- Supporting real-time communication in mobile networks
- Novel transmission scheduling techniques that handle the routing uncertainty introduced by mobility
- Used for mission-critical applications such as medical monitoring and factory automation
The document discusses how to characterize and dimension user traffic in 4G networks. It describes how to define data traffic in terms of data speed and data tonnage. Data speed is the rate at which data is transferred, while data tonnage refers to the total amount of data exchanged. The document provides examples of data speed metrics used in 3GPP standards and outlines factors to consider when calculating expected data usage per subscriber based on typical mobile application usage patterns and available data plans. Dimensioning user traffic accurately is important for designing 4G networks to meet capacity demands.
4G cellular systems aim to provide broadband wireless access with peak data rates over 20 Mbps. Key challenges for 4G include limited coverage due to higher frequencies, capacity constraints of current air interfaces, and availability of suitable spectrum below 5 GHz for wide-area coverage. 4G concepts involve small cell sizes, adaptive antennas, asymmetric data rates, and advanced air interfaces to improve coverage and capacity over 3G systems.
This document provides an overview of wireless networking technologies. It discusses the history and evolution of wireless networks from 1G to 4G. It describes different types of wireless networks including wireless local area networks (using Wi-Fi), personal area networks (using Bluetooth and infrared), wireless wide area networks, and metropolitan area networks (using WiMAX and LTE). The document also covers wireless security concerns and encryption methods.
Het nets up close - Webinar with ThinkSmallCell and IXIADavid Chambers
Slides from joint webinar by ThinkSmallCell and IXIA outlining the progress towards HetNets using Small Cells and the solution testing scenarios and capabilities required
A proposal to enhance cellular and wifiIJCNCJournal
WiFi offloading is becoming one of the key enablers to help the network operators dealing with the exponentially growing demand of mobile data. The idea of using WiFi to offload data traffic from cellular network has proposed for many years. However, the interoperability issue between the two networks needs to be enhanced so that WiFi can efficiently supplement for the cellular network in case of congestion or outage. In this paper, we propose a novel network roaming and selection scheme based on 3GPP TS 24.312 and IEEE 802.11k, u standards to enhance cellular and WiFi interworking. The proposed scheme is aimed at enhancing the network roaming and selection so that WiFi network can serve as a supplement and backup access network for the cellular not only for congestion control but also in case of unexpected network failure event. We also model and evaluate the proposed scheme in a typical HetNet with interworking WiFi access points and cellular base stations. The simulation result shows that our proposed scheme quickly detects unexpected network failure event and assists active UEs to perform handoff to preferable alternative point of access. As a result, service disruption is substantially reduced and quality of experience (downlink/uplink’s throughput) is improved. Therefore, our proposed scheme can be used for a more reliable HetNet in terms of congestion control and disruption tolerance.
Edge device multi-unicasting for video streamingTal Lavian Ph.D.
After a decade of research and development, IP multicast has still not been deployed widely in the global Internet due to many open technical issues: lack of admission control, poorly scaled with large number of groups, and requiring substantial infrastructure modifications. To provide the benefits of IP multicast without requiring direct router support or the presence of a physical broadcast medium, various Application Level Multicast (ALM) models have been attempted. However, there are still several problems with ALM: unnecessary coupling between an application and its multicasting supports, bottleneck problem at network access links and considerable processing power required at the end nodes to support ALM mechanisms. This paper proposes an architecture to address these problems by delegating application-multicasting support mechanisms to smart edge devices associated with the application end nodes. The architecture gives rise to an interesting Edge Device Any-casting technology that lies between the IP-multicasting and the Application Layer Multicasting and enjoys the benefits of both. Furthermore, the architecture may provide sufficient cost-benefit for adoption by service providers. The paper presents initial results obtained from the implementation of a video streaming application over the testbed that implements the proposed architecture.
VoIP allows users to make voice calls using an Internet connection instead of a regular phone line. It works by converting voice into digital data packets that are transmitted over the IP network and then reconstructed at the receiving end. The key benefits of VoIP include lower costs compared to traditional phone service, open standards that ensure interoperability between vendors, and the ability to integrate voice and data onto a single network. Common VoIP protocols are H.323, SIP, and MGCP. VoIP sees broad use for internet calling and is widely used to provide phone services at a lower cost than traditional telephone networks.
What is internet architecture? - (Darren's Study Guide: CompTIA A+, 220-1001 ...BDDazza
The document discusses the architecture of the Internet. It describes the Internet as a collection of thousands of independent networks that interconnect using the TCP/IP protocol. This allows any network to communicate with any other network. The architecture is hierarchical, with small local networks connecting to medium regional networks and then large national backbones. This hierarchy and the use of common protocols allows the Internet to function as a single global network. The original architecture was designed to promote innovation but is changing in ways that may reduce innovation.
The document discusses how to characterize and dimension user traffic in 4G networks. It describes how to define data traffic in terms of data speed and data tonnage. Data speed is the rate at which data is transferred, while data tonnage refers to the total amount of data exchanged. The document provides examples of data speed metrics used in 3GPP standards and outlines factors to consider when calculating expected data usage per subscriber based on typical mobile application usage patterns and available data plans. Dimensioning user traffic accurately is important for designing 4G networks to meet capacity demands.
4G cellular systems aim to provide broadband wireless access with peak data rates over 20 Mbps. Key challenges for 4G include limited coverage due to higher frequencies, capacity constraints of current air interfaces, and availability of suitable spectrum below 5 GHz for wide-area coverage. 4G concepts involve small cell sizes, adaptive antennas, asymmetric data rates, and advanced air interfaces to improve coverage and capacity over 3G systems.
This document provides an overview of wireless networking technologies. It discusses the history and evolution of wireless networks from 1G to 4G. It describes different types of wireless networks including wireless local area networks (using Wi-Fi), personal area networks (using Bluetooth and infrared), wireless wide area networks, and metropolitan area networks (using WiMAX and LTE). The document also covers wireless security concerns and encryption methods.
Het nets up close - Webinar with ThinkSmallCell and IXIADavid Chambers
Slides from joint webinar by ThinkSmallCell and IXIA outlining the progress towards HetNets using Small Cells and the solution testing scenarios and capabilities required
A proposal to enhance cellular and wifiIJCNCJournal
WiFi offloading is becoming one of the key enablers to help the network operators dealing with the exponentially growing demand of mobile data. The idea of using WiFi to offload data traffic from cellular network has proposed for many years. However, the interoperability issue between the two networks needs to be enhanced so that WiFi can efficiently supplement for the cellular network in case of congestion or outage. In this paper, we propose a novel network roaming and selection scheme based on 3GPP TS 24.312 and IEEE 802.11k, u standards to enhance cellular and WiFi interworking. The proposed scheme is aimed at enhancing the network roaming and selection so that WiFi network can serve as a supplement and backup access network for the cellular not only for congestion control but also in case of unexpected network failure event. We also model and evaluate the proposed scheme in a typical HetNet with interworking WiFi access points and cellular base stations. The simulation result shows that our proposed scheme quickly detects unexpected network failure event and assists active UEs to perform handoff to preferable alternative point of access. As a result, service disruption is substantially reduced and quality of experience (downlink/uplink’s throughput) is improved. Therefore, our proposed scheme can be used for a more reliable HetNet in terms of congestion control and disruption tolerance.
