Semi-arid savannah rangelands are diverse environments (in terms of species) that play an important role in sustaining biodiversity and providing ecosystem services. However, the emergence of non-native species, as we...
详细信息
Semi-arid savannah rangelands are diverse environments (in terms of species) that play an important role in sustaining biodiversity and providing ecosystem services. However, the emergence of non-native species, as well as bush encroachment, are currently threatening these (semi-arid rangeland and grassland) ecosystems. The purpose of this study was therefore to map and quantify the spatial extents of non-native woody vegetation in the Kruger National Park and surrounding communal areas in Mpumalanga, South Africa. To achieve the study's objectives, Sentinel-1 and Sentinel-2 remotely sensed data were combined and analysed using the random forest (RF) machine-learning algorithm in the Google Earth Engine (GEE) cloud computing platform. Specifically, spectral bands and selected spectral derivatives, e.g. enhanced vegetation index (EVI2), normalized difference moisture index (NDMI) and normalized difference phenology index (NDPI) were computed and used to map non-native woody vegetation. After optimizing the model combination, the classification outputs had an overall accuracy of 70%, with class accuracies such as producer's accuracy (PA) and user's accuracy (UA) ranging from 67% to 95%.It was shown in this study that using Sentinel-2 and Sentinel-1 data together led to better overall accuracy than using single sensor models when mapping semi-arid savannah rangelands. It was also found in this study that the overall classification accuracy of non-native (invasive) species using optical sensors was higher than in previous studies. On a free platform like GEE, it was possible to utilize advanced classification processes to fully exploit the informative content of Sentinel-1 and Sentinel-2 data.
The carbon and water footprint of large-scale computing systems poses serious environmental sustainability risks. In this study, we discover that, unfortunately, carbon and water sustainability are at odds with each o...
详细信息
ISBN:
(纸本)9798400714436
The carbon and water footprint of large-scale computing systems poses serious environmental sustainability risks. In this study, we discover that, unfortunately, carbon and water sustainability are at odds with each other - and, optimizing one alone hurts the other. Toward that goal, we introduce, WaterWise, a novel job scheduler for parallel workloads that intelligently co-optimizes carbon and water footprint to improve the sustainability of geographically distributed data centers.
This is a great book on the topic of cloud computing.--Kapil Bakshi, Architecture and Strategy, Cisco Systems Inc. We will recommend this book to Oracle customers, partners, and users for their journey toward cloud co...
详细信息
ISBN:
(纸本)9780133387520;0133387526
This is a great book on the topic of cloud computing.--Kapil Bakshi, Architecture and Strategy, Cisco Systems Inc. We will recommend this book to Oracle customers, partners, and users for their journey toward cloud computing.--Jurgen Kress, Fusion Middleware Partner Adoption, Oracle EMEA A cloud computing book that will stand out and survive the test of time.... I highly recommend this book...--Christoph Schittko, Principal Technology Strategist & cloud Solution Director, Microsoft Corp. ...a must-read for any IT professional interested in cloud computing.--Andre Tost, Senior Technical Staff Member, IBM Software Group The richness and depth of the topics discussed are incredibly impressive. The depth and breadth of the subject matter are such that a reader could become an expert in a short amount of time.--Jamie Ryan, Solutions Architect, Layer 7 Technologies Thomas, in his own distinct and erudite style, provides a comprehensive and a definitive book on cloud computing. Just like his previous masterpiece, Service-Oriented Architecture: Concepts, Technology, and Design, this book is sure to engage CxOs, cloud architects, and the developer community involved in delivering software assets on the cloud. Thomas and his authoring team have taken great pains in providing great clarity and detail in documenting cloud architectures, cloud delivery models, cloud governance, and economics of cloud, without forgetting to explain the core of cloud computing that revolves around Internet architecture and virtualization. As a reviewer for this outstanding book, I must admit I have learned quite a lot while reviewing the material. A must have book that should adorn everybodys desk!--Vijay Srinivasan, Chief Architect - Technology, Cognizant Technology Solutions This book provides comprehensive and descriptive vendor-neutral coverage of cloud computing technology, from both technical and business aspects. It provides a deep-down analysis of cloud architectures and mechanisms that ca
The evolution of cloud computing has brought great progress in data processing capabilities but advanced issues still hinder the performance of mobile applications, especially those that require fast interaction and d...
详细信息
The cloud offers applications, infrastructure, and storage services to consumers that must be secure by some strategies. Hence, security in the cloud is to protect consumer data and structure from malicious users by d...
详细信息
This study looks at how the Internet of Things (IoT) and cloud computing are revolutionising agriculture, specifically in terms of empowering farmers to use electronic devices to monitor and optimise crops and machine...
