This document discusses smart device collaboration for energy saving in home networks. It provides background on the increasing economic and environmental reasons for green home initiatives to reduce energy consumption. It then reviews the state of the art in power management techniques at the device and network levels, such as advanced configuration and power interface specification, dynamic power management, low power networking technologies, and home automation energy control. The thesis contributions are outlined, including a ZigBee mandatory energy saving solution, ZigBee optional energy saving solution, an overlay energy control network architecture, three use cases, and collaborative power control management approaches. Evaluation results show that while ZigBee mandatory control provides more energy savings, ZigBee optional control offers a better tradeoff
Sklubi AlumniWeekend 23.10.2010:
Reijo Maihaniemi
Electricity Consumption: General
Electricity Savings Through DC Power Feed
DC Data Center Projects in the World
ICT Energy saving actions
Ph d thesis_seminar_on the design of energy efficient wireless access_sibelto...Sibel Tombaz
This document provides an outline for a Ph.D. thesis defense on the design of energy efficient wireless access networks. The thesis focuses on assessing energy efficiency at the network level and developing solutions to deploy and operate networks in an energy efficient manner while considering total cost. Key findings include identifying appropriate metrics to assess energy efficiency to avoid misleading results, developing models for backhaul power consumption that show its growing impact, and quantifying potential energy savings of 30% through heterogeneous network architectural solutions that optimize deployment based on traffic demand. Operational solutions like cell dormancy tracking are also analyzed to efficiently match capacity with traffic.
This document contains 17 slides summarizing research related to smart grid supply chain partners. It identifies potential partner companies using NAICS and SIC codes covering areas such as power distribution, construction, wiring installation, computer and electronics manufacturing, communications equipment, meters, sensors and other smart grid technologies. Example companies mentioned include ABB, Alcatel-Lucent, Aviat Networks, Black & Veatch, Brocade, Cisco, Cree, Cypress Semiconductor, and others.
This document provides a summary of a presentation on the design of a smart off-grid energy system. It discusses India's energy scenario and the need for smart grids. It describes the components, software, and standards used for hybrid and smart grid system design. It covers the sizing, modeling, and scheduling of a wind-diesel-battery storage system including wind speed forecasting and load assessment. Circuit diagrams and results are presented for a developed smart off-grid energy system model that integrates renewable energy and allows for smart utilization of energy through various sensors and controls.
Matthew Hause: The Smart Grid and MBSE Driven IoT EnergyTech2015
EnergyTech2015.com
Track 3 Session 3
Moderator: Mark Walker
The integration of the Internet of Things (IoT) and MBSE in an Energy System and Complex energy grid management in a changing and dynamic future.
Matthew Hause – Paper 1: Making the Smart Grid Smarter, MBSE Driven IoT The future of IoT success, including technology advancements and revenue generating potential across the business spectrum, is dependent on the application of solid Systems Engineering and Model Based Systems Engineering (MBSE) principals. Without MBSE, the complexity involved in the design, development, and deployment of IoT systems would consume both system and operational providers. Absent of any industry standards, IoT systems cannot be built in a vacuum and their success will only be realized through application of modern day systems engineering processes, methods, and tools. The infrastructure and management will need to be established prior to, or in conjunction with, the smart systems that support them. This paper will show an Energy system and connected systems and how an MBSE and SoS approach will help guide development.
The document discusses the key aspects and technologies of the smart grid, including smart meters, demand response, renewable energy integration, energy storage, wide area monitoring, and standards development. It outlines the vision of a highly instrumented and interconnected grid that can better accommodate new technologies and optimize operations.
This document is the first Smart Grid System Report to Congress mandated by the Energy Independence and Security Act of 2007. It summarizes the key findings of the report, which assess the status of smart grid deployments nationwide and any barriers. The report finds that while distributed energy resources and advanced metering infrastructure are growing, penetration remains low. It also finds that modernizing the electricity infrastructure is progressing, but understanding the business cases and policies is still emerging. Overall, the smart grid represents a significant technological and cultural change for the electric system.
Sklubi AlumniWeekend 23.10.2010:
Reijo Maihaniemi
Electricity Consumption: General
Electricity Savings Through DC Power Feed
DC Data Center Projects in the World
ICT Energy saving actions
Ph d thesis_seminar_on the design of energy efficient wireless access_sibelto...Sibel Tombaz
This document provides an outline for a Ph.D. thesis defense on the design of energy efficient wireless access networks. The thesis focuses on assessing energy efficiency at the network level and developing solutions to deploy and operate networks in an energy efficient manner while considering total cost. Key findings include identifying appropriate metrics to assess energy efficiency to avoid misleading results, developing models for backhaul power consumption that show its growing impact, and quantifying potential energy savings of 30% through heterogeneous network architectural solutions that optimize deployment based on traffic demand. Operational solutions like cell dormancy tracking are also analyzed to efficiently match capacity with traffic.
This document contains 17 slides summarizing research related to smart grid supply chain partners. It identifies potential partner companies using NAICS and SIC codes covering areas such as power distribution, construction, wiring installation, computer and electronics manufacturing, communications equipment, meters, sensors and other smart grid technologies. Example companies mentioned include ABB, Alcatel-Lucent, Aviat Networks, Black & Veatch, Brocade, Cisco, Cree, Cypress Semiconductor, and others.
This document provides a summary of a presentation on the design of a smart off-grid energy system. It discusses India's energy scenario and the need for smart grids. It describes the components, software, and standards used for hybrid and smart grid system design. It covers the sizing, modeling, and scheduling of a wind-diesel-battery storage system including wind speed forecasting and load assessment. Circuit diagrams and results are presented for a developed smart off-grid energy system model that integrates renewable energy and allows for smart utilization of energy through various sensors and controls.
Matthew Hause: The Smart Grid and MBSE Driven IoT EnergyTech2015
EnergyTech2015.com
Track 3 Session 3
Moderator: Mark Walker
The integration of the Internet of Things (IoT) and MBSE in an Energy System and Complex energy grid management in a changing and dynamic future.
Matthew Hause – Paper 1: Making the Smart Grid Smarter, MBSE Driven IoT The future of IoT success, including technology advancements and revenue generating potential across the business spectrum, is dependent on the application of solid Systems Engineering and Model Based Systems Engineering (MBSE) principals. Without MBSE, the complexity involved in the design, development, and deployment of IoT systems would consume both system and operational providers. Absent of any industry standards, IoT systems cannot be built in a vacuum and their success will only be realized through application of modern day systems engineering processes, methods, and tools. The infrastructure and management will need to be established prior to, or in conjunction with, the smart systems that support them. This paper will show an Energy system and connected systems and how an MBSE and SoS approach will help guide development.
The document discusses the key aspects and technologies of the smart grid, including smart meters, demand response, renewable energy integration, energy storage, wide area monitoring, and standards development. It outlines the vision of a highly instrumented and interconnected grid that can better accommodate new technologies and optimize operations.
This document is the first Smart Grid System Report to Congress mandated by the Energy Independence and Security Act of 2007. It summarizes the key findings of the report, which assess the status of smart grid deployments nationwide and any barriers. The report finds that while distributed energy resources and advanced metering infrastructure are growing, penetration remains low. It also finds that modernizing the electricity infrastructure is progressing, but understanding the business cases and policies is still emerging. Overall, the smart grid represents a significant technological and cultural change for the electric system.
