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11th International conference on Future internet of Things and Cloud

作者： Veloso, Artur F. da S. Abreu, Pedro F. F. da Silva, Thiago A. R. Neto, Geraldo A. S. Mendes, Luis H. de O. Junior, Jose V. R. Univ Fed Piaui Teresina PI Brazil

ISBN: (纸本)9798331527204;9798331527198

This study addresses the optimization challenge of Smart Grid (SG) and Microgrid (MG) networks, aiming to reduce the number of Data Aggregation Points (DAPs) and Concentrators (CONs) required to ensure an efficient and sustainable grid. Within this context, an optimization model is proposed that aims to balance network quality with cost reduction, while ensuring superior performance compared to conventional SG networks. The proposed approach involves implementing a decentralized architecture, with an emphasis on integrating residential DAPs, enabling a granular analysis of energy consumption and generation data, and facilitating the implementation of advanced energy control and optimization strategies at the local level. The main contributions include the development of a hybrid network model, a network planning model for positioning CONs and DAPs, an optimization model for minimizing DAPs and CONs and the proposal of a large-scale network planning model. As main results, we highlight a significant reduction in DAPs, with a decrease of up to 5 units, and a reduction in CONs, with a decrease of up to 2 units. These numbers demonstrate the effectiveness of the proposed model in achieving a more efficient and adaptable electrical infrastructure, representing a significant step towards a smart and sustainable energy network.

关键词： network Planning Smart Grid Neural networks LoRaWAN NS-3 Simulation

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Link quality Estimation in Wireless Software Defined network with a Reliable control Plane 9

Link Quality Estimation in Wireless Software Defined Network...

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9th IEEE International conference on network Softwarization (IEEE NetSoft) - Boosting Future networks through Advanced Softwarization

作者： Veisi, Farzad Montavont, Julien Theoleyre, Fabrice Univ Strasbourg CNRS ICube Pole API F-67412 Illkirch Graffenstaden France

ISBN: (纸本)9798350399806

The Industrial internet of Things (IIoT) has now emerged for many industrial applications. However, many critical applications require high reliability and bounded end-toend latency. Fortunately, scheduled wireless networks such as IEEE 802.15.4-TSCH try to orchestrate finely the transmissions. In particular, the Software-Defined networking (SDN) paradigm is promising to concentrate the intelligence of the network in a controller and to simplify the functions achieved by the motes. SDN controller relies on link quality information of wireless devices to construct the routing topology of the network and to provision adequate radio resources for each link. We propose here an accurate link quality estimation scheme based on the SDN-TSCH, as an SDN solution for IEEE 802.15.4-TSCH network. We exploit the centralized view of the SDN controller to transmit packets of link quality estimation in a collisionfree manner. Moreover, we investigate the performance of the control plane of SDN-TSCH through different shared, dedicated, and hybrid (mix of shared and dedicated cells) approaches. We figured out that the dedicated control plane provides high reliability and fast convergence for wireless SDN networks.

关键词： Industrial internet of Things Software Defined networking scheduling resource allocation control plane flow isolation

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Embedded Intelligence Algorithms to Improve performance in Software-Defined networks (SDN) 2

Embedded Intelligence Algorithms to Improve Performance in S...

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2nd International conference on Artificial Intelligence, Blockchain, and internet of Things, AIBThings 2024

作者： Abed, Ghassan A. Al-Iraqia University Network Engineering Department Engineering College Iraq