Edge device multi-unicasting for video streamingTal Lavian Ph.D.
After a decade of research and development, IP multicast has still not been deployed widely in the global Internet due to many open technical issues: lack of admission control, poorly scaled with large number of groups, and requiring substantial infrastructure modifications. To provide the benefits of IP multicast without requiring direct router support or the presence of a physical broadcast medium, various Application Level Multicast (ALM) models have been attempted. However, there are still several problems with ALM: unnecessary coupling between an application and its multicasting supports, bottleneck problem at network access links and considerable processing power required at the end nodes to support ALM mechanisms. This paper proposes an architecture to address these problems by delegating application-multicasting support mechanisms to smart edge devices associated with the application end nodes. The architecture gives rise to an interesting Edge Device Any-casting technology that lies between the IP-multicasting and the Application Layer Multicasting and enjoys the benefits of both. Furthermore, the architecture may provide sufficient cost-benefit for adoption by service providers. The paper presents initial results obtained from the implementation of a video streaming application over the testbed that implements the proposed architecture.
VoIP allows users to make voice calls using an Internet connection instead of a regular phone line. It works by converting voice into digital data packets that are transmitted over the IP network and then reconstructed at the receiving end. The key benefits of VoIP include lower costs compared to traditional phone service, open standards that ensure interoperability between vendors, and the ability to integrate voice and data onto a single network. Common VoIP protocols are H.323, SIP, and MGCP. VoIP sees broad use for internet calling and is widely used to provide phone services at a lower cost than traditional telephone networks.
What is internet architecture? - (Darren's Study Guide: CompTIA A+, 220-1001 ...BDDazza
The document discusses the architecture of the Internet. It describes the Internet as a collection of thousands of independent networks that interconnect using the TCP/IP protocol. This allows any network to communicate with any other network. The architecture is hierarchical, with small local networks connecting to medium regional networks and then large national backbones. This hierarchy and the use of common protocols allows the Internet to function as a single global network. The original architecture was designed to promote innovation but is changing in ways that may reduce innovation.
Enabling active flow manipulation in silicon-based network forwarding enginesTal Lavian Ph.D.
A significant challenge arising from today’s increasing Internet traffic is the ability to flexibly incorporate intelligent control in high performance commercial network devices. This paper tackles this challenge by introducing the Active Flow Manipulation (AFM) mechanism to enhance traffic control intelligence of network devices through programmability. With AFM, customer network services can exercise active network
control by identifying distinctive flows and applying specified actions to alter network behavior in real-time. These services are dynamically loaded through Openet by the CPU-based control unit of a network node and are closely coupled with its silicon-based forwarding engines, without negatively impacting forwarding performance. AFM is exposed as a key enabling technology of the programmable networking platform Openet. The effectiveness of our approach is demonstrated by four active network services on commercial network nodes.
Studying performance barriers to cloud services in Africa's public sectorAFRINIC
Cloud computing allows individuals and organisations to remotely lease storage and computation resources as needed. For such
remote access to computational resources to work efciently, there is need for well-developed Internet infrastructure to support reliable and low-delay delivery of trac. By carrying out the month-long Internet measurement campaign, this paper investigates the hosting situation and latencies in the public sector of ve African countries. Results of the study show that a large percentage of the public sector websites across the countries are hosted in cloud-based infrastructure and are physically located in America and Europe. Analysis of delays shows signicant diferences between local and remotely hosted websites, and that latencies are signficantly lower for countries that host CDN nodes. The results also suggest higher delays for local websites that are accessed circuitously.
Wireless – It’s complicated! By Albert KangasAnn Treacy
Wireless is complicated involving various technologies, geographic and topographic implications, legal considerations, pricing models, all wrapped in marketing jargon that is sure to confuse.
Join us for an informative webinar, aimed to give participants a more solid understanding about which wireless technologies will provide the broadband Internet your community wants and needs.
Learn:
The various parts of the radio spectrum are allocated and used.
How your community’s topography and tree cover impacts wireless performance.
About licensed and unlicensed frequencies and why that matters.
About how fiber makes wireless better
What is “Last Mile Access”
It is the final leg of delivering connectivity from a communications provider to a customer. Usually referred to by the telecommunications and cable television industries. It is typically scene as an expensive challenge because “fanning out” wires and cables is a considerable physical undertaking.” (from Wikipedia)
Last Mile Access Technologies discusses various methods for connecting homes and businesses to internet service providers. It covers traditional copper wire technologies like dial-up, ISDN, and DSL. It also discusses cable networks, wireless networks using technologies like WiFi and WiMax, and other emerging methods like powerline networking. Future technologies may rely more on fiber connectivity and wireless solutions to avoid installing new copper wiring. The document provides details on the capabilities and pros and cons of each technological approach for establishing the "last mile" of connectivity.
http://wartremovalexperts.com/
Warts are a common skin problem that affects a quarter of the world every year. Even though these little skin growths are highly contagious they aren’t considered dangerous. They can look like a rough blister or resemble the appearance of a cauliflower.
Internet of Civil Unmanned Aerial Systems: Challenges and Opportunities (by J...TUS Expo
At TUS Nordics 2017, Jie Jin gave the keynote presentation ‘Internet of Civil Unmanned Aerial Systems: Challenges and Opportunities’ on Thursday 12 October 2017.
High-Tech Drones and Immersive Displays – Exploiting New Technologies for Dig...RCAHMW
Professor Bob Stone discusses his work using new technologies like drones and immersive displays for digital heritage projects. His team has created virtual reconstructions of historic sites like Stonehenge, Scylla, and various locations in Devon like Burrator Reservoir and Wembury Bay. He cautions that immersive technologies are overhyped and have limitations, especially in outdoor environments. Stone emphasizes engaging stakeholders and designing experiences and content before implementing technology.
Drones have been around since 1898 when Nikola Tesla demonstrated a remote-controlled miniature boat. Drones can now be controlled remotely or function autonomously, and can even be operated from a phone. They have a wide range of uses from delivery to surveillance to agriculture. Drones have become popular culture as their military use decreased prices and expanded commercial applications, especially in the United States. While drones raise privacy concerns, they also have potential benefits such as monitoring wildlife, fighting fires, and assisting emergency responders.
This document provides an introduction to drones and unmanned aerial vehicles (UAVs). It discusses the history of drones dating back to 1924, differences between remote controlled toys and UAVs, components of drones like frames, motors, electronic speed controllers and batteries. Applications of drones mentioned include emergency medical assistance, photography, search and rescue, agriculture, and more. The document also contrasts helicopters with quadcopters and lists common tools used for drone building/repair.
The document proposes an Ambulance Drone system to reduce emergency response times. The drone would be triggered by 911 calls and reach patients within 1 minute on average, compared to 10 minutes for ambulances. It would carry an emergency medical kit and allow doctors to monitor the situation and guide treatment. This could significantly increase survival rates for conditions like cardiac arrest. The drone would also alert hospitals and help ambulances navigate to reach patients faster.