A smart grid uses digital technology and automation to detect and react to local changes in usage. It incorporates smart meters, renewable energy sources, and energy efficiency resources. The Government of India approved the National Smart Grid Mission to plan and monitor smart grid policies and programs. The NSGM will have its own resources and autonomy. It aims to deploy smart meters and substations, develop distributed generation like rooftop solar, and create infrastructure like EV charging stations.
CloudFuzion solutions for the Smart GridCloudFuzion
The document discusses technology solutions for the smart grid, focusing on Axceleon's CloudFuzion platform. CloudFuzion can accelerate simulations and analyses for various smart grid domains like transmission and distribution. It enables automated workflows and faster processing of applications to help optimize grid operations and integrate distributed energy resources like wind and solar. CloudFuzion supports applications in transmission, distribution, and market domains to provide near real-time analytics needed for improved grid management and efficiency.
Assessment to Delegate the Task to Cloud for Increasing Energy Efficiency of ...IRJET Journal
This document presents a study on offloading tasks from mobile phones to cloud computing to improve energy efficiency. It discusses how offloading computationally intensive tasks to faster cloud servers can reduce the time and energy required compared to performing tasks locally on mobile devices. The document outlines an analytical model and experimental setup to compare the energy consumption of performing tasks locally versus offloading. The results show that offloading tasks to cloud computing can significantly improve energy efficiency when the processing speed difference and data transfer sizes are considered.
The document discusses smart grid control. It defines smart grid control as algorithms or rules to handle smart grid systems. This allows for implementation of renewable energy and microgrids while making power grid control over wide area networks more challenging. The document outlines various smart grid control enablers like sensors, communication channels, and computational platforms. It also discusses frameworks for smart grid control from standards bodies like NIST. Specific control applications discussed include automated demand response, distribution grid optimization, and wide-area control using phasor measurement units.
Wide area network in smart grid kundanKundan Kumar
The document discusses the need for a wide area network (WAN) in a smart grid. It describes the roles of the WAN in connecting utilities across regional grids and allowing communication with customers and distributed energy sources. The document evaluates both public and private network options for a smart grid WAN and determines that a private wireless WAN is the most suitable approach. It outlines critical requirements for a private wireless WAN, including coverage, capacity, cost, range, supporting real-time two-way communication, security, and reliability.
[Case study] DONG Energy: Improving the bottom line and getting better data q...Schneider Electric
Applications:
An intelligent, easy-to-use drawing tool in which all the features selected in the design
phase are automatically saved in the GIS immediately.
Customer benefits:
• Improved bottom line
• Better data quality
• Better customer service
• Greater organisational knowledge about the projects
• Minimize the risks of errors
There are many factors in the data center that are driving the new data center design considerations. This slideshare discusses several of the trends in the data center and covers several solutions to implement.
A survey on smart grid technologies and applicationsdileep punalur
This document provides a survey of smart grid technologies and applications. It defines smart grid and discusses its key characteristics and functions. The smart grid uses digital technologies to provide a two-way power flow system that is self-healing, resilient, and sustainable. It allows for integration of renewable energy and distributed generation. Smart grid technologies discussed include smart meters, smart sensors, vehicle-to-grid, and home and building automation. The document also explores smart grid applications for metering, communication, and substation, feeder, and home automation. Overall, the smart grid is expected to provide economic and environmental benefits through improved efficiency, reliability, and integration of renewable energy.
The document outlines a student project to develop a prototype for a smart grid system. A group of 4 students - Zeeshan Shabbir, Umer Sohail, Haroon Sikandar, and Awais Yunis - along with their supervisor Dr. Shahid Khattak, plan to build a single-phase smart grid prototype that can harvest energy from renewable sources like solar panels, store it in batteries, and use it or supply it back to the grid. The presentation covers the vision, scope, basic operation, synchronization of PV and grid, energy management, required equipment, and project schedule of the smart grid prototype.
This document discusses smart energy and the transition to a smarter electric grid. It defines smart energy as integrating technologies like renewable power generation, energy storage, electric vehicle charging infrastructure, advanced metering infrastructure, and building energy management systems. The key benefits are more reliable and efficient energy delivery, better integration of renewable energy sources, and giving consumers more control over their energy usage. The document outlines the various components of a smart grid including generation, transmission & distribution networks, energy storage, demand management, and sensor technologies.
Challenges in smart grid project executionChandan Patary
The document discusses challenges in executing smart grid projects and solutions to address them. It outlines an agenda covering when grids became smart, challenges in developing smart grid solutions, and various approaches taken to improve the situation. It then discusses ABB's role in the smart grid horizon, smart grid market trends, focus areas, and solutions. Some challenges discussed include aging infrastructure and the need for stakeholder engagement. The document proposes solutions such as developing the right products through requirements engineering, product management, controlled development models, innovation frameworks, agility, gamification, cybersecurity compliance, collaboration, and serving customers.
This document discusses smart energy systems and the future of energy in India. It addresses the increasing energy demand, shortage of sources, and issues of pollution and climate change. Smart energy solutions are presented as being available now to help manage these challenges through greater energy efficiency, distributed generation, smart grids, and demand response. The role of various players and new technologies in creating a more decentralized and interactive energy system is outlined.
Data center power and cooling infrastructure worldwide wastes more than 60,000,000 megawatt-hours per year of electricity that does no useful work powering IT equipment. This represents an enormous financial burden on industry, and is a significant public policy environmental issue. This paper describes the principles of a new, commercially available data center
architecture that can be implemented today to dramatically improve the electrical efficiency of data centers.
This document provides an overview of smart grid technology. It begins by describing the conventional power grid and its drawbacks, such as aging equipment, obsolete systems, and lack of storage. It then introduces the smart grid as an infrastructure that supports advanced electricity generation, delivery, consumption, metering, monitoring, management, and communication technologies. Key differences between the conventional and smart grids are discussed. The document outlines various components that can be made smart, such as generation, transmission, distribution, and consumption. It proposes using optimization techniques and algorithms like genetic algorithms and particle swarm optimization to design an energy efficient and cost effective smart grid model.
As steel operations rely heavily on low-voltage motors, the introduction of new technologies which target motor performance have a direct impact on energy, commissioning and maintenance costs. Networking allows for easy monitoring of critical data of
each motor or load connected to the intelligent motor control center (iMCC), enabling precise process control. However, the iMCC concept isn’t a new technology. Networked protection relays and speed drivers are mature technologies with consolidated acceptance. Explore new trends for iMCCs including new Ethernet technologies, Web, wireless, biometric devices, and new technologies for metering and motor branch circuit protection. Copyright AIST Reprinted with Permission
Neural computing is now one of the most promising technologies in all fields of engineering,
resulting in the development of a number of Artificial Neural Networks (ANN). Double circuit transmission lines
are being employed in the distribution of power to consumers and have become more widespread than single
transmission line, as they increase the electric power transmission capacity and the reliability of an electrical
system. Losses along transmission lines occur due to faults. Possible faults on the transmission line were
predicted using Artificial Neutral Network. In this work, the simulation of fault on a 132kV double circuit
transmission lines using MATLAB was undertaken. Parameters considered during the simulation were the input
of the network which is the fault current value at each fault location while the output of the network is the fault
location. The efficiency of the neural network was tested and verified. This approach provided satisfactory
results with accuracy of 95% or higher.
