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Experimental Studies of the Complex Method of Increasing the Load Processing Efficiency in distributed Data Centers

Experimental Studies of the Complex Method of Increasing the...

引用

2023 IEEE international Black Sea conference on Communications and networking, BlackSeaCom 2023

作者： Globa, Larysa Raichuk, Andrii Gvozdetska, Nataliia Igor Sikorsky Kyiv Politechnic Institute Institute of Telecomunication System Kyiv Ukraine

ISBN: (纸本)9798350337822

In this paper, the experimental studies for increasing the load processing efficiency in distributed data centers of communication operators are presented. The communication operators widely use the up-to-day technologies function virtualization such as NFV, SDN, Network Slicing, Edge computing, and bDDN, which require a significant amount of calculations, and accordingly consume significant amounts of energy during load processing in data centers. Existing approaches do not provide simultaneous improvements in energy efficiency and performance while meeting SLA requirements. To ensure energy-efficient data processing and improve its processing performance, while maintaining the quality of SLA requirements, an approach was proposed, the essence of which is to take into account the daily load and allocate data processing resources in such a way as to minimize energy consumption and not lose performance during processing. When comparing the proposed approach with Backfill load planning, it was possible to determine an increase in energy efficiency indicators up to 9.953%, and up to 26.382% in comparison with Round Robin. © 2023 IEEE.

关键词： Energy utilization

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Application and Energy-Aware Data Aggregation using Vector Synchronization in distributed Battery-less IoT Networks 24

Application and Energy-Aware Data Aggregation using Vector S...

引用

25th international conference on distributed computing and networking, ICDCN 2024

作者： Singhal, Chetna Barick, Subhrajit Sonkar, Rishabh Kharagpur India Iit Kharagpur India

ISBN: (纸本)9798400716737

The battery-less Internet of Things (IoT) devices are a key element in the sustainable green initiative for the next-generation wireless networks. These battery-free devices use the ambient energy, harvested from the environment. The energy harvesting environment is dynamic and causes intermittent task execution. The harvested energy is stored in small capacitors and it is challenging to assure the application task execution. The main goal is to provide a mechanism to aggregate the sensor data and provide a sustainable application support in the distributed battery-less IoT network. We model the distributed IoT network system consisting of many battery-free IoT sensor hardware modules and heterogeneous IoT applications that are being supported in the device-edge-cloud continuum. The applications require sensor data from a distributed set of battery-less hardware modules and there is provision of joint control over the module actuators. We propose an application-aware task and energy manager (ATEM) for the IoT devices and a vector-synchronization based data aggregator (VSDA). The ATEM is supported by device-level federated energy harvesting and system-level energy-aware heterogeneous application management. In our proposed framework the data aggregator forecasts the available power from the ambient energy harvester using long-short-term-memory (LSTM) model and sets the device profile as well as the application task rates accordingly. Our proposed scheme meets the heterogeneous application requirements with negligible overhead;reduces the data loss and packet delay;increases the hardware component availability;and makes the components available sooner as compared to the state-of-the-art. © 2024 ACM.

关键词： Internet of things

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SCORING: Towards Smart Collaborative computing, caching and networking paradIgm for Next Generation communication infrastructures 31

SCORING: Towards Smart Collaborative cOmputing, caching and ...

引用

31st international conference on Computer Communications and Networks (ICCCN)

作者： Hmitti, Zakaria Ait Ben Ammar, Hamza Soyak, Ece Gelal Kardjadja, Youcef Malektaji, Sepideh Ali, Soukaina Ouledsidi Rayani, Marsa Saqib, Muhammad Taghizadeh, Seyedreza Ajib, Wessam Elbiaze, Halima Ercetin, Ozgur Ghamri-Doudane, Yacine Glitho, Roch Univ Quebec Montreal Montreal PQ Canada La Rochelle Univ La Rochelle France Sabanci Univ Istanbul Turkey Concordia Univ Montreal PQ Canada Bahcesehir Univ Istanbul Turkey

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

The unprecedented increase of heterogeneous devices connected to the Internet, along with tight requirements of future networks, including 5G and beyond, poses new design challenges to network infrastructures. Collaborative computing, caching and communication paradigm together with artificial intelligence have the potential to enable the Next-Generation networking Infrastructure (NGNI) that is needed to fulfill the stringent requirements of emerging applications. In this paper, we propose the SCORING project vision for reshaping the current network infrastructure towards an NGNI acting as a truly distributed, collaborative, and pervasive system that enables the execution of application-specific tasks and the storage of the related data contents in the Cloud-Edge-Mist continuum with high QoS/QoE guarantees.

