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BCLB: A Scalable and Cooperative Layer-4 Load Balancer for Data Centers 44

BCLB: A Scalable and Cooperative Layer-4 Load Balancer for D...

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44th IEEE international conference on distributed computing Systems (ICDCS)

作者： Yang, Shu Wu, Xinze Cui, Laizhong Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen Peoples R China

ISBN: (纸本)9798350386066;9798350386059

Nowadays, load balancing is more and more important for huge data centers. Most data centers usually adopt a software-based load balancer (LB), which consumes too many server resources and does not scale with the increasing traffic volume. However, there is an increased demand for layer-4 load balancers, which need to check more bits in packet headers. Although hardware-based load balancers can meet the requirements, they are much more expensive. During the past years, data centers frequently update their devices, including kinds of switches. thus, there exists a huge number of obsolete switches, some of which are in good condition and equipped with high-performance storage like SRAM (Static Random Access Memory). In this paper, we proposed BCLB (Bit-based Collaborative Load Balancer), a new cooperative LB, which builds more powerful load balancing based on existing switches. Different with previous cooperative mechanisms that distribute rules to different LBs, BCLB lets switches cooperate based on bits. Many switches along the data path check different bits, and cooperatively check all bits in 5-tuple (which would be 296 bits in IPv6) for layer-4 packet header. In this way, rule updating will not influence the load balancing in BCLB. To optimize the performance of BCLB, we formulate the problem as an optimization problem, then we propose a dynamic programming algorithm to solve it. Finally, we conduct comprehensive simulations using both real-world traffic datasets and a P4-based prototype, the results show that BCLB performs much better than previous rule-based cooperative schemes.

关键词： data center distributed lookup five-tuple load balancing programmable switch

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An Optimized Design of RIS-assisted Ambient internet of things for Heterogeneous Networks 2

An Optimized Design of RIS-assisted Ambient Internet of Thin...

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2nd international conference on Mobile internet, Cloud computing and Information Security (MICCIS)

作者： Zhang, Shuhao Cheng, Bo Ma, Xiangchen Zhang, Ziyang Ma, Ying Li, Huijun Zhou, Weitong China Mobile Grp Design Inst Beijing Peoples R China China Mobile Commun Grp Beijing Peoples R China Harbin Engn Univ Harbin Peoples R China

ISBN: (纸本)9798350389913;9798350389906

Ambient internet of things (A-IoT), which harnesses ambient backscatter communication, has emerged as a critical technology for sixth-generation (6G) mobile networks. In this study, we introduce a novel heterogeneous network-oriented system that integrates reconfigurable intelligent surfaces (RIS) with A-IoT devices. the system's complexity arises from the highly obstructed environments where signals undergo multiple reflections via the IRS before reaching the receiver, resulting in a non-trivial optimization challenge. To tackle this issue, we propose a sophisticated alternating optimization algorithm that leverages machine learning principles to approximate the optimal solution for maximizing system throughput. Our analysis assumes Rayleigh-distributed channel gains for both forward and backscatter links. through rigorous numerical analysis and simulation, we delve into the intricacies of how various system parameters impact rate performance. the simulation results reveal that the integration of RIS in A-IoT systems significantly reduces the required transmit power at base stations while enhancing the overall communication efficiency. Furthermore, our proposed algorithm exhibits superior performance when compared to existing methods, achieving comparable optimization results with reduced computational overhead. this underscores its potential for enabling cost-effective, energy-efficient, and low-complexity communication solutions in future 6G networks.

关键词： component 6G wireless communication ambient internet of things reconfigurable Intelligent surface deep reinforcement learning

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Partitioning-based Active Trust Mechanism in Cloud-Edge-Device Collaborative Data Collection 21

Partitioning-based Active Trust Mechanism in Cloud-Edge-Devi...

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21st IEEE international Symposium on Parallel and distributed Processing with Applications, 13th IEEE international conference on Big Data and Cloud computing, 16th IEEE international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Xia, Zhuoqun Wang, Ziyu Liu, Xiao Changsha University of Science and Technology School of Computer and Communication Engineering Changsha China Guangxi University School of Computer Electronics and Information Nanning China

ISBN: (纸本)9798350329223

Since the open character of the internet of things (IoT), IoT devices are vulnerable to various attacks. Compromised devices may maliciously provide unreliable data to the cloud. Furthermore, existing trust evaluation models struggle to balance data security needs across different regions. To address this issue, the paper proposes a partition-based active trust mechanism (PATM). this PATM scheme mainly includes the following parts: First, the region is divided into subregions, and evaluations are conducted for the indicators of each subregion. Mechanism modeling and fuzzy analytic hierarchy process are used to analyze the impact of each indicator on the sensitivity of subregions. Second, the direct estimation method is utilized to estimate the demand for active detection routing based on the sensitivity of subregions. then, the number of operations of malicious nodes is increased through the high-frequency transmission of detection routes required by each subregion. Additionally, a trust calculation method based on node operations is proposed to evaluate the reliability of the device. the experimental results show that the PATM scheme proposed in this article can quickly identify the trust degree of nodes while balancing the needs of different regions, ensuring the credibility of data collection. © 2023 IEEE.