Internet of Things - structured approach to the physical plant network - Rock...Carotek
The convergence of new technologies that securely connect plant information with enterprise systems can bring greater productivity, better utilization of assets, and improved decision-making to industrial companies. By bridging the gap between factory-level systems and enterprise systems, Rockwell Automation and Cisco can show how the connected enterprise offers ease of use, lower total cost of ownership, and improved operations.
This document discusses smart management strategies for smart grids. It introduces concepts like unified energy systems (UES) with generation, transmission, and distribution nodes. It frames smart grids as logistics networks that can apply supply chain management (SCM) approaches. Key technologies mentioned include mixed linear programming, regression, benchmarking, and blockchain. The document outlines a portfolio of projects including modeling energy streams, demand forecasting, data management, and reference architectures. Overall, it argues that optimization models are core to SCM in smart grids and can create opportunities like improved operational management and forecasting across different time horizons.
[Case study] Dakota Electric Association: Solutions to streamline GIS, design...Schneider Electric
Applications:
Integration of GIS-based processes makes existing circuits and proposed circuits
available in the same system so operations staff can work in parallel with the designers
rather than in succession.
Customer benefits
• Model, design and manage critical infrastructure
• Highly configurable
• Easily adapted for multiple uses
• Proactively identify needed repairs and replacements well in advance
Zigbee is a technological standard designed for control and sensor networks based on IEEE 802.15.4. The standard is developed and promoted by the Zigbee Alliance.
This document provides an overview of Zigbee, a wireless protocol that allows low-cost devices to transmit small amounts of data. It discusses the history and development of Zigbee, why it was needed as an alternative to WiFi and Bluetooth, its static architecture and device types. The document then explains how Zigbee networks and mesh networking work and describes applications of Zigbee for home automation, remote control and telecom services. It highlights advantages such as long battery life, low complexity and cost, and flexibility through mesh networking.
A smart grid uses digital technology and automation to detect and react to local changes in usage. It incorporates smart meters, renewable energy sources, and energy efficiency resources. The Government of India approved the National Smart Grid Mission to plan and monitor smart grid policies and programs. The NSGM will have its own resources and autonomy. It aims to deploy smart meters and substations, develop distributed generation like rooftop solar, and create infrastructure like EV charging stations.
CloudFuzion solutions for the Smart GridCloudFuzion
The document discusses technology solutions for the smart grid, focusing on Axceleon's CloudFuzion platform. CloudFuzion can accelerate simulations and analyses for various smart grid domains like transmission and distribution. It enables automated workflows and faster processing of applications to help optimize grid operations and integrate distributed energy resources like wind and solar. CloudFuzion supports applications in transmission, distribution, and market domains to provide near real-time analytics needed for improved grid management and efficiency.
Assessment to Delegate the Task to Cloud for Increasing Energy Efficiency of ...IRJET Journal
This document presents a study on offloading tasks from mobile phones to cloud computing to improve energy efficiency. It discusses how offloading computationally intensive tasks to faster cloud servers can reduce the time and energy required compared to performing tasks locally on mobile devices. The document outlines an analytical model and experimental setup to compare the energy consumption of performing tasks locally versus offloading. The results show that offloading tasks to cloud computing can significantly improve energy efficiency when the processing speed difference and data transfer sizes are considered.
The document discusses smart grid control. It defines smart grid control as algorithms or rules to handle smart grid systems. This allows for implementation of renewable energy and microgrids while making power grid control over wide area networks more challenging. The document outlines various smart grid control enablers like sensors, communication channels, and computational platforms. It also discusses frameworks for smart grid control from standards bodies like NIST. Specific control applications discussed include automated demand response, distribution grid optimization, and wide-area control using phasor measurement units.
Wide area network in smart grid kundanKundan Kumar
The document discusses the need for a wide area network (WAN) in a smart grid. It describes the roles of the WAN in connecting utilities across regional grids and allowing communication with customers and distributed energy sources. The document evaluates both public and private network options for a smart grid WAN and determines that a private wireless WAN is the most suitable approach. It outlines critical requirements for a private wireless WAN, including coverage, capacity, cost, range, supporting real-time two-way communication, security, and reliability.
[Case study] DONG Energy: Improving the bottom line and getting better data q...Schneider Electric
Applications:
An intelligent, easy-to-use drawing tool in which all the features selected in the design
phase are automatically saved in the GIS immediately.
Customer benefits:
• Improved bottom line
• Better data quality
• Better customer service
• Greater organisational knowledge about the projects
• Minimize the risks of errors
There are many factors in the data center that are driving the new data center design considerations. This slideshare discusses several of the trends in the data center and covers several solutions to implement.
A survey on smart grid technologies and applicationsdileep punalur
This document provides a survey of smart grid technologies and applications. It defines smart grid and discusses its key characteristics and functions. The smart grid uses digital technologies to provide a two-way power flow system that is self-healing, resilient, and sustainable. It allows for integration of renewable energy and distributed generation. Smart grid technologies discussed include smart meters, smart sensors, vehicle-to-grid, and home and building automation. The document also explores smart grid applications for metering, communication, and substation, feeder, and home automation. Overall, the smart grid is expected to provide economic and environmental benefits through improved efficiency, reliability, and integration of renewable energy.
The document outlines a student project to develop a prototype for a smart grid system. A group of 4 students - Zeeshan Shabbir, Umer Sohail, Haroon Sikandar, and Awais Yunis - along with their supervisor Dr. Shahid Khattak, plan to build a single-phase smart grid prototype that can harvest energy from renewable sources like solar panels, store it in batteries, and use it or supply it back to the grid. The presentation covers the vision, scope, basic operation, synchronization of PV and grid, energy management, required equipment, and project schedule of the smart grid prototype.
This document discusses smart energy and the transition to a smarter electric grid. It defines smart energy as integrating technologies like renewable power generation, energy storage, electric vehicle charging infrastructure, advanced metering infrastructure, and building energy management systems. The key benefits are more reliable and efficient energy delivery, better integration of renewable energy sources, and giving consumers more control over their energy usage. The document outlines the various components of a smart grid including generation, transmission & distribution networks, energy storage, demand management, and sensor technologies.
Challenges in smart grid project executionChandan Patary
The document discusses challenges in executing smart grid projects and solutions to address them. It outlines an agenda covering when grids became smart, challenges in developing smart grid solutions, and various approaches taken to improve the situation. It then discusses ABB's role in the smart grid horizon, smart grid market trends, focus areas, and solutions. Some challenges discussed include aging infrastructure and the need for stakeholder engagement. The document proposes solutions such as developing the right products through requirements engineering, product management, controlled development models, innovation frameworks, agility, gamification, cybersecurity compliance, collaboration, and serving customers.
This document discusses smart energy systems and the future of energy in India. It addresses the increasing energy demand, shortage of sources, and issues of pollution and climate change. Smart energy solutions are presented as being available now to help manage these challenges through greater energy efficiency, distributed generation, smart grids, and demand response. The role of various players and new technologies in creating a more decentralized and interactive energy system is outlined.
Data center power and cooling infrastructure worldwide wastes more than 60,000,000 megawatt-hours per year of electricity that does no useful work powering IT equipment. This represents an enormous financial burden on industry, and is a significant public policy environmental issue. This paper describes the principles of a new, commercially available data center
architecture that can be implemented today to dramatically improve the electrical efficiency of data centers.