ISBN: (纸本)9798331529529

Software-defined networking is a mature technology that has been included into several networks and new designs including 5 G and 6 G. It is a paradigm change that adopts dynamic software-driven models instead of old hardware-centric paradigms, resulting in network infrastructures that are nimble, efficient, and safe. Additionally, SDN complies with the network Function Virtualization Framework's virtualization design. SDN must, however, work harmoniously for a few years with the global distributed control of TCP/IP that has evolved over time. The standard chores of routing, load balancing, quality of service, security, and privacy need to be resolved, among other things. In addition, the initial centralization of SDN presents unique difficulties and problems for dispersed control that set it apart from conventional IP networks. The ability of the algorithms and protocols used in SDN to scale the network by adding new devices, respond quickly in real time, and use organized automation to make the network more flexible and adaptable are the three main requirements that need to be met in order for the algorithms and protocols to be proven effective. In addition to a critical analysis and comparison of multiple algorithms with the goals of routing, rerouting, load balancing, traffic optimization, and reducing rerouting delay, this paper offers a theoretical assessment of the most recent SDN optimization techniques. This paper also discusses important algorithms that can provide feasible solutions to solve problems in large systems or multi-scale routing. © 2024 IEEE.

关键词： quality of service

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Context-Aware Cross-Layer Congestion control for Large-Scale Live Streaming

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IEEE-ACM TRANSACTIONS ON networkING 2024年第5期32卷 3743-3759页

作者： Yuan, Danfu Zhang, Weizhan Qiu, Yubing Huang, Haiyu Yang, Mingliang Chen, Peng Xiao, Kai Yan, Hongfei He, Yaming Zhang, Yiping Xi An Jiao Tong Univ Sch Comp Sci & Technol MOEKLINNS Lab Xian 710049 Shanxi Peoples R China Alibaba Grp Hangzhou 311121 Peoples R China

Live video streaming has come to dominate today's internet traffic. Content Delivery network (CDN) providers, responsible for hosting outsourced live streaming services, are now striving to ensure an enhanced quality of experience (QoE) to meet the ever-increasing user expectations. Existing congestion control (CC) schemes in the kernel, however, suffer from unsatisfactory performance for live video delivery due to disparities in traffic characteristics and differentiated optimization goals between generic traffic and live video traffic. In this paper, we propose XCC, a streaming context-aware CC approach that helps achieve better QoE for the live streaming services from CDN provider. The core of XCC is to adaptively coordinate the transmission strategy and frame rate through a cross-layer feedback framework, responding to the fluctuating traffic dynamics and network conditions in the short term. Further, XCC matches the long-term traffic characteristics (i.e., two-stage delivery mode) by employing a task-specific state transition mechanism as the underlying TCP. XCC has been implemented in the Linux kernel's TCP stack and media engine and has been fully deployed in Alibaba Cloud's production service. Evaluation in experimental environments and A/B testing serving tens of millions of sessions demonstrate that XCC is competitive in streaming delay against the most prevalent TCP in today's Operating systems, while reducing startup delay by 9.9%, stall time by 36.4%, and stall frequency by 42.5% on average in deployment.

关键词： Live video streaming TCP congestion control content delivery quality of experience large-scale deployment

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Hybrid control of Channel Selection and Transmission Power for Low Power Wireless Sensor network 12th

Hybrid Control of Channel Selection and Transmission Power f...

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12th International conference on Communications, Circuits, and systems (ICCCAS)

作者： Hung, Chung-Wen Lee, Tzu-Hui Natl Yunlin Univ Sci & Technol Dept Elect Engn Touliu Yunlin Taiwan

ISBN: (纸本)9789819726387;9789819726363;9789819726356

A hybrid low power control of channel selection and transmission power (TP) which is suitable for Sub-1 GHz Wireless Sensor network (WSN) is proposed in this paper. internet of thing (IoT) is popular, and WSN is getting even much hotter due to build convenience and low cost. A large number of devices which share the Sub1 GHz Industrial Scientific Medical Band (ISM Band) together may cause channel contention. Therefore, the way to maintain the quality of communication with lower power consumption became an important issue. The technique of channel estimation is adopted to select the best channel for communication. The Signal-to-Noise Ratio (SNR) is chosen as the reference to present the state of environment and propagation path. By determining the SNR value, the quality of communication can be detected and the TP or channel will be adjusted when errors occur. The experimental results show that under the proposed hybrid control node the Packet Error Rate (PER) is efficiently reduced due to the choice of stable channel compared with the control group and the TP-controlled node. Moreover, the hybrid control node can ensure the similar quality of communication with better current consumption contrasts with channel-controlled node.