UAV(unmanned aerial vehicle) and its application Joy Karmakar
This document discusses unmanned aerial vehicles (UAVs), including their definition, history, components, applications, and disadvantages. UAVs are aircraft without human pilots that can be controlled autonomously or remotely. They have various applications both militarily and civilly, such as aerial surveillance, search and rescue operations, agriculture, filmmaking, and more. The key components of UAVs are the payload, air vehicle, navigation systems, and communications systems. India has developed several UAVs domestically such as Rustom, Nishant, and Lakshya for military purposes. The future of UAV technology remains dynamic with new discoveries expected over the next 16 years.
UAVs (drones) for Humanitarian EffortsBiren Gandhi
Can Drones Save Lives?
Join us for a discovery conversation on how Unmanned Aerial Vehicles (Drones) could aid humanitarians in preparing for and responding to emergencies and disasters.
Technologists, humanitarians, thought leaders and experts will be convening on the Singularity University Campus for a happy hour of networking and special presentations on UAVs in Humanitarian Response.
Learn how drones and UAVs are currently being used to strengthen disaster response capabilities and also their exciting future potential as new technologies are developed.
InSTEDD, Cisco, and Singularity University have joined together to offer this event to showcase leading experts in the field. The event is the concluding segment of a 3-day workshop hosted at SU with UAV engineers and humanitarian response professionals from around the world.
This document describes an air drone designed to carry objects through the sky. The drone has 6 wings and a powerful engine, allowing it to fly speedily and safely. It also has a hooking part under its body to carry bags and items. The drone is designed with high contrast black and white coloring on the bottom to make it easily visible and safe. Its purpose is to carry objects constantly regardless of terrain, such as during traffic jams or disasters.
An Israeli company is testing ambulance drones to transport injured soldiers from the battlefield to hospitals faster than traditional methods. If successful, these drones could save lives by getting people medical attention more quickly and decreasing the number of deaths in war. However, the drones currently being tested are not bulletproof and there are safety risks if they were to fall from the sky.
Drones have the potential to save lives by delivering urgent medical supplies. They can transport supplies like blood, which expires quickly, to rural areas and offshore vessels more rapidly than traditional methods. A pilot project in Rwanda will use drones to deliver medical supplies across the country through a network of drone ports. Drones have also delivered medicines to rural health clinics in the US and provided aid during disasters by transporting supplies and emergency equipment. They can assist in transporting medical samples between specialist labs within time limits. Drones carrying defibrillators could reach emergency patients much faster than ambulances and significantly increase survival rates.
This document discusses drones or unmanned aerial vehicles (UAVs). It provides an introduction to UAVs, including a brief history starting from 1916. It describes the key sub-systems of UAVs including the unmanned aircraft, control system, control link and support equipment. The document discusses various design parameters and applications of UAVs, including disaster relief, search and rescue, sports and armed attacks. It also discusses UAV programs in India and compares Indian and U.S. drones. Finally, it outlines some disadvantages of UAVs such as civilian casualties and hacking risks.
DEF CON 25 (2017)- Game of Drones - Brown,Latimer - 29July2017 - Slides.PDFBishop Fox
https://www.defcon.org/html/defcon-25/dc-25-speakers.html#Brown
Game of Drones - 2017
When you learned that military and law enforcement agencies had trained screaming eagles to pluck drones from the sky, did you too find yourself asking: “I wonder if I could throw these eagles off my tail, maybe by deploying delicious bacon countermeasures?” Well you’d be wise to question just how effective these emerging, first generation ‘drone defense’ solutions really are, and which amount to little more than ‘snake oil’.
There is no such thing as “best practices” when it comes to defending against ‘rogue drones’ – period. Over the past 2 years, new defensive products that detect and respond to ‘rogue drones’ have been crawling out of the woodwork. The vast majority are immature, unproven solutions that require a proper vetting.
We’ve taken a MythBusters-style approach to testing the effectiveness of a variety of drone defense solutions, pitting them against our DangerDrone. Videos demonstrating the results should be almost as fun for you to watch as they were for us to produce. Expect to witness epic aerial battles against an assortment of drone defense types, including:
• trained eagles and falcons that hunt ‘rogue drones’
• fighter drones that hunt and shoot nets
• drones with large nets that swoop in and snatch up ‘rogue drones’
• surface-to-air projectile weapons, including bazooka-like cannons that launch nets, and shotgun shells containing nets
• signal jamming and hijacking devices that attack drone command and control interfaces
• even frickin’ laser beams and Patriot missiles!
We’ll also be releasing DangerDrone v2.0, an upgraded version of our free Raspberry Pi-based pentesting quadcopter (basically a ~$500 hacker’s laptop… that can also fly). We’ll be giving away a fully functional DangerDrone v2.0 to one lucky audience member!
So come see what’s guaranteed to be the most entertaining talk this year and find out which of these dogs can hunt!
This document discusses the use of drones for disaster response and humanitarian efforts. It outlines several projects at the Civic Drone Centre including aeroSee, which uses crowdsourced photos from drones to help with search and rescue efforts, and DroneHack, which brings groups together for rapid drone prototyping. Guidelines for humanitarian drone use were developed and launched at the World Humanitarian Summit. Future areas of focus include more autonomous drones, specialist sensors, multiple coordinating drones, and delivering supplies with drones. The document advocates for further testing and development of existing projects.
Enabling active flow manipulation in silicon-based network forwarding enginesTal Lavian Ph.D.
A significant challenge arising from today’s increasing Internet traffic is the ability to flexibly incorporate intelligent control in high performance commercial network devices. This paper tackles this challenge by introducing the Active Flow Manipulation (AFM) mechanism to enhance traffic control intelligence of network devices through programmability. With AFM, customer network services can exercise active network
control by identifying distinctive flows and applying specified actions to alter network behavior in real-time. These services are dynamically loaded through Openet by the CPU-based control unit of a network node and are closely coupled with its silicon-based forwarding engines, without negatively impacting forwarding performance. AFM is exposed as a key enabling technology of the programmable networking platform Openet. The effectiveness of our approach is demonstrated by four active network services on commercial network nodes.
Studying performance barriers to cloud services in Africa's public sectorAFRINIC
Cloud computing allows individuals and organisations to remotely lease storage and computation resources as needed. For such
remote access to computational resources to work efciently, there is need for well-developed Internet infrastructure to support reliable and low-delay delivery of trac. By carrying out the month-long Internet measurement campaign, this paper investigates the hosting situation and latencies in the public sector of ve African countries. Results of the study show that a large percentage of the public sector websites across the countries are hosted in cloud-based infrastructure and are physically located in America and Europe. Analysis of delays shows signicant diferences between local and remotely hosted websites, and that latencies are signficantly lower for countries that host CDN nodes. The results also suggest higher delays for local websites that are accessed circuitously.
Wireless – It’s complicated! By Albert KangasAnn Treacy
Wireless is complicated involving various technologies, geographic and topographic implications, legal considerations, pricing models, all wrapped in marketing jargon that is sure to confuse.