This document provides an overview of smart grid technology. It begins by describing the conventional power grid and its drawbacks, such as aging equipment, obsolete systems, and lack of storage. It then introduces the smart grid as an infrastructure that supports advanced electricity generation, delivery, consumption, metering, monitoring, management, and communication technologies. Key differences between the conventional and smart grids are discussed. The document outlines various components that can be made smart, such as generation, transmission, distribution, and consumption. It proposes using optimization techniques and algorithms like genetic algorithms and particle swarm optimization to design an energy efficient and cost effective smart grid model.
As steel operations rely heavily on low-voltage motors, the introduction of new technologies which target motor performance have a direct impact on energy, commissioning and maintenance costs. Networking allows for easy monitoring of critical data of
each motor or load connected to the intelligent motor control center (iMCC), enabling precise process control. However, the iMCC concept isn’t a new technology. Networked protection relays and speed drivers are mature technologies with consolidated acceptance. Explore new trends for iMCCs including new Ethernet technologies, Web, wireless, biometric devices, and new technologies for metering and motor branch circuit protection. Copyright AIST Reprinted with Permission
Neural computing is now one of the most promising technologies in all fields of engineering,
resulting in the development of a number of Artificial Neural Networks (ANN). Double circuit transmission lines
are being employed in the distribution of power to consumers and have become more widespread than single
transmission line, as they increase the electric power transmission capacity and the reliability of an electrical
system. Losses along transmission lines occur due to faults. Possible faults on the transmission line were
predicted using Artificial Neutral Network. In this work, the simulation of fault on a 132kV double circuit
transmission lines using MATLAB was undertaken. Parameters considered during the simulation were the input
of the network which is the fault current value at each fault location while the output of the network is the fault
location. The efficiency of the neural network was tested and verified. This approach provided satisfactory
results with accuracy of 95% or higher.
Internet of Things - structured approach to the physical plant network - Rock...Carotek
The convergence of new technologies that securely connect plant information with enterprise systems can bring greater productivity, better utilization of assets, and improved decision-making to industrial companies. By bridging the gap between factory-level systems and enterprise systems, Rockwell Automation and Cisco can show how the connected enterprise offers ease of use, lower total cost of ownership, and improved operations.
This document discusses smart management strategies for smart grids. It introduces concepts like unified energy systems (UES) with generation, transmission, and distribution nodes. It frames smart grids as logistics networks that can apply supply chain management (SCM) approaches. Key technologies mentioned include mixed linear programming, regression, benchmarking, and blockchain. The document outlines a portfolio of projects including modeling energy streams, demand forecasting, data management, and reference architectures. Overall, it argues that optimization models are core to SCM in smart grids and can create opportunities like improved operational management and forecasting across different time horizons.
[Case study] Dakota Electric Association: Solutions to streamline GIS, design...Schneider Electric
Applications:
Integration of GIS-based processes makes existing circuits and proposed circuits
available in the same system so operations staff can work in parallel with the designers
rather than in succession.
Customer benefits
• Model, design and manage critical infrastructure
• Highly configurable
• Easily adapted for multiple uses
• Proactively identify needed repairs and replacements well in advance
Zigbee is a technological standard designed for control and sensor networks based on IEEE 802.15.4. The standard is developed and promoted by the Zigbee Alliance.
This document provides an overview of Zigbee, a wireless protocol that allows low-cost devices to transmit small amounts of data. It discusses the history and development of Zigbee, why it was needed as an alternative to WiFi and Bluetooth, its static architecture and device types. The document then explains how Zigbee networks and mesh networking work and describes applications of Zigbee for home automation, remote control and telecom services. It highlights advantages such as long battery life, low complexity and cost, and flexibility through mesh networking.
ZigBee is a wireless networking standard focused on low-cost, low-power consumption devices for monitoring and control applications. It uses the IEEE 802.15.4 standard for the physical and MAC layers and provides data rates from 20-250kbps depending on frequency band. ZigBee networks can support hundreds of devices with flexible star, peer-to-peer, or cluster tree topologies and address devices using short or IEEE addresses. The technology is well-suited for wireless control in industrial, commercial, and home automation applications where low data rates and power usage are priorities.
ZigBee is a wireless networking standard used for control and sensor applications that requires low data rates, low power consumption, and secure networking. It is based on the IEEE 802.15.4 standard and allows for up to 65,000 nodes to connect in a mesh network topology. ZigBee operates in the 2.4GHz, 868MHz, and 915MHz frequency bands and is designed for use in personal area networks for applications like home automation, lighting control, and wireless sensor networks. Research is ongoing to expand ZigBee's uses in fields like wireless communications and neuroengineering.
The document discusses Zigbee, a wireless networking standard based on IEEE 802.15.4. Some key points include:
- Zigbee allows for low-power wireless networks at data rates up to 250 kbps using the 2.4 GHz frequency band.
- It supports mesh networking topologies and can have thousands of nodes with extremely low duty cycles and long battery life.
- Zigbee networks operate using CSMA-CA channel access and can operate in beacon-enabled or non-beacon modes.
The document discusses device-level artificial intelligence (AI) for 5G networks and beyond. It describes how on-device AI can process and analyze data closer to its source, minimizing data transmission and protecting privacy while reducing latency. Examples of on-device AI applications include facial recognition and virtual assistants. The document also examines challenges of on-device AI like obtaining accurate data sets and balancing device autonomy with network impacts. It concludes that some level of device-level AI is inevitable as networks become more complex and intelligent devices are needed to help manage this complexity.
This document presents a presentation on home automation by Burungale Dhanaji Shivaji. It discusses designing a home automation system using an ARM7 controller that allows controlling home appliances wirelessly via switch, Wi-Fi, or GSM. The system aims to provide effective and efficient control of devices to help elderly or disabled people. It presents the objectives, scope, relevance, block diagram, software/language used, sequence diagrams, and conclusions regarding developing a low-cost, high-performance home automation system that allows easy user interaction through an Android phone.
Design of wireless sensor network for building management systemsTSriyaSharma
The primary objective of such this project is to achieve an optimal level of control of occupant comfort while minimizing energy use. Monitoring temperature, pressure, humidity occupancy, and flow rates are key functions of modern building control systems.
Infrastructure Solutions for Commercial Properties and DevelopersMestizo Enterprises
The days of talking about cost reduction are over. Our solutions are more sustainable, cost effective and less risky for your business. You'll end up with increased property value, increased marketability and lower operating and maintenance costs. Your Smart Property begins with our Intelligent Design. As a Private Operator you'll have more choice in how and where to apply the cost savings.
The document discusses the Office of Electricity Delivery and Energy Reliability's (OE) efforts to modernize the electric grid and ensure its resilience. Key points:
- OE leads the Department of Energy's work to maintain a reliable, flexible electric system and serves as the energy sector lead during federal emergencies.
- OE is working to develop a future grid that provides clean, affordable, and customizable electricity through projects like microgrid R&D and developing advanced distribution management systems.
- Microgrids are seen as integral to making cities smarter by providing reliability and resiliency during extreme events through integrating distributed energy resources and controls.
