检索结果-内蒙古大学图书馆

Design and implementation of energy-aware cross-layer routing protocol for wearable body area network

INTERNATIONAL JOURNAL OF PERVASIVE COMPUTING AND COMMUNICATIONS 2022年第5期18卷 645-663页

作者： Vadlamudi, Muniraju Naidu Hussain, M. D. Asdaque Koneru Lakshmaiah Educ Fdn Dept Comp Sci & Engn Guntur Andhra Pradesh India

Purpose A wireless body area network (WBAN) plays a crucial role in the health-care domain. With the emergence of technologies like the internet of things, there is increased usage of WBAN for providing quality health services. With wearable devices and sensors associated with human body, patient's vital signs are captured and sent to doctor. The WBAN has number of sensor nodes that are resource constrained. The communications among the nodes are very crucial as human health information is exchanged. The purpose of this paper aims to have quality of Service (QoS) with energy aware and control overhead aware. Maximizing network lifetime is also essential for the improved quality in services. There are many existing studies on QoS communications in WBAN. Design/methodology/approach In this paper, with the aim of energy-efficient WBAN for QoS, a cross-layer routing protocol is designed and implemented. A cross-layer routing protocol that is ad hoc on-demand distance vector (AODV)-based, energy and control overhead-aware (AODV-ECOA) is designed and implemented for energy-efficient routing in WBAN. The cross-layer design that involves multiple layers of open systems interconnection reference model, which will improve energy efficiency and thus QoS. Findings Implementation is simulated using the network simulator tool, i.e. NS-2. The proposed cross-layer routing protocol AODV-ECOA shows least bandwidth requirement by control packets, leading to less control overhead, highest packet delivery ratio and energy efficiency. The experimental results revealed that AODV-ECOA shows better performance over existing protocols such as AODV and POLITIC. Originality/value An efficient control overhead reduction algorithm is proposed for reducing energy consumption further and improves performance of WBAN communications to realize desired QoS.

关键词： Wireless body area network (WBAN) Sensor network Routing protocol Energy efficiency quality of service Reduction of control overhead

来源：评论

学校读者我要写书评

暂无评论

Microgrid Energy Management Considering Communication: A Bayesian Deep Q-learning Learning Approach 3

Microgrid Energy Management Considering Communication: A Bay...

引用

3rd International conference on Power systems and Electrical Technology

作者： Hu, Qinhan Ye, Yujian Wu, Yizhi Xie, Xiangpeng Nanjing Univ Posts & Telecommun Coll Automat Nanjing Peoples R China Nanjing Univ Posts & Telecommun Coll Artificial Intelligence Nanjing Peoples R China Southeast Univ Sch Elect Engn Nanjing Peoples R China Nanjing Univ Posts & Telecommun Sch Internet Things Nanjing Peoples R China

ISBN: (纸本)9798350353211;9798350353204

Microgrid (MG) represents a compact power generation and distribution system comprising renewable energy sources (RES), energy storage structure (ESS), and controllable loads. However, challenges arise due to the inherent uncertainty in renewable energy generation, market price fluctuations, and restrictions related to load start-stop cycles, making it arduous to ensure consistent power quality, achieve power generation-consumption balance, and minimize costs. Moreover, communication breakdowns among MG participants can result in the loss of collaborative information, jeopardizing the stable operation of the MG. Thus, the pivotal strategy for enhancing MG resilience lies in facilitating flexible energy scheduling amidst communication disruptions. Capitalizing on the advancements in reinforcement learning, this article conceptualizes MG as a multi-agent environment and proposes an innovative MG energy management solution based on Bayesian double deep Q-Leaning network (BDDQN). Each electrical participant is represented as an agent, furnished with a neural network for predicting its own Q-value, alongside employing Bayesian belief update techniques to estimate other agents' behaviors. Subsequently, a method leveraging correlated equilibrium is employed for joint action selection. Simulation outcomes underscore the robustness of BDDQN in the face of communication failures and uncertainties in power generation, yielding increased profits for ESS and RES agents respectively, while concurrently reducing costs for DSL agents.

关键词： Micro-grid Communication Multi-agent collaboration Double deep Q-Leaning network(DDQN) Bayesian technique Energy management

来源：评论

学校读者我要写书评

暂无评论

Enhanced SNR Based Admission control Algorithm for Vehicular Ad-Hoc network 7

Enhanced SNR Based Admission Control Algorithm for Vehicular...