Join us for an informative webinar, aimed to give participants a more solid understanding about which wireless technologies will provide the broadband Internet your community wants and needs.
Learn:
The various parts of the radio spectrum are allocated and used.
How your community’s topography and tree cover impacts wireless performance.
About licensed and unlicensed frequencies and why that matters.
About how fiber makes wireless better
What is “Last Mile Access”
It is the final leg of delivering connectivity from a communications provider to a customer. Usually referred to by the telecommunications and cable television industries. It is typically scene as an expensive challenge because “fanning out” wires and cables is a considerable physical undertaking.” (from Wikipedia)
Last Mile Access Technologies discusses various methods for connecting homes and businesses to internet service providers. It covers traditional copper wire technologies like dial-up, ISDN, and DSL. It also discusses cable networks, wireless networks using technologies like WiFi and WiMax, and other emerging methods like powerline networking. Future technologies may rely more on fiber connectivity and wireless solutions to avoid installing new copper wiring. The document provides details on the capabilities and pros and cons of each technological approach for establishing the "last mile" of connectivity.
http://wartremovalexperts.com/
Warts are a common skin problem that affects a quarter of the world every year. Even though these little skin growths are highly contagious they aren’t considered dangerous. They can look like a rough blister or resemble the appearance of a cauliflower.
Internet of Civil Unmanned Aerial Systems: Challenges and Opportunities (by J...TUS Expo
At TUS Nordics 2017, Jie Jin gave the keynote presentation ‘Internet of Civil Unmanned Aerial Systems: Challenges and Opportunities’ on Thursday 12 October 2017.
High-Tech Drones and Immersive Displays – Exploiting New Technologies for Dig...RCAHMW
Professor Bob Stone discusses his work using new technologies like drones and immersive displays for digital heritage projects. His team has created virtual reconstructions of historic sites like Stonehenge, Scylla, and various locations in Devon like Burrator Reservoir and Wembury Bay. He cautions that immersive technologies are overhyped and have limitations, especially in outdoor environments. Stone emphasizes engaging stakeholders and designing experiences and content before implementing technology.
Drones have been around since 1898 when Nikola Tesla demonstrated a remote-controlled miniature boat. Drones can now be controlled remotely or function autonomously, and can even be operated from a phone. They have a wide range of uses from delivery to surveillance to agriculture. Drones have become popular culture as their military use decreased prices and expanded commercial applications, especially in the United States. While drones raise privacy concerns, they also have potential benefits such as monitoring wildlife, fighting fires, and assisting emergency responders.
This document provides an introduction to drones and unmanned aerial vehicles (UAVs). It discusses the history of drones dating back to 1924, differences between remote controlled toys and UAVs, components of drones like frames, motors, electronic speed controllers and batteries. Applications of drones mentioned include emergency medical assistance, photography, search and rescue, agriculture, and more. The document also contrasts helicopters with quadcopters and lists common tools used for drone building/repair.
The document proposes an Ambulance Drone system to reduce emergency response times. The drone would be triggered by 911 calls and reach patients within 1 minute on average, compared to 10 minutes for ambulances. It would carry an emergency medical kit and allow doctors to monitor the situation and guide treatment. This could significantly increase survival rates for conditions like cardiac arrest. The drone would also alert hospitals and help ambulances navigate to reach patients faster.
UAV(unmanned aerial vehicle) and its application Joy Karmakar
This document discusses unmanned aerial vehicles (UAVs), including their definition, history, components, applications, and disadvantages. UAVs are aircraft without human pilots that can be controlled autonomously or remotely. They have various applications both militarily and civilly, such as aerial surveillance, search and rescue operations, agriculture, filmmaking, and more. The key components of UAVs are the payload, air vehicle, navigation systems, and communications systems. India has developed several UAVs domestically such as Rustom, Nishant, and Lakshya for military purposes. The future of UAV technology remains dynamic with new discoveries expected over the next 16 years.
UAVs (drones) for Humanitarian EffortsBiren Gandhi
Can Drones Save Lives?
Join us for a discovery conversation on how Unmanned Aerial Vehicles (Drones) could aid humanitarians in preparing for and responding to emergencies and disasters.
Technologists, humanitarians, thought leaders and experts will be convening on the Singularity University Campus for a happy hour of networking and special presentations on UAVs in Humanitarian Response.
Learn how drones and UAVs are currently being used to strengthen disaster response capabilities and also their exciting future potential as new technologies are developed.
InSTEDD, Cisco, and Singularity University have joined together to offer this event to showcase leading experts in the field. The event is the concluding segment of a 3-day workshop hosted at SU with UAV engineers and humanitarian response professionals from around the world.
This document describes an air drone designed to carry objects through the sky. The drone has 6 wings and a powerful engine, allowing it to fly speedily and safely. It also has a hooking part under its body to carry bags and items. The drone is designed with high contrast black and white coloring on the bottom to make it easily visible and safe. Its purpose is to carry objects constantly regardless of terrain, such as during traffic jams or disasters.
An Israeli company is testing ambulance drones to transport injured soldiers from the battlefield to hospitals faster than traditional methods. If successful, these drones could save lives by getting people medical attention more quickly and decreasing the number of deaths in war. However, the drones currently being tested are not bulletproof and there are safety risks if they were to fall from the sky.
Drones have the potential to save lives by delivering urgent medical supplies. They can transport supplies like blood, which expires quickly, to rural areas and offshore vessels more rapidly than traditional methods. A pilot project in Rwanda will use drones to deliver medical supplies across the country through a network of drone ports. Drones have also delivered medicines to rural health clinics in the US and provided aid during disasters by transporting supplies and emergency equipment. They can assist in transporting medical samples between specialist labs within time limits. Drones carrying defibrillators could reach emergency patients much faster than ambulances and significantly increase survival rates.
This document discusses drones or unmanned aerial vehicles (UAVs). It provides an introduction to UAVs, including a brief history starting from 1916. It describes the key sub-systems of UAVs including the unmanned aircraft, control system, control link and support equipment. The document discusses various design parameters and applications of UAVs, including disaster relief, search and rescue, sports and armed attacks. It also discusses UAV programs in India and compares Indian and U.S. drones. Finally, it outlines some disadvantages of UAVs such as civilian casualties and hacking risks.
DEF CON 25 (2017)- Game of Drones - Brown,Latimer - 29July2017 - Slides.PDFBishop Fox
https://www.defcon.org/html/defcon-25/dc-25-speakers.html#Brown
Game of Drones - 2017
When you learned that military and law enforcement agencies had trained screaming eagles to pluck drones from the sky, did you too find yourself asking: “I wonder if I could throw these eagles off my tail, maybe by deploying delicious bacon countermeasures?” Well you’d be wise to question just how effective these emerging, first generation ‘drone defense’ solutions really are, and which amount to little more than ‘snake oil’.
There is no such thing as “best practices” when it comes to defending against ‘rogue drones’ – period. Over the past 2 years, new defensive products that detect and respond to ‘rogue drones’ have been crawling out of the woodwork. The vast majority are immature, unproven solutions that require a proper vetting.
