Education cloud platform is an online education platform built on cloud computing to provide students with a more efficient and convenient teaching and learning environment. However, due to the increasing scale of the...
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ISBN:
(纸本)9789819623907
Education cloud platform is an online education platform built on cloud computing to provide students with a more efficient and convenient teaching and learning environment. However, due to the increasing scale of the platform and the increasing number of users, it is particularly important to effectively manage and optimize the users and resources in the network. On this basis, a teaching cloud platform based on the Louvain algorithm is proposed, which can effectively solve the above problems. the Louvain algorithm is a community discovery method based on graph theory, which maximizes the connectivity within the community and minimizes the connectivity between communities. On this basis, the Louvain algorithm is used to divide student clubs, in order to better meet the personalized learning needs of students. Dividing users into different levels can provide students with richer teaching and learning resources more accurately, improving their learning efficiency and quality. In addition, the teaching cloud platform constructed using the Louvain algorithm has achieved optimal allocation of teaching resources. By properly allocating resources within the platform, the efficiency of resource utilization can be effectively improved, thereby enhancing the operational efficiency of the system. A optimization scheduling method based on user group characteristics and resource requirements was proposed, achieving optimal resource allocation. In addition, the satisfaction level of users is highest at 85% to 89%, indicating a high overall satisfaction. therefore, this article proposes a teaching cloud platform design and implementation scheme based on the Louvain algorithm, which is of great significance for improving the performance of teaching systems, optimizing resource allocation, and enhancing user experience. By discovering clubs and optimizing resource allocation, the education cloud platform can better meet the personalized needs of users, providing students with a mor
distributed compressed sensing aims at the joint reconstruction of sparse signals with a common support. In some applications, complex-valued signals and sensing matrices are present. In this paper, we investigate rec...
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ISBN:
(数字)9798331522896
ISBN:
(纸本)9798331522902
distributed compressed sensing aims at the joint reconstruction of sparse signals with a common support. In some applications, complex-valued signals and sensing matrices are present. In this paper, we investigate recovery algorithms for complex-valued distributed scenarios. To that end, we review a compact exposition of complex- and vector-valued MMSE estimators. these can be used in approximate-message-passing-type algorithms. We explain joint reconstruction via iterative algorithms and evaluate suitable recovery algorithms. the performance of these algorithms is evaluated by numerical simulations for different scenarios.
the proceedings contain 28 papers. the topics discussed include: Triggerflow: trigger-based orchestration of serverless workflows;leaving stragglers at the window: low-latency stream sampling with accuracy guarantees;...
ISBN:
(纸本)9781450380287
the proceedings contain 28 papers. the topics discussed include: Triggerflow: trigger-based orchestration of serverless workflows;leaving stragglers at the window: low-latency stream sampling with accuracy guarantees;EdgeScaler: effective elastic scaling for graph stream processing systems;mechanisms for outsourcing computation via a decentralized market;FaaSdom: a benchmark suite for serverless computing;ByzGame: Byzantine generals game;the Kaiju project: enabling event-driven observability;DeepMatch: deep matching for in-vehicle presence detection in transportation;Hermes: enabling energy-efficient IoT networks with generalized deduplication;and doctoral symposium: trade-off analysis of thermal-constrained scheduling strategies in multi-core systems.
the proceedings contain 264 papers. the topics discussed include: analytical assessment of the suitability of multicast communications for the SpiNNaker neuromimetic system;exploring potential parallelism of sequentia...
ISBN:
(纸本)9780769547497
the proceedings contain 264 papers. the topics discussed include: analytical assessment of the suitability of multicast communications for the SpiNNaker neuromimetic system;exploring potential parallelism of sequential programs with superblock reordering;a parallel multi-core team of multiobjective evolutionary algorithms to discover DNA motifs;fully distributed on-chip instruction memory design for stream architecture based on field-divided VLIW compression;parallel speculative DOM-based XML parser;implementation of motion estimation based on heterogeneous parallel computing system with OpenCL;a parallel multiobjective artificial bee colony algorithm for dealing withthe traffic grooming problem;space-efficient sparse matrix storage formats for massively parallel systems;architectural support for exploiting fine grain parallelism;and MHPM: multi-scale hybrid programming model: a flexible parallelization methodology.
the proceedings contain 70 papers. the special focus in this conference is on distributed multimedia systems I, distributed multimedia systems II, distributed multimedia computing, distributed multimedia systems III a...
ISBN:
(纸本)1891706233
the proceedings contain 70 papers. the special focus in this conference is on distributed multimedia systems I, distributed multimedia systems II, distributed multimedia computing, distributed multimedia systems III and Digital home and healthcare. the topics include: A recommendation system for segmented video-streaming content utilizing categorized events and stimuli;a comparison of distributed data parallel multimedia computing over conventional and optical wide-area networks;a lightweight augmented reality system;measuring reliability component in business process automation;optimizing the architecture of adaptive complex applications using genetic programming;a soft real time scheduling algorithm;videoconference support system using printed and handwritten keywords;reporting events in a multimedia content distribution and consumption system;distributed interactive multimedia for technology-enhanced learning and automated content production and distribution;unifying quality standards to capture architectural knowledge for web services domain;Tassonomy and review of complex content models;testing multi agent systems for deadlock detection based on UML models;ip-surveillance system using interactive dual camera hand-off control with FOV boundary detection;action patterns probing for dynamic service composition in home network;a flexibile contxt-aware middleware for developing context-aware applications;projects and goals for the eclipse Italian community;enhancing rationale management with second life meetings;a method to diagnose self-weaknesses for software development organizations;a distributed system for continuous integration with JINI;transforming UML sequence diagrams to class diagrams and goal-driven design transformation by applying design patterns.
