scholarly journals Method for Designing Robust and Energy Efficient Railway Schedules

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8248
Author(s):  
Franciszek Restel ◽  
Łukasz Wolniewicz ◽  
Matea Mikulčić
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Evaluation Model ◽  
Railway Line ◽  
Railway Traffic ◽  
Sensitive Issue ◽  
Buffer Time ◽  
Simulation Based ◽  
Time Buffer ◽  
Operational Data

The robustness of the timetable is a sensitive issue in the daily realization of railway operations. As shown in the paper, robustness is a function of time reserves that helps to prevent unscheduled stops resulting from traffic disruptions and causing a higher energy consumption. The correct handling of time reserves while scheduling is a multidimensional issue, and it has a significant influence on the energy consumption of railway traffic. Therefore, the paper aims to show a simulation-based method, taking into account failure occurring probabilities and their consequences to get an acceptable level of robustness, that can be quantified by the probability of no delay propagation. This paper presents a method for the addition of time margins to the railway timetable. The iterative time buffer adding method is based on operational data as a knowledge source, to achieve the punctuality target. It was verified on a real railway line. An analysis of energy consumption for unscheduled train stops depending on the added buffer time was conducted after the literature review and the presentation of the evaluation model. The paper ends with discussion of the results and conclusions.

scholarly journals Simulation-Based Genetic Algorithm towards an Energy-Efficient Railway Traffic Control

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Daniel Tuyttens ◽  
Hongying Fei ◽  
Mohand Mezmaz ◽  
Jad Jalwan
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Total Energy ◽  
Traffic Control ◽  
Energy Efficient ◽  
Energy Utilization ◽  
Utilization Rate ◽  
Total Energy Consumption ◽  
Railway Traffic ◽  
Mode Control

The real-time traffic control has an important impact on the efficiency of the energy utilization in the modern railway network. This study is aimed to develop an energy-efficient railway traffic control solution for any specified railway. In other words, it is expected to define suitable driving profiles for all the trains running within a specified period through the targeted network with an objective to minimize their total energy consumption. How to optimize the train synchronization so as to benefit from the energy regenerated by electronic braking is also considered in this study. A method based on genetic algorithm and empirical single train driving strategies is developed for this objective. Six monomode strategies and one multimode strategy are tested and compared with the four scenarios extracted from the Belgian railway system. The results obtained by simulation show that the multi-mode control strategy overcomes the mono-mode control strategies with regard to global energy consumption, while there is no firm relation between the utilization rate of energy regenerated by dynamic braking operations and the reduction of total energy consumption.

scholarly journals Energy Efficiency of Railway Lines

2011 ◽  
Vol 23 (3) ◽  
pp. 187-193 ◽  
Author(s):  
Tomislav Josip Mlinarić ◽  
Klemen Ponikvar
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Traffic Management ◽  
Railway Stations ◽  
Railway Traffic ◽  
Railway Infrastructure ◽  
Ending Process ◽  
Production Capacities ◽  
Optimal Construction ◽  
Consumption Efficiency

Energy saving is necessary in accordance with the principles of sustainable development. Energy consumption is increasing, and the production capacities are limited. The three main railway segments such as: railway infrastructure, traffic management and dynamic train movement have an important impact on energy consumption for train haulage. The aim of the research presented in this paper is to determine energy consumption efficiency for train haulage, by choosing optimal construction parameters of railway lines, modern design of railway stations, optimal traffic management and energy efficient dynamic train movement. The paper gives a concrete presentation of energy consumption in all three segments of railway traffic and proposals for rationalization of energy consumption. The infrastructure managers and rail carriers should cooperate in the process of efficiency consumption of energy for train haulage. Saving of energy is a never-ending process.

Network Energy Consumption Models and Energy Efficient Algorithms

2012 ◽  
Vol 35 (3) ◽  
pp. 603-615 ◽  
Author(s):  
Fa ZHANG ◽  
Antonio Fernandez Anta ◽  
Lin WANG ◽  
Chen-Ying HOU ◽  
Zhi-Yong LIU
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Efficient Algorithms

Performance Analysis of Energy Efficient Opportunistic Routing Protocols in Wireless Sensor Network

2019 ◽  
Vol 09 ◽  
Author(s):  
Premkumar Chithaluru ◽  
Rajeev Tiwari ◽  
Kamal Kumar
Keyword(s):  
Energy Consumption ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Data Communication ◽  
Opportunistic Routing ◽  
Link Quality ◽  
Delivery Ratio ◽  
Performance Parameters ◽  
Wireless Medium ◽  
Reduce Energy Consumption

Background: Energy Efficient wireless routing has been an area of research particularly to mitigate challenges surrounding performance in category of Wireless Networks. Objectives: The Opportunistic Routing (OR) technique was explored in recent times and exhibits benefits over many existing protocols and can significantly reduce energy consumption during data communication with very limited compromise on performance. Methods : Using broadcasting nature of the wireless medium, OR practices to discourse two foremost issues of variable link quality and unpredictable node agility in constrained WSNs. OR has a potential to reduce delay in order to increase the consistency of data delivery in network. Results : Various OR based routing protocols have shown varying performances. In this paper, a detailed conceptual and experimental analysis is carried out on different protocols that uses OR technique for providing more clear and definitive view on performance parameters like Message Success Rate, Packet Delivery Ratio and Energy Consumption.