引用

7th International conference on Future networks and Distributed systems, ICFNDS 2023

作者： Sameen, Aws Zuhair Alwan, Mohammed Hasan Kadhum, Mayssam Saad Hammadi, Yousif I Alsaeedi, Mokhalad Abdulameer Kadhim Aziz, Ahmed Muthanna, Mohammed Saleh Ali Department Of Medical Instrumentation Engineering Techniques College Of Medical Techniques Al-Farahidi University Baghdad10015 Iraq Department Of Communications Engineering College Of Engineering University Of Diyala Baqubah32001 Iraq Bilad Alrafidain University College Diyala32001 Iraq Department Of Computer Science Faculty Of Computer And Artificial Intelligence Benha University Egypt Department Of International Business Management Tashkent State University Of Economics Tashkent Uzbekistan Institute Of Computer Technologies And Information Security Southern Federal University Taganrog344006 Russia

ISBN: (纸本)9798400709036

Vehicular Ad-hoc network (VANET) becomes a fundamental subcategory of mobile ad-hoc networks that provides vehicles to communicate with each other and with roadside infrastructure smartly. Various VANET performance challenges are considered in terms of quality of Service (QoS) due to vehicle speed and transmission rates. Different problems cause performance degradation as performance anomaly where high rates of vehicles have to meet the speed of the low rates vehicle while transmitting data. In this paper, a QoS-aware Signal to Noise Ratio (SNR) admission control mechanism (QASAC) is proposed to handle the performance anomaly problem while maintaining the QoS levels for different traffic types. QASAC has been compared against the latest SNR based admission control mechanism. QASAC has enhanced the performance of data delivery up to 23% in terms of data dropping rates for high priority traffic. © 2023 ACM.

关键词： Vehicular ad hoc networks

来源：评论

学校读者我要写书评

暂无评论

Dual-Channel Wind Power Forecasting Model Using Squeeze and Excitation network 4

Dual-Channel Wind Power Forecasting Model Using Squeeze and ...

引用

4th International conference on Smart Power and internet Energy systems (SPIES)

作者： Li, Haonan Jiang, Bozhen Ma, Zhengyang Geng, Hua Liu, Yi Zhejiang Univ Technol Inst Proc Equipment & Control Engn Hangzhou 310023 Peoples R China Tsinghua Univ Dept Automat Beijing 100084 Peoples R China

ISBN: (纸本)9781665489577

Accurate wind power forecasting plays an increasingly important role in the field of wind power forecasting but still intractable in practice. In order to improve the accuracy of wind power forecasting, a novel model based on squeeze and excitation network (SENet) embedded in a dual-channel is proposed. The dual-channel mechanism integrates convolutional neural network and gated recurrent unit, both of which can be used without interfering with each other. SENet can increase the attention of each important features, thus improving the network efficiency. Compared with a single model, the proposed model has better feature extraction performance with the root mean square error of 29.9. The test results of wind power data based on Kaggle platform show that the proposed method outperforms several deep learning forecasting methods.

关键词： wind power forecasting feature extraction feature weight squeeze and excitation networks convolutional neural network

来源：评论

学校读者我要写书评

暂无评论

Research and Analysis of Well-Known Solutions and Development of DNS Server Software in the Infrastructure of the Digital Economy 1

引用

5th International Russian Automation conference, RusAutoCon 2023

作者： Martyshkin, A.I. Biktashev, R.A. Karlyganov, A.D. Baydukov Proyezd/Gagarin Street 1a/11 Penza440039 Russia 40 Krasnaya Street Penza440026 Russia

ISBN: (数字)9783031511271

ISBN: (纸本)9783031511264

The article presents a study and analysis of known solutions and implementations of DNS servers, as well as the development of DNS server software, for which modern programming tools and technologies are used. In the process of development, the requirements for performance, scalability, security and reliability of DNS server are taken into account. The development of an efficient DNS server is an urgent task in today's digital economy. This paper aims to develop an efficient and reliable DNS server that will meet the requirements of the infrastructure of the digital economy. The results obtained can be used by organizations and enterprises to ensure stable and efficient operation of their network infrastructure. Also, the results of this work can be used to improve the quality of user experience in the field of internet services, as DNS servers play an important role in ensuring the availability of web resources. The results are verified in real world conditions by testing the developed DNS server. Experiments are conducted to evaluate the performance and reliability of DNS server under different loads and usage conditions. The main results of this research are given in conclusion. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Transmission control protocol

来源：评论

学校读者我要写书评

暂无评论

A Method for Enabling Context-Awareness at Transport Layer for Improved quality-of-Service control

引用

IEEE ACCESS 2021年 9卷 123987-123998页

作者： Ppallan, Jamsheed Manja Arunachalam, Karthikeyan Gantha, Shiva Souhith Jaiswal, Sweta Song, Seongkyu Nigam, Anshuman Samsung Res & Dev Inst India Bangalore 6G Lab Bengaluru 560037 India Samsung Seoul Res & Dev Campus 6G Res Team Seoul 06765 South Korea

