MPI programs represent a major type of workloads running on parallel and distributed systems: tightly coupled high performance computing (HPC) workloads which use MPI to communicate between processes and instances. On...
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This research develops and optimizes an optical character recognition (OCR) system for goat weighing scales using intelligent computer vision and distributedcomputing to enhance accuracy and efficiency in real-world ...
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Power Quality (PQ) directly affects the reliability and stability of power system, so it is of great significance to monitor it in real time. This paper introduces a PQ real-time detection system based on Genetic Algo...
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Online storage and use of digital assets and applications are both aspects of cloud computing. Through a computer network, distributed information systems store and transmit data. Data and effort have both grown for s...
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Cloud computing (CC) is a fundamental technology for distributed networks, enabling the execution of programs across multiple networked computers simultaneously. The major challenge in cloud computing (CC) is optimizi...
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Low voltage ride through (LVRT) is the ability of a photovoltaic (PV) system to maintain continuous operation during grid voltage dips or short-term power outages. To meet the LVRT requirements, PV systems typically i...
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Cloud computing enables users to access the online resource over the internet. Therefore, the efficient task scheduling approach should be designed to fulfil the user’s demands and achieve quality of service(QoS). In...
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ISBN:
(数字)9798331521349
ISBN:
(纸本)9798331521356
Cloud computing enables users to access the online resource over the internet. Therefore, the efficient task scheduling approach should be designed to fulfil the user’s demands and achieve quality of service(QoS). In this paper, we present an improved task scheduling using particle swarm optimization (PSO) that aims to enhance the QoS. The tasks are modeled as discrete entities with specific QoS demands, and resources are specified by their distinct capacities to meet those demands. The proposed algorithm combines exploration and exploitation strategies to efficiently search the solution space based on constraints given for deadlines and budgets. Our contributions in this research will include the modification of an objective function that contains cost and execution time as the decision criteria. Our proposed algorithm DBPSO achieves 202 ms of makespan while DPSO obtains 233 ms of makespan for 250 tasks and 5 virtual machines.
The proceedings contain 68 papers. The topics discussed include: effect of the downstream blockage induced under-rib convection on oxygen feeding in a PEMFC with parallel flow field;simulation and analysis of the dete...
The proceedings contain 68 papers. The topics discussed include: effect of the downstream blockage induced under-rib convection on oxygen feeding in a PEMFC with parallel flow field;simulation and analysis of the detection effect of seafloor shallow thermal origin gas release by marine resistivity method;dual-objective optimal scheduling of grid-connected distributed photovoltaic systems considering life loss cost of energy storage;research on security protection strategies for household distributed photovoltaic clusters;short-term wind speed prediction based on time series trends and periodic characteristics;experimental research on heating performance of solar energy coupled with water source heat pump system;research on variable pressure oil supply servo system based on accumulator;and optimal scheduling of building integrated energy system considering the interaction of electric energy and heat energy.
The rise and proliferation of Artificial Intelligence (AI) technologies are bringing transformative changes to various sectors, signaling a new era of innovation in fields as diverse as medicine, manufacturing, and ev...
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ISBN:
(纸本)9798350371000;9798350370997
The rise and proliferation of Artificial Intelligence (AI) technologies are bringing transformative changes to various sectors, signaling a new era of innovation in fields as diverse as medicine, manufacturing, and even day-to-day social interactions. Notable advancements are not just confined to textual understanding, as seen in models like GPT, but also extend to visual cognition through image recognition and more. Beyond surface interactions and predictions, AI finds profound applications in life-saving domains such as medical diagnostics and becomes an integral part of daily life through chatbot-based customer interactions. However, as the horizon of AI expands, a crucial yet often overlooked aspect emerges- the underlying mission-critical infrastructure required to support and deploy these models effectively. The intricacies of efficient communication systems, foundational for real-time AI model operations, take center stage in ensuring the seamless functioning of AI-driven applications. This paper explores the quintessential changes needed in communication paradigms to keep pace with the evolving AI landscape. Specifically, we highlight the pivotal role of multipath communication in enhancing the responsiveness and efficiency of AI applications [1]. As a case in point, we investigate its impact on mission-critical operations in robotics. Through experimentation and analysis, the results elucidate the substantial benefits of this approach, revealing a significant improvement in delay metrics. This work underscores the imperative of aligning communication systems with the ever-growing demands of AI, ensuring that infrastructural capabilities do not lag in the race for innovation.
Geospatial Cloud and fog computing have experienced significant growth due to advanced Information and Communication Technology (ICT) that enables geospatial web services. These technologies are known for their robust...
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