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11th ieee international conference on Cloud computing in Emerging Markets, CCEM 2023

作者： Govindarajan, Priya Mothi, Shubhada M. Tesfahun, Abebe Department of Computer Science School of Computing Amrita Vishwa Vidyapeetham Mysuru Campus India Department of Computer Science School of Computing Amrita Vishwa Vidyapeetham Mysuru Campus India School of Electrical & Computer Engineering Scientific Director Debre Markos Institute of Technology Debre Markos University Ethiopia

ISBN: (纸本)9798350360059

Music is a sound based form of art. From medieval periods there has been a constant effort to create great melodies for the purpose of entertainment, propaganda and healing. There are many formal music systems worldwide that provide a proper method and framework to create great melodies. Music is created by voice and hundreds of musical instruments available worldwide. The two popular classical music systems available in India are Hindustani Classical Music and Carnatic Classical Music. Although there are a few similarities between both the systems such as swaras and Raagas, both have different basic frame work. The basic aim of this review is to collect and analyze all the previous works and research done in the field of Raaga Recognition of Classical Music using Automation and AI. It also involves review of few research journals which are purely based on classification and framework of Carnatic Classical Music in the traditional method without involving Automation or Artificial Intelligence. The analysis is in the pursuit of finding the scope for further research and to create a complete model to recognize maximum possible Raagas with minimal errors. ©2023 ieee.

关键词： Automation

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distributed Cooperative Control for Human-Unmanned Aerial Vehicle Swarm Teaming in Target Tracking∗

Distributed Cooperative Control for Human-Unmanned Aerial Ve...

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2024 ieee international conference on Robotics and Biomimetics, ROBIO 2024

作者： He, Hangxuan Huo, Mengzhen Duan, Haibin School of Automation Science and Electrical Engineering Beihang University Beijing100083 China School of Automation Science and Electrical Engineering Beihang University Science and Technology on Aircraft Control Laboratory Beijing100083 China

ISBN: (纸本)9781665481090

Over the last decade, the relationship between humans and cyber-physical systems has grown closer, particularly in fields such as manufacturing and transportation. This paper presents a control framework within the engineering domain, wherein a human operator collaborates with a swarm of unmanned aerial vehicles (UAVs) to achieve a shared goal. First, we construct a human-swarm mutual trust model that empowers both parties with a degree of autonomy. Second, we adopt a distributed optimization algorithm integrated with control barrier functions to manage the swarm's motion. The cooperative control framework is demonstrated in a 3D scenario, and simulation results verify the feasibility of the proposed method. © 2024 ieee.

关键词： Unmanned aerial vehicles (UAV)

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Increasing Feasibility with Dynamic Priority Assignment in distributed Trajectory Planning for Road Vehicles 25

Increasing Feasibility with Dynamic Priority Assignment in D...

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ieee 25th international conference on Intelligent Transportation systems (ITSC)

作者： Scheffe, Patrick Dorndorf, Georg Alrifaee, Bassam Rhein Westfal TH Aachen Chair Embedded Software Aachen Germany

ISBN: (数字)9781665468800

ISBN: (纸本)9781665468800

Nonconvex, nonlinear optimal control problems for large-scale networked control systems (NCSs) can be distributed to accelerate computation time. One distribution strategy is priority-based non-cooperative distributed model predictive control. A key problem in this strategy is the priority assignment to agents, as the priorities highly impact the solution quality and even determine if a feasible solution for all agents exists. This problem has been investigated in the domain of robotics for many years, and has recently been picked up in the domain of road vehicles. We propose a distributed reprioritization process for priority-based non-cooperative distributed model predictive control and prove recursive feasibility for the NCS. We develop a dynamic priority assignment algorithm for road vehicles, which we use in our reprioritization process. In our algorithm, each vehicle determines its priority in a distributed fashion. Inspired by an approach from the domain of robotics, we increase the priority of a vehicle with the number of potential collisions with other vehicles on its planned trajectory. We evaluate our distributed reprioritization process and our dynamic priority assignment algorithm in experiments. We compare the algorithm's performance to dynamic random priorities and to static priorities.

关键词： Trajectory planning Networked control systems Heuristic algorithms Road vehicles Optimal control Prediction algorithms Trajectory

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VXLAN - A practical approach to cloud computing scalability 22

VXLAN - A practical approach to cloud computing scalability

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22nd RoEduNet conference: Networking in Education and Research, RoEduNet 2023

作者： Traistaru, Claudiu Universitatea din Craiova Departamentul de Calculatoare si Tehnologia Informatiei Craiova Romania

ISBN: (纸本)9798350393651

关键词： Cloud computing

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Hybrid Golden Jackal and Whale Optimization Algorithm (HGJWOA) for Optimizing Resource and Service Allocation in Edge computing Environments

Hybrid Golden Jackal and Whale Optimization Algorithm (HGJWO...

