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Load Balancing to Optimize MPEG-DASH Video Streaming

Load Balancing to Optimize MPEG-DASH Video Streaming

引用

International conference on Information networking

作者： Edenilson Jônatas Dos Passos Adriano Fiorese Department of Computer Science (DCC) Graduate Program in Apllied Computing (PPGCAP) Santa Catarina State University (UDESC) Joinville Brazil

ISBN: (数字)9798331506940

ISBN: (纸本)9798331506957

Recent advancements in on-demand multimedia streaming have revealed the potential of this business model, driven by the convenience of accessing content anytime and anywhere. However, delivering a seamless user experience remains challenging due to the demanding nature of audiovisual streams, despite significant resource allocation. A promising solution involves using load balancers to distribute workloads evenly among processing units. This study proposes optimizing the processing and transmission resources by means of Software-Defined Networks (SDN). By continuously monitoring performance metrics like CPU usage and throughput, the SDN network controller determines the best server for handling new connections, even allowing seamless server migration during playback. The results show up to 80% faster response times and more consistent video quality, with reduced latency and uninterrupted playback. The approach also confirms the feasibility of SDN in streaming services, providing a foundation for future network improvements.

关键词： Transform coding Streaming media Load management User experience Quality assessment Servers Time factors Software defined networking Video recording Monitoring

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Capacity Improvement with NOMA-CI Precoding for MU-MISO Downlink Systems

Capacity Improvement with NOMA-CI Precoding for MU-MISO Down...

引用

International conference on computing, networking and Communications (ICNC)

作者： Yanfei Lu Qing Li Qinghe Gao Yingzhen Wu Yan Huo Tao Jing School of Electronics and Information Engineering Beijing Jiaotong University Beijing China

ISBN: (数字)9798350370997

ISBN: (纸本)9798350371000

In the communication process of the Internet of Things (IoT), non-orthogonal multiple access (NOMA) technology is usually used to improve spectrum efficiency and system capacity. However, due to the wide application of multimedia in the IoT, the high amount of data generated puts a higher demand on the system capacity. Each targeted user in a NOMA group uses successive interference cancellation (SIC) to decode useful information where the signals from other users are usually taken as interference, which hinders the improvement of the system capacity. In addition, the transmit power distribution between groups does not consider edge users, which affects the fairness of users. To solve above problems, we propose to combine the constructive interference (CI) precoding with NOMA by making the interference between users constructive for each NOMA user. Specifically, the NOMA-CI precoding is dedicatedly designed to improve the system capacity and a proportional power distribution scheme between NOMA groups is deployed to improve the capacity for edge users. We conduct extensive simulation experiments by comparing with existing schemes under different modulation methods, which demonstrate our scheme can improve the system capacity than the NOMA scheme by about 60% and achieve significant increase of the edge user capacity, enhancing the system fairness.

关键词： NOMA Interference cancellation Quadrature amplitude modulation Precoding Simulation multimedia systems Power distribution

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Compression-Based Image Retrieval for Efficient Networked Applications

Compression-Based Image Retrieval for Efficient Networked Ap...

引用

International conference on computing and networking Technology (ICCNT)

作者： T. Kuppuraj Paramjit Baxi N.T. Velusudha Samaksh Goyal P.S Pavan Jayashree V. Bagade Department of Computer Applications Karpagam Academy of Higher Education Coimbatore India Centre for Interdisciplinary Research for Business and Technology Chitkara University Institute of Engineering and Technology Punjab India Department of Electronics and Communication Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Quantum University Research Center Quantum University School of Engineering and Technology Civil Engineering JAIN (Deemed to be University) Bangalore Karnataka India Department of Information Technology Vishwakarma Institute of Information Technology Pune India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Compression-based total photograph retrieval (CBIR) is a method that is used to retrieve pictures from big datasets correctly. Unlike traditional photo retrieval methods, CBIR utilizes lossless or loss compression algorithms to lessen the scale of the image statistics for transmission over a network connection. That is particularly useful in programs wherein transmitting cumbersome image statistics is only sometimes viable. With the aid of compressing the facts related to a photo and sending only the compressed version, transmission instances are significantly decreased, even though nonetheless maintaining the visual first-rate and integrity of the photo. This makes CBIR a possible choice for packages consisting of streaming video, medical imaging, far-flung sensing, and massive-scale surveillance systems. CBIR also has packages in multimedia databases and different networked structures that require efficient image retrieval and viewing.

关键词： Visualization Image coding Accuracy Surveillance Image retrieval Streaming media multimedia databases Propagation losses Software Sensors

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Content Poisoning Attacks in Named Data Networks: Detection and Mitigation Approaches

Content Poisoning Attacks in Named Data Networks: Detection ...