This is the idea of using existing power lines for communication purposes. Power line communications (PLC)
enables network communication of voice, data, and video over direct power lines. High-speed PLC involves
data rates in excess of 10 Mbps. PLC has attracted a lot of attention and has become an interesting subject of
research lately.
The document discusses the history and goals of smart grids, including modernizing energy transmission and distribution networks. It describes how smart grids use digital technologies, two-way communication, and automation to improve reliability, efficiency and integration of renewable energy. Some key benefits are enabling consumer participation through demand response, reducing peak demand, and allowing easier integration of electric vehicles and distributed generation. The document also outlines some technical aspects and challenges to wider smart grid adoption.
Skt.2013.innovation technology for future convergence networkson6971
This document discusses innovation technologies for future convergence networks, including:
1. Software-defined networking (SDN) and network function virtualization (NFV) to create a more agile, cost-efficient network architecture.
2. SUPER Cell, a future network architecture that aims to enhance capacity 100x and reduce costs 10x through techniques like massive MIMO, small cells, and new frequency bands.
3. The importance of R&D collaboration for developing leadership in 5G technologies and convergence networks.
This document presents a presentation on a smart home energy management system using IEEE 802.15.4 and ZigBee. It outlines the related work on ZigBee and smart home networks. It then describes the proposed smart home design including a system design using a smart node, disjoint multi-path routing protocol, and device binding system. It also discusses developing the control system including binding management and a sensor network analyzer. The presentation concludes by discussing how this work contributes to more intelligent and automatic home networks and potential energy savings.
This document outlines the key elements of a smart home system, including objectives, components, devices, networking protocols, and integration with the smart grid. The objectives are to provide convenience, comfort, energy efficiency and security. System elements include sensors, controllers, actuators, and buses. Example devices are PLCs, wireless technologies like Z-Wave, and IP cameras. Networking uses various protocols like X-10, ZigBee, and wireless. Integration with the smart grid enables demand response and sharing energy usage data to promote conservation. Social awareness features also help users compare energy usage.
The document discusses the environmental costs of cloud computing in terms of power usage and impacts. It notes that while data center electricity usage is growing rapidly as cloud services increase, the efficiency of information technology is also improving quickly. The cloud offers advantages over in-house IT in load diversity and economies of scale that help reduce power usage and costs. Overall, the indirect environmental and productivity benefits of IT may be more significant than direct electricity consumption.
The document discusses smart grid technology. It begins with an introduction and then covers related work, components of a smart grid like connectivity networks and access networks, how smart grids work using two-way communication, features, comparisons to traditional grids, advantages like reduced losses and carbon footprint, and disadvantages like intermittent renewable sources. It concludes that smart grids will modernize energy supply and create smart homes and cities. The future scope is improved infrastructure and widespread adoption like the Internet. References are provided.
The document discusses smart grid technology. It begins with an introduction and then covers related work, components of a smart grid, how it works, features, advantages and disadvantages. A smart grid integrates information and communication technologies with the traditional power grid. It allows two-way communication between utilities and customers. Key components include connectivity networks, smart meters, and sensors. A smart grid provides benefits like reduced losses, automated control, reliability and reduced carbon emissions. However, challenges include the need to augment existing infrastructure and ensuring communication is not interrupted. Overall, smart grids are expected to become more widely used in the future.
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1. Smart Devices Collaboration for
Energy Saving in Home Networks
Han YAN Ph.D defense
19 December, 2014
Orange Labs, France
IRISA, France
Pr. Ye-Qiong SONG
Pr. Mohamed Yacine GHAMRI DOUDANE
Dr. Stéphane LOHIER
Pr. Bernard COUSIN
Dr. Cédric GUEGUEN
Dr. Jean-Paul VUICHARD
Jury
2. 2
08/01/2015
Why Green Home ?
Economic Reason [2] [3]:
• In 2012, electricity price increases 2% faster than inflation
• In 2014, the total annual cost of electricity is estimated at 1,775€. In 2020, it is
expected to reach 2,486 €
[1] IPCC. Climate change 2013: The physical science basis, 2013
[2] Christophe Dromacque and Anna Bogacka. European residential energy price report, 2013
[3] Vers electricite plus chere, ecosocioconso, 2014
Environmental Reason [1]:
• Information and Communication technology sector represents 2% CO2emssion
3. 3
08/01/2015
Global energy consumption is increasing with a rhythm at 3% every year
Residential energy consumption has multiplied 5 times [4]
Twh
Energy Consumption Evolution in France
[4] Le bilan énergétique de la France pour 2010. Technical report, SOeS, 2010
5. 5
08/01/2015
Energy Saving Challenges in the Home Network
NAS
Laptop
HGW
STB
Pad
controller
PLC
plug
WAN
PLC plug
WiFi Ethernet
ADSL PLC
Devices should be used efficiently:
• In collaborative services
• Energy consumption efficiency
Turned on / off efficiently
User is important in the home network
• Increasing satisfaction
• Behavior learning
User
satisfaction
Energy
efficiency
WAN
6. 6
08/01/2015
Device level
• Advanced configuration and power interface specification
• Dynamic power management
• Ethernet, memory etc.
Network level
• Low power network technologies
• Home automation energy control
• Network connection power control
• Power control elements
State of the Art in Power Management
7. 7
08/01/2015
Device level
• Advanced configuration and power interface specification [6]
• Dynamic power management
• Ethernet, memory etc.
Network level
• Low power network technologies
• Home automation energy control
• Network connection power control
• Power control elements
State of the Art in Power Management
[6] ACPI Advanced configuration and power interface specification
9. 9
08/01/2015
Device level
• Advanced configuration and power interface specification
• Dynamic power management [7]-[9]
• Ethernet, memory etc.
Network level
• Low power network technologies
• Home automation energy control
• Network connection power control
• Power control elements
State of the Art in Power Management
[7] Trevor Pering, Tom Burd, and Robert Brodersen, The simulation and evaluation of dynamic voltage scaling algorithms,1998 international
symposium on Low power electronics and design, pages 76--81. ACM, 1998
[8] Padmanabhan Pillai and Kang G Shin. Real-time dynamic voltage scaling for low-power embedded operating systems. In ACM SIGOPS
Operating Systems Review, 35, pages 89–102. ACM, 2001
[9] Dirk Grunwald, Charles B Morrey III, Philip Levis, Michael Neufeld, and Keith I Farkas. Policies for dynamic clock scheduling. In
Proceedings of the 4th conference on Symposium on Operating System Design & Implementation-Volume 4, pages 6–6. USENIX
Association, 2000
10. 10
08/01/2015
Dynamic Power Management
𝑃 ∝ 𝐶𝑉2 𝑓 [10]
Capacitance
Voltage Frequency
Dissipated power
The voltage or the frequency or both parameters could reduce the power
consumption of the system:
• Dynamic voltage scaling power management [7] [8]
• Dynamic frequency scaling power management [9]
[7] Trevor Pering, Tom Burd, and Robert Brodersen, The simulation and evaluation of dynamic voltage scaling algorithms,1998 international
symposium on Low power electronics and design, pages 76--81. ACM, 1998
[8] Padmanabhan Pillai and Kang G Shin. Real-time dynamic voltage scaling for low-power embedded operating systems. In ACM SIGOPS
Operating Systems Review, 35, pages 89–102. ACM, 2001
[9] Dirk Grunwald, Charles B Morrey III, Philip Levis, Michael Neufeld, and Keith I Farkas. Policies for dynamic clock scheduling. In
Proceedings of the 4th conference on Symposium on Operating System Design & Implementation-Volume 4, pages 6–6. USENIX
Association, 2000
[10] Neil Weste and David Harris. Cmos vlsi design. A Circuits and Systems perspective, Pearson Addison Wesley, 2005
11. 11
08/01/2015
Device level
• Advanced configuration and power interface specification
• Dynamic power management
• Ethernet, memory etc. [11]-[13]
Network level
• Low power network technologies
• Home automation energy control
• Network connection power control
• Power control elements
State of the Art in Power Management
[11] Chamara Gunaratne and Ken Christensen. Ethernet adaptive link rate: System design and performance evaluation. In Local
Computer Networks, Proceedings 2006 31st IEEE Conference on, pages 28–35. IEEE, 2006
[12] Maruti Gupta and Suresh Singh. Dynamic ethernet link shutdown for energy conservation on ethernet links. In Communications
ICC’07. IEEE International Conference on, pages 6156–6161. IEEE, 2007
[13] Kiran Puttaswamy, Kyu-Won Choi, Jun Cheol Park, Vincent J Mooney III, Abhijit Chatterjee, and Peeter Ellervee. System level power-
performance trade-offs in embedded systems using voltage and frequency scaling of off-chip buses and memory. In Proceedings of the
15th international symposium on System Synthesis, pages 225–230. ACM, 2002.