关键词： NGNI Cloud Edge QoS/QoE distributed computing

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DDoS Attack Detection System for IoT Enabled Smart City Applications with Correlation Analysis 4

DDoS Attack Detection System for IoT Enabled Smart City Appl...

引用

4th international conference on Advances in Electrical, computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Nirosha, Veeramachaneni Hemamalini, V. Srm Institute of Science and Technology Department of Networking and Communication Kattankulathur India

ISBN: (纸本)9798350343670

The topic of cybersecurity remains a significant concern for industries involved in digital operations, as seen by the recurring increase in security incidents. The increasing use of Internet of Things (IoT) devices in various settings such as homes, offices, transportation, and healthcare has resulted in a corresponding rise in the frequency of malicious assaults. Machine Learning (ML) is frequently utilized for the purpose of detecting attacks on IoT devices. This study presents a novel approach to cybersecurity-focused network traffic correlation analysis and the detection of distributed Denial of Service (DDoS) attacks using artificial intelligence techniques in the context of an IoT-enabled smart city, with the aim of promoting sustainability. A traffic analysis was conducted by utilizing a wireshark network analyser tool, which effectively improves data transmission. The experimental investigation was conducted to evaluate various performance metrics, including accuracy, precision, recall, attack detection rate and time. The proposed technique achieved anaccuracy rate of 96%, precision and recall rates are 93.6% and 91% respectively. © 2024 IEEE.

关键词： correlation analysis Cyber security DDoS attack smart city

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Multi-Carrier (OFDM) Cooperative Transmission in MANETs with Multiple Carrier Frequency Offsets 18

Multi-Carrier (OFDM) Cooperative Transmission in MANETs with...

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18th international conference on Wireless and Mobile computing, networking and Communications (WiMob)

作者： Yuksel, Mus'ab Rolny, Raphael T. L. Kuhn, Marc Kuhn, Michael Hsch Darmstadt Darmstadt Germany Armasuisse Sci & Technol Thun Switzerland ZHAW Winterthur Switzerland

ISBN: (数字)9781665469753

ISBN: (纸本)9781665469753

Cooperative transmission, realized by aggregating several nodes to a virtual multiple input system, is an auspicious approach to establish a more robust and effective communication in MANETs. In such a setup, impairments, i. e. multiple timing and carrier frequency offsets (TO, CFO) will occur. While multi-carrier schemes, e. g. Orthogonal Frequency Division Multiplexing (OFDM), are well-known to mitigate the impact of multipath propagation and TO, multiple CFO causes inter-carrier-interference (ICI) which typically degrades the performance significantly. Within this paper, we propose an effective code and equalizer structure that allows to overcome this limitation. It mitigates the impact of multiple CFO that can be significantly larger than the subcarrier spacing with a reasonable computational effort. For that, we utilize inherent code properties of Linear-Scalable Dispersion Codes (LSDCs) and propose a communication system composed of an equalizer structure in combination with LSDCs that enables multi-carrier distributed cooperative transmission for practical MANETs with high node mobility. We demonstrate the benefits of cooperative transmission in comparison to classical non-cooperative multi-hop or concurrent transmission by outage simulations, which clearly indicate that our proposal can be of crucial importance for the overall MANET scalability. Lastly, we compare our OFDM system with a recently proposed time-domain equalization single-carrier system and point out use cases, where the OFDM system can be more advantageous.

关键词： MANET Scalability distributed Cooperative Transmission (Broadcasting) Space-Time Block Codes (STBC) Carrier Frequency Offset (CFO) Timing Offset (TO) OFDM

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distributed Quantum computing in Dynamic Environments: Concept and Challenges

Distributed Quantum Computing in Dynamic Environments: Conce...

引用

Quantum Communications, networking, and computing (QCNC), international conference on

作者： Seng W. Loke School of Information Technology Deakin University Burwood VIC Australia

This paper discusses distributed quantum computing in dynamic environments where conditions on quantum nodes might change causing original qubit allocations on distributed quantum workers to be further from optimal, a... 详细信息

ISBN: (数字)9798331531591

ISBN: (纸本)9798331531607

关键词： Degradation Sensitivity Computational modeling Qubit Logic gates Dynamic scheduling Resource management Integrated circuit modeling Quantum communication Periodic structures

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MetaWBC: POSIX-Compliant Metadata Write-Back Caching for distributed File Systems

MetaWBC: POSIX-Compliant Metadata Write-Back Caching for Dis...