关键词： Wireless sensor network (WSN) Low-rate wireless personal area network (LR-WPAN) Channel estimation Transmission power control (TPC) Power consumption

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A Flexible In-band network Telemetry Framework for Heterogeneous Private networks 20

A Flexible In-band Network Telemetry Framework for Heterogen...

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20th International conference on Factory Communication systems (WFCS)

作者： Miranda, Gilson, Jr. Haxhibeqiri, Jetmir Hoebeke, Jeroen Moerman, Ingrid Macedo, Daniel F. Marquez-Barja, Johann M. Univ Antwerp IDLab IMEC Antwerp Belgium Univ Ghent IDLab IMEC Ghent Belgium Univ Fed Minas Gerais Dept Comp Sci Belo Horizonte MG Brazil

ISBN: (纸本)9798350319347;9798350319354

As network management operations increasingly rely on automation and finer control actions, there is a need for precise telemetry systems. In-band network Telemetry (INT) methods use data packets to carry telemetry and give real-time insights about network performance. Existing solutions often require specialized hardware or offer limited runtime configuration options. This work presents an INT Framework for heterogeneous private networks, targeting industrial and multimedia applications. The framework is designed to be flexible and runtime-reconfigurable, addressing challenges in real-world applications. We provide implementation details of our elements supporting the configurability and the consolidation of raw telemetry into high-level quality of Service (QoS) metrics. We evaluated the framework in a testbed with wired and wireless devices. The results show the accuracy in monitoring QoS, as well as an analysis of synchronization requirements, showcasing the feasibility of our framework for solutions requiring precise and flexible QoS monitoring.

关键词： In-band network Telemetry QoS

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Ivycide: Smart Intrusion Detection System Against E-IoT Driver Threats

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IEEE internet OF THINGS JOURNAL 2023年第10期10卷 8533-8546页

作者： Rondon, Luis Puche Babun, Leonardo Aris, Ahmet Akkaya, Kemal Uluagac, A. Selcuk Florida Int Univ Cyber Phys Syst Secur Lab Miami FL 33199 USA Florida Int Univ Adv Wireless & Secur Lab Miami FL 33199 USA

The rise of internet of Things (IoT) devices has led to the proliferation of smart environments worldwide. Although commodity IoT devices are employed by ordinary end users, complex environments, such as smart buildings, government, or private offices, or conference rooms require customized and highly reliable IoT solutions. Enterprise IoT (E-IoT) connect such environments to the internet and are professionally managed solutions usually offered by dedicated vendors As E-IoT systems require specialized training, closed-source software, and proprietary equipment to deploy. In effect, E-IoT systems present an unprecedented, under-researched, and unexplored threat vector for an attacker. In this work, we focus on E-IoT drivers, software modules used to integrate devices into E-IoT systems, as an attack mechanism. We first present PoisonIvy, a series of generalized proof-of-concept attacks used to demonstrate that an attacker can use a malicious driver to perform denial-of-service attacks, gain remote control, and abuse E-IoT system resources. To defend against E-IoT driver-based threats, we introduce Ivycide, a novel intrusion detection system used to detect unexpected E-IoT network traffic from an E-IoT system. Ivycide operates as a passive monitoring system within an E-IoT system using machine learning and signature-based classification to detect Poisonivy attacks. We evaluated the performance of Ivycide in a realistic E-IoT deployment. Our detailed evaluation results show that Ivycide achieves an average accuracy of 97% in classifying the type of Poisonivy attack and operates without modifications or operational overhead to the existing E-IoT systems.

关键词： internet of Things Smart buildings Monitoring control systems TV User interfaces Behavioral sciences Cyber attacks enterprise IoT (E-IoT) systems intrusion detection

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DPN: Density-Based Probability VANET Caching Method Leveraging with NDN Concept 21

DPN: Density-Based Probability VANET Caching Method Leveragi...