As the 5G systems have introduced network slicing on the virtualized network environment, application-specific QoS (quality of Service) management has come to the fore to support a range of services, such as eMBB (enhanced Mobile Broadband), URLLC (Ultra-Reliable Low Latency Communications), and mIoT (massive internet of Things). It is expected for the next-generation systems to support more diverse applications demanding newer and granular quality characteristics for network services. Most of the current transport layer protocols, built on layering design and best-effort paradigm, do not provide the necessary precision and adaptability required for various QoS support. Therefore, we need new protocols that comprehend application behaviours and adapt to dynamic network conditions for more fine-grained QoS enhancement. This paper presents a Context-oriented Transport (CoT) layer for the next-generation network that understands the application context and adapts to varying network conditions with flow-based QoS control. CoT is an end-to-end software solution that improves the underlying network capacity utilization and prioritizes the traffic flows according to quality needs. We prototyped CoT in Linux/Android devices and evaluated the performance with emulated traffic environment. The experiments show that CoT reduces latency by up to 16.5% and improves average throughput by up to 30%, compared with Android 10 in LTE network, resulting from enhanced traffic classification and network utilization.

关键词： quality of service 5G mobile communication Protocols 6G mobile communication Throughput Reliability Next generation networking Cross-layer method inter-layer optimization machine learning quality of service QoS control TCP IP traffic classification traffic control transport protocols

来源：评论

学校读者我要写书评

暂无评论

Dynamic Bandwidth Slicing for Time-Critical IoT Data Streams in the Edge-Cloud Continuum

引用

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2022年第11期18卷 8017-8026页

作者： Habeeb, Fawzy Alwasel, Khaled Noor, Ayman Jha, Devki AlQattan, Duaa Li, Yinhao Aujla, Gagangeet Singh Szydlo, Tomasz Ranjan, Rajiv Newcastle Univ Newcastle Upon Tyne NE4 5TG Tyne & Wear England Univ Jeddah Jeddah 21959 Saudi Arabia Saudi Elect Univ Riyadh 13323 Saudi Arabia Taibah Univ Coll Comp Sci & Engn Madinah 42353 Saudi Arabia Univ Oxford Oxford OX1 2JD England Tech & Vocat Training Corp Sakakah 72389 Saudi Arabia Newcastle Univ Sch Comp Newcastle Upon Tyne NE4 5TG Tyne & Wear England Univ Durham Durham DH1 3LE England AGH Univ Sci & Technol Inst Comp Sci PL-30059 Krakow Poland

Edge computing has gained momentum in recent years, as complementary to cloud computing, for supporting applications (e.g., industrial control systems) that require time-critical communication guarantees. While edge computing can provide immediate analysis of streaming data from internet of Things devices, those devices lack computing capabilities to guarantee reasonable performance for time-critical applications. To alleviate this critical problem, the prevalent trend is to offload these data analytic tasks from the edge devices to the cloud. However, existing offloading approaches are static in nature as they are unable to adapt varying workload and network conditions. To handle these issues, we present a novel distributed and quality of services based multilevel queue traffic scheduling system that can undertake semiautomatic bandwidth slicing to process time-critical incoming traffic in the edge-cloud environments. Our developed system shows a great enhancement in latency and throughput as well as reduction in energy consumption for edge-cloud environments.

关键词： internet of Things Cloud computing Bandwidth quality of service Microservice architectures Ecosystems Time factors Bandwidth slicing cloud data stream edge internet of Things (IoT) multiqueues software-defined networking (SDN) time critical

来源：评论

学校读者我要写书评

暂无评论

7th International conference on Communication, Device and networking, ICCDN 2024

7th International Conference on Communication, Device and Ne...