12. 12
08/01/2015
Device level
• Advanced configuration and power interface specification
• Dynamic power management
• Ethernet, memory etc.
Network level
• Low power network technologies [14]-[16]
• Home automation energy control
• Network connection power control
• Power control elements
State of the Art in Power Management
[14] Carles Gomez, Joaquim Oller, and Josep Paradells. Overview and evaluation of bluetooth low energy: An emerging low-power
wireless technology. Sensors, 12[9]:11734–11753, 2012
[15] ZigBee Alliance. Zigbee specifications, 2008
[16] Zach Shelby and Carsten Bormann. 6LoWPAN: The wireless embedded Internet, 43. John Wiley & Sons, 2011.
13. 13
08/01/2015
Low Power Technologies
Technologies ZigBee/
6LoWPAN
(over 802.15.4)
Bluetooth Low
Energy
WiFi
IEEE spec 802.15.4 802.15.1 802.11 a/b/g
Frequency
Band
868/915 MHz;
2.4 GHz
2.4 GHz 2.4 GHz;
5 GHz
Nominal
Range
10-100 m 10 m 100 m
Chipset cc2531 cc2540 cx53111
RX 25 mA 19.6 mA 219 mA
TX 34 mA 31.6 mA 215 mA
14. 14
08/01/2015
Device level
• Advanced configuration and power interface specification
• Dynamic power management
• Ethernet, memory etc.
Network level
• Low Power network technologies
• Home automation energy control[17][18]
• Network connection power control
• Power control elements
State of the Art in Power Management
[17] Han and Jae-Hyun Lim. Design and implementation of smart home energy management systems based on zigbee. Consumer
Electronics, IEEE Transactions on, 56[3]:1417-1425, 2010
[18] Il-Kyu Hwang, Dae-sung Lee, and Jin-wook Baek. Home network conguring scheme for all electric appliances using zigbee-based
integrated remote controller. Consumer Electronics, IEEE Transactions on,55[3]:1300{1307, 2009
15. 15
08/01/2015
Device level
• Advanced configuration and power interface specification
• Dynamic power management
• Ethernet, memory etc.
Network level
• Low Power network technologies
• Home automation energy control
• Network connection power control [19][20]
• Power control elements
State of the Art in Power Management
[19] Olivier Bouchet, Abdesselem Kortebi, and Mathieu Boucher. Inter-mac green path selection for heterogeneous networks. In
Globecom Workshops (GC Wkshps), 2012 IEEE, pages 487-491. IEEE, 2012
[20] Vincenzo Suraci, Alessio Cimmino, Roberto Colella, Guido Oddi, and Marco Castrucci. Convergence in home gigabit networks:
implementation of the inter-mac layer as a pluggable kernel module. In Personal Indoor and Mobile Radio Communications (PIMRC),
2010 IEEE 21st International Symposium on, pages 2569{2574. IEEE, 2010
16. 16
08/01/2015
Device level
• Advanced configuration and power interface specification
• Dynamic power management
• Ethernet, memory etc.
Network level
• Low Power network technologies
• Home automation energy control
• Network connection power control
• Power control elements [21]
State of the Art in Power Management
[21] Youn-Kwae Jeong, Intark Han, and Kwang-Roh Park. A network level power management for home network devices. Consumer
Electronics, IEEE Transactions on, 54[2]:487-493, 2008
17. 17
08/01/2015
NAS
HGW
STB
PLC
plug
PLC plug
WiFi Ethernet ADSL PLC
Audio Video Use Case
Laptop
Devices work no more alone in home network
Devices are not used efficiently
Film selection
Video Push
Film selection Video Push
Local network connection
time
18. 18
08/01/2015
Contributions of the Thesis
• ZigBee mandatory energy saving solution
• ZigBee optional energy saving solution
An overlay network for energy control
• Architecture of HOPE system
• Three use cases
HOme Power Efficiency (HOPE) system
• Collaborative services analysis and definitions
• Refined overlay and auto learning power management
• Power delay tradeoffs
Collaborative power control management
19. 19
08/01/2015
Contributions of the Thesis
• ZigBee mandatory energy saving solution
• ZigBee optional energy saving solution
An overlay network for energy control
• Architecture of HOPE system
• Three use cases
HOme Power Efficiency (HOPE) system
• Collaborative services analysis and definitions
• Refined overlay and auto learning power management
• Power delay tradeoffs
Collaborative power control management
20. 20
08/01/2015
Power Consumption of Home Network Devices
Power consumption (Watt) of the home network devices
in different power states [22]:
States
Device
Working Idling Sleeping Soft-off
HGW 12.6 11 3.9 2
STB 21 19.2 13.5 2.5
Workstation 205 123.5 4.9 3.2
Laptop 79 54 5 2.5
PLC plug 6 3 2.6 0.15
A great power consumption difference from state to state
How to go to the low power consumption states?
