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Design and Implementation of Garment Trade Information Management System Based on Cloud computing

Design and Implementation of Garment Trade Information Manag...

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Smart Generation computing, Communication and Networking (SMART GENCON), international conference on

作者： Ruirui Li Mei Li Shaanxi Fashion Engineering University Shaanxi China

Cloud computing is an internet-based computing model, which provides users with on-demand and pay-as-you-go services by virtualizing computing resources, storage resources and network resources. In recent years, with the rapid development of cloud computing technology, more and more industries began to apply it to information management, clothing industry is no exception. Cloud computing can store and manage a large amount of data centrally, which avoids the problem that data needs to be stored on various computers in the traditional way. At the same time, cloud computing can also process and analyze data quickly through distributed computing, which improves the efficiency of information processing.

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A Blockchain Architecture for Secure Decentralized System and computing

A Blockchain Architecture for Secure Decentralized System an...

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Power Electronics & IoT Applications in Renewable Energy and its Control (PARC), 2020 international conference on

作者： Sandhya Avasthi Khushboo Jain Ayushi Prakash Tanushree Sanwal Department of CSE ABES Engineering College Ghaziabad UP India School of Computer Science UPES Dehradun UK India Department of CSE AKGEC Engineering College Ghaziabad India KIET School of Management KIET Group of Institutions Delhi-NCR Ghaziabad India

Recent growth in internet infrastructure has increased demands for internet technology and so there is a need for a secure decentralized system that is combined with secure and transparent infrastructure. Blockchain technology can store information in a distributed manner securely. Blockchain technology has expanded significantly over the past few years, with new applications and use cases being discovered and developed every day. The decentralized nature of blockchain, combined with its secure and transparent infrastructure, has made it a highly sought-after solution for various industries, including finance, healthcare, supply chain management, and government services. The expansion of blockchain technology is a result of its increasing adoption and integration into various sectors such as finance, healthcare, supply chain management, and more. One of the key drivers of the expansion of blockchain is the increasing demand for secure, tamper-proof, and transparent transactions. This has led to the development of various blockchain platforms, such as Ethereum, which helps in the development of decentralized applications or Apps for a variety of purposes from financial records to data storage.

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Deep Reinforcement Learning-based Task Offloading in MEC for energy and resource-constrained devices 3

Deep Reinforcement Learning-based Task Offloading in MEC for...

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3rd IEEE international Mediterranean conference on Communications and Networking, MeditCom 2023

作者： Nieto, Gorka De La Iglesia, Idoia Lopez-Novoa, Unai Perfecto, Cristina Ikerlan Technology Research Centre Mondragon Arrasate Spain Spain

ISBN: (纸本)9798350333732

The combination of Multi-access Edge computing (MEC) and task offloading paradigms will enable next-generation IoT applications that are currently hampered due to the computational and battery limitations of IoT devices. Moreover, the requirements of such apps can be so variable that guaranteeing a certain Quality-of-Experience (QoE) level when performing offloading decisions means enhancing the user experience of IoT services. To address this problem, in this paper, a QoE-based offloading algorithm is proposed. Considering an unpredictable time-varying environment, a Deep Reinforcement Learning (DRL) algorithm is proposed, specifically, an Actor-Critic (AC) algorithm, which targets maximizing the QoE value. To that end, a novel QoE calculation method is proposed, encompassing both latency and energy performance, along with the success rate of the arriving tasks, i.e. the tasks that are correctly executed, having their time and energy requirements fulfilled. In addition, computational tasks are classified into three classes, being delay-sensitive, energy-aware, and non-constrained tasks. Some experiment results are presented to show the performance of the algorithm in terms of energy consumption, task success rate, and, finally, QoE values. Simulation results show that the proposed method maximizes success rate and QoE values, which may be conflicting to battery saving in the analyzed environment. © 2023 IEEE.

关键词： internet of things

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The World of Communication & computing Platform In Research Perspective: Opportunities and Challenges 3

The World of Communication & Computing Platform In Research ...

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3rd international conference on Signal Processing and Communication (ICPSC)

作者： Kasyap, V. Balaji Jayapandian, N. CHRIST Deemed Univ Sch Engn & Technol Bengaluru India

ISBN: (纸本)9781665428644

computing paradigms are introduced for solving complex problems by analyzing, designing and implementing by complex systems. computing can be defined as the effective use of computer or computer technology to solve tasks that are goal oriented. computing is used in development of producing scientific studies, building intelligent systems, channeling different media for communication. Over the last few years, internet became so popular which lead to the increase in computer processing capacity, data storage and communication with one another. computing has evolved from one technology to another in its field and formed a robust framework over the years. In this paper a survey on different computing paradigms like evergreen computing is cloud computing, to deal with basic scheduling is grid computing, for multi task handing is parallel computing, to handle smart phone data's that is mobile computing, cluster computing, and distributed computing is carried out. These technologies improved the way computing functions and made it easier to the computer world. The applications and research issues of the most of the computing paradigms are discussed in this article. The recent research issues in computing platform are scheduling and security. The scheduling is dealing with data processing from one computing platform to other computing device. Security is one of the important research issues.