Mobile edge computing (MEC) promises to be a useful technology to enable applications in a smart city. However, the task offloading becomes challenging as the MEC infrastructure has limited resources. To solve the cha...
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ISBN:
(数字)9798331531935
ISBN:
(纸本)9798331531942
Mobile edge computing (MEC) promises to be a useful technology to enable applications in a smart city. However, the task offloading becomes challenging as the MEC infrastructure has limited resources. To solve the challenges of MEC, we have proposed a system architecture with an optimization algorithm to minimize the task delay in MEC. A Genetic Algorithm based task allocation algorithm finds the optimal set of edge servers for task deployment and processing. the proposed system efficiently optimizes the task delay in MEC as analyzed from the experiments performed by taking virtual machines as MEC servers. We show the usefulness of the proposed system by taking an application scenario for efficient vehicle management in a smart city.
Irrigation control is essential for optimizing water usage in smart agricultural systems, especially where there is water scarcity. the fast development of IoT and fog computing brings up new opportunities for develop...
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ISBN:
(数字)9798331531935
ISBN:
(纸本)9798331531942
Irrigation control is essential for optimizing water usage in smart agricultural systems, especially where there is water scarcity. the fast development of IoT and fog computing brings up new opportunities for developing new and advanced systemsthat are both efficient and flexible. Further integration of fog computing with machine learning will bring more developments to smart agriculture systems. this paper has framed an irrigation supervision algorithm to predict irrigation needs in the smart agriculture system. the methodology uses a hybrid algorithm that incorporates Gradient Boosting (GB), Logistic Regression (LR) and Random Forest (RF). the system accurately forecasts the irrigation requirement by processing ecological information such as humidity, temperature, and time-based factors. 97.78% of accuracy illustrates the reliability of the resultant model, and initial processing of the data illustrates that information is concise and accurate. Recall, precision and F1- score are computed as metrics for the performance. the system is integrated into fog computing and machine learning to manage real-time data processing to achieve faster and more accurate predictions.
the proceedings contain 46 papers. the topics discussed include: power-aware data buffer cache management in real-time embedded databases;a distributedcomputing environment for embedded control systems with time-trig...
ISBN:
(纸本)9780769533490
the proceedings contain 46 papers. the topics discussed include: power-aware data buffer cache management in real-time embedded databases;a distributedcomputing environment for embedded control systems with time-triggered and event-triggered processing;a lightweight kernel objects monitoring infrastructure for embedded systems;a run-time environment supporting real-time execution of embedded control applications;efficient query processing for tracing RFID tags by recording location identifiers;an efficient anti-collision protocol using bit change sensing unit in RFID system;impact of cache partitioning on multi-tasking real time embedded systems;concepts of switching in the time-triggered network-on-chip;new tracing performance analysis techniques for embedded applications;static loop bound analysis of C programs based on flow analysis and abstract interpretation;and swapping strategy to improve I/O performance of mobile embedded systems using compressed file systems.
the proceedings contain 16 papers. the topics discussed include: a risk-based model for service level agreement differentiation in cloud market providers;adaptive and scalable high availability for infrastructure clou...
ISBN:
(纸本)9783662433515
the proceedings contain 16 papers. the topics discussed include: a risk-based model for service level agreement differentiation in cloud market providers;adaptive and scalable high availability for infrastructure clouds;trust-aware operation of providers in cloud markets;scaling HDFS with a strongly consistent relational model for metadata;distributed exact deduplication for primary storage infrastructures;scalable and accurate causality tracking for eventually consistent stores;cooperation across multiple healthcare clinics on the cloud;behave: behavioral cache for web content;implementing the WebSocket protocol based on formal modeling and automated code generation;autonomous multi-dimensional slicing for large-scale distributedsystems;and bandwidth-minimized distribution of measurements in global sensor networks.
the rapid advancement in retail technology has necessitated the development of systemsthat can adapt to dynamic customer behaviours and optimize pricing strategies in real time. this paper presents a smart retail sys...
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ISBN:
(数字)9798331531935
ISBN:
(纸本)9798331531942
the rapid advancement in retail technology has necessitated the development of systemsthat can adapt to dynamic customer behaviours and optimize pricing strategies in real time. this paper presents a smart retail system that integrates edge computing and IoT automation to address these challenges effectively. the system utilises YOLOv8 for real-time crowd counting, with camera sensors deployed around product shelves to monitor customer interactions. IoT devices, including smart shelves and QR codes, facilitate real-time data communication and enhance customer engagement. Edge computing processes this data locally to enable immediate adjustments in pricing and inventory management, minimizing latency and improving responsiveness. the integration of these technologies aims to optimize operational efficiency, enhance the shopping experience, and provide personalized promotions based on real-time crowd density and sales data.
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