引用

international conference for High Performance computing, networking, Storage and Analysis (HPC)

作者： Qian, Yingjin Cheng, Wen Zeng, Lingfang Vef, Marc-Andre Drokin, Oleg Dilger, Andreas Ihara, Shuichi Zhang, Wusheng Wang, Yang Brinkmann, Andre Data Direct Networks DDN Shanghai Peoples R China HUST Wuhan Peoples R China Zhejiang Lab Hangzhou Peoples R China Johannes Gutenberg Univ Mainz Mainz Germany Whamcloud Inc Los Angeles CA USA Whamcloud Inc Calgary AB Canada Data Direct Networks DDN Tokyo Japan Tsinghua Univ Beijing Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China

ISBN: (纸本)9781665454445

In parallel and distributed file systems, caching can improve data performance and metadata operations. Currently, most distributed file systems adopt a write-back data cache for performance and a write-through metadata cache for simplifying consistency. However, with modern file systems scales and workloads, write-through metadata caching can impact overall file system performance, e.g., through lock contention and heavy RPC loads required for namespace synchronization and transaction serialization. This paper proposes a novel metadata write-back caching (MetaWBC) mechanism to improve the performance of metadata operations in distributed environments. To achieve extreme metadata performance, we developed a fast, lightweight, and POSIX-compatible memory file system as a metadata cache. Further, we designed a file caching state machine and included other performance optimizations. We coupled MetaWBC with Lustre and evaluated that MetaWBC can outperform the native parallel file system by up to 8x for metadata-intensive benchmarks, and up to 7x for realistic workloads in throughput.

关键词： File system metadata write-back caching data-intensive application Lustre

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Optimizing distributed networking with Big Data Scheduling and Cloud computing

Optimizing Distributed Networking with Big Data Scheduling a...

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2022 international conference on Cloud computing, Internet of Things, and Computer Applications, CICA 2022

作者： Zhu, Wenbo College of Arts and Science New York University New YorkNY10003 United States

ISBN: (纸本)9781510656673

With the rapid transformation of computer hardware and algorithms, mobile networking has evolved from low data-carrying capacity and high latency to better-optimized networks, either by enhancing the digital network or using different approaches to reduce network traffic. This paper discusses the big data applications and scheduling in the distributed networking and analyzes the opportunities and challenges of data management systems. The analysis shows that the big data scheduling in the cloud computing environment produces the most efficient way to transfer and synchronize data. Since scheduling problems and cloud models are very complex to analyze in different settings, we set it to the typical software defined networks. The development of cloud management models and coflow scheduling algorithm is proved to be the priority of the digital communications and networks development in the future. © 2022 SPIE.

关键词： Big data

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A Novel Evolutionary Neural Network-based Approach for Online Bus Scheduling 21

A Novel Evolutionary Neural Network-based Approach for Onlin...

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21st international conference on networking, Sensing and Control, ICNSC 2024

作者： Tian, Wenyang Wang, Feiyang Zuo, Xingquan School of Computer Science Beijing University of Posts and Telecommunications Beijing China Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing China

ISBN: (纸本)9798350365221

Bus scheduling is vital to ensure service quality and save operational costs. Current studies typically consider the problem as an optimization problem and solve it using exact or heuristic approaches. In this paper, we consider the problem as a sequential decision-making problem and propose an Evolutionary Neural Network-based Approach (ENNA) for it. A neural network is used to make a decision at each departure time in the bus timetable. It selects which bus should depart at that specific time. By this means, a complete bus scheduling scheme is generated by a series of decisions made by the neural network. The structure and weights of the neural network are optimized by a genetic algorithm. To meet the real-world operational needs of bus duty types and improve bus utilization, we design a bus duty type transition rule that dynamically decides the duty type of buses. Experimental results demonstrate that the proposed ENNA outperforms manual scheduling schemes and can generate bus scheduling schemes with fewer buses. © 2024 IEEE.

关键词： Genetic algorithms

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SNPD 2024 Summer international Program Committee

SNPD 2024 Summer International Program Committee

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ACIS international conference on Software Engineering, Artificial Intelligence, networking, and Parallel/distributed computing (SNPD)

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