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2024 international conference on Knowledge Engineering and Communication systems, ICKECS 2024

作者： Saradha, M. Sasivanan, T. Monishkumar, C. Muralidharan, J. Nivitha, K. K. S. Rangasamy College of Technology Computer Science and Engineering Tiruchengode637 215 India Vellore Institute of Technology Computer Science and Engineering Vellore632 014 India

ISBN: (纸本)9798350359688

Edge computing has emerged as a promising paradigm to address the latency and bandwidth constraints of traditional cloud computing by bringing computation and storage closer to the data source. In edge computing environments, efficient resource and service allocation are crucial for optimizing performance and meeting user requirements. This paper proposes a novel approach for optimizing resource and service allocation in edge computing environments using a hybrid algorithm (HGJWOA)combining Golden Jackal Optimization (GJO) and Whale Optimization Algorithm (WOA). The hybridization of GJO and WOA aims to leverage the strengths of both algorithms to achieve superior optimization performance. We develop a framework for resource and service allocation, formulate the optimization problem, and define evaluation metrics. The hybrid algorithm is integrated into the framework and evaluated through extensive simulations. Experimental results demonstrate the effectiveness of the proposed approach in improving resource utilization, reducing latency, and enhancing service delivery in edge computing environments compared to traditional optimization algorithms. Additionally, case studies and real-world deployment scenarios illustrate the practical applicability and benefits of the hybrid algorithm. Overall, the proposed hybrid Golden Jackal and Whale Optimization Algorithm presents a promising solution for optimizing resource and service allocation in edge computing environments, contributing to the advancement of efficient and scalable edge computing systems. © 2024 ieee.

关键词： Mobile edge computing

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distributed Training of Large Language Models 29

Distributed Training of Large Language Models

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29th ieee international conference on Parallel and distributed systems, ICPADS 2023

作者： Zeng, Fanlong Gan, Wensheng Wang, Yongheng Yu, Philip S. Jinan University Zhuhai519070 China Pazhou Lab Guangzhou510330 China University of Illinois Chicago Chicago United States

ISBN: (纸本)9798350330717

The advent of large language models (LLMs), like ChatGPT ushers in revolutionary opportunities that bring a vast variety of applications (such as healthcare, law, and education) across various disciplines. The research report pointed out that the model showcases excellent performance often closely related to the parameter scale of the model, so how to train an LLM? This is a question that everyone is more concerned about. At present, there are several commonly used distributed training frameworks including Megatron-LM, DeepSpeed, etc. In this paper, we first provide a brief introduction, which refers to the current development status of LLM. Second, we start from the status, introducing the current common parallel strategies of LLM distributed training. Next, we briefly introduce the underlying technologies and frameworks that LLM relies on nowadays, describing the current popular ones and types of large models. Then we introduce the optimization techniques used in the LLMs. Finally, we summarize the problems and challenges encountered in the current LLM training and describe the possible future development direction of LLM. © 2023 ieee.

关键词： Big data data parallelism distributed training large language models pipeline parallelism

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Privacy-Preserving Average Consensus for Multi-Agent System with Event-Triggered Method 6

Privacy-Preserving Average Consensus for Multi-Agent System ...

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6th ieee international conference on Pattern Recognition and Artificial Intelligence, PRAI 2023

作者： Shi, Shuyu Cao, Xinyang Zhang, Qingmiao Chengdu Foreign Languages School International Department Chengdu China

ISBN: (纸本)9798350325485

The paper considers the privacy-preserving and communication constraints for multi-Agent systems. Firstly, a lightweight, decentralized, time-varying transformation method is introduced to prevent information leakage during information exchange between agents. This approach requires less computation and is compatible with systems with limited computing resources. Secondly, the paper proposes an event-Triggered mechanism that considers both privacy-preserving and communication constraints to avoid continuous updates of the privacy-preserving controller. By using intermittent communication mode, this approach effectively reduces computing and communication resources compared to traditional time-Triggered methods. Overall, these methods offer efficient solutions for privacy and communication challenges in multi-Agent systems. The finite-Time privacy-preserving control protocol is validated through numerical simulation examples to demonstrate its effectiveness. © 2023 ieee.

