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NPBMT: A Novel and Proficient Buffer Management Technique for Internet of Vehicle-Based DTNs

computers, Materials & Continua 2023年第10期77卷 1303-1323页

作者： Sikandar Khan Khalid Saeed Muhammad Faran Majeed Salman A.AlQahtani Khursheed Aurangzeb Muhammad Shahid Anwar Department of Computer Science Shaheed Benazir Bhutto University SheringalDir(U)Khyber Pakhtunkhwa18200Pakistan Department of Computer Science Kohsar University MurreePunjab47150Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Department of AI and Software Gachon UniversitySeongnam-si13120South Korea

Delay Tolerant Networks(DTNs)have the major problem of message delay in the network due to a lack of endto-end connectivity between the nodes,especially when the nodes are *** nodes in DTNs have limited buffer storage for storing delayed *** instantaneous sharing of data creates a low buffer/shortage ***,buffer congestion would occur and there would be no more space available in the buffer for the upcoming *** address this problem a buffer management policy is proposed named“A Novel and Proficient Buffer Management Technique(NPBMT)for the Internet of Vehicle-Based DTNs”.NPBMT combines appropriate-size messages with the lowest Time-to-Live(TTL)and then drops a combination of the appropriate messages to accommodate the newly arrived *** evaluate the performance of the proposed technique comparison is done with Drop Oldest(DOL),Size Aware Drop(SAD),and Drop Larges(DLA).The proposed technique is implemented in the Opportunistic Network Environment(ONE)*** shortest path mapbased movement model has been used as the movement path model for the nodes with the epidemic routing *** the simulation results,a significant change has been observed in the delivery probability as the proposed policy delivered 380 messages,DOL delivered 186 messages,SAD delivered 190 messages,and DLA delivered only 95 messages.A significant decrease has been observed in the overhead ratio,as the SAD overhead ratio is 324.37,DLA overhead ratio is 266.74,and DOL and NPBMT overhead ratios are 141.89 and 52.85,respectively,which reveals a significant reduction of overhead ratio in NPBMT as compared to existing *** network latency average of DOL is 7785.5,DLA is 5898.42,and SAD is 5789.43 whereas the NPBMT latency average is *** reveals that the proposed policy keeps the messages for a short time in the network,which reduces the overhead ratio.

关键词： Delay tolerant networks buffer management message drop policy ONE simulator NPBMT

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Broadcasting and Three List Subtraction 17th

Broadcasting and Three List Subtraction

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17th International Conference on Combinatorial Optimization and Applications, COCOA 2024

作者： Harutyunyan, Hovhannes A. Hovhannisyan, Narek Department of Computer Science and Software Engineering Concordia University MontrealQCH3G 1M8 Canada

ISBN: (纸本)9789819644476

Broadcasting is an information dissemination primitive where a message is passed from one node (called originator) to all other nodes in the network. In the scope of this paper, we will mainly focus on determining the broadcast time and the optimal broadcasting scheme for graphs. Determination of the broadcast time of a node in an arbitrary network is known to be NP-hard. Polynomial time solutions are known only for a few classes of networks. In this paper, we will consider networks that can be represented as k-path graphs. We will pose a new problem, called 3 list subtraction, and discuss its relation to the broadcast time problem on k-path graphs. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Interconnection networks (circuit switching)

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MLRaft: Improvement of Raft Based on Multi-log Synchronization Model 6

MLRaft: Improvement of Raft Based on Multi-log Synchronizati...

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6th International Conference on Electronic Information Technology and computer engineering, EITCE 2022

作者： Zhang, Menghao Xu, Lizhen Department of Software Engineering Southeast University Nanjing China Department of Computer Science and Engineering Southeast University Nanjing China

ISBN: (纸本)9781450397148

Raft is currently the most popular distributed consensus protocol. Due to the single leader mechanism of Raft, the performance of the distributed system is degraded to that of a single-machine system. Aiming at this shortcoming, this paper proposes a MLRaft protocol based on the multi-log synchronization model. MLRaft divides a single log file in Raft into n log files. For each log file, a leader can be elected to maintain the consistency of the log file. Multiple leaders jointly undertake the requests of the distributed system, which improves the performance of the distributed system and makes the entire cluster more balanced. At the same time, this paper also proposes the priority election method and the dynamic transfer mechanism of leader to ensure the uniform distribution of multiple leaders in distributed nodes. Finally, this paper built a 3-node KV storage system, and tested three aspects of throughput, latency, and load balance. The experimental results show that MLRaft has better performance than Raft. © 2022 Association for Computing Machinery.

关键词： consensus protocol distributed system multi leader Raft

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Advancements in Cybersecurity Using Deep Learning Techniques Attack Detection for Trojan Horses

Advancements in Cybersecurity Using Deep Learning Techniques...