关键词： internet of things

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Design of Structural routing optimization of Bluetooth Mesh networks for multi-scenario applications in distributed smart grid 6

Design of Structural routing optimization of Bluetooth Mesh ...

引用

6th international conference on Wireless Communications and Smart Grid, ICWCSG 2024

作者： Tang, Delong Xiao, Zhenfeng Min, Rui Changsha University of Science and Technology ChangSha410000 China State Grid Hunan Electric Power Company Limited Economic Technical Research Institute ChangSha410000 China

ISBN: (纸本)9781510682962

Due to the characteristic of low-power, the bluetooth mesh network has a great potential in distributed smart grids due to their low-powers. However, due to duplicate forwarding brought on by data broadcasting, traditional routing protocols based on flooding algorithms increase energy consumption. It is obviously unsustainable for battery-powered mesh networks relying on battery power that handlea large amount of data. therefore, this study designs a novel routing protocol for multi-node, multi-level tree network topology for the specific needs of battery-powered device-dependent nodes in distributed smart grids for multiple application scenarios such as environmental monitoring. the routing protocol is designed by abstracting and analyzing the wireless self-organizing network topology in different scenarios and optimizing the design based on this topological abstraction. Simulation results show that the proposed protocol reduces the energy consumption of sensor nodes by 52.8% compared to the traditional Bluetooth Mesh, and improves the communication reliability at the same time. this improvement provides a new technical path for the wide deployment of Bluetooth Mesh networks in battery-powered smart grid applications. © 2024 SPIE.

关键词： Trees (mathematics)

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internet of things Challenges and the Emerging technology of TinyML 19

Internet of Things Challenges and the Emerging Technology of...

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19th Annual international conference on distributed computing in Smart Systems and the internet of things, DCOSS-IoT 2023

作者： Tsoukas, Vasileios Gkogkidis, Anargyros Kakarountas, Athanasios University of Thessaly Intelligent Systems Laboratory Department of Computer Science and Biomedical Informatics Lamia Greece

ISBN: (纸本)9798350346497

the merger of internet of things (IoT) and Machine Learning undoubtedly offers several benefits, but due to the nature of IoT devices and their underlying design, a number of difficulties and challenges exist. the most fundamental of these has to do with the security dangers posed by the transmission of voluminous amounts of data, as well as several networking obstacles, such as delay and bandwidth constraints. Moving all processing close to the network's edge and preventing the transmission of data to third parties, such as the cloud or other devices, is a potential solution. Embedded Machine Learning, and TinyML in particular, is a new technology that allows the implementation of Machine Learning on hardware with limited resources, such as Microcontrollers and FPGAs. In this paper, the fundamental issues of IoT devices are examined, the TinyML technology's advantages are outlined, and a summary of the most recent TinyML apps and systems is offered. © 2023 IEEE.

关键词： Microcontrollers

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Trust-Based Secure Task Offloading in Digital Twin Empowered Vehicular Edge computing 6

Trust-Based Secure Task Offloading in Digital Twin Empowered...

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6th international conference on Pattern Analysis and Intelligent Systems, PAIS 2024

作者： Bounaira, Soumaya Alioua, Ahmed Souici, Ismahane University of Jijel LaRIA Laboratory Jijel18000 Algeria University of Jijel Faculty of Exact Sciences And Computer Science Jijel18000 Algeria University of Jijel Laoti Laboratory Jijel18000 Algeria

ISBN: (纸本)9798350350265

Task offloading in Vehicle Edge computing (VEC) refers to the process whereby computational tasks generated by a vehicle are transferred to and executed by edge servers. this process aims to optimize performance and reduce the vehicle's computational load by exploiting edge servers' computational capabilities. However, the lack of trust between participating entities and the unreliability of communication channels cause various threats on communication and data exchange. Motivated by this discussion, in this paper, we present a framework integrating blockchain and digital twin (DT) to secure task offloading operations from mobile vehicles to edge servers. the framework first presents a novel DT-enabled computation offloading model that facilitates and minimizes the cost of communication between physical entities. Secondly, we propose a trust evaluation system based on subjective logic that considers temporal correlation and focuses on current behavior for the calculation of entity reputation. To ensure reliable management of reputation score values, we have used blockchain to store these scores in a distributed and immutable manner. Intensive experimentation has demonstrated the good performance of the proposed framework in terms of early detection of malicious nodes, reliable offloading communications, and high data confidentiality thanks to DT and blockchain. © 2024 IEEE.

关键词： Blockchain

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D-Alarm: An Efficient Driver Drowsiness Detection and Alarming System 6

D-Alarm: An Efficient Driver Drowsiness Detection and Alarmi...