A Split Network based Routing Approach in Wireless Sensor Network to Enhance Network Stability

2019 ◽  
Vol 9 (4) ◽  
pp. 480-487 ◽  
Author(s):  
Hardeep S. Saini ◽  
Dinesh Arora
Keyword(s):  
Energy Consumption ◽  
Sensor Network ◽  
Energy Efficient ◽  
Cluster Head ◽  
Base Station ◽  
Operating Efficiency ◽  
Network Stability ◽  
Major Factors ◽  
Ch Selection

Background & Objective: The operating efficiency of a sensor network totally relies upon the energy that is consumed by the nodes to perform various tasks like data transmission etc. Thus, it becomes mandatory to consume the energy in an intelligent way so that the network can run for a long period. This paper proposed an energy efficient Cluster Head (CH) selection mechanism by considering the distance to Base Station (BS), distance to node and energy as major factors. The concept of volunteer node is also introduced with an objective to reduce the energy consumption of the CH to transmit data from source to BS. The role of the volunteer node is to transmit the data successfully from source to destination or BS. Conclusion: The results are observed with respect to the Alive nodes, dead nodes and energy consumption of the network. The outcome of the proposed work proves that it outperforms the traditional mechanisms.

Energy Efficient Clustering and Routing Algorithm for WSN

2019 ◽  
Vol 12 ◽  
Author(s):  
Mohit Kumar ◽  
Sonu Mittal ◽  
Md. Amir Khusru Akhtar
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Hot Spot ◽  
Routing Algorithm ◽  
Relay Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Clustering ◽  
Hot Spot Problem

Background: This paper presents a novel Energy Efficient Clustering and Routing Algorithm (EECRA) for WSN. It is a clustering-based algorithm that minimizes energy dissipation in wireless sensor networks. The proposed algorithm takes into consideration energy conservation of the nodes through its inherent architecture and load balancing technique. In the proposed algorithm the role of inter-cluster transmission is not performed by gateways instead a chosen member node of respective cluster is responsible for data forwarding to another cluster or directly to the sink. Our algorithm eases out the load of the gateways by distributing the transmission load among chosen sensor node which acts as a relay node for inter-cluster communication for that round. Grievous simulations show that EECRA is better than PBCA and other algorithms in terms of energy consumption per round and network lifetime. Objective: The objective of this research lies in its inherent architecture and load balancing technique. The sole purpose of this clustering-based algorithm is that it minimizes energy dissipation in wireless sensor networks. Method: This algorithm is tested with 100 sensor nodes and 10 gateways deployed in the target area of 300m × 300m. The round assumed in this simulation is same as in LEACH. The performance metrics used for comparisons are (a) network lifetime of gateways and (b) energy consumption per round by gateways. Our algorithm gives superior result compared to LBC, EELBCA and PBCA. Fig 6 and Fig 7 shows the comparison between the algorithms. Results: The simulation was performed on MATLAB version R2012b. The performance of EECRA is compared with some existing algorithms like PBCA, EELBCA and LBCA. The comparative analysis shows that the proposed algorithm outperforms the other existing algorithms in terms of network lifetime and energy consumption. Conclusion: The novelty of this algorithm lies in the fact that the gateways are not responsible for inter-cluster forwarding, instead some sensor nodes are chosen in every cluster based on some cost function and they act as a relay node for data forwarding. Note the algorithm does not address the hot-spot problem. Our next endeavor will be to design an algorithm with consideration of hot-spot problem.

scholarly journals Collision Avoidance Geographic P2P-RPL in Multi-Hop Indoor Wireless Networks

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1484
Author(s):  
Yunyoung Choi ◽  
Jaehyung Park ◽  
Jiwon Jung ◽  
Younggoo Kwon
Keyword(s):  
Energy Consumption ◽  
Collision Avoidance ◽  
Energy Efficient ◽  
Convergence Time ◽  
Location Information ◽  
Route Discovery ◽  
Localization Algorithm ◽  
Control Packet ◽  
Network Convergence ◽  
Routing Control

