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A Multi-layer and Vanet-based Approach to Improve Accident Management in Smart Cities 16

A Multi-layer and Vanet-based Approach to Improve Accident M...

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16th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： Brandao, Yan, V De Souza, Lucas M. Gomides, thiago S. De Grande, Robson E. Souza, Fernanda S. H. Guidoni, Daniel L. Univ Fed Sao Joao del Rei Dept Comp Sci Sao Joao Del Rei MG Brazil Brock Univ Dept Comp Sci St Catharines ON Canada

ISBN: (纸本)9781728143514

the growth in the number of traffic accidents has become a cause for concern in urban centers. As a result of the increase in population in large cities and the number of vehicles, the consequences of accidents and congestion can be even more significant, considering the impacts on the economy, environment and people's quality of life. therefore, aiming to minimize these impacts, we present ALIVE, a distributed and Vanet-based solution that reduces congestion caused by different sources and, especially, from accident sources, contributing to efficient urban mobility in smart cities. the solution performs the detection of accidents and the dissemination of warning messages in multiple hops. Besides, the system can share the road traffic information with the nearby streets to improve traffic efficiency. We evaluated the proposed solution with PANDORA and NRR Traffic Management solutions. Simulation results indicate that the proposed solution reduces the average travel time, time lost, and the number of transmitted messages.

关键词： Smart city multi-layer distributed algorithm traffic and congestion management

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A Physarum-based Boost Algorithm for Network Optimization in Dense Wireless sensor Networks 30

A Physarum-based Boost Algorithm for Network Optimization in...

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30th international conference on Computer Communications and Networks (ICCCN)

作者： Zhang, Haiyang Qi, Fang Liu, Xiaomeng Beijing Univ Posts & Telecommun Sch Comp Sci Beijing Peoples R China

ISBN: (纸本)9780738113302

With the emergence and development in 5G cellular systems and ultra dense networks, recent years have witnessed a surge of interest in Dense Wireless sensor Network (DWSN) in academia and industry. Although many existing works have explored the Steiner tree problem (STP) like multicast and topology design in WSN scenarios, new challenges introduced by growing node number and redundant links receive much less attention yet. the complexity of the topology usually makes algorithms that find the optimal solution unacceptable in terms of running time. Meanwhile, other approximate algorithms with lower time complexity cause too much performance loss. In this paper, we propose a physarum-based pre-processing algorithm called PBA for boosting up a traditional algorithm that can find STP's optimal solution. the proposed algorithm could select crucial edges and vertices quickly by imitating the physarum's foraging process. Our algorithm could eliminate edges and vertices irrelevant to the optimal solution by 80% and 50% in the original graph, respectively. this simplified graph produced by PBA is used in the traditional algorithm for obtaining the final result. PBA could also be transformed into a distributed version with minor changes for large-scale topology. Simulation results demonstrate that the proposed algorithm can shorten the original algorithm's running time by one to two orders of magnitude with less than 5% performance loss in general.

关键词： Dense wireless sensor network Steiner tree problem physarum optimization network optimization

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Research on PUE Prediction Model of Data Center Based on Artificial Intelligence

Research on PUE Prediction Model of Data Center Based on Art...

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ieee international conference on Civil Aviation Safety and Information Technology (ICCASIT)

作者： Yongkang Hu Yanling Zhao Linkun Wang Network and Sensor Center Instrumentation Technology and Economy Institute Beijing China

With the development of artificial intelligence technology, the power consumption of data centers is increasing rapidly. How to reduce the energy consumption level of data centers and improve their green level is the current research hotspot. Since data center refrigeration system power consumption accounts for more than 40%, some scholars proposed to use artificial intelligence technology to model and analyze the refrigeration system to improve its operation efficiency and reduce the overall energy consumption of the data center. At present, Google uses neural network to build data center PUE Analysis Model and applied it in daily lives. the overall PUE of the data center is reduced by 0.5% to 2%. the basis of PUE optimization is PUE accurate prediction, so it is of great significance to study PUE prediction model. Given the large amount of operating data and the uneven level of data quality, it is difficult to model and analyze the refrigeration system in the data center. In this paper, deep neural networks are used to predict the PUE of data centers, and a PUE prediction model is constructed. through field experimental analysis in data centers, the results show that the scheme proposed in this paper can accurately predict the PUE, which lays a foundation for further research on the influencing factors of PUE of refrigeration systems and then proposes the PUE optimization scheme.