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6th IEEE international conference on Advances in Science and technology, ICAST 2023

作者： Borah, Biju Mukherjee, Shyamapada National Institute of Technology Silchar Department of Electrical Engineering Assam 788010 India National Institute of Technology Rourkela Department of Computer Science and Engineering Odisha 769008 India

ISBN: (纸本)9798350359817

In the coming years, the demand for IoT devices connecting our homes, cities, and industries will grow significantly. We now inhabit a world where interconnected smart devices can be controlled through single commands, fostering an era of automation, particularly in smart homes. IoT is at the forefront of this transformation, with many of these devices relying on machine learning models to decode data and make accurate predictions. However, as the number of connected devices escalates, network congestion becomes a challenge. To address this, incorporating machine learning intelligence into edge devices is essential. Edge computing, which involves processing data closer to its source, reduces latency and enables faster analysis. Consequently, IoT data can be gathered and processed at the edge, reducing the reliance on cloud-based solutions. Yet, deploying machine learning models on small IoT microcontroller units presents memory and computation constraints. this paper introduces a deep learning model for driver engagement recognition in real-time video streams, alongside optimization techniques for deployment on edge devices like Nvidia Jetson. the goal is to facilitate the execution of machine learning models on compact, low-power integrated circuits, addressing this critical bottleneck. © 2023 IEEE.

关键词： internet of things

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Specification and Operation of Privacy Models for Data Streams on the Edge 6

Specification and Operation of Privacy Models for Data Strea...

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6th IEEE international conference on Fog and Edge computing (ICFEC)

作者： Sedlak, Boris Murturi, Ilir Dustdar, Schahram Vienna Univ Technol Distributed Syst Grp Vienna Austria

ISBN: (纸本)9781665495240

the growing number of internet of things (IoT) devices generates massive amounts of diverse data, including personal or confidential information (i.e., sensory, images, etc.) that is not intended for public view. Traditionally, predefined privacy policies are usually enforced in resource-rich environments such as the cloud to protect sensitive information from being released. However, the massive amount of data streams, heterogeneous devices, and networks involved affects latency, and the possibility of having data intercepted grows as it travels away from the data source. therefore, such data streams must be transformed on the IoT device or within available devices (i.e., edge devices) in its vicinity to ensure privacy. In this paper, we present a privacy-enforcing framework that transforms data streams on edge networks. We treat privacy close to the data source, using powerful edge devices to perform various operations to ensure privacy. Whenever an IoT device captures personal or confidential data, an edge gateway in the device's vicinity analyzes and transforms data streams according to a predefined set of rules. How and when data is modified is defined precisely by a set of triggers and transformations - a privacy model - that directly represents a stakeholder's privacy policies. Our work answered how to represent such privacy policies in a model and enforce transformations on the edge.

关键词： Edge computing Privacy Models Data Stream Transformations Data Anonymization

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An Intelligent Security Systems in Cloud computing using Cryptography Techniques 5

An Intelligent Security Systems in Cloud Computing using Cry...

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5th international conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Srilakshmi, V. Chetana, V. Lakshmi Dornala, Raghunadha Reddi Vallabaneni, S. Parvathi Ramanjaiah, Ganji School of Computer Science and Engineering Vit -AP University Andhra Pradesh Amaravati522237 India School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Amaravati Campus India Walgreens United States Pvp Siddhartha Institute of Technology Department of It Vijayawada India R v Institute of Technology Dept.of Cse Guntur India

ISBN: (纸本)9798350379945

Delivering computing resources over the internet has seen a paradigm shift towards cloud computing. However, there are serious security risks because cloud environments are distributed and shared. Intelligent Security Systems (ISS) that use cryptographic techniques are now necessary to overcome these issues, such as data confidentiality, integrity, and authenticity;this study developed an ISS for cloud computing, concentrating on cryptographic techniques. the RSA-OAEP (Optimal Asymmetric Encryption Padding) and X.509 algorithms are combined to create the ISS and further cover a variety of cryptographic methods, emphasizing their functions in protecting cloud-based systems, including encryption, digital signatures, and key management. It also looks at improving security systems' threat detection and response capabilities by integrating artificial intelligence (AI) algorithms like Grubbs' Test. In addition, several issues and potential paths for intelligent security systems in cloud computing are examined, highlighting the necessity of ongoing study and development to remain ahead of developing cyber threats. © 2024 IEEE.

关键词： Cloud security

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Sixth international conference on Intelligent computing, Communication, and Devices, ICCD 2023

Sixth International Conference on Intelligent Computing, Com...

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6th international conference on Intelligent computing, Communication, and Devices, ICCD 2023

ISBN: (纸本)9781510666252

the proceedings contain 106 papers. the topics discussed include: simulation of apron taxiway layout pattern in the new terminal area of Nanning airport;joint source-channel coding based on polar code;lithium battery transport test analysis and equipment optimization exploration;scenario based intelligent desensitization and dynamic access control technology for power distribution and distributed new energy data resources;research and implementation of a traceability algorithm for electric distribution data resources considering distributed new energy;research and implementation of key technologies for electric distribution data analysis;research on the influence of artificial intelligence technology based on big data analysis on modern art creation;research and implementation of grid based on electric distribution network composite evaluation method;application status and development of artificial intelligence technology in large data center;and research on protection monitoring and early warning technology of power time synchronization system.

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