving northward, mainly concentrated in Inner Mongolia, Ningxia, Gansu, Xinjiang, and other northern provinces, which also coincides with the key ecological restoration policies in northern China in recent years. (3) City scale, economic level, population scale, agro-industrial structure, and water resources content have significant effects on the spatial distribution of green vegetation.

Information and library services for library users: Innovative approaches and vectors modifications

The relevance lies in the in-depth analysis of the problems of development and transformation of library and information services, as well as in the changed user requests and information needs caused by the information development of society. The purpose is to explore the benefits of using the latest technologies and services in information services in the context of research by Ukrainian library professionals; to analyse the dynamics of library development and its modification in the system of user service. The study used general scientific methods (analysis, synthesis, generalisation) and approaches: socio-cultural, socio-communicative, and systemic. The current challenges of informatisation of society and the rapid expansion of the volume and content of information resources raise the issue of revising the methods of work in the field of reference and bibliographic services for libraries. This requires the development of scientific principles of modern activities of reference and bibliographic services aimed at providing information to users and based on a systematic approach to the formation, organisation and use of reference and information resources. Also, in the study of trends in the use of cloud services as an innovative tool in libraries in the era of digitalisation, which has become an effective means of expanding the possibility of remote access to library collections, resources, promoting the storage and analysis of data for more convenient user service. The results of the study may be important for employees of methodological and bibliographic departments, Internet centers in libraries, and can also serve as a basis for a more detailed study of specific aspects of this topic by library practitioners, teachers and students studying in information and library specialty programs. They can also be useful for replenishing the information base on the organisation and development of reference and bibliographic services in libraries

A comprehensive evaluation of online inhaler use techniques for obstructive airway disease

BackgroundPulmonary inhaler therapy is a core treatment modality for >600 million individuals affected by obstructive airways disease globally. Poor inhaler technique is associated with reduced disease control and increased health care utilization; however, many patients rely on the internet as a technical resource. This study assesses the content and quality of online resources describing inhaler techniques. MethodsA Google search was conducted in April 2023 capturing the top 5 search results for 12 common inhaler devices. Websites were compared to product monographs for preparation/first use, inhalational technique, and post-usage/device care. They were also assessed using accepted quality metrics (GQS, DISCERN, JAMA Benchmark scores) and clinically relevant aspects based on the literature and consensus statements. ResultsWebsites regularly excluded critical steps important for proper inhaler technique. They performed best on information related directly to inhalation technique (average median score 78%), whereas steps related to preparation/first use (58%) or post-usage/device care (50%) were less frequently addressed. Median GQS, DISCERN, and JAMA Benchmark scores were 3 [IQR 3–4], 3 [IQR 2–4], and 1 [IQR 1–3], respectively. Clinically relevant factors were only addressed in about one-fifth of websites with no websites addressing smoking cessation, environmental considerations, or risk factors for poor technique. ConclusionsThis study highlights gaps in online resources describing inhaler technique, particularly related to preparation/first use and post-usage/device care steps. Clinically relevant factors were rarely addressed across websites. Improvements in these areas could lead to enhanced inhaler technique and clinical outcomes.

Pharmacy Students’ Perception of the Content and Delivery of Drug Information Training: A Mixed-Methods Study

ObjectiveTo explore the pharmacy students’ perception of the content and pedagogical strategies used for the delivery of drug information (DI) training. MethodsAn explanatory sequential mixed-methods study was conducted among BSc Pharmacy and PharmD students at the College of Pharmacy, Qatar University. The first phase consisted of a quantitative cross-sectional survey using a 34-item pretested questionnaire. The Donabedian framework guided the development of the questionnaire. This was followed by a phenomenological qualitative phase that was conducted based on the result of the first phase. Descriptive statistics and thematic content analysis were used for data analyses. ResultsThe completion and usable rates were 88.7% (102 of 115) and 91.2% (93 of 102) respectively. The online resources used for the delivery of DI and the progressive structuring from year 1 to 4 were reported to be adequate by a majority of the respondents (93.55%). Ninety percent of the students opined that the use of simulation-based assessments improved their integration of the theoretical and practical aspects, and their preparedness to apply the DI concepts in practice. However, 20% of the participants reported inconsistency of the DI curricular content with some practices encountered during their experiential learning exposures. The themes identified from the focus group discussion included the perceived value and skills acquired from the DI content, availability and currency of DI resources, students’ preparedness, curricular structuring of DI content, and reflection on and recommendations to improve DI coverage and delivery. ConclusionThe curricular structuring of the DI content across varieties of relevant undergraduate pharmacy courses from the lower to higher professional years and its focus on the progressive development of DI-related competencies appeared to have enhanced the students’ perception of the relevance, appropriateness, and utility of the content, resources, and pedagogical strategies used for the delivery of DI education at the undergraduate level.

Multi-dimensional distribution network voltage collaborative estimation method using wavelet transform based multiscale analysis

Conventional methods for distribution network voltage estimation may encounter resource contention issues when performing noise reduction, harmonic calculation, and singular inspection. To address such problems, this study presents a wavelet transform based multiscale analysis (WT-MSA) method for achieving multifunctional integration of multi-objective collaborative voltage estimation in distribution networks. First, the basic concepts of multiscale space and wavelet function are described, mainly used for decomposing the original signal under different scales of wavelet spaces and then conducting filtering. Second, a voltage coordinated estimation method is established, with a marginal threshold function employed as the criterion for correcting wave coefficients. Following that, an interpolation-energy based method for gradually estimating both fundamental and harmonic effective information is developed. Finally, three different types of Cases are set up for simulation verification, demonstrating that the proposed method meets the accuracy requirements for voltage estimation in distribution networks.

A comprehensive research on open surface drinking water resources in Istanbul using remote sensing technologies.

Istanbul is a megacity with a population of 15.5 million and is one of the fastest-growing cities in Europe. Due to the rapidly increasing population and urbanization, Istanbul's daily water needs are constantly increasing. In this study, eight drinking water basins that supply water to Istanbul were comprehensively examined using remote sensing observations and techniques. Water surface area changes were determined monthly, and their relationships with meteorological parameters and climate change were investigated. Monthly water surface areas of natural lakes and dams were determined with the Normalized Difference Water Index (NDWI) applied to Sentinel-2 satellite images. Sentinel-1 Synthetic Aperture Radar (SAR) images were used in months when optical images were unavailable. The study was carried out using 3705 optical and 1167 SAR images on the Google Earth Engine (GEE) platform. Additionally, to determine which areas of water resources are shrinking, water frequency maps of the major drinking water resources were produced. Land use/land cover (LULC) changes that occurred over time were determined, and the effects of the increase in urbanization, especially on drinking water surface areas, were investigated. ESRI LULC data was used to determine LULC changes in watersheds, and the increase in urbanization areas from 2017 to 2022 ranged from 1 to 91.43%. While the basin with the least change was in Istranca, the highest increase in the artificial surface was determined to be in the Büyükçekmece basin with 1833.03ha (2.89%). While there was a 1-12.35% decrease in the surface areas of seven water resources from 2016 to 2022, an increase of 2.65-93% was observed in three water resources (Büyükçekmece, Sazlıdere, and Elmalı), each in different categories depending on their size. In the overall analysis, total WSA decreased by 62.33ha from 2016 to 2022, a percentage change of 0.70%. Besides the areal change analysis, the algae contents of the drinking water resources over the years were examined for the major water basins using the Normalized Difference Chlorophyll Index (NDCI) and revealed their relationship with meteorological factors and urbanization.