关键词： Cloud computing Cluster computing distributed computing Grid computing Mobile computing Parallel computing

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Short Term Nonlinear Load Forecasting Method for distributed Photovoltaic Grid Connection Based on GSA Algorithm

Short Term Nonlinear Load Forecasting Method for Distributed...

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Artificial Intelligence, internet of Things and Cloud computing technology (AIoTC), international conference on

作者： Pengfei Xu Yan Li Mengyuan Tang Xing Tian Baohao Gao Economic and Technological Research Institute of State Grid Ningxia Electric Power Co. Ltd. Yinchuan Ningxia China

ISBN: (数字)9798331530280

ISBN: (纸本)9798331530297

In order to cope with the intermittency and uncertainty of photovoltaic power generation and improve the accuracy of short-term load forecasting, a distributed photovoltaic grid connected short-term nonlinear load forecasting method based on Genetic Simulated Annexing Algorithm (GSA) is proposed. The historical data of the distributed photovoltaic grid connected system is used as the analysis basis, and the concept of particle aggregation is introduced to establish a solution space. The global load data is searched in the space, and the original data is substituted into the solution space to achieve load data normalization processing. Design a distributed photovoltaic grid connected short-term nonlinear load forecasting method based on GSA, obtain the global optimal solution, and accurately predict short-term load changes. The experimental results show that this method has significantly improved prediction accuracy and can more accurately predict short-term nonlinear loads.

关键词： Photovoltaic systems Accuracy Uncertainty Load forecasting Processor scheduling Simulated annealing Prediction algorithms Genetics Scheduling Resource management

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Research on distributed Photovoltaic Monitoring System Based on internet of Things and Cloud computing

Research on Distributed Photovoltaic Monitoring System Based...

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Energy, Power and Electrical technology (ICEPET), international conference on

作者： Huiling Qin Shuang Li Chengyu He Zhi Rao Di Gan China Southern Power Grid Company Limited Guangxi Power Grid Corporation Guangxi China China Southern Power Grid Company Limited Energy Development Research Institute Guangdong China

ISBN: (数字)9798350352658

ISBN: (纸本)9798350352665

Due to the depletion of fossil fuels globally and the rapid advancement of solar power generating technologies, solar power generation has increasingly emerged as a viable method for energy development. The concept of a distributed Photovoltaic Power System (DPPS) promotes the generation, connection to the grid, conversion, and utilisation of power in close proximity. This approach has the potential to significantly decrease the consumption of fossil fuels. Managing photovoltaic power stations is becoming challenging due to the proliferation of distributed solar power stations. This study proposes a distributed PV monitoring system that utilises the internet of things (IoT) and cloud computing. The system aims to achieve centralised management of several solar power stations. It offers cloud-based storage, data processing, and retrieval, and delivers a wide range of information to the client. A comprehensive explanation of the operational principles and execution procedure of the suggested plan is provided. This paper discusses a case study focused on achieving remote monitoring and control. In addition, the text explores the interconnected cycle of data generation, transmission, processing, and presentation.

关键词： Photovoltaic systems Economics Cloud computing Power supplies Data processing Fossil fuels Real-time systems

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Edge computing: Architecture, Implications and Future with Latest Trends

Edge Computing: Architecture, Implications and Future with L...

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Pervasive computing and Social Networking (ICPCSN), international conference on

作者： Krish Thakkar Akash Patel Aishwariya Budhrani Khushi Patel Sachin Patel Amit Nayak Department of Information Technology Faculty of Technology and Engineering (FTE) Devang Patel Institute of Advance Technology and Research (DEPSTAR) Charotar University of Science and Technology (CHARUSAT) Changa Gujarat India Department of Computer Science & Engineering Faculty of Technology and Engineering (FTE) Devang Patel Institute of Advance Technology and Research (DEPSTAR) Charotar University of Science and Technology (CHARUSAT) Changa Gujarat India Department of Computer Engineering Faculty of Technology and Engineering (FTE) Devang Patel Institute of Advance Technology and Research (DEPSTAR) Charotar University of Science and Technology (CHARUSAT) Changa Gujarat India

As a result of the proliferation of internet-connected smart devices brought about by the explosive growth of the internet of Everything (IoE), lower bandwidth load, slower response, bad security, and poor privacy are just some of the issues that have arisen with data growth. Edge computing solutions have arisen as a response to the limitations of traditional cloud computing in meeting the data processing demands of modern societies. Edge computing, the new era of distributed computing, differs from cloud computing in that it places greater emphasis on being physically proximate to both the user and the data itself. The primary focus of this article is a critical examination of the associated literature and findings around edge computing. Edge computing is first briefly compared with cloud computing. Then, briefly discuss edge computing's architecture, followed by major challenges with edge computing and ending with latest trends with edge computing.

