scholarly journals Green distributed algorithm for energy saving in IP wired networks using sleep scheduling

2021 ◽  
Vol 11 (6) ◽  
pp. 5160
Author(s):  
Mohammed Hussein ◽  
Wisam Alabbasi ◽  
Ahmad Alsadeh
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Learning Algorithm ◽  
Critical Issue ◽  
The Internet ◽  
Great Effort ◽  
Network Nodes ◽  
Backbone Networks ◽  
Wired Networks ◽  
Traffic Matrix

Energy saving has become a critical issue and a great challenge in the past few decades, and a great effort as well is being made to reduce consumed energy. The Internet forms a major source for energy consumption. Therefore, in this work we propose an algorithm for energy saving in distributed backbone networks, the reduced energy consumption (RedCon) algorithm. In this paper, we introduce a new version for saving energy on the Internet by switching off underutilized links and switching on idle links when the network is overloaded in a distributed manner over the network nodes based on LSA messages and without any knowledge of the traffic matrix. Our algorithm is more accurate and outperforms other algorithms with its time checks and advanced learning algorithm.

Blackout Avoidance and Energy Saving Services with Alert Aggregation

2012 ◽  
Vol 3 (4) ◽  
pp. 40-56
Author(s):  
Erica Fong ◽  
Dickson K.W. Chiu ◽  
Haiyang Hu ◽  
Yi Zhuang ◽  
Hua Hu
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Real Time ◽  
Mobile Devices ◽  
Critical Energy ◽  
The Internet ◽  
Monitor System ◽  
Energy Usage ◽  
Huge Number ◽  
Smart Meters

Peak electricity demands from huge number of households in a mega-city would cause contention, leading to potential blackout. This paper proposes bi-directional collaboration via a Smart Energy Monitor System (SEMS) between consumers and energy suppliers, exchanging real-time energy usage data with smart meters over the Internet and mobile devices for well-informed decisions and even predictions. The authors further propose the use of an Alert Management System (AMS) to monitor and aggregate critical energy consumption events for this purpose.

scholarly journals HEMS-IoT: A Big Data and Machine Learning-Based Smart Home System for Energy Saving

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1097 ◽  
Author(s):  
Isaac Machorro-Cano ◽  
Giner Alor-Hernández ◽  
Mario Andrés Paredes-Valverde ◽  
Lisbeth Rodríguez-Mazahua ◽  
José Luis Sánchez-Cervantes ◽  
...  
Keyword(s):  
Machine Learning ◽  
Energy Efficiency ◽  
Big Data ◽  
Energy Consumption ◽  
Energy Saving ◽  
Smart Home ◽  
User Preferences ◽  
The Internet ◽  
Automation Systems ◽  
Home Energy Management

Energy efficiency has aroused great interest in research worldwide, because energy consumption has increased in recent years, especially in the residential sector. The advances in energy conversion, along with new forms of communication, and information technologies have paved the way for what is now known as smart homes. The Internet of Things (IoT) is the convergence of various heterogeneous technologies from different application domains that are used to interconnect things through the Internet, thus allowing for the detection, monitoring, and remote control of multiple devices. Home automation systems (HAS) combined with IoT, big data technologies, and machine learning are alternatives that promise to contribute to greater energy efficiency. This work presents HEMS-IoT, a big data and machine learning-based smart home energy management system for home comfort, safety, and energy saving. We used the J48 machine learning algorithm and Weka API to learn user behaviors and energy consumption patterns and classify houses with respect to energy consumption. Likewise, we relied on RuleML and Apache Mahout to generate energy-saving recommendations based on user preferences to preserve smart home comfort and safety. To validate our system, we present a case study where we monitor a smart home to ensure comfort and safety and reduce energy consumption.

scholarly journals Intelligent spacing selection model under energy-saving constraints for the selection of communication nodes in the Internet of Things

2021 ◽  
Author(s):  
Jing-Shu Sun ◽  
Teng Zhu ◽  
Marcin Wozniak
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Energy Saving ◽  
Transition Amplitude ◽  
Selection Model ◽  
Link Quality ◽  
The Internet ◽  
The Internet Of Things ◽  
Spacing Selection ◽  
Selection Of

AbstractCurrent IoT communication node spacing selection process show may potential areas for improvements such as high delay ratio, high total energy consumption ratio, confusion of the optimal communication information band, intelligent spacing node design under the constraints of the energy-saving selection of IoT communication. Based on energy-saving constraints, the link status between nodes is evaluated through link stability and link quality. In order to prevent the generation of serious noisy nodes and frequency hopping data, the interference nodes under the intrusion of the Internet of Things are identified by determining transition amplitude of the noise nodes in the transmission data sequence. Finally, according to the calculation results of the optimal communication node selection, the design of the intelligent spacing selection model for the communication nodes of the Internet of Things is realized. The simulation results show that the established model not only reduces energy consumption of nodes, shortens the average transmission delay of nodes, but also improves anti-interference effect of node spacing selection.