We’ve taken a MythBusters-style approach to testing the effectiveness of a variety of drone defense solutions, pitting them against our DangerDrone. Videos demonstrating the results should be almost as fun for you to watch as they were for us to produce. Expect to witness epic aerial battles against an assortment of drone defense types, including:
• trained eagles and falcons that hunt ‘rogue drones’
• fighter drones that hunt and shoot nets
• drones with large nets that swoop in and snatch up ‘rogue drones’
• surface-to-air projectile weapons, including bazooka-like cannons that launch nets, and shotgun shells containing nets
• signal jamming and hijacking devices that attack drone command and control interfaces
• even frickin’ laser beams and Patriot missiles!
We’ll also be releasing DangerDrone v2.0, an upgraded version of our free Raspberry Pi-based pentesting quadcopter (basically a ~$500 hacker’s laptop… that can also fly). We’ll be giving away a fully functional DangerDrone v2.0 to one lucky audience member!
So come see what’s guaranteed to be the most entertaining talk this year and find out which of these dogs can hunt!
This document discusses the use of drones for disaster response and humanitarian efforts. It outlines several projects at the Civic Drone Centre including aeroSee, which uses crowdsourced photos from drones to help with search and rescue efforts, and DroneHack, which brings groups together for rapid drone prototyping. Guidelines for humanitarian drone use were developed and launched at the World Humanitarian Summit. Future areas of focus include more autonomous drones, specialist sensors, multiple coordinating drones, and delivering supplies with drones. The document advocates for further testing and development of existing projects.
An unmanned aerial vehicle (UAV), commonly known as a Drone, is an aircraft without a human pilot on board. UAVs can be remote controlled aircraft (e.g. flown by a pilot at a ground control station) or can fly autonomously based on pre-programmed flight plans or more complex dynamic automation systems
A UAV is defined as being capable of controlled, sustained level flight and powered by a jet or reciprocating engine. In addition, a cruise missile can be considered to be a UAV, but is treated separately on the basis that the vehicle is the weapon.
Unmanned Aerial Vehicles (UAVs) are aircrafts that fly without any humans being onboard. They are either remotely piloted, or piloted by an onboard computer. This kind of aircrafts can be used in different military missions such as surveillance, reconnaissance, battle damage assessment, communications relay, minesweeping, hazardous substances detection and radar jamming. However they can be used in other than military missions like detection of hazardous objects on train rails and investigation of infected areas. Aircrafts that are able of hovering and vertical flying can also be used for indoor missions like counter terrorist operations
To download this ppt click on this link
https://adf.ly/PdL4V
The document discusses the present and future of the drone industry. It covers the commercial, military, and hobbyist markets for drones and how drones are being used for applications like delivery, agriculture, filmmaking, and more. The document predicts that commercial drone spending will reach $4.8 billion globally by 2021 and that drones will continue revolutionizing various industries through innovations in engagement, solutions to unique challenges, and new forms of advertising and events.
Wireless network (cellular network architecture and http.)Abdullah Moin
Cellular architecture is constituted of the following − A network of cells each with a base station. A packet-switched network for communication between the base stations and mobile switching centres. The public switched telephone networks to connect subscribers to the wider telephony network.
In all cellular systems, land area is divided into a number of cells each with its radio service. In AMPS the area is large which in digital services, the area is much smaller. Conventionally cells are hexagonal in shape. Each cell uses a frequency range that is not used by its adjacent cells. However, frequencies may be reused in non-adjacent cells.
This document outlines the course content for a class on Wireless Communication and Mobile Computing. The course consists of 5 chapters that cover topics such as wireless and mobile technologies, wireless communication environments, emerging wireless networks, and pervasive computing. Student assessment includes a mobile application development project, seminar presentation, assignments, and a final written exam. The document then provides details on the first chapter, which covers an overview of wireless technologies, radio platforms, and wireless communication algorithms like MIMO and cooperative communications. It also introduces some key concepts relating to mobile computing such as location awareness and quality of service in wireless networks.
This document provides an overview of computer networks and the TCP/IP protocol suite. It describes network criteria like performance and reliability. It discusses physical network structures like point-to-point, multipoint, mesh, star, bus and ring topologies. It also defines categories of networks such as local area networks (LANs), wide area networks (WANs) and metropolitan area networks (MANs). A key point is that the TCP/IP protocol suite, which controls the Internet, is organized into five layers: application, transport, internet, network interface and physical. The layers are described along with how a message travels through them.
Communications Asymmetry, Classification of Data Delivery Mechanisms, Data Dissemination, Broadcast Models, Selective Tuning and Indexing Methods, Data Synchronization – Introduction, Software, and Protocols
Handover for 5G Networks using Fuzzy Logic: A ReviewAI Publications
The future organization world will be inserted with various ages of remote advances, like 4G and 5G. Simultaneously, the advancement of new gadgets outfitted with different interfaces is filling quickly as of late. As a result, the upward handover convention is created to give pervasive availability in the heterogeneous remote climate. Handover might be a fundamental a piece of any remote Mobile Communication Network. It is a way of mobile communication and portable communication during which cellular broadcast is relocate from one base station to another without losing connection to the mobile communication. Handover is one problem on Wireless Network (WN) and to unravel this problem various sorts of HO methods utilized in network. Fuzzy logic, Machine Learning and Optimization are the handover solving methods that are studied during this paper. This paper is a review of the handoff techniques. Fuzzy logic is that the best technique to unravel the HO problem and it's further implemented in 4G/5G network.
Edhole School provides best Information about Schools in India, Delhi, Noida, Gurgaon. Here you will get about the school, contact, career, etc. Edhole Provides best study material for school students.
Multi Bandwidth Data path design for 5G Wireless SystemsChaitanya Krishna
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This document provides an overview of networking concepts and how to set up a home network. It discusses networking fundamentals like nodes, benefits of networking, and network architectures. It also covers connecting to the internet via broadband or dial-up, basic network hardware components, and installing and configuring a home network. This includes planning the network, connecting devices to a router, using network-attached storage, and configuring software. The document concludes with securing wireless networks and troubleshooting wireless problems.
Wireless networking in schools provides mobility for students and supports e-learning. It allows students to access the curriculum and research resources from anywhere in the school using devices like laptops and tablets. Wireless networks eliminate the need to run cables and wires, making installation faster and more flexible. They also reduce costs compared to wired networks. While wireless improves access and mobility, schools must also implement security measures to protect their network and devices on it. Newer wireless standards like 802.11ac provide faster speeds and greater capabilities to meet the needs of students' use of technology in schools.
This document provides an overview of a data communications course, including information about the professor, textbook, lecture notes, and course outline. It covers topics like the definition of data communications, the five components of a data communication system, direction of data flow (simplex, half-duplex, and full-duplex), different network types (LAN, MAN, WAN, internetwork), physical network topologies (mesh, star, bus, ring, hybrid), categories of networks, a brief history of the Internet, protocols, standards and standards organizations.