引用

Electronics, computing, Communication and Control Technology (ICECCC), International conference on

作者： Annapurna P Patil Lalitha Chinmayee H M Bharadwaj Nagendiran Department of ISE Dayanand Sagar College of Engineering Affiliated to VTU Bengaluru INDIA Department of CSE Ramaiah Institute of Technology Affiliated to VTU Bengaluru INDIA Ramaiah Pre-University College Bengaluru INDIA

ISBN: (数字)9798350371802

ISBN: (纸本)9798350371819

With the increase in content-based communication in applications such as the web, multimedia streaming, social media, Internet of things etc., the content-based communication paradigm, ICN in general and NDN architecture in particular, is becoming popular. Although NDN has proved to be a potential replacement for IP host-based Internet, inherent security threats such as Content Poisoning Attacks (CPAs) pose a severe threat to communication. To tackle the issue, the research community has been discussing detection and mitigation methods of various scales. This paper is an attempt to bring out the state-of-the-art methods in CPA detection and mitigation and the analysis of the same concerning its overhead, latency, resiliency to malicious entities etc. The approach discussed in this work provides a better insight into the robust requirements of CPA detection and mitigation methods in the future.

关键词： Social networking (online) Prevention and mitigation Computer architecture Streaming media Service-oriented architecture Security multimedia communication

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Multimodal Enhanced Sentiment Analysis with Hierarchical Feature Extraction

Multimodal Enhanced Sentiment Analysis with Hierarchical Fea...

引用

International conference on Communications, Information System and Computer Engineering (CISCE)

作者： Sha Liu Shuyue Wang Bin Chen College of Information Engineering Yangzhou University Yangzhou China

ISBN: (数字)9798350353174

ISBN: (纸本)9798350353181

Multi-modal sentiment analysis (MSA), as a hot research topic in the fields of natural language processing, affective computing, and multimedia analysis, has gradually become an important method for sentiment analysis in social networks, especially in combining text and image modalities for data analysis. However, existing studies suffer from the issue of ineffective fusion of multimodal sentiment features. In this paper, we propose a method for multimodal enhanced sentiment analysis using hierarchical feature extraction (ME-SAHFE). When extracting text features using RoBERTa, our method further extracts features from each layer output by employing a Convolutional Neural Network (CNN) to enhance the representation capability of text features. Subsequently, the extracted text features are concatenated with image features and inputted into a multilayer perceptron (MLP) for effective fusion. Our method achieves significant improvements in accuracy, precision, recall, and F1 score in sentiment classification on the MVSA-Multi dataset.

关键词： Sentiment analysis Accuracy Data analysis Social networking (online) multimedia computing Computer architecture Multilayer perceptrons

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Enhancing multimedia Forwarding in Software- Defined Networks: An Optimal Flow Mechanism Approach

Enhancing Multimedia Forwarding in Software- Defined Network...

引用

Advancement in Computation & Computer Technologies (InCACCT), International conference on

作者： Pardeep Singh Tiwana Jaspreet Singh Computer Science & Engineering Chandigarh University Gharuan Mohali Punjab Chandigarh Engineering College-CGC Landran Mohali Punjab

ISBN: (数字)9798350371314

ISBN: (纸本)9798350371321

Software-defined networking (SDN) has revolutionized the way in which current modern networks are constructed. SDN offers dynamic and centralized administration resources that are available for the network, but multimedia traffic still a challenge on modern communication networks and it is very important to protect network systems that can reliably and effectively send multimedia data over the network form one end to another end. The goal of this new approach, which is called the Optimal Proposed Flow Mechanism (OPFM), is to make it easier for SDN (software-defined networking) devices to send multimedia data. This method of managing flow at the D-Plane involves the enforcement of device thresholds that are determined by the packet content of messages. By implementing this approach, not only are speed of response and computational efficiency improved, but processing delays are also reduced. The subsequent emphasis is on flow classification, which involves the categorization of incoming flows into delay-sensitive and nondelay-sensitive streams. A Non-Deep Lightweight Parallel Network (ND-LPN) is used for classification in software defined network and it has parallel layers that can manage flow delay limits, device efficiency, and service categorization. In the way to prevent packet loss while load balancing, this approach prioritizes flow classification in a computing efficient and latency-free manner. This means that traffic flow is sent to controllers according to their importance. The proposed method conducted in Network Simulator 3.2 and it makes the network work better by fixing flow management problems through more efficient methods for categorizing and transferring traffic in terms of network load and packet loss rate during flow forwardoing.

关键词： Computer network reliability Packet loss Load management Dynamic scheduling Delays multimedia communication Reliability

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A Distributed Task Allocation Methodology for Edge computing in a LEO Satellite IoT Context

A Distributed Task Allocation Methodology for Edge Computing...