详细信息
Smartphones and other mobile device users are becoming increasingly susceptible to malicious applications or apps that compromise user privacy. Malicious applications are more invasive than required because they requi...
详细信息
Smartphones and other mobile device users are becoming increasingly susceptible to malicious applications or apps that compromise user privacy. Malicious applications are more invasive than required because they require less authorization to operate them. The Android platform is more vulnerable to attacks since it is open-source, allows third-party app stores and it has extensive app screening. Thus the usage of mobile cloud applications has also expanded due to android platform. The mobile apps are useful for e-transportation, augmented reality, 2D and 3D games, ehealth care and education. Consequently, maintaining MCC security and optimization of resources according to the task becomes significant task. Though recent research has been focused in the area of task scheduling, supporting multiple objectives still becomes a significant issue due to the Non-deterministic Polynomial (NP) hard problem. In this paper, Federated Learning with Blockchain Technology (FLBCT) is introduced for Microservice-based Mobile cloud computing Applications (MSCMCC). Mobile app permissions dataset has to be offloaded to a mobile cloud and protected using FL and BCT. FL permit mobile users to train models without sending raw data to third-party servers. FL is also used to trains the data across various decentralized devices holding of samples without exchanging them. BCT is introduced for enhancing data traceability, trust, security and transparency among participating companies. Resource matching, task sequencing, and task scheduling are major steps of Optimization Task Scheduling based Computational Offloading (OTSCO) framework. OTSCO framework increases application efficiency and gives the successful resource constraints to increase application-based efficiency, tasks are executed under deadline, and minimize application cost. The proposed system has a lower overhead of 20.14%, lesser boot time of 20.47 ms, lesser CPU usage of 0.45%, failure task ratio of the suggested system is 2.52%
PurposeThis study aims to identify significant factors, analyse them using the consistent fuzzy preference relations (CFPR) method and forecast the probability of successful deployment of the internet of things (IoT) ...
详细信息
PurposeThis study aims to identify significant factors, analyse them using the consistent fuzzy preference relations (CFPR) method and forecast the probability of successful deployment of the internet of things (IoT) and cloud computing (CC) in Gujarat, India's building ***/methodology/approachFrom the previous studies, 25 significant factors were identified, and a questionnaire survey with personal interviews obtained 120 responses from building experts in Gujarat, India. The questionnaire survey data's validity, reliability and descriptive statistics were also assessed. Building experts' opinions are inputted into the CFPR method, and priority weights and ratings for probable outcomes are obtained to forecast success and *** findings demonstrate that the most important factors are affordable system and ease of use and battery life and size of sensors, whereas less important ones include poor collaboration between IoT and cloud developer community and building sector and suitable location. The forecasting values demonstrate that the factor suitable location has a high probability of success;however, factors such as loss of jobs and data governance have a high probability of failure. Based on the forecasted values, the probability of success (0.6420) is almost twice that of failure (0.3580). It shows that deploying IoT and CC in the building sector of Gujarat, India, is very much ***/valuePrevious studies analysed IoT and CC factors using different multi-criteria decision-making (MCDM) methods to merely prioritise ranking in the building sector, but forecasting success/failure makes this study unique. This research is generally applicable, and its findings may be utilised for decision-making and deployment of IoT and CC in the building sector anywhere globally.
In the context of cloud computing, preserving the privacy of big data while also allowing for secure access control is a critical concern. With the increasing adoption of cloud technology, it is imperative to address ...
详细信息
In the context of cloud computing, preserving the privacy of big data while also allowing for secure access control is a critical concern. With the increasing adoption of cloud technology, it is imperative to address the challenges associated with safeguarding sensitive data while enabling authorized access. This paper develops an efficient privacy-preserving security model that uses cryptographic techniques to protect sensitive data and ensure that only authorized individuals can access it. The research puts together a secure data authentication technique, named secured privacy protection access control (SecPPAccess), allowing secured communication in cloud computing. For the protection of privacy for sensitive data, the protected transferring of data is commenced among the elements, like a user, cloud server, registration authority, key generation center and data owner, by using many phases mainly the key generation phase, setup phase, server registration, user registration, data upload, data encryption, requester authentication, data access, and data download phase. Here, a method is designed newly for securing data privacy using various operations, like secret keys, hashing, encryption, etc. The study proves that the initiated SecPPAccess model achieves the highest rate of detection of 0.85, the lowest usage for memory of 0.505 MB, and less computation time of 51.50 s.
The concept of cloud computing has significantly aided in the development of new application for IT services. However, developing reliable and effective cloud architecture requires a thorough understanding of the...
详细信息
暂无评论