[22] Yan, H, Vuichard, J, Cousin, B, Gueguen, C, and Mardon, G "Green Home Network based on an Overlay Energy Control Network"
in the book "Green Networking and Communications" , CRC Press, USA, oct 2013
21. 21
08/01/2015
Working
Sleeping
Idling
Soft off
21 watt
19.2 watt
13.5 watt2.5 watt
An Example of STB Power States
Service execution time
Less than 4 hours
After 4 hours idling time
User controls manually
to turn on/off
Noservice
Userservice
request
• Long waiting time from idling to sleeping
• Explicit user commands are required to go to soft off state
• User controls manually to
go to sleeping state
• User service request to
turn on
22. 22
08/01/2015
Overlay Energy Control Network
Proposition:
Controlling the devices by a ultra-low power consumption overlay network
The Overlay Energy Control Network (OECN) is formed by:
• Control nodes associated to each device
• OECN manager
Overlay Energy Control Network (OECN) can switche devices:
• From working or idling to sleeping power state much more quickly
• From working to soft off power state automatically
23. 23
08/01/2015
Contributions of the Thesis
• ZigBee mandatory energy saving solution
• ZigBee optional energy saving solution
An overlay network for energy control
• Architecture of HOPE system
• Three use cases
HOme Power Efficiency (HOPE) system
• Collaborative services analysis and definitions
• Refined overlay and auto learning power management
• Power delay tradeoffs
Collaborative power control management
24. 24
08/01/2015
ZigBee Mandatory energy saving Solution (ZMS)
The advantages of ZMS:
• A device can be turned off and can also be started up by the associated ZigBee
module which is always on
• This device can go to a real low power consumption state (soft off state)
• All the energy control nodes are ZigBee
• Energy control messages are sent via ZigBee network
workstation
HGWSTB WANPLC plug
WiFi Ethernet ADSL PLC
Laptop
PLC plug
ZigBee
25. 25
08/01/2015
Working
Sleeping
Idling
Soft off
Service execution time
Device stays in soft off state
while there is no service
• ZMS turns on device for
service execution
• ZMS turns off device while
there is no service
Device Power States Control Model by ZMS
26. 26
08/01/2015
Contributions of the Thesis
• ZigBee mandatory energy saving solution
• ZigBee optional energy saving solution
An overlay network for energy control
• Architecture of HOPE system
• Three use cases
HOme Power Efficiency (HOPE) system
• Collaborative services analysis and definitions
• Refined overlay and auto learning power management
• Power delay tradeoffs
Collaborative power control management
27. 27
08/01/2015
• Device itself can become the energy control node
• Energy control messages could be sent via the data home network
workstation
HGWSTB WAN
WiFi Ethernet ADSL PLC
Laptop
ZigBee Optional energy saving Solution (ZOS)
The advantages of ZOS:
• It might not be possible to connect a ZigBee module on device
• ZigBee transmission diameter is limited, we have another alternative solution
ZigBee
PLC
plug
PLC
plug
28. 28
08/01/2015
Working
Sleeping
Idling
Soft off
Service execution time
• ZOS switches device to working state
for service execution
• ZOS switches device to sleeping state
while there is no service
Device stays in sleeping state
while there is no service
Device Power States Control Model by ZOS
29. 29
08/01/2015
33.5 21.3 22.4
735.3
527.1 575.2
244.8
188.3
197.6
475.5
425.2
441.2
0
200
400
600
800
1000
1200
1400
1600
Self-controlled ZMS ZOS
Annual Power ConsumptionKwh
13.9 160 16
12.3
436
44
11.6
457
46.2
7.4
86
8
0
200
400
600
800
1000
1200
Self-controlled ZMS ZOS
Daily DelaySecond
Energy Consumption and Delay Results
in 4 Types of Days
ZMS is more energy efficient; but ZMS has a relatively high delay
ZOS is a good tradeoff between the energy gain and delay
ZMS ZOS
21.97% 16.96%
Energy gain of two solutions
30. 30
08/01/2015
Expense results
• ZMS and ZOS are profitable after 1.2 year
• ZMS is more profitable than ZOS after 1.6 year
Total expense is a sum of total ZigBee modules expense and
total electricity expense
31. 31
08/01/2015
Contributions of the Thesis
• ZigBee mandatory energy saving solution
• ZigBee optional energy saving solution
An overlay network for energy control
• Architecture of HOPE system
• Three use cases
HOme Power Efficiency (HOPE) system
• Collaborative services analysis and definitions
• Refined overlay and auto learning power management
• Power delay tradeoffs
Collaborative power control management
33. 33
08/01/2015
UPnP Low Power
UPnP Low Power is proposed to implement different power saving modes to save
energy for devices
There are three types of elements:
• UPnP Low Power device
• UPnP Low Power power management proxy
• UPnP Low Power aware control point
Announcement:
• Power states
• Methods of waking
• Entry & exit information
UPnP Low Power device
UPnP Low Power proxy
UPnP Low Power
aware control point
Discovery the UPnP Low
Power devices with their
waking methods
• Monitor
• Send a “wake up”
or “go to sleep”
36. 36
08/01/2015
Contributions of the Thesis
• ZigBee mandatory energy saving solution
• ZigBee optional energy saving solution
An overlay network for energy control
• Architecture of HOPE system
• Three use cases
HOme Power Efficiency (HOPE) system
• Collaborative services analysis and definitions
• Refined overlay and auto learning power management
• Power delay tradeoffs
Collaborative power control management
37. 37
08/01/2015
Contributions of the Thesis
• ZigBee mandatory energy saving solution
• ZigBee optional energy saving solution
An overlay network for energy control
• Architecture of HOPE system
• Three use cases
HOme Power Efficiency (HOPE) system
• Collaborative services analysis and definitions
• Refined overlay and auto learning power management
• Power delay tradeoffs
Collaborative power control management
38. 38
08/01/2015
NAS
LaptopSTB
HGW
Pad controller
WiFi activation of
the HGW through
ZigBee
PLC plugs
Three Use Cases for HOPE system
Energy Gain :
2.9 Watt
NAS is woke up
through ZigBee and
Wake-On-Lan
NAS is switched off
through ZigBee and
UPnP Low Power
+ 23.4 Watt
Wake up
PLC plugs
through ZigBee
PLC plugs are
switched off
through ZigBee
+ 12 Watt
39. 39
08/01/2015
Contributions of the Thesis
• ZigBee mandatory energy saving solution
• ZigBee optional energy saving solution
An overlay network for energy control
• Architecture of HOPE system
• Three use cases
HOme Power Efficiency (HOPE) system
• Collaborative services analysis and definitions
• Refined overlay and auto learning power management
• Power delay tradeoffs
Collaborative power control management
41. 41
08/01/2015
Audio Video Use Case
NAS
HGW
STB
PLC
plug
PLC plug
Laptop
Film selection
Video Push
Film selection Video Push
Local network connection
Film selection Content directory function block
Content directory function block
Transfer server, content directory function blocks
Video stream decoder; display interface;
authentication; transfer client function blocks
Connection function block
Video Push
Local network connection
time
44. 44
08/01/2015
Contributions of the Thesis
• ZigBee mandatory energy saving solution
• ZigBee optional energy saving solution
An overlay network for energy control
• Architecture of HOPE system
• Three use cases
HOme Power Efficiency (HOPE) system
• Collaborative services analysis and definitions
• Refined overlay and auto learning power management
• Power delay tradeoffs
Collaborative power control management
45. 45
08/01/2015
Refined overlay algorithms
Two propositions based on the refined overlay algorithms:
• Refined Overlay Power Management (ROPM):
We assume that ROPM registered user habits of using collaborative
services
• Refined Overlay Auto Learning (ROAL):
ROAL learns the habits how user uses their collaborative services
The control decisions depend on:
• ROPM Pre-saved user habit information
• ROAL Learns user habit when they request services
time
time
𝑡_𝑟𝑒𝑞𝑢𝑒𝑠𝑡
𝑡_𝑎𝑣𝑎𝑖𝑙𝑎𝑏𝑙𝑒
𝑡_𝑎𝑣𝑎𝑖𝑙𝑎𝑏𝑙𝑒
Operating
Idling
Starting
46. 46
08/01/2015
Video Push
Power Control Elements
Reference model:
• Devices are configured as power control elements
• All necessary power control elements are on at the beginning
of the service
NAS
HGW
STB
PLC
plug
PLC plug
Laptop
Film selection
Video Push
Film selection
Local network connection
time
47. 47
08/01/2015
Simulation Results on the
Auto Learning Period
Simulation time varies from 10 hours to 500 hours
ROAL needs about 200 hours to learn an accurate value of the request time
Simulation time (h)
Requesttime(s)
48. 48
08/01/2015
Simulation Result on the Energy Gain
In a collaborative service, if several functional blocks are
needed lately, we gain more energy in these use cases
ROPM ROAL
41.85% 35.25%
Energy gain of two solutions
49. 49
08/01/2015
Simulation Result on the Delay
• ROPM and ROAL have greater delay than the PCE, but
much more efficient in the term of energy saving
• ROAL has less delay than ROPM
How to be more accurate in the user habits learning?