A Study on the Convergence Adaptor Using Plug Computer

2012 ◽  
Vol 462 ◽  
pp. 348-352
Author(s):  
Jung Mee Yun ◽  
Dae Hwan Kim
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Saving ◽  
Energy Efficient ◽  
The Internet ◽  
Internet Applications ◽  
Power Monitoring ◽  
Mac Layers ◽  
Related Energy ◽  
Cooling Devices

Recent studies have shown that the Internet-related energy consumption represents a significant, and increasing, part of the overall energy consumption of our society. Therefore, it is extremely important to look for energy-efficient Internet applications and protocols. For EPON, research on the development of protocols for higher energy efficiency at the PHY/MAC layers and the enactment of standards, and the improvement of energy efficiency of EPON devices is being conducted, while for networking equipment such as routers and switches and IDCs, research on saving the energy consumed by devices and the management of energy efficiency using power monitoring, cooling devices and metering technologies is being conducted. Against this backdrop, this study is aimed to develop methodology for the improvement of network energy efficiency in existing home/ small and medium-sized office network environments and to develop, test and evaluate an energy saving prototype for Convergence Adaptor

A Comprehensive Survey of Energy-Efficiency Approaches in Wired Networks

2021 ◽  
Author(s):  
Rahil Gandotra ◽  
Levi Perigo
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
The Internet ◽  
Critical Research ◽  
Wired Networks ◽  
Link Rate ◽  
Comprehensive Survey ◽  
Reduce Energy Consumption ◽  
Store And Forward ◽  
Future Work

Energy consumption by the network infrastructure is growing expeditiously with the rise of the Internet. Critical research efforts have been pursued by academia, industry and governments to make networks, such as the Internet, operate more energy efficiently and reduce their power consumption. This work presents an in-depth survey of the approaches to reduce energy consumption in wired networks by first categorizing existing research into broad categories and then presenting the specific techniques, research challenges, and important conclusions. At abroad level, we present five categories of approaches for energy efficiency in wired networks – (i) sleeping of network elements, (ii) link rate adaptation, (iii) proxying, (iv) store and forward, and (v) network traffic aggregation. Additionally, this survey reviews work in energy modeling and measurement, energy-related standards and metrics, and enumerates discussion points for future work and motivations.

CLOUD BASED INTERNET OF THINGS FOR SMART CONNECTED OBJECTS

2019 ◽  
Vol 01 (02) ◽  
pp. 31-39 ◽  
Author(s):  
Duraipandian M. ◽  
Vinothkanna R.
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Smart Home ◽  
Electricity Consumption ◽  
Considerable Improvement ◽  
The Internet ◽  
The Internet Of Things ◽  
At Home

The paper proposing the cloud based internet of things for the smart connected objects, concentrates on developing a smart home utilizing the internet of things, by providing the embedded labeling for all the tangible things at home and enabling them to be connected through the internet. The smart home proposed in the paper concentrates on the steps in reducing the electricity consumption of the appliances at the home by converting them into the smart connected objects using the cloud based internet of things and also concentrates on protecting the house from the theft and the robbery. The proposed smart home by turning the ordinary tangible objects into the smart connected objects shows considerable improvement in the energy consumption and the security provision.

The Research of Measuring Approach and Energy Efficiency for Hadoop Periodic Jobs

2015 ◽  
Vol 8 (1) ◽  
pp. 206-210 ◽  
Author(s):  
Yu Junyang ◽  
Hu Zhigang ◽  
Han Yuanyuan
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Energy Saving ◽  
Energy Estimate ◽  
Cloud Platform ◽  
Periodic Tasks ◽  
Current Consumption ◽  
Reduce Energy Consumption

Current consumption of cloud computing has attracted more and more attention of scholars. The research on Hadoop as a cloud platform and its energy consumption has also received considerable attention from scholars. This paper presents a method to measure the energy consumption of jobs that run on Hadoop, and this method is used to measure the effectiveness of the implementation of periodic tasks on the platform of Hadoop. Combining with the current mainstream of energy estimate formula to conduct further analysis, this paper has reached a conclusion as how to reduce energy consumption of Hadoop by adjusting the split size or using appropriate size of workers (servers). Finally, experiments show the effectiveness of these methods as being energy-saving strategies and verify the feasibility of the methods for the measurement of periodic tasks at the same time.

Design and Implementation of Low Energy Wireless Network Nodes based on Hardware Compression Acceleration

2019 ◽  
Vol 12 ◽  
Author(s):  
Hui Yang ◽  
Anand Nayyar
Keyword(s):  
Energy Consumption ◽  
Data Compression ◽  
Energy Saving ◽  
Optimization Design ◽  
Hardware Acceleration ◽  
Transmission Efficiency ◽  
General Purpose ◽  
Storage Space ◽  
General Purpose Processor ◽  
Compression Time

: In the fast development of information, the information data is increasing in geometric multiples, and the speed of information transmission and storage space are required to be higher. In order to reduce the use of storage space and further improve the transmission efficiency of data, data need to be compressed. processing. In the process of data compression, it is very important to ensure the lossless nature of data, and lossless data compression algorithms appear. The gradual optimization design of the algorithm can often achieve the energy-saving optimization of data compression. Similarly, The effect of energy saving can also be obtained by improving the hardware structure of node. In this paper, a new structure is designed for sensor node, which adopts hardware acceleration, and the data compression module is separated from the node microprocessor.On the basis of the ASIC design of the algorithm, by introducing hardware acceleration, the energy consumption of the compressed data was successfully reduced, and the proportion of energy consumption and compression time saved by the general-purpose processor was as high as 98.4 % and 95.8 %, respectively. It greatly reduces the compression time and energy consumption.

Sign in / Sign up

Export Citation Format

Share Document