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2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Hosanna Princye, P. Ahila, A. Lakshmi, A. Anna Ragavendran, N. Purushothaman, K.E. Uma Maheswari, G. Saravanakumar, R. Sri Sairam College of Engineering Department of Electronics and Communication Engineering Anekal Bangalore India R.M.K. Engineering College Department of Information Technology Tamil Nadu Chennai India RMK College of Engineering and Technology Department of Artificial Intelligence and Data Science Engineering Tamil Nadu Chennai India Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India RMK College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Software Analyst Iconix Software Solution Tamil Nadu Tirunelveli India

ISBN: (纸本)9798350378092

Today's computer networks are threatened by Trojan horse assaults and other cybersecurity dangers. We propose and evaluate deep learning methods using the Kaggle-hosted Trojan Detection dataset to detect Trojan horse assaults. This project uses these approaches. Our malware detection technology uses CNN classification for accuracy. We clean and enhance the dataset to make the model more versatile. Due to extensive testing and optimization, Trojan horse detection rates reach 98.47%. We found that the deep learning architecture accurately identifies malware. We also discuss CNN model features that illuminate Trojan horse attacks. The technique offers complete cyber security and expands our knowledge of harmful software. Deep learning may boost cybersecurity defenses against emerging attacks like Trojan horses, according to our study. © 2024 IEEE.

关键词： Cyber attacks

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Economical Requirements Elicitation Techniques During COVID-19: A Systematic Literature Review

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computers, Materials & Continua 2021年第5期67卷 2665-2680页

作者： Tauqeer ul Amin Basit Shahzad Fazal-e-Amin Muhammad Shoaib Department of Software Engineering National University of Modern LanguagesIslamabadPakistan Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia

Requirements elicitation is a fundamental phase of software development in which an analyst discovers the needs of different stakeholders and transforms them into *** phase is cost-and time-intensive,and a project may fail if there are excessive costs and schedule ***-19 has affected the software industry by reducing interactions between developers and *** a lack of interaction is a key reason for the failure of software *** can also fail when customers do not know precisely what they ***,selecting the unsuitable elicitation technique can also cause project *** present study,therefore,aimed to identify which requirements elicitation technique is the most cost-effective for large-scale projects when time to market is a critical issue or when the customer is not *** that end,we conducted a systematic literature review on requirements elicitation *** primary studies identified introspection as the best technique,followed by survey and *** finding suggests that introspection should be the first choice of elicitation technique,especially when the customer is not available or the project has strict time and cost ***,introspection should also be used as the starting point in the elicitation process of a large-scale project,and all known requirements should be elicited using this technique.

关键词： COVID-19 software engineering requirements engineering requirements elicitation introspection project failure SLR on elicitation techniques large-scale projects economical elicitation techniques costeffective time constraints

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Heterogeneous Domain Adaptation via Correlative and Discriminative Feature Learning

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IEEE Transactions on Multimedia 2025年 27卷 3447-3461页

作者： Lu, Yuwu Lin, Dewei Shen, Linlin Zhou, Yicong Pan, Jiahui South China Normal University School of Artificial Intelligence Foshan528225 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518055 China Shenzhen University Guangdong Key Laboratory of Intelligent Information Processing Shenzhen518060 China University of Nottingham Ningbo China Department of Computer Science Ningbo315100 China University of Macau Department of Computer and Information Science China

Heterogeneous domain adaptation seeks to learn an effective classifier or regression model for unlabeled target samples by using the well-labeled source samples but residing in different feature spaces and lying different distributions. Most recent works have concentrated on learning domain-invariant feature representations to minimize the distribution divergence via target pseudo-labels. However, two critical issues need to be further explored: 1) new feature representations should be not only domain-invariant but also category-correlative and discriminative, and 2) alleviating the negative transfer caused by the incorrect pseudo-labeling target samples could boost the adaptation performance during the iterative learning process. To address these issues, in this paper, we put forward a novel heterogeneous domain adaptation method to learn category-correlative and discriminative representations, referred to as correlative and discriminative feature learning (CDFL). Specifically, CDFL aims to learn a feature space where class-specific feature correlations between the source and target domains are maximized, the divergences of marginal and conditional distribution between the source and target domains are minimized, and the distances of inter-class distribution are forced to be maximized to ensure the discriminative ability. Meanwhile, a selective pseudo-labeling procedure based on the correlation coefficient and classifier prediction is introduced to boost class-specific feature correlation and discriminative distribution alignment in an iteration way. Extensive experiments certify that CDFL outperforms the state-of-the-art algorithms on five standard benchmarks. © 1999-2012 IEEE.

关键词： Contrastive Learning

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Implementation of Lean Management in software Project Management

Implementation of Lean Management in Software Project Manage...

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International Conference on Advancements in Computational Sciences (ICACS)

作者： Uzair Rasheed Sadia Khalid Mishal Muneer Israr Ahmad Ibraheem Khalil Faisal Masood Department of Computer and Software Engineering College of Electrical and Mechanical Engineering NUST Islamabad Pakistan

ISBN: (数字)9798331533038

ISBN: (纸本)9798331533045

Organizations normally focus on delivering the product that could earn maximum profit for the client. They do not focus on time, cost and quality. So the resultant product is of poor quality, over budget, over time, poorly satisfies the client’s requirements, and is high in cost. In this research paper, we will use lean concepts in software project management. It will not only remove all the waste in project management but also improve the project’s quality, time, and cost. We will also compare the project management concept with the lean project management concept and how combining these two will give us a perfect idea to increase software quality, reduce time, and deliver faster delivery. The only drawback is that current standards of software project management are not mature enough to adopt lean management to its extent.