The document discusses ad hoc wireless networks and their characteristics. Ad hoc wireless networks are infrastructureless networks that use multi-hop relaying between nodes. They are suitable for applications such as military operations, emergency response, and collaborative computing. Issues with ad hoc networks include distributed routing, frequent path breaks due to mobility, and shared bandwidth. The document also describes different types of wireless networks including mesh networks, sensor networks, and hybrid networks.
Front End Intelligence for Large scale Application Oriented IoT - Ahmed Bader, Hakkim Gazzai, Muhammed Alouini, Abdhulla kadri.
Published in IEEE Open Access Journal, July 2016.
Data Communication Lecture Slides containing a timeline on the history of data communication and the definition ob basic data communication terms and concepts based largely on the book Electronic Communication by Wayne Tomasi.
This document discusses the coexistence of WiFi and LiFi networks towards 5G. It provides an overview of WiFi and LiFi technologies, comparing their characteristics. Challenges of incorporating both include how user devices connect to the network, supporting user mobility, and accommodating multiple users. The document proposes a LiFi transceiver model and evaluates performance of indoor and outdoor links. It compares using only WiFi, a hybrid WiFi-LiFi system, and an aggregate system. Coexistence of LiFi and WiFi is promising for applications like healthcare and IoT, with opportunities for further research on higher data rates, CSMA/CA and OFDMA coexistence, and mobility enhancements.
Interference Revelation in Mobile Ad-hoc Networks and Confrontationirjes
In this paper, we utilize the Several interference revelation techniques proposed for mobile ad hoc
networks rely on each node passively monitoring the data forwarding by its next hop. This paper presents
quantitative evaluations of false positives and their impact on monitoring based interference revelation for ad
hoc networks. Experimental results show that, even for a simple three-node configuration, an actual ad-hoc
network suffers from high false positives; these results are validated by Markov and probabilistic models.
However, this false positive problem cannot be observed by simulating the same network using popular ad hoc
network simulators, such as ns-2, OPNET or Glomosim. To remedy this, a probabilistic noise generator model
is implemented in the Glomosim simulator. With this revised noise model, the simulated network exhibits the
aggregate false positive behavior similar to that of the experimental tested. Simulations of larger (50-node) ad
hoc networks indicate that monitoring-based interference revelation has very high false positives. These false
positives can reduce the network performance or increase the overhead. In a simple monitoring-based system
where no secondary and more accurate methods are used, the false positives impact the network performance in
two ways: reduced throughput in normal networks without attackers and inability to mitigate the effect of
attacks in networks with attackers.
AAP Part I DeliverableHere is the assignment to be comple.docxannetnash8266
AAP Part I Deliverable:
Here is the assignment to be completed in your group. The tasks are organized in no particular order.
Highlevel drawing of proposed upgrades
Drawing of existing network
WAN links bandwidth for the network
Inventory and IP scheme
Scope of work or design requirements
The first task in a network design or an upgrading of the network is defining the scope of work. This
scope of work is outlined in the client’s Request for Proposal. This is your base line for developing the
scope of work. Here you will start gathering information about the client’s business goals and technical
requirements. To identify the business goals, interview upper management, focusing on technical
requirements. The IT department can then provide you with the specifications. In the real world, this step
is necessary to validate the information provided by the client’s RFP. In this assignment, however, this
part of the scope of work is optional. Either you can role play and interview each other to come up with
the information or you can skip it. If you skip it, your scope of work is the client’s RFP
Example: Identifying the scope of work:
The scope of this project consists of major modifications to the existing network, along with the
implementation of many new network devices and protocols. The main intent of this redesign is to: improve
network availability, network reliability, and network security; create a centralized network backbone;
implement the use of wireless access, and migrate from a PBX telephony system to an IP based telephony
solution.
The proposed design will affect all areas of the current network. Implementing a centralized backbone and
upgrading the speed of current links (from 10Mbs to 100Mbs) will greatly improve the entire network. The
implementation of a new IP schema, the introduction of VLAN’s, and implementation of new routing
protocols and security protocols will improve the network layer. Just as the implementation of wireless,
redundant switches, along with the design of a network edge area will improve the data link layer of the
network.
Ultimately, the redesign of the network needs to meet the customer’s intent for the redesign. During the
implementation phase of the redesign, the entire network will be affected in some way – that is, some
improvements will have an immediate impact, while other improvements are going to take more time to
implement and may cause some network disruption for a short time. However upon the conclusion of the
design implementation, the customer will have a greatly improved network, which will fulfill their company’s
IT needs, at present, and for many years to come.
The second task is to prepare the existing drawings, if not provided by the client.
The third task is to prepare an inventory list. This can be done by using software or physically verifying
the existing equipment. Your inventory list should include currently operable equipment and new
equipment (You can use the inventory t.
PROnet is an NSF-supported research project being conducted by researchers at the University of Texas at Dallas. PROnet is dedicated to enabling the design, development, demonstration and deployment of innovative ultrahigh-speed low-latency applications being created in and across North Texas and beyond.
wireless sensor networks using zigbee and wifisunil raj kumar
the ppt presents a brief view of how we can transmit zigbee collected data to wifi transceiver and flow chart ,block diagram gives you a clear idea of how data are transmitting
Introduction to Computer Networks Basics.pptxBlerta50
This document discusses the basics of computer networks and the evolution of networking technologies over time. It covers topics like the definition of a computer network, different types of nodes and communication links, the emergence of blogs, the transition from analog to digital transmission, the development of broadband and Ethernet, wireless innovations like Wi-Fi and Bluetooth, and future directions in ubiquitous computing. The overall document examines how computer networks and connectivity have advanced significantly in recent decades to support new applications and provide faster, more ubiquitous access to information and services.
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Monitoring and Managing Anomaly Detection on OpenShift
Overview
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Mobility-Aware Real-Time Scheduling for Low-Power Wireless Networks
1. Mobility-Aware Real-Time Scheduling for
Low-Power Wireless Networks
• Behnam Dezfouli
• Marjan Radi
• Octav Chipara
Contact:
http://behnam.dezfouli.com
dezfouli [at] ieee [dot] org
IEEE 35th International Conference on Computer Communications (INFOCOM’16)
10-15 April 2016 San Francisco, CA, USA
Department of Computer Science
The University of Iowa
2. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Introduction
Non Real-Time vs Real-Time Wireless Networks
2
Nodes contend for transmission
whenever they have data
Non Real-Time Networks
• Provide a best-effort service
• No guarantee of timeliness or
reliability
• Network dynamics affect the
service provided
• For example: Connecting
devices using WiFi
Real-Time Networks
• Packets should be delivered in a
timely and reliable manner
• Network dynamics do not affect
the service provided
• For example: Connecting
devices using WirelessHART
Nodes’ transmission schedules
are predetermined
3. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Introduction
• Wireless devices in industrial
applications: annual growth
rate of 27.2%
• 43.5 million devices by 2020
Industrial Real-Time Wireless Networks
3
Make wireless technology an attractive solution for
process monitoring and control applications
• Reducing the cost
• Simplifying the deployment
4. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Introduction
WirelessHART
4
4-20 mA
Access
Point
Access
Point
HART All-Digital Multidrop Mode
Security Manager
Network Manager
Host Application
(e.g. Asset Management)
Process Automation
Controller
AcAcAAccececesssssss
AcAcAcAccecececesssssss
WirelessHART
Devices
WirelessHART
Adapter
WirelessHART
Adapter
WirelessHART
Devices
WirelessHART
Gateway
WirelessHART
Gateway
Connections
HART-IP
Modbus
Ethernet
more
WIRELESSHART MESH NETWORK
HART Device +
WirelessHART Adapter
Non-HART Device +
WirelessHART Adapter
Time Slot
Channel
The schedules assigned
to the red and blue links
Courtesy of: Field Comm Group
Gateway is responsible
for managing medium
access schedules
Through time slot and
channel assignment
(FTDMA: Frequency-Time
Division Multiple Access)
Central Network Management
5. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Introduction
1. Shortcomings of contention-based medium access:
• Does not guarantee end-to-end delay
• Significant packet collision and loss
2. Shortcomings of distributed schedule-based medium access:
• Does not guarantee end-to-end delay
• Moderate packet loss due to intra-network interference
Why Centralized Medium Access Scheduling?