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21st IEEE International conference on Mobile Ad-Hoc and Smart systems (MASS)

作者： Li, Yuanchen Guan, Lin Zhang, Ziyang Vogiatzis, George Loughborough Univ Sch Sci Loughborough Leics England

ISBN: (纸本)9798350363999;9798350364002

Vehicular Ad Hoc network (VANET) is expected to have broad applications, such as traffic warnings and accident rescue. However, the highly dynamic nature of VANET topology challenges conventional Mobile Ad-hoc network (MANET) data retrieval mechanisms, causing significant performance degradation. To address this, we propose a novel caching mechanism that leverages density-based probability caching and incorporates Named Data networking (NDN). This approach aims to improve the quality of Service (QoS) in VANET, especially in high-traffic urban environments, by dynamically adapting to topology changes and uneven traffic density. Empirical experiments show that our proposed mechanism surpasses existing benchmarks in latency and link load metrics while maintaining a competitive cache hit ratio.

关键词： Vehicular Ad Hoc network Caching Density Probability NDN

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Achieving Fairness Generalizability for Learning-based Congestion control with JURY 25

Achieving Fairness Generalizability for Learning-based Conge...

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20th European conference on Computer systems-EuroSys

作者： Tian, Han Liao, Xudong Sun, Decang Zeng, Chaoliang Jin, Yilun Zhang, Junxue Wan, Xinchen Wang, Zilong Wang, Yong Chen, Kai Univ Sci & Technol China Beijing Peoples R China Hong Kong Univ Sci & Technol iSING Lab Hong Kong Peoples R China BitIntelligence West Boylston MA USA

ISBN: (纸本)9798400711961

internet congestion control (CC) has long posed a challenging control problem in networking systems, with recent approaches increasingly incorporating deep reinforcement learning (DRL) to enhance adaptability and performance. Despite promising, DRL-based CC schemes often suffer from poor fairness, particularly when applied to network environments unseen during training. This paper introduces Jury, a novel DRL-based CC scheme designed to achieve fairness generalizability. At its heart, Jury decouples the fairness control from the principal DRL model with two design elements: i) By transforming network signals, it provides a universal view of network environments among competing flows, and ii) It adopts a post-processing phase to dynamically module the sending rate based on flow bandwidth occupancy estimation, ensuring large flows behave more conservatively and smaller flows more aggressively, thus achieving a fair and balanced bandwidth allocation. We have fully implemented Jury, and extensive evaluations demonstrate its robust convergence properties and high performance across a broad spectrum of both emulated and real-world network conditions.

关键词： Congestion control Reinforcement Learning Transport Protocol

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Reinforced Learning Model with Coati optimization Algorithm for Energy Efficient Routing for WSN Connecting IoT

Reinforced Learning Model with Coati optimization Algorithm ...

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2024 International conference on System, Computation, Automation and networking, ICSCAN 2024

作者： SriHasini, J. Coumar, Oudaya Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Avadi Chennai India

ISBN: (纸本)9798331510022

The emergence of notable obstacles such heterogeneity, dependability, and scalability has been brought about by the growth of varied wireless devices in real-time internet of Things applications. A new architecture known as Energy-Efficient Routing for IoT (EER-IoT) has been designed to efficiently address these problems. IoT devices in these systems, however, have to deal with unpredictable network dynamics, energy limitations, and strict quality of service requirements. The importance of having a well-designed routing protocol is highlighted by these reasons. Inaction on this part frequently results in frequent network disconnections and poor performance. In this work, we offer the intelligent, energy-efficient routing protocol, called EER-COA-RL, that combines reinforcement learning with the Coati Optimization Algorithm. This protocol evaluates fitness functions based on residual energy (RER) and distance limitations in an effort to improve network performance and lifespan. Optimizing energy usage in internet of Things networks is the main goal of implementing this routing method. This is especially important since wireless internet of Things devices have limited energy resources and you need to be able to quickly adjust to changes in the network to minimize interruptions and maximize network performance. © 2024 IEEE.

关键词： energy consumption Energy-Efficient Routing internet of Things (IoT) network performance Reinforcement Learning (RL)

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