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Implementation of distributed Crawler System Based on Spark for Massive Data Mining 5

Implementation of Distributed Crawler System Based on Spark ...

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ieee 5th international conference on Computer and Communication systems (ICCCS)

作者： Liu, Feng Xin, Wang Hebei GEO Univ Shijiazhuang Hebei Peoples R China Hebei Software Testing Ctr Shijiazhuang Hebei Peoples R China

ISBN: (纸本)9781728161365

In the era of rapid development of Internet technology and increasing social needs of people, web crawlers have been maturely applied to major search engines and search fields. By using Spark's RDD elastic computing architecture and task assignment algorithm, this paper integrates the architecture of Spark-based distributed crawler system, gives the corresponding framework diagram, and introduces the distributed framework system in detail. through this Spark-based distributed crawler system we can solve the problem of insufficient resource utilization and low collection efficiency, and then solve the contradiction between the current explosive growth of data scale and the speed of obtaining information.

关键词： spark distributed web crawler framework

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Deep Reinforcement Learning and distributed Solution for Local Network based Optimization of Network Slicing in 5G Communications

Deep Reinforcement Learning and Distributed Solution for Loc...

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distributed computing and Electrical Circuits and Electronics (ICDCECE), ieee international conference on

作者： Naziya Hussain Anoop Singh Taki Alrwbaye Yogesh Ramaswamy L. Ramesh Department of Computer Science and Engineering Mukesh Patel School of Technology Management & Engineering SVKM's NMIMS Deemed to be University Shirpur India Group of IPS Academy Indore India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Electronics and Communication Engineering M.Kumarasamy College of Engineering Karur India

ISBN: (数字)9798331533663

ISBN: (纸本)9798331533670

Nowadays, the advent of 5G networks has introduced the concept of network slicing to allow the multiple independent networks for coexisting on a shared physical infrastructure. However, the existing Mixed-Integer Linear Programming (MILP) solution suffered inefficient resource utilization which has led to reduced network performance and increased latency. Hence, this research proposes Deep Reinforcement Learning and distributed Solution for Local Network (DRL-DSLN) based optimization of network slicing in 5G for efficient resource allocation and low latency. the proposed DRL-DSLN framework increases the network performance where it learns from interactions with adapting to changing conditions and makes real time decisions. Initially, the network slicing architecture is introduced to maintain a high performance of network operation by supporting various services. Here, each network slice has a four specific Key Performance Indicators (KPIs) and these are identified to optimize slicing process. Finally, DRL-DSLN are employed to solve the inter-slice allocation and intra-slice allocation problems respectively. From the results, the proposed DRL-DSLN achieved better results in terms of accuracy (98.27%), precision (97.31%), recall (92.94%), and F1-score (97.53%) when compared to existing Harris Hawks Optimization with Convolutional Neural Network (HHO-CNN) model.

关键词： 5G mobile communication Network slicing Key performance indicator Telecommunication traffic Deep reinforcement learning Real-time systems Mixed integer linear programming Resource management Software defined networking Optimization

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Empowering Mobility: A Smart Wheelchair Integrated with Health Monitoring System

Empowering Mobility: A Smart Wheelchair Integrated with Heal...