5
3. Benefits of centralized schedule-based medium access:
• Guaranteed end-to-end delay
• Avoids packet loss due to intra-network interference
6. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Introduction
Research Gap
6
Existing real-time wireless networks assume:
Nodes are stationary, and
The set of traffic flows are fixed
Limits the applicability of these solutions to dynamic
applications with mobile entities such as
patients, robots, firefighters, etc.
How to support real-time communication with mobile nodes?
7. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Objective
7
8. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Objective
Sample Application
8
— Timely and reliable delivery of patients’ vital signs to the Gateway
Gateway
Patient
(Mobile)
Ready Ready
Deadline Deadline
Time
Ready
9. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Basic Assumptions and Requirements
9
• Each mobile node can generate one or more data flows
• Each flow i is characterized by its period (Pi) and deadline (Di)
• The mobility pattern of the mobile nodes is unknown
• Packets of each data flow should be delivered to the Gateway
before their deadline
• For example:
• A mobile node samples heart rate every 1 sec
• The sample should be delivered to the Gateway no later than
0.9 sec after its generation
Ready Ready Ready
Deadline Deadline
Time
Objective 9
packet
generation
packet
delivery
10. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
10
11. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Architecture
11
A Low-Power Wireless Infrastructure Node
• Communicates in a real-time manner with the Gateway Gateway
• Communicates with the nodes
• Computes and distributes
nodes’ schedules
A Low-Power Wireless Mobile Node
• Communicates in a real-time manner
with the Gateway
Communication Between
Infrastructure Nodes
12. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Architecture
12
• Base stations are connected
through wire links
• Similar to cellular (3G, 4G) and most
WiFi networks
• Hard network deployment
• Bandwidth reservation only between
mobile-infrastructure
• A multi-hop wireless infrastructure
• Easy network deployment
• Bandwidth reservation between
infrastructure-infrastructure as well as
mobile-infrastructure
Wireless Link Wire LinkWire Link
Wireless
Link
Wireless
Link
Wireless
Link
Wired infrastructure
Wireless infrastructure (our choice)
13. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Implication of Assumptions on Scheduling
13
Unpredictable mobility paths
Low energy consumption:
Short communication ranges
The need to deliver data in a timely
and reliable manner
How these assumptions affect
our network design?
Network Design
14. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Mobility and Data Forwarding Paths
14
Low
Power Consumption
Short
Communication Range
Frequent
Association with
Infrastructure Nodes
Frequent
Changes in Data
Forwarding Paths
Bandwidth Reservation
Upon Node Admission
15. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Two Bandwidth Reservation Strategies
15
• Whenever a mobile node needs to communicate over a path, it sends a
request to the Gateway
• Shortcoming #1: Huge bandwidth should be reserved for
exchanging control data
• Gateway performs bandwidth reservation over the new communication
path after receiving a request
• Shortcoming #2: The Gateway may not be able to reserve bandwidth
over the new communication path: CONNECTION LOSS!
1: On-Demand Bandwidth Reservation
Mobile
Node
Gateway
Request for bandwidth
reservation over Path i
New transmission schedules
Mobile
Node
Gateway
Request for bandwidth
reservation over Path i
Failed scheduling
16. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Two Bandwidth Reservation Strategies
16
• Bandwidth is reserved over all the potential communication paths
upon node join
• Gateway admits a mobile node if bandwidth reservation over all the
potential communications paths was successful
• Shortcoming: If performed naively, the number of admitted mobile
nodes would be very small
• We propose techniques to address this shortcoming
2: On-Join Bandwidth Reservation (our choice)
Mobile
Node
Gateway
Request for admission
Successful scheduling:
New transmission schedules
Unsuccessful scheduling:
Rejection
17. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Mobile Node Admission
17
Admitting a mobile node:
1. Beaconing:
• Infrastructure nodes periodically broadcast beacon packets
• Mobile node can discover nearby infrastructure nodes
2. Request for Join:
• Mobile node sends a request for join
• Infrastructure nodes forward the request towards the Gateway
3. Schedule Computation and Dissemination
• The Gateway computes a new schedule to accommodate for the new
node
• Infrastructure nodes distribute the computed schedule
• The mobile node receives the schedule
Network Design 17
18. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Admission: First Step
18
1. Beaconing
• Infrastructure nodes regularly broadcast beacon packets
• Mobile nodes discover nearby nodes
19. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Admission: Second Step
19
2. Join Request
• The mobile node sends a join request
• Infrastructure nodes forward the request to the Gateway
• Gateway decides about the admission of the mobile node
Gateway implements a scheduling algorithm that
reserves bandwidth for the new mobile node
20. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Admission: Third Step
20
3. Schedule Computation and Dissemination
If:
The mobile node can be admitted
Then:
Distribute transmission schedules
How much data
should be
distributed?
21. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Network Design
Schedule Computation and Dissemination
21
How much data should be distributed when a mobile node is admitted?
Existing scheduling strategies:
Scheduling a new flow may modify
the schedules of existing flows
Every admission requires distributing the transmissions of:
new mobile node + existing mobile nodes
A huge amount of control data should be distributed after each join
Long node admission delay
Increasing #Admitted Nodes Increasing Admission Delay
22. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Observations
22
We should employ on-join scheduling instead of on-demand scheduling
Observation 1
We propose mechanisms that increase real-time capacity
We should minimize the amount of
control data required for schedule dissemination
We propose additive scheduling
Contribution:
Observation 2
Contribution:
Network Design 22
23. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
23
24. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Mobility, Association, and Routing Paths
24
• To forward a flow i:
• M associates with infrastructures nodes, depending on its location
— On-join bandwidth reservation:
• Reserve bandwidth for M over all the potential communication paths
• How a scheduling algorithm designed for stationary real-time networks
would perform the scheduling?