关键词： Waste management Costs Standards organizations Decision making Project management software quality Organizations software reliability software development management

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DESIGN, MODELING AND SIMULATION OF CYBERCRIMINAL PERSONALITY-BASED CYBERATTACK CAMPAIGNS

DESIGN, MODELING AND SIMULATION OF CYBERCRIMINAL PERSONALITY...

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2024 Winter Simulation Conference, WSC 2024

作者： Shin, Jeongkeun Dobson, Geoffrey B. Carley, L. Richard Carley, Kathleen M. Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA United States Software and Societal Systems Department Carnegie Mellon University PittsburghPA United States

ISBN: (纸本)9798331534202

Cybersecurity challenges are inherently complex, characterized by both advanced technical elements and complex aspects of human cognition. Although extensive research has explored how victims’ human factors affect their susceptibility to cyberattacks, the influence of cybercriminals’ personalities on the pattern of cyberattack campaigns and the resulting damage to organizations has not received equivalent attention. To bridge this research gap through computer simulation, we introduce a cyberattack campaign designer that enables modelers to construct cyberattack campaigns. This tool allows modelers to define how the process or pattern of the cyberattack campaign can change based on the cybercriminal’s personality and simulates how these personality differences influence the magnitude of cyberattack damage on the target organization. In this paper, through computer simulation, we demonstrate how cautious and reckless personalities result in variations in the cyberattack pattern and, consequently, affect the magnitude of cyberattack damage, despite identical cyberattack objectives and techniques used at each step. © 2024 IEEE.

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MAiVAR-T: Multimodal Audio-image and Video Action Recognizer using Transformers 11

MAiVAR-T: Multimodal Audio-image and Video Action Recognizer...

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11th European Workshop on Visual Information Processing, EUVIP 2023

作者： Shaikh, Muhammad Bilal Chai, Douglas Shamsul Islam, Syed Mohammed Akhtar, Naveed Edith Cowan University School of Engineering Australia Edith Cowan University School of Science Australia The University of Western Australia Department of Computer Science & Software Engineering Australia

ISBN: (纸本)9798350342185

In line with the human capacity to perceive the world by simultaneously processing and integrating high-dimensional inputs from multiple modalities like vision and audio, we propose a novel model, MAiVAR-T (Multimodal Audio-Image to Video Action Recognition Transformer). This model employs an intuitive approach for the combination of audio-image and video modalities, with a primary aim to escalate the effectiveness of multimodal human action recognition (MHAR). At the core of MAiVAR-T lies the significance of distilling substantial representations from the audio modality and transmuting these into the image domain. Subsequently, this audio-image depiction is fused with the video modality to formulate a unified representation. This concerted approach strives to exploit the contextual richness inherent in both audio and video modalities, thereby promoting action recognition. In contrast to existing state-of-the-art strategies that focus solely on audio or video modalities, MAiVAR-T demonstrates superior performance. Our extensive empirical evaluations conducted on a benchmark action recognition dataset corroborate the model's remarkable performance. This underscores the potential enhancements derived from integrating audio and video modalities for action recognition purposes. To ensure transparency and reproducibility of our work, the source code is made publicly available at https://***/43do8DH. © 2023 IEEE.

关键词： Benchmarking

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Development of Day-Ahead Peer-to-Peer Energy Trading with Time-Series Clustering

Development of Day-Ahead Peer-to-Peer Energy Trading with Ti...

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2023 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices, ASEMD 2023

作者： Noorfatima, Nadya Jung, Jaesung Onen, Ahmet Yoldas, Yeliz Ajou University Department of Energy Systems Research Suwon Korea Republic of Sultan Qaboos University Department of Electrical and Computer Engineering Muscat Oman Kayseri University Department of Software Engineering Kayseri Turkey

ISBN: (纸本)9798350301571

Day-ahead trading of electricity has been applied to ensure the balance between the amount of electricity sold and bought. Even so, due to the intermittent distributed energy resources (DERs), the actual condition can be varied significantly, and forecasting can be costly in order to provide high accuracy to minimize losses. Hence, this paper proposes a novel model-based day-ahead peer-to-peer (P2P) energy trading with regionalized trading prices, which are determined through time-series clustering. To improve the determination of price regions, the data parameter is derived from the day-ahead condition, which is forecasted from network condition, trading capacity, and trading price of the P2P energy trading. The performance of the proposed model of day-ahead P2P energy trading is evaluated with respect to the market operation stability and optimality. © 2023 IEEE.

关键词： day-ahead trading distributed optimization Peer-to-peer energy trading time-series clustering

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