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India Council international Subsections conference (INDISCON), ieee

作者： Someshwar Ware Yogita Kolge Eshin Somkuwar Marwana Sayed Department of Biomedical Engineering Ajeenkya D Y Patil University Pune India School of Engineering Ajeenkya D Y Patil University Pune India

ISBN: (数字)9798350376753

ISBN: (纸本)9798350376760

this paper represents a groundbreaking fusion of modern electronics and healthcare technology, offering a comprehensive solution for individuals facing mobility challenges. this research project introduces an innovative approach, leveraging the power of a 12 V 1.3 Ah Lead Acid Battery and the intelligence of an Arduino Uno R3 development board to redefine the conventional wheelchair paradigm. At its core, the project focuses on integrating critical health monitoring components, including ECG and SpO 2 sensors, a DS18B20 Temperature sensor, and a Pulse sensor. this integration allows real-time monitoring of vital health parameters, providing users with immediate insights into their well-being. Key to the system’s functionality is its ability to process and display real-time health data on a $20 \times 4$ LCD screen, offering users and caregivers a snapshot of the user’s health status. Moreover, including an alert mechanism featuring a Buzzer ensures timely notifications of any emergent health conditions, further enhancing user safety and well-being. this amalgamation of mobility support and health awareness represents a significant step forward in assistive device technology. By redefining the conventional wheelchair, this project aims to offer an inclusive, intelligent, and compassionate solution for individuals seeking independence and enhanced healthcare accessibility. As technology evolves, this research project stands as a testament to the intersection of innovation and empathy, paving the way for a new era in personalized mobility solutions.

关键词： Temperature sensors Technological innovation Patient monitoring Wheelchairs Transportation Medical services Real-time systems sensor systems Predictive analytics Intelligent sensors

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Double Mobile Sinks Architecture for WSN Data Gathering and Critical Events Detection 16

Double Mobile Sinks Architecture for WSN Data Gathering and ...

引用

16th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： KhalifEh, Ala F. Abed, Husam Darabkh, Khalid A. Chatzichristofis, Savvas Zinonos, Zinon German Jordanian Univ Dept Elect & Commun Engn Amman 11180 Jordan Univ Jordan Dept Comp Engn Amman 11942 Jordan Neapolis Univ Pafos Dept Comp Sci CY-8042 Pafos Cyprus

ISBN: (纸本)9781728143514

Data gathering and critical events detection are two essential functionalities for Wireless sensor Network (WSN). In this paper, we propose double mobile sinks network architecture, where two mobile sink nodes visit the Cluster Heads (CHs) to collect the captured data, which is very energy effective in terms of energy transmission efficiency and reliable compared with the case of having one static sink node. Moreover, the proposed architecture provides a capable scheme for supporting critical and non-critical data, which assures a timely delivery for any critical event to the remote monitoring and decision-making center with minimal interference to the non-critical data. Our proposed architecture shows a superior performance in terms of packets transmission delay, and requires low buffer occupancy for the CHs nodes when compared to related work in the literature. Finally, the paper provides a preliminary hardware design and implementation for the proposed architecture.

关键词： WSNs Spiral trajectory CHs Mobile sensor node

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Overlapped Mobile Charging for sensor Networks 40

Overlapped Mobile Charging for Sensor Networks

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40th ieee international conference on distributed computing systems (ICDCS)

作者： Zhang, Sheng Liang, Yu Qian, Zhuzhong Xiao, Mingjun Ge, Jidong Wu, Jie Lu, Sanglu Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China Univ Sci & Technol China Sch Comp Sci & Technol Suzhou Inst Adv Study Hefei Peoples R China Temple Univ Dept Comp & Informat Sci Philadelphia PA 19122 USA

ISBN: (纸本)9781728170022

In this paper, we consider a fundamental problem: given one mobile charger that can charge multiple sensor nodes simultaneously, how we can schedule it to charge a given WSN to maximize the energy usage effectiveness (EUE)? We propose a novel charging paradigm Overlapped Mobile Charging (OMC) the first of its kind to the best of our knowledge. Firstly, OMC clusters sensor nodes into multiple non-overlapped sets using k-means evaluated by the Davies-Bouldin Index, such that the sensor nodes in each set have similar recharging cycles. Secondly, for each set of sensor nodes, OMC further divides them into multiple overlapped groups, and charges each group at different locations for different time durations to make sure that each overlapped sensor node just receives its required energy from multiple charging locations.