引用

Advanced Satellite Mobile Systems (ASMS)

作者： Swapnil Sadashiv Shinde David Naseh Tomaso DeCola Daniele Tarchi CNIT - University of Florence Research Unit Firenze Italy Department of Electrical Electronic and Information Engineering "Guglielmo Marconi" University of Bologna Bologna Italy Institute of Communications and Navigation German Aerospace Center (DLR) Weßling Germany Department of Information Engineering University of Florence Firenze Italy

ISBN: (数字)9798331522353

ISBN: (纸本)9798331522384

The Internet of Things (IoT) is one of the most promising applications in the field of computer networking. Edge computing is a computationally efficient method for processing user data in a terrestrial-satellite hybrid environment, where each device is connected exclusively through a low-elevation (LEO) satellite. This paper focuses on an IoT context, introducing methodologies to effectively manage the computation-communication trade-off by strategically distributing processing tasks across various satellites. In particular, an adaptive load balancing approach is considered for efficient utilization of satellite resources. The proposed method can be implemented in a distributed manner, enabling each satellite to evaluate its task handling capacity and forward tasks if it is beyond its capability. The numerical results demonstrate the effectiveness of the proposed method compared to conventional fixed allocation and cloud processing methodologies.

关键词： Cloud computing Satellites Space communications multimedia systems Low earth orbit satellites Signal processing Load management Internet of Things Resource management Edge computing

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Enhancing Cyber Security Through Phish-Net -An Artificial Neural Network for Phishing Detection

Enhancing Cyber Security Through Phish-Net -An Artificial Ne...

引用

Network, multimedia and Information Technology (NMITCON) International conference on

作者： M Diviya K Jyoshika Shri D Gopala Krishnan Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India

ISBN: (数字)9798350372892

ISBN: (纸本)9798350372908

The widespread development of internet technology has made life easier in many ways, such as social networking, online banking, and information retrieval. But this growth has also brought forth a multitude of security risks, one of which is phishing, which has become a major worry. Phishing attacks employ websites that seem similar to authentic ones to obtain sensitive user data illegally, especially by using phony URLs. Finding malicious URLs is one of cybersecurity’s biggest challenges. The potential losses in money resulting from phishing make it imperative to create efficient methods for detecting phishing websites. To tackle such problems, Phish-Net has been proposed using 3-layered Artificial Neural Network by fine tuning the hyperparameter that is used to catch the phishing sites and also assessed the classifier’s effectiveness using a large dataset. The suggested strategy surpasses current approaches in accuracy, obtaining 98.0% and further study in this field can enhance their functionality and aid in protecting against online dangers.

关键词： Accuracy Social networking (online) Online banking Phishing Artificial neural networks Security Computer crime Information technology Tuning

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ASMMC21: The 6th International Workshop on Affective Social multimedia computing 21

ASMMC21: The 6th International Workshop on Affective Social ...

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23rd ACM International conference on Multimodal Interaction, ICMI 2021

作者： Huang, Dongyan Schuller, Björn Tao, Jianhua Xie, Lei Yang, Jie Ubtech Robotics United States Ieee United States National Laboratory of Pattern Recognition China Northwestern Polytechnical University China Iis Nsf United States

ISBN: (纸本)9781450384810

Affective social multimedia computing is an emergent research topic for both affective computing and multimedia research communities. Social multimedia is fundamentally changing how we communicate, interact, and collaborate with other people in our daily lives. Comparing with well-organized broadcast news and professionally made videos such as commercials, TV shows, and movies, social multimedia media computing imposes great challenges to research communities. Social multimedia contains much affective information. Effective extraction of affective information from social multimedia can greatly help social multimedia computing (e.g., processing, index, retrieval, and understanding). Although much progress have been made in traditional multimedia research on multimedia content analysis, indexing, and retrieval based on subjective concepts such as emotion, aesthetics, and preference, affective social multimedia computing is a new research area. The affective social multimedia computing aims to proceed affective information from social multi-media. For massive and heterogeneous social media data, the research requires multidisciplinary understanding of content and perceptual cues from social multimedia. This workshop served as a successful step towards this goal and attracted contributions from different research disciplines on the analysis of affective signals in interaction (multimodal analyses enabling artificial agents in Human-Machine Interaction, social Interaction with artificial agents) and social multimedia (e.g., twitter, wechat, weibo, youtube, facebook, etc). This paper provides a summary of the activities of the workshop and the accepted papers and abstracts. © 2021 Owner/Author.

关键词： Social networking (online)

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Arabic hate speech detection system based on AraBERT 21

Arabic hate speech detection system based on AraBERT

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21st IEEE International conference on Cognitive Informatics and Cognitive computing, ICCI*CC 2022

作者： Salomon, Pale Ollo Kechaou, Zied Wali, Ali Higher Institute of Computer Science and Multimedia of Sfax sfax Tunisia sfax Tunisia

ISBN: (纸本)9781665490849

Tunisia has entered a phase freedom of speech with access to social media since the Jasmine Revolution in 2011. Toxic contents such as abusive and hateful speeches have become omnipresent on Tunisian social media. Considering the side effects of these toxic contents on the psychology of users, it is necessary to detect them automatically. The dialect of Tunisian is underrepresented. As a consequence, there is not enough data set. In this paper, we present the data collection process with the aim of having a Tunisian reference dataset, to evaluate different models of hate speech and abuse detection. We also present our neural network model based on AraBERT. Our experimental results on our dataset shows that the AraBERT model performs better with an F1 score of 0.99. © 2022 IEEE.

关键词： Social networking (online)

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