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Fog-Cloud-IoT Enabled WSN Architecture 3

Fog-Cloud-IoT Enabled WSN Architecture

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3rd international conference on Intelligent Engineering and Management, ICIEM 2022

作者： Anitha Christy Angelin, P. Samuel Devakumar, P.V. Al-Farhani, Liwa H. Kumar, Gandam Vijay Deep, Shaurya Mohammad, Shoaib PSNA College of Engineering and Technology Tamilnadu Dindigul India Karunya Institute of Technology and Sciences Tamilnadu Coimbatore India RUDN University System Analysis Control and Information Processing Academy of Engineering Moscow Russia Career Point University Computer Science and Engineering Rajasthan India IIMT College of Management Greater Noida India IMS Unison University Department of Law Uttarakhand Dehradun India

ISBN: (数字)9781665467568

ISBN: (纸本)9781665467568

Remote Because of the exciting innovation it introduces, the WSN likely to be a subject of research in recent time. Because of the impromptu distant connections, adaptability, and simplicity of execution, this has all the makings of becoming the most maintainable innovation for ecological detecting, whether it's about limited or huge scope watching. In any case, the main drawbacks stem from the limited capacity, processing, and accessibility of organization centers for information. Virtual machines resources have been adopted to overcome such constraints, devices to expanded capacity, computation, and easy-to-understand availability. This was a natural progression from traditional WSN designs among pattern in recent theories evolved along advent of internet-of-Things advancements. Against the growing popularity of WSN associated cloud checking frameworks, still the issues are detected because of the distributed comp ting's disadvantages, like dormancy with the capacity charges. In this paper, the advancements achieved to a fog-cloud-IoT associated with WSN architecture of putting a bit of computing at the network part are elaborated, a process, which follows the smart Fog associated with Cloud-computing concept of dissecting also following up on IoT data. A similar investigation was carried out to illustrate the improvements made possible by processing at the organization's edge. © 2022 IEEE.

关键词： Fog computing

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Matching Based Intelligent Edge Resource Allocation 3rd

Matching Based Intelligent Edge Resource Allocation

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3rd international conference on Artificial Intelligence, 2022

作者： Qin, Peng Wang, Miao Zhao, Xiongwen Liu, Jiayan Wang, Shuo He, Haoting Xie, Yuanbo State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources School of Electrical and Electronic Engineering North China Electric Power University Beijing102206 China Hebei Key Laboratory of Power Internet of Things Technology North China Electric Power University Baoding071003 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9789811694226

With the rapid development of the internet of Things, multi-access edge computing (MEC) has emerged as a key technique and intelligent edge resource allocation has become one of the important research issues in MEC. In this paper, we utilize advantages of matching game to integrate users’ needs and the position of edge computing nodes in IoT networks. The proposed GS-based two-sided matching approach simulates the competition and negotiation relationship between different user sets in IoT edge nodes, and provides feasible options based on the preference between different entities. Simulations show that it not only solves the problem of edge resource allocation in a semi-distributed manner, but also effectively improves SP’s revenue. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Edge computing

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Implementation of IoT Security System by Incorporating Block Chain technology

Implementation of IoT Security System by Incorporating Block...

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Smart Data Intelligence (ICSMDI), international conference on

作者： Arepalli Gopi Nedunuri Madhu Venkata Sai Daswanth S.S. Aravinth P.V.Siva Rambabu Department of CSE Koneru Lakshmaiah Education Foundation Vaddeswaram AndhraPradesh India

internet of Things (IoT) allows both physical and virtual objects to communicate with each other over a network. The services provided with IoT helps in easing the day-to-day activities. IoT has numerous advantages like scalability and ease of access but the drawback of the IoT system is that a centralized cloud is required for data storage and ensure the security and privacy of the users. In order to eliminate the drawback of IoT, recent studies have highlighted the integration of IoT systems with the distributed ledger technologies like Blockchain. The Blockchain technology would provide military grade security to the data. This article presents a comprehensive literature review for the internet of Things (IoT) and Blockchain protocols.

关键词： Data privacy Cloud computing distributed ledger Scalability Bibliographies Smart contracts Memory

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