关键词： sensor nodes

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IRS-Aided Caching with Channel Power-Delay-Profile via DDPG and Self-Supervision Learning

IRS-Aided Caching with Channel Power-Delay-Profile via DDPG ...

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international conference on Computers, Communications, and systems (ICCCS)

作者： Huang Huang Fasheng Zhou School of Electronics and Communication Engineering Guangzhou University Key Laboratory of On-Chip Communication and Sensor Chip of Guangdong Higher Education Institutes Guangzhou China

ISBN: (数字)9798350350210

ISBN: (纸本)9798350350227

the 5G information age requires a large number of marginal nodes distributed around users to provide digital services. By caching and processing data at edge nodes close to users, edge caching technology can effectively collaborate with cloud computing and edge computing to improve the transmission efficiency as well as network response time. Meanwhile, intelligent reflective surface (IRS) is a promising technology for achieving high reductions in hardware cost and power consumption as compared to traditional relaying systems. It provides reliable and scalable backhaul transmission for base stations and access points in ultra-dense networks, which is in line with the requirements of 5G green technology. therefore, in this paper, we propose a collaborative edge caching method that effectively combines IRS-aided wireless communication and channel power-delay-profile to design joint caching decisions in a centralized manner through limited cache capacity, improving the quality of content delivery in information transmission. then we proposed a deep deterministic policy gradient learning method based on the framework of deep reinforcement learning along with self-supervision learning to predict IRS phases and collaborative caching strategies. the numerical simulation results show that the proposed algorithm has better convergence speed and learning accuracy than that of the existing algorithms, and is expected to be applied for future massive and dynamical content delivery applications.

关键词： Wireless communication Accuracy 5G mobile communication Heuristic algorithms Collaboration Time-varying channels Prediction algorithms

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Using Sub-Giga Hertz Technology In High Sampling Rate Wireless Monitoring systems Used In High-Rise Buildings 7

Using Sub-Giga Hertz Technology In High Sampling Rate Wirele...

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Moratuwa Engineering Research conference (MERCon) / 7th international Multidisciplinary Engineering Research conference

作者： Vishnu, P. Kirishikesan, K. Lewangamage, C. S. Jayasinghe, M. T. R. Univ Moratuwa Dept Civil Engn Moratuwa Sri Lanka Univ Moratuwa Dept Comp Sci & Engn Moratuwa Sri Lanka

ISBN: (纸本)9781665437530

Structural Health Monitoring (SHM) systems have been increasingly used in Civil Infrastructures to extract reliable information about the integrity and other important parameters of the structure in real-time. Using wireless sensor networks (WSN) in SHM applications has seen exponential growth in the last decade with the introduction of new communication protocols. WSN makes monitoring of structures easy and fast with low-cost involved. However, some structures such as high-rise buildings, are considered difficult for establishing WSN due to the presence of vertical obstructions. Radio waves with low-frequency are widely used in long-range SHM applications and monitoring high-rise buildings. Carrier waves with lower frequencies used in WSN travel over long-range and through obstructions easily compared to waves that are with higher frequency. Even though the range is increased in low-frequency waves, data rate is also reduced with decreasing frequency. In the SHM applications of high-rise buildings, it is not possible to compensate one - data transfer rate and penetrating ability for the other. this paper discusses the applications of Sub-Giga hertz technology and the corresponding performance of the developed WSN. Also, the application of simple and efficient data handling method used to ensure near real-time SHM is discussed in this paper.

关键词： Sub-Gigahertz Wireless sensor networks Low-cost Structural health monitoring distributed computing Long-range Data handling

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