In home and building automation applications, wireless sensor devices need to be connected via unreliable wireless links within a few hundred milliseconds. Routing protocols in Low-power and Lossy Networks (LLNs) need to support reliable data transmission with an energy-efficient manner and short routing convergence time. IETF standardized the Point-to-Point RPL (P2P-RPL) routing protocol, in which P2P-RPL propagates the route discovery messages over the whole network. This leads to significant routing control packet overhead and a large amount of energy consumption. P2P-RPL uses the trickle algorithm to control the transmission rate of routing control packets. The non-deterministic message suppression nature of the trickle algorithm may generate a sub-optimal routing path. The listen-only period of the trickle algorithm may lead to a long network convergence time. In this paper, we propose Collision Avoidance Geographic P2P-RPL, which achieves energy-efficient P2P data delivery with a fast routing request procedure. The proposed algorithm uses the location information to limit the network search space for the desired route discovery to a smaller location-constrained forwarding zone. The Collision Avoidance Geographic P2P-RPL also dynamically selects the listen-only period of the trickle timer algorithm based on the transmission priority related to geographic position information. The location information of each node is obtained from the Impulse-Response Ultra-WideBand (IR-UWB)-based cooperative multi-hop self localization algorithm. We implement Collision Avoidance Geographic P2P-RPL on Contiki OS, an open-source operating system for LLNs and the Internet of Things. The performance results show that the Collision Avoidance Geographic P2P-RPL reduced the routing control packet overheads, energy consumption, and network convergence time significantly. The cooperative multi-hop self localization algorithm improved the practical implementation characteristics of the P2P-RPL protocol in real world environments. The collision avoidance algorithm using the dynamic trickle timer increased the operation efficiency of the P2P-RPL under various wireless channel conditions with a location-constrained routing space.

scholarly journals Energy-Efficient Packet Forwarding Scheme Based on Fuzzy Decision-Making in Underwater Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4368
Author(s):  
Jitander Kumar Pabani ◽  
Miguel-Ángel Luque-Nieto ◽  
Waheeduddin Hyder ◽  
Pablo Otero
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Real Life ◽  
Base Station ◽  
Fuzzy Decision Making ◽  
Underwater Sensor Networks ◽  
Packet Forwarding ◽  
Node Number ◽  
The Impact

Underwater Wireless Sensor Networks (UWSNs) are subjected to a multitude of real-life challenges. Maintaining adequate power consumption is one of the critical ones, for obvious reasons. This includes proper energy consumption due to nodes close to and far from the sink node (gateway), which affect the overall energy efficiency of the system. These wireless sensors gather and route the data to the onshore base station through the gateway at the sea surface. However, finding an optimum and efficient path from the source node to the gateway is a challenging task. The common reasons for the loss of energy in existing routing protocols for underwater are (1) a node shut down due to battery drainage, (2) packet loss or packet collision which causes re-transmission and hence affects the performance of the system, and (3) inappropriate selection of sensor node for forwarding data. To address these issues, an energy efficient packet forwarding scheme using fuzzy logic is proposed in this work. The proposed protocol uses three metrics: number of hops to reach the gateway node, number of neighbors (in the transmission range of a node) and the distance (or its equivalent received signal strength indicator, RSSI) in a 3D UWSN architecture. In addition, the performance of the system is also tested with adaptive and non-adaptive transmission ranges and scalable number of nodes to see the impact on energy consumption and number of hops. Simulation results show that the proposed protocol performs better than other existing techniques or in terms of parameters used in this scheme.

Wearable energy efficient fitness tracker for sports person health monitoring application

2021 ◽  
pp. 1-10
Author(s):  
Yongyue Huang ◽  
Min Hu ◽  
BalaAnand Muthu ◽  
R. Gayathri
Keyword(s):  
Energy Consumption ◽  
Data Storage ◽  
Energy Efficient ◽  
Consumer Satisfaction ◽  
Form Factors ◽  
Recognition System ◽  
Energy Utilization ◽  
Biologically Inspired Algorithms ◽  
Enhance Efficiency ◽  
Fitness Tracker

Continuous evaluation of biological and physiological metrics of sports personalities, evaluating general health status, and alerting for life-saving treatments, is supposed to enhance efficiency and healthy performance. Wearable devices with acceptable form factors compact, flexibility, minimal power consumption, etc., are needed for continuous monitoring to avoid affecting everyday operations, thereby retaining functional effectiveness and consumer satisfaction. This research focuses on the acceleration tracker for particularizing the work. Acceleration data is typically collected on battery-powered sensors for activity detection, referring to an exchange between high-precision detection and energy-efficient processing. From a feature selection perspective, the paper explores this trade-off. It suggests an Energy-Efficient Behavior Recognition System with a comprehensive energy utilization model and the Multi-objective Algorithm of Particle Swarm Optimization (EEBRS-MPSO). Therefore, using Random Forest (RF) classifiers, the model and algorithm are tested to measure the precision of identification and obtain the task’s best performance with the lowest energy consumption, among other biologically-inspired algorithms. The findings indicate that energy consumption for data storage and data processing is minimized with magnitude relative to the raw data method by choosing suitable groups of attributes. Thus, the platform allows a scalable range of feature clusters that require the authors to provide an adequate power adjustment for given target use.

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