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Domination based graph neural networks

International Journal of computers and Applications 2024年第11期46卷 998-1005页

作者： Meybodi, Mohsen Alambardar Safari, Mahdi Davoodijam, Ensieh Department of Applied Mathematics and Computer Science Faculty of Mathematics and Statistics University of Isfahan Isfahan Iran Department of Software Engineering University of Kashan Kashan Iran

Graph Neural Networks (GNNs) have emerged as a widely used and effective method across various domains for learning from graph data. Despite the abundance of GNN variants, many struggle with effectively propagating messages over long distances. This paper introduces a novel hierarchical message passing framework for graph learning, specifically designed to address the challenge of long-distance message propagation in graphs. By constructing smaller graphs from the main graph using the concept of domination, a fundamental principle in graph theory, we facilitate more efficient message passing within each subgraph. Subsequently, we employ a Graph Attention Network (GAT) to aggregate these features and propagate them to distant nodes across the graph. Experimental results on standard node classification datasets validate that the proposed architecture achieves performance comparable to or better than conventional GNNs. Additionally, our model consistently performs better on graphs with missing edges. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Neural network models

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Multi-Agent Graph Reinforcement Learning based On-Demand Wireless Energy Transfer in Multi-UAV-aided IoT Network 21

Multi-Agent Graph Reinforcement Learning based On-Demand Wir...

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21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2023

作者： Zhao, Ze Yu Che, Yueling Luo, Sheng Wu, Kaishun Leung, Victor C.M. College of Computer Science and Software Engineering Shenzhen University China

ISBN: (纸本)9783903176553

This paper proposes a new on-demand wireless energy transfer (WET) scheme of multiple unmanned aerial vehicles (UAVs). Unlike the existing studies that simply pursuing the total or the minimum harvested energy maximization at the Internet of Things (IoT) devices, where the IoT devices’ own energy requirements are barely considered, we propose a new metric called the hungry-level of energy (HoE), which reflects the time-varying energy demand of each IoT device based on the energy gap between its required energy and the harvested energy from the UAVs. With the purpose to minimize the overall HoE of the IoT devices whose energy requirements are not satisfied, we optimally determine all the UAVs’ trajectories and WET decisions over time, under the practical mobility and energy constraints of the UAVs. Although the proposed problem is of high complexity to solve, by excavating the UAVs’ self-attentions for their collaborative WET, we propose the multi-agent graph reinforcement learning (MAGRL) based approach. Through the offline training of the MAGRL model, where the global training at the central controller guides the local training at each UAV agent, each UAV then distributively determines its trajectory and WET based on the well-trained local neural networks. Simulation results show that the proposed MAGRL-based approach outperforms various benchmarks for meeting the IoT devices’ energy requirements. © 2023 IFIP.

关键词： Reinforcement learning

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Efficient Federated Learning Using Dynamic Update and Adaptive Pruning with Momentum on Shared Server Data

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ACM Transactions on Intelligent Systems and Technology 2024年第6期15卷 1-28页

作者： Liu, Ji Jia, Juncheng Zhang, Hong Yun, Yuhui Wang, Leye Zhou, Yang Dai, Huaiyu Dou, Dejing Hithink RoyalFlush Information Network Co. Ltd. Hangzhou China School of Computer Science and Technology Soochow University Suzhou China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing China Baidu Research Beijing China Key Lab of High Confidence Software Technologies Ministry of Education and Software Institute Peking University Beijing China Department of Computer Science and Software Engineering Auburn University AuburnAL United States Department of Electrical and Computer Engineering North Carolina State University RaleighNC United States Bedi Cloud and School of Computer Science Fudan University Beijing China

Despite achieving remarkable performance, Federated Learning (FL) encounters two important problems, i.e., low training efficiency and limited computational resources. In this article, we propose a new FL framework, i.e., FedDUMAP, with three original contributions, to leverage the shared insensitive data on the server in addition to the distributed data in edge devices so as to efficiently train a global model. First, we propose a simple dynamic server update algorithm, which takes advantage of the shared insensitive data on the server while dynamically adjusting the update steps on the server in order to speed up the convergence and improve the accuracy. Second, we propose an adaptive optimization method with the dynamic server update algorithm to exploit the global momentum on the server and each local device for superior accuracy. Third, we develop a layer-adaptive model pruning method to carry out specific pruning operations, which is adapted to the diverse features of each layer so as to attain an excellent tradeoff between effectiveness and efficiency. Our proposed FL model, FedDUMAP, combines the three original techniques and has a significantly better performance compared with baseline approaches in terms of efficiency (up to 16.9 times faster), accuracy (up to 20.4% higher), and computational cost (up to 62.6% smaller). © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Federated learning

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Lightwight Image Super-Resolution: The Shift Ladder Transformer Approach 2

Lightwight Image Super-Resolution: The Shift Ladder Transfor...

