For effective city planning and traffic control, it is now crucial to develop some effective monitoring systems for vehicle traffic in order to address this quickly growing tendency within a city. As a result, the Tra...
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作者：
Soma, Arun KumarPark University
Department of Information Systems & Business Analytics 8700 NW River Park Dr ParkvilleMO64152 United States
Graph data analysis benefits from detecting substructures to infer meaning and interpret data correctly. However, many existing graph clustering algorithms are not applicable to weighted graphs, which contain edge wei...
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With the continuous expansion of the power system scale and the continuous development of the power network, the traditional power system management and optimization methods face many challenges. In order to meet the ...
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With the continuous expansion of the power system scale and the continuous development of the power network, the traditional power system management and optimization methods face many challenges. In order to meet the requirements of voltage optimization and adjustment, the optimization problem is divided into cloud front precomputation and edge computing device cooperative optimization computation with the framework of cloudedge cooperation. The cloud front-end precomputation uses an improved reactive-voltage sensitivity based on an improved modularity function to partition the power system on a 15 min basis and stores the results in the cloud data memory. The voltage threshold device detects the node voltage overrun and triggers the collaborative optimization computation of the edge computing devices, which sends a command to the cloud to call the partitioning result of this time period, and the cloud sends the result to each edge computing device, which determines the area it is responsible for, and adjusts the voltage overrun partitioning by using the mixed-integer second-order conic planning, and ultimately realizes the optimization strategy within the minute-level zone. Since the voltage adjustment is a fine-grained optimization of the local area, it is highly flexible and targeted. Moreover, using the cloud-edge collaboration technology, the intelligent management and optimization of the power system is finally realized. Case analysis and comparative verification show that the method proposed in this paper is accurate and highly efficient.
Natural Language Processing (NLP) systems rely heavily on prompt engineering to enhance performance. This study evaluates various prompt techniques across different sizes of the Gemini API models ('small', ...
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As the number of vehicles rises, there is a problem with traffic congestion on the roads. This problem is characterized by slower speeds, greater time spent travelling, and more congestion in the traffic lanes. In add...
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This article delves into the issue of formation-containment control for multiple Euler-Lagrange systems with input saturation, where the leaders have unknown bounded control inputs. In this article, a distributed even...
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The rapid growth of the Internet of Things (IoT) has created a pressing need for efficient service allocation methods to manage the multitude of connected devices. Edge computing has become essential to fulfill the lo...
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ISBN:
(纸本)9783031814037;9783031814044
The rapid growth of the Internet of Things (IoT) has created a pressing need for efficient service allocation methods to manage the multitude of connected devices. Edge computing has become essential to fulfill the low-latency and high-bandwidth demands of IoT applications. This paper investigates the use of game theory as a framework for optimizing service allocation in edge computing environments. By treating the interactions between IoT devices and edge servers as a strategic game, we propose strategies to achieve optimal allocation and resource utilization. Our approach tackles key challenges such as minimizing latency, improving energy efficiency, and balancing load. Experimental results indicate that game-theoretic methods greatly improve the performance and scalability of IoT systems in edge computing, positioning them a promising solution for future applications.
With the rapid development and widespread application of cloud computing, container technology has become a hot topic for enterprises and research institutions in recent years. This article proposes an automated conta...
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Over the past few years, the integration of mobile edge computing (MEC) and serverless computing, known as serverless MEC (SMEC), has garnered considerable attention. Despite abundant existing works on SMEC exploratio...
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Over the past few years, the integration of mobile edge computing (MEC) and serverless computing, known as serverless MEC (SMEC), has garnered considerable attention. Despite abundant existing works on SMEC exploration, there remains an unaddressed gap in guaranteeing dependable application outputs due to ignoring the threat of both soft and bit errors on SMEC infrastructures. Furthermore, existing works fall short of accommodating the personalized requirements and approximate computation of Internet of Things (IoT) applications, thereby resulting in holistic quality-of-service (QoS) degradation of SMEC systems typically provisioned by limited edge resources. In this article, we investigate the reliability-aware personalized deployment of approximate computation IoT applications for QoS maximization in SMEC environments. To this end, we propose a hybrid methodology composed of offline and online optimization phases. At the offline phase, a decomposition-based function placement method is devised to accomplish function-to-server mapping by integrating convex optimization, cross-entropy method, and incremental control techniques. At the online phase, a lightweight reinforcement learning scheme based on proximal policy optimization (PPO) is developed to handle the inherent dynamicity of IoT applications. We also build a simulation platform upon the real-world base station distribution in Shanghai Telecom and the practical cluster trace in the Alibaba open program. Evaluations demonstrate that our hybrid approach boosts the holistic QoS by 63.9% compared with the state-of-the-art peer algorithms.
Radio Frequency Identification (RFID) door lock systems are at the forefront of modern access control technology, combining security, convenience, and scalability. This paper presents a comprehensive review of RFID-ba...
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