关键词： Multi agent systems

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Application Level Synthesis: Creating Matrix-Matrix Multiplication Library: A Case Study

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ieee ACCESS 2024年 12卷 155885-155903页

作者： Pudi, Dhilleswararao Yang, Yu Stathis, Dimitrios Prajapati, Sunil Kumar Boppu, Srinivas Hemani, Ahmed Cenkeramaddi, Linga Reddy Indian Inst Technol Bhubaneswar Sch Elect Sci Bhubaneswar 752050 India KTH Royal Inst Technol Div Elect & Embedded Syst S-11428 Stockholm Sweden Indian Inst Technol Bhubaneswar Sch Basic Sci Bhubaneswar 752050 India Univ Agder Dept ICT N-4879 Grimstad Norway

Efficiently synthesizing an entire application that consists of multiple algorithms for hardware implementation is a very difficult and unsolved problem. One of the main challenges is the lack of good algorithmic libraries. A good algorithmic library should contain algorithmic implementations that can be physically composable, and their cost metrics can be accurately predictable. Physical composability and cost predictability can be achieved using a novel framework called SiLago. By physically abutting small hardware blocks together like Lego bricks, the SiLago framework can eliminate the time-consuming logic and physical synthesis and immediately give post-layout accurate cost estimation. In this paper, we build a library for matrix-matrix multiplication algorithm based on the SiLago framework as a case study because matrix-matrix multiplication is a fundamental operation in scientific computing that is frequently found in applications such as signal processing, image processing, pattern recognition, robotics, and so on. This paper demonstrates the methodology to construct such a library containing composable and predictable algorithms so that the application-level synthesis tools can utilize it to explore the design space for an entire application. Specifically, in this paper, we present an algorithm for matrix decomposition, several mapping strategies for selected kernel functions, an algorithm to construct the mapping of each matrix-matrix multiplication, and finally, the method to calculate the cost estimation of each solution.

关键词： Coarse grain reconfigurable architecture field programmable gate array (FPGA) dynamically reconfigurable resource array (DRRA) distributed memory architecture (DiMArch) matrix multiplication high-level synthesis hardware accelerators hardware-software co-design Coarse grain reconfigurable architecture field programmable gate array (FPGA) dynamically reconfigurable resource array (DRRA) distributed memory architecture (DiMArch) matrix multiplication high-level synthesis hardware accelerators hardware-software co-design

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Improved-Hybrid GA-Based Technique to Optimize the Resource Utilization in Cloud 6

Improved-Hybrid GA-Based Technique to Optimize the Resource ...

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6th international conference on Contemporary computing and Informatics, IC3I 2023

作者： Kumar, Amodh Ahlawat, Deepak Harnal, Shilpi Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350304480

Data clustering is a technique related to technology that can be used and utilized in vast areas of computer science and other applications. In this work, the technique access and used for clustering is improved-hybrid clustering in cloud computing with the application of GA in the algorithm. The process is started by uploading the text documents on the cloud and the GA algorithm of improved-hybrid similarity is applied and results are considered for analysis. The research is a step towards innovation and two parameters for resource optimization are taken into consideration viz., memory consume and CPU utilization. The results obtained for memory utilization and CPU utilization are scalable and optimal in the carried-out study. © 2023 ieee.

关键词： Cloud computing Genetic algorithm Hadoop distributed File System (HDFS) Improved-Hybrid Similarity Service-Level Agreement (SLA) Teaching-Learning Based Optimization (TLBO)

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Smart Home Automation System Powered by Renewable Energy

Smart Home Automation System Powered by Renewable Energy

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2022 ieee international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2022

作者： Hasan, Mehidi Talukder, Touhidul Islam Saima, Fatema Tauze Zohora Joy, Md. Nazim Uddin Das, Adrik Sheham, Md. Nursari Hasan American International University-Bangladesh Electrical and Electronic Engineering Dhaka1229 Bangladesh

ISBN: (纸本)9781665483162

The paper's object is to develop a smart home automation system with sustainable renewable energy. The paper presents a conceptualization and implementation of developing a smart home system that uses solar panels to maximize the use of abundant renewable energy. This system is created to minimize the carbon footprint and energy consumption. This will simultaneously be a great solution for the climate issues in the world as well while using renewable energy simultaneously. Integrated renewable energy in this project to build an IoT-based smart automated home system. One of the major features of the system is to integrate the sun tracking method for maximum solar power harnessing. In this SHAS or Smart Home Automation System, lighting, climate, entertainment systems, and appliances are all monitored and controlled by the system. Home security systems such as access control, face recognition, and alarm systems are also be included. The project has features like activating loads using a Bluetooth system. The Arduino UNO board, a Bluetooth module controlled by a remote, and an infrared sensor are used to offer a low-cost and user-friendly remote-controlled home automation system in this work. IoT or Internet of Things technology is used to connect device communication in smart home appliances. In this home automation system technologies are used like Wi-Fi, Bluetooth where several types of electrical devices are used for controlling and monitoring various kinds of appliances of a household. This project offers a low-cost, eco-friendly smart home solution for individuals in underdeveloped nations like Bangladesh. © 2022 ieee.

关键词： Energy utilization

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