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2nd International Conference on Image Processing, computer Vision and Machine Learning, ICICML 2023

作者： Zhang, Jian Wu, Yujie Ma, Jingbin Ling, Siyao Li, Zhaoyan School of Computer and Software Engineering Xihua University Chengdu China

ISBN: (纸本)9798350331417

In lightweight Super Resolution (SR) tasks, balancing performance and efficiency is a challenge for CNN-based models. The Transformer architecture has been introduced into super-resolution tasks due to its global self-attention mechanism. However, existing lightweight image super-resolution networks based on Transformers typically employ localized attention to sparsify their attention, thereby limiting their receptive field and uniformity of pixel weight distribution. To address these challenges, this paper introduces the Shift Ladder Transformer for Super Resolution (slTSR), a lightweight model that melds lightweight convolutional layers with a distinct residual Shift Ladder Transformer block. With the integration of the Shift Ladder Transformer Layer (SLTL) strategy, slTSR effectively amalgamates information from diverse spatial windows, enhancing information exchange. Experiments on diverse datasets consistently highlight the exceptional performance and efficiency of slTSR. © 2023 IEEE.

关键词： Lightweight image super-resolution Localized attention Shift Ladder Transformer

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Water Consumption Dynamics in Izmir: Analyzing Influences of District, Seasonality, and External Events

Water Consumption Dynamics in Izmir: Analyzing Influences of...

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2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024

作者： Arslan, Ahmet Titiz, Imren Ece Gürcan, Ege Can Demir, Alper Software Engineering Izmir University of Economics Izmir Turkey Computer Engineering Izmir University of Economics Izmir Turkey

ISBN: (纸本)9798350379433

This study investigates the patterns of water consumption in Izmir from January 2015 to January 2024, using a dataset provided by Izmir's Open Data Portal. The research aims to understand how different factors such as district, seasons, and external events like the COVID-19 pandemic influence water usage across the city. By employing statistical analysis and machine learning models including Decision Trees and K-means, this project identifies significant spatial and temporal variations in water consumption. This analysis not only aids in the efficient management of water resources but also serves as a foundation for future predictive modeling and sustainability efforts in urban settings. © 2024 IEEE.

关键词： COVID-19 data science Izmir urban sustainability water consumption

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An Efficient and Fast Area Optimization Approach for Mixed Polarity Reed-Muller Logic Circuits

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Chinese Journal of Electronics 2024年第5期33卷 1165-1180页

作者： Yuhao ZHOU Zhenxue HE Jianhui JIANG Xiaojun ZHAO Fan ZHANG Limin XIAO Xiang WANG School of Software Engineering Tongji University Key Laboratory of Agricultural Big Data of Hebei Province Hebei Agricultural University School of Computer Science and Engineering Beihang University School of Electronic and Information Engineering Beihang University

Area has become one of the main bottlenecks restricting the development of integrated circuits. The area optimization approaches of existing XNOR/OR-based mixed polarity Reed-Muller(MPRM) circuits have poor optimization effect and efficiency. Given that the area optimization of MPRM logic circuits is a combinatorial optimization problem, we propose a whole annealing adaptive bacterial foraging algorithm(WAA-BFA), which includes individual evolution based on Markov chain and Metropolis acceptance criteria, and individual mutation based on adaptive probability. To address the issue of low conversion efficiency in existing polarity conversion approaches, we introduce a fast polarity conversion algorithm(FPCA). Moreover, we present an MPRM circuits area optimization approach that uses the FPCA and WAA-BFA to search for the best polarity corresponding to the minimum circuits area. Experimental results demonstrate that the proposed MPRM circuits area optimization approach is effective and can be used as a promising EDA tool.

关键词： Integrated circuits Microorganisms Annealing Logic circuits Circuits Benchmark testing Delays

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A Systematic Review of Complexity in Agile software Project Delivery 34

A Systematic Review of Complexity in Agile Software Project ...