引用

7th International conference on Communication, Device and networking, ICCDN 2024

ISBN: (纸本)9789819764648

The proceedings contain 34 papers. The special focus in this conference is on Communication, Device and networking. The topics include: Mode Suppression in SIW Bandpass Filter for K-Band Applications;slot-Infused Patch Antenna with Improved Radiation Characteristics for 5G Millimeter Wave Application;performance Evaluation of Pasapalli and Modified Sierpinski Square Fractal Antennas in X-Band Spectrum;Investigation of Different DGSs for Miniaturized Hexagonal Patch Antennas;Design and Analysis of Octogon EBG for Patch Antenna in ISM Band;performance Evaluation of ISM Circular Patch Antennas with Various Feeding Mechanisms;flexible and Comfortable Textile Antenna for On/Off Body Biomedical Communication;A Unit Gain Approach with Reconfigurable Antenna for ISM Band;A Millimetre-Wave LNA for Défense Covert Warfare Operations and Cybersecurity Applications;ultra-Wide Band Linearized Silicon Radio Frequency Low Noise Amplifier for Diagnosis and Monitoring of Chronic Cases in Healthcare;optimization Design of Microstrip Bandpass Filters for Ultra-Wideband Wireless Communication Based on Distributed Algorithms;speaker Adaptation in Disaster Management systems: A Comparative Study and Research Gap Analysis;optimizing Data Center Power Usage: Server Consolidation and Efficient Cooling Techniques;Optimized Frequency control Strategy for an AC Microgrid;optimization of Hydraulic Power Generation System Based on Particle Swarm Optimization Algorithm;Modeling and PID control of Unmanned Aerial Vehicles Based on Machine Vision;effectiveness of Blockchain and IoT in Horticulture Crop Supply Chain;IOT Based Gas Level and Leakage Detection for Domestic Applications;an Enhanced Low-Power Coding Technique for network-on-Chip Links;physical Layer Security Analysis for Correlated Nakagami-m Fading Channel;Emergency Message Dissemination Through Efficient Acknowledgment Aggregation Technique with Cloud Based MQTT Over internet of Vehicles.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Traffic Anomaly Detection Model of Electric Power Industrial control Based on DBN-LSTM 23

Traffic Anomaly Detection Model of Electric Power Industrial...

引用

23rd IEEE International conference on High performance Computing and Communications, 7th IEEE International conference on Data Science and systems, 19th IEEE International conference on Smart City and 7th IEEE International conference on Dependability in Sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Zhang, Shijun Lai, Ji Yao, Qigui Platform Operation and Safety Center Information and Communication Branch of State Grid Jibei Electric Power Co. Ltd Beijing China Global Energy Interconnection Research Institute Co. Ltd State Grid Key Laboratory of Information & Network Security Nanjing China

ISBN: (纸本)9781665494571

With the construction of smart city and smart grid, energy internet is booming, and the deployment of smart power terminals has increased, with a wide range of deployment locations, and the level of intelligence of the terminals has increased. However, most of the intelligent terminals are deployed in the non-controlled industrial control network environment, which brings new challenges to the network security. Therefore, the traffic anomaly detection of electric power industrial control becomes the first step to ensure the safety of the peripheral network. Currently, the traffic anomaly detection system of electric power industrial control based on machine learning has the problems of low computing efficiency and weak representation ability. To solve the problem of low efficiency in traditional deep learning, the deep belief network (DBN) is used to extract the non-linear features of data, which can improve the time efficiency to a certain extent. To solve the problem that the representation ability of traditional machine learning is weak, long short term memory network (LSTM) is used to improve the representation ability of traditional shallow machine learning. The experimental results suggest that the method is better than the traditional machine learning method in accuracy, and the recall rate reaches up to 97.3%, AUC runs up to 0.927. © 2021 IEEE.

关键词： Smart cities Industrial control network security Feature extraction Power systems Smart grids Safety

来源：评论

学校读者我要写书评

暂无评论

Swarm Intelligence based Deep Learning Method for Health Monitoring System using internet of Things (IoT) 3

Swarm Intelligence based Deep Learning Method for Health Mon...

引用

3rd International conference on Smart Technologies, Communication and Robotics, STCR 2023

作者： Pavithra, R. Venkateshkumar, S. Department of Commerce with It Coimbatore India Department of Cyber Security Coimbatore India

ISBN: (纸本)9798350370867

The research conducted is significant because there is an increasing demand for reliable health monitoring, particularly in underserved and far-flung areas. However, issues with data quality, network optimization, and resource limits might hinder the efficacy of data collected by IoT devices, which otherwise provide until then unimaginable prospects. Swarm intelligence and deep learning together can improve these areas, making IoT-based health monitoring more effective. Efficient sensor placement, data transmission, and processing of massive, frequently noisy health data streams are among the biggest obstacles to widespread adoption of IoT-based health monitoring. Using swarm intelligence algorithms to optimize sensor placement and deep learning for data analysis, the proposed internet of Things-based swarm health monitoring system (IoT-SHMS) approach addresses the aforementioned challenges. IoT-SHMS uses swarm intelligence techniques, such as Particle Swarm Optimization (PSO), to optimize sensor location and network topologies. This helps to increase the reliability of health prediction while decreasing operational expenses. Constant patient monitoring, early detection of health anomalies, and the detection of falls are a few of the numerous applications of an IoT-SHMS approach in the medical field. It additionally has applications in telemedicine, wellness monitoring, and emergency response systems to give doctors and nurses up-to-date information in a timely manner. Extensive simulation evaluations are presented to prove that IoT-SHMS works as intended. The advantage of our technology over conventional approaches is illustrated by the performance criteria of accuracy, latency, and energy efficiency. Based on these findings, IoT-SHMS appears to be a viable option for healthcare applications in the internet of Things environment © 2023 IEEE.

关键词： internet of things

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：