50. 50
08/01/2015
Contributions of the Thesis
• ZigBee mandatory energy saving solution
• ZigBee optional energy saving solution
An overlay network for energy control
• Architecture of HOPE system
• Three use cases
HOme Power Efficiency (HOPE) system
• Collaborative services analysis and definitions
• Refined overlay and auto learning power management
• Power delay tradeoffs
Collaborative power control management
51. 51
08/01/2015
𝑡_𝑟𝑒𝑞𝑢𝑒𝑠𝑡_𝑙𝑒𝑎𝑟𝑛𝑒𝑑i,j =
𝑘=1
𝑁𝑏_𝑠𝑒𝑟
𝑡_𝑟𝑒𝑞𝑢𝑒𝑠𝑡𝑖,𝑗
𝑘
𝑁𝑏_𝑠𝑒𝑟
𝑡_𝑡𝑟𝑎𝑑𝑒𝑜𝑓𝑓 = 𝑡_𝑟𝑒𝑞𝑢𝑒𝑠𝑡_𝑙𝑒𝑎𝑟𝑛𝑒𝑑_𝑣𝑎𝑟𝑖𝑎𝑛𝑐𝑒i,j × 𝛼
𝑡_𝑑𝑒𝑐_𝑜𝑛𝑖,𝑗
𝑘
= 𝑡_𝑟𝑒𝑞𝑢𝑒𝑠𝑡_𝑙𝑒𝑎𝑟𝑛𝑒𝑑i,j − 𝑡_𝑡𝑟𝑎𝑑𝑒𝑜𝑓𝑓
Collaborative Overlay Power management
Power-Delay Tradeoff Algorithm
The t_tradeoff will be configured by the user satisfaction requirement α
and the variance of the request (𝑡_𝑟𝑒𝑞𝑢𝑒𝑠𝑡_𝑙𝑒𝑎𝑟𝑛𝑒𝑑_𝑣𝑎𝑟𝑖𝑎𝑛𝑐𝑒) as shown
in formula
Our proposition Collaborative Overlay Power management Power-Delay
Tradeoff (COPM-PDT α) algorithm varies by tradeoff coefficient α.
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Energy Delay Results
COPM-PDT 99 COPM-PDT 75 COPM-PDT 50
Energy gain 23.62% 31.29% 34.15%
Increased
delay
0.5% 20.06% 43.75%
404
78.9 79.3 98.7 140.3
0
100
200
300
400
500
Delay (s)
135.8
97.8
74.7 67.2 64.4
0
50
100
150
Energy (Watt-hour)
Energy gain and delay for different parameters of α
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Energy Delay Results
by tuning the tradeoff coefficient
Tradeoff Coefficient Tradeoff Coefficient
Delayperservice(s)
Energyconsumptionperservice(watthour)
Energy consumption
• Control algorithms based on the learned information
• Good energy efficiency and low waiting delay obtained
Delay
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Conclusion:
Responses for Energy Saving in Home Network
We proposed an always-on low power network over the traditional network
• ZMS is energy efficient, high delay
• ZOS is a good tradeoff between the energy gain and the delay
A testbed of home power efficiency system is implemented
• Devices are turned on by service requests
• Energy efficiency with a high ease of use
Collaborative power management
• Collaborative service analysis
• User behavior learning
• Control algorithms based on the learned information
• Good energy efficiency and low waiting delay obtained
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Perspectives for Future Works
Short Term Perspectives:
• Different types of function blocks
• Resource allocation
• Collaborative analysis
• Analysis the tradeoffs between energy and other metrics
• User habits learning could be more intelligent and adaptive
Long Term Perspectives:
• A more heterogeneous overlay control network
• The collected information could be explored for other usages
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List of Publications
International papers with peer review:
• Yan, H, Cousin, B, Gueguen, C and Vuichard, J. “Refined Overlay Power Management in the Home Environment” IEEE
GREENCOM '2014, Taipei, Taiwan
• Yan, H, Gueguen, C, Cousin, B, and Vuichard, J. "Collaborative Overlay Power Management based on the Delay-Power
Tradeoffs" IEEE FGCT '2014, London (Best paper award)
• Yan, H, Fontaine, F, Bouchet, O, Vuichard, J, Javaudin, Lebouc, M, Hamon, M, Cousin, B, and Gueguen, C. "HOPE: HOme
Power Efficiency System for a Green Network" IEEE INFOCOM'2013 Demo/Poster Session, Turin, Italy
Book Chapter:
• Yan, H, Vuichard, J, Cousin, B, Gueguen, C, and Mardon, G "Green Home Network based on an Overlay Energy Control
Network" in the book "Green Networking and Communications" (Published by CRC Press, USA, oct 2013)
Poster:
• Yan, H, "Smart devices collaboration for a greener home network" Presented at "Journée des doctorants" Orange Labs,
France , Sep 2014
French patents:
• Yan, H, Mardon, G, and Gueguen, C (Dec 2012). "Economiser l’énergie du réseau domestique tout en maintenant la QoE de
l’utilisateur" Patent 1261565
• Yan, H, Fontaine, F, and Vuichard, J (Avr 2013) "Procédé de contrôle de la consommation énergétique d’équipements d’un
réseau de communication local" Patent 1352881
• Yan, H, Fontaine, F, (Oct 2013) "Gestion améliorée des connexions réseau", Patent 1359446
• Fontaine, F, Yan, H, (Dec 2013) "Technique de communication dans un réseau local", Patent 1362832
• Fontaine, F, Yan, H, (Feb 2014) "Mécanisme de lissage de la consommation électrique des équipements UPnP", Patent
1452655
• Yan, H, Fontaine, F, (Feb 2014) "An adaptive proxy for compliance of the equipments to IEEE 1905" Patent 1454940
• Yan, H, Fontaine, F, (Sep 2014) "A repetition proxy for long distance communication between Bluetooth devices" Patent
1459280
• Fontaine, F, Yan, H,(Sep 2014) "Detection mechanism of Bluetooth Low Energy devices (BLE) on the IP network using UPnP"
Patent 1459283
Editor's Notes
Low power technologies comparaisons
Day type 1 (Working day): Parents go to work and children go to school.
Day type 2 (Wednesday ): On this day type, the children stay at home and parents are at work.
The set-top box has a relatively high utilization ratio during the daytime.
Day type 3 (Weekend): All family members are at home.
The laptop, PC and set-top box are needed at different times over the weekend.
Day type 4 (Holiday day): The whole family is on holiday.
PC which is equipped with a home security camera, is on.
Other devices are off.