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34th Australasian Conference on Information Systems, ACIS 2023

作者： Vaipulu, Taniela Lal, Ramesh Thorpe, Stephen J. Project Management Research Office Software Engineering Research Centre Department of Computer Science and Software Engineering School of Engineering Computer and Mathematical Sciences Auckland University of Technology New Zealand

In Agile software delivery, complexity factors have become an important part that has been linked to the success of software projects, especially with highly structured plan-driven approaches. Although there are a range of known techniques, practices and structures aimed at improving communication, team, and organisational cohesion, there remains a poor understanding of how organisations and teams can effectively deal with complexity in Agile software delivery. While theoretical and management frameworks of complexity exist, nevertheless, little is known about the important complexity factors at play in the planning, design, and creation of Agile software at the various levels of organisational structures. To better understand complexity and how it may impact Agile delivery across organisational structures, processes and roles, a systematic literature review was undertaken to identify the known complexity factors, to identify gaps in our knowledge, and to identify the approaches that have been undertaken to date to address complexity. This review contributes a fresh perspective to the literature on complexity in Agile software delivery and forwards our conversation on complexity in IT projects, and their effective management. The review was structured around Remington and Pollack’s (2016) model identifying different types of complexity. The review’s findings indicate that complexities result from aspects in functional teams, organizational structures, roles, Agile tasks, and practice-related issues that were identified in distributed Agile projects. We conclude that there may remain a lack of understanding in practice of the complexity factors that are at play in an Agile software delivery context. These findings are relevant to researchers and practitioners seeking to identify areas of focus for addressing complexity in Agile software delivery. Copyright © 2023 Taniela Ramesh Stephen.

关键词： software design

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Framework for Effective Utilization of Distributed Scrum in software Projects

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computer Systems Science & engineering 2023年第1期44卷 407-422页

作者： Basit Shahzad Wardah Naeem Awan Fazal-e-Amin Ahsanullah Abro Muhammad Shoaib Sultan Alyahya Department of Software Engineering National University of Modern LanguagesIslamabad44000Pakistan Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computer Science Sukkur IBA UniversitySindh65200Pakistan Department of Information Systems College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia

There is an emerging interest in using agile methodologies in Global software Development(GSD)to get the mutual benefits of both *** is currently admired by many development teams as an agile most known meth-odology and considered adequate for collocated *** the same time,stake-holders in GSD are dispersed by geographical,temporal,and socio-cultural *** to the controversial nature of Scrum and GSD,many significant challenges arise that might restrict the use of Scrum in *** conducted a Sys-tematic Literature Review(SLR)by following Kitchenham guidelines to identify the challenges that limit the use of Scrum in GSD and to explore the mitigation strategies adopted by practitioners to resolve the *** validate our reviewfindings,we conducted an industrial survey of 305 *** results of our study are consolidated into a research *** framework represents current best practices and recommendations to mitigate the identified distributed scrum challenges and is validated byfive experts of distributed *** of the expert review were found supportive,reflecting that the framework will help the stakeholders deliver sustainable products by effectively mitigating the identified challenges.

关键词： Global software development distributed Scrum sustainable development challenges mitigation strategies

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Intelligent Resource Allocations for software-Defined Mission-Critical IoT Services

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computers, Materials & Continua 2022年第11期73卷 4087-4102页

作者： Chaebeen Nam Sa Math Prohim Tam Seokhoon Kim Department of Software Convergence Soonchunhyang UniversityAsan31538Korea Department of Computer Software Engineering Soonchunhyang UniversityAsan31538Korea

Heterogeneous Internet of Things(IoT)applications generate a diversity of novelty applications and services in next-generation networks(NGN),which is essential to guarantee end-to-end(E2E)communication resources for both control plane(CP)and data plane(DP).Likewise,the heterogeneous 5th generation(5G)communication applications,including Mobile Broadband Communications(MBBC),massive Machine-Type Commutation(mMTC),and ultra-reliable low latency communications(URLLC),obligate to perform intelligent Quality-of-Service(QoS)Class Identifier(QCI),while the CP entities will be suffered from the complicated massive HIOT ***,the existing management and orchestration(MANO)models are inappropriate for resource utilization and allocation in large-scale and complicated network *** cope with the issues mentioned above,this paper presents an adopted software-defined mobile edge computing(SDMEC)with a lightweight machine learning(ML)algorithm,namely support vector machine(SVM),to enable intelligent MANO for real-time and resource-constraints IoT applications which require lightweight computation ***,the SVM algorithm plays an essential role in performing QCI ***,the software-defined networking(SDN)controller allocates and configures priority resources according to the SVM classification ***,the complementary of SVM and SDMEC conducts intelligent resource MANO for massive QCI environments and meets the perspectives of mission-critical communication with resource constraint *** on the E2E experimentation metrics,the proposed scheme shows remarkable outperformance in key performance indicator(KPI)QoS,including communication reliability,latency,and communication throughput over the various powerful reference methods.

关键词： Mobile edge computing Internet of Things software defined networks traffic classification machine learning resource allocation

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A Systematic Review of Complexity in Agile software Project Delivery 44

A Systematic Review of Complexity in Agile Software Project ...

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44th International Conference on Information Systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023

ISBN: (纸本)9781713893622

关键词： software design

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