• We refer to this algorithm as Static Real-time Scheduling (SRS)
Potential Communication Paths
A
B
C
E
D
MPath 1 MA
Path 2 MB BA
Path 3 MC CA
Path 4 MD DC CA
Path 5 ME EC CA
25. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
SRS: Static Real-time Scheduling
25
The scheduling matrix produced by SRS
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME MD MB MC MA CA CA CA
c2 EC DC BA
c3
…
This schedule is inefficient !
Path 1 MA
Path 2 MB BA
Path 3 MC CA
Path 4 MD DC CA
Path 5 ME EC CA
A
B
C
E
D
M
Scheduling Constraints:
• A node cannot send and receive simultaneously
• On a path, a transmission BC can be scheduled
after transmission AB has been scheduled
26. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
SRS: Static Real-time Scheduling
26
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME
c2
c3
…
ready transmissions =
{(ME), (MD), (MC), (MB), (MA)}
highest depth:
higher priority
lowest depth:
lower priority
D = 1
D = 2
D = 2
D = 3
D = 3
Potential Communication Paths
A
B
C
E
D
M
Path 1 MA
Path 2 MB BA
Path 3 MC CA
Path 4 MD DC CA
Path 5 ME EC CA
27. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
SRS: Static Real-time Scheduling
27
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME MD
c2 EC
c3
…
ready transmissions =
{(MD), (EC), (MC), (MB), (MA)}
D = 1
D = 2
D = 2
D = 3
D = 2
A
B
C
E
D
M
Potential Communication Paths
Path 1 MA
Path 2 MB BA
Path 3 MC CA
Path 4 MD DC CA
Path 5 EC CA
28. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
SRS: Static Real-time Scheduling
28
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME MD MB
c2 EC DC
c3
…
ready transmissions =
{(MB), (MC), (DC), (MA), (CA)}
D = 1
D = 2
D = 2
D = 2
D = 1
A
B
C
E
D
M
Potential Communication Paths
Path 1 MA
Path 2 MB BA
Path 3 MC CA
Path 4 DC CA
Path 5 CA
29. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
SRS: Static Real-time Scheduling
29
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME MD MB MC
c2 EC DC BA
c3
…
ready transmissions =
{(MC), (BA), (MA), (CA), (CA)}
D = 1
D = 1
D = 2
A
B
C
E
D
M
Potential Communication Paths
Path 1 MA
Path 2 BA
Path 3 MC CA
Path 4 CA
Path 5 CA
D = 1
30. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
SRS: Static Real-time Scheduling
30
ready transmissions =
{(MA), (CA), (CA), (CA)}
D = 1
D = 1
A
B
C
E
D
M
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME MD MB MC MA
c2 EC DC BA
c3
…
Potential Communication Paths
Path 1 MA
Path 2
Path 3 CA
Path 4 CA
Path 5 CA
31. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Static Real-time Scheduling
31
ready transmissions =
{(CA), (CA), (CA)}
D = 1
A
B
C
E
D
M
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME MD MB MC MA CA
c2 EC DC BA
c3
…
SRS: Static Real-time Scheduling
Potential Communication Paths
Path 1
Path 2
Path 3 CA
Path 4 CA
Path 5 CA
32. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
SRS: Static Real-time Scheduling
32
ready transmissions =
{(CA), (CA)}
D = 1
A
B
C
E
D
M
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME MD MB MC MA CA CA
c2 EC DC BA
c3
…
Potential Communication Paths
Path 1
Path 2
Path 3 CA
Path 4 CA
Path 5
33. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
SRS: Static Real-time Scheduling
33
ready transmissions =
{(CA)}
D = 1
A
B
C
E
D
M
0 1 2 3 4 5 6 7 8 9 10 …
c1 ME MD MB MC MA CA CA CA
c2 EC DC BA
c3
…
Potential Communication Paths
Path 1
Path 2
Path 3 CA
Path 4
Path 5
34. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Path-Dependent Schedule Activation
34
CA BAMB
period k:
Data forwarding over Path 5
period k+1:
Data forwarding over Path 2
Path-Dependent Schedule Activation
ECME
CACACAMA
MC
BA
period k period k+1
Actual Transmission Schedules Assignment
MB
DC
MD
EC
ME CACACAMA
MC
BA
MB
DC
MD
EC
ME
35. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 1: Schedule Combination
35
For a flow i, two transmissions belonging to two different paths
can be combined in one entry of the scheduling matrix.
A
B
C
E
D
M
For Example:
• Transmissions (MA), (MB), (MC), (MD) and (ME) can be combined.
• Transmissions (MC), (DC) and (EC) can be combined.
• …
36. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 1: Schedule Combination
36
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MC
MB
MA
…
ready transmissions =
{(ME), (MD), (MC), (MB), (MA)}
D = 1
D = 2
D = 2
D = 3
D = 3
A
B
C
E
D
M
Potential Communication Paths
Path 1 MA
Path 2 MB BA
Path 3 MC CA
Path 4 MD DC CA
Path 5 ME EC CA
37. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 1: Schedule Combination
37
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MC
MB
MA
BA
CA
DC
EC
…
ready transmissions =
{(BA), (CA), (DC), (EC)}
D = 2
D = 1
D = 2
D = 2
A
B
C
E
D
M
Potential Communication Paths
Path 1
Path 2 BA
Path 3 CA
Path 4 DC CA
Path 5 EC CA
38. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 1: Schedule Combination
38
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MC
MB
MA
BA
CA
DC
EC
CA
CA
…
ready transmissions =
{(CA), (CA)}
D = 1
A
B
C
E
D
M
Potential Communication Paths
Path 1
Path 2
Path 3
Path 4 CA
Path 5 CA
39. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 1: Schedule Combination
39
The scheduling matrix produced by employing:
Schedule Combination
3 entries of the scheduling matrix are used
We have scheduled the five paths more efficiently
However:
Data flows over these five paths can be coordinated
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MC
MB
MA
BA
CA
DC
EC
CA
CA
…
We propose the Flow Coordination technique to:
Reduce the number of transmissions scheduled in each entry
40. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 2: Flow Coordination
40
Path 1 MA
Path 2 MB BA
Path 3 MC
Path 4 MD DC
Path 5 ME EC CA
Path 1 MA
Path 2 MB BA
Path 3 MC CA
Path 4 MD DC CA
Path 5 ME EC CA
Without Flow Coordination With Flow Coordination
Transmission CA is scheduled once
after transmissions MC, DC, and EC have been scheduled
Replicated transmission schedules can be eliminated through
coordinating the scheduling of potential communication paths
41. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 2: Flow Coordination
41
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MC
MB
MA
…
ready transmissions =
{(ME), (MD), (MC), (MB), (MA)}
D = 1
D = 2
D = 2
D = 3
D = 3
A
B
C
E
D
M
Potential Communication Paths
Path 1 MA
Path 2 MB BA
Path 3 MC
Path 4 MD DC
Path 5 ME EC CA
42. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 2: Flow Coordination
42
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MC
MB
MA
BA
DC
EC
…
ready transmissions =
{(BA), (DC), (EC)}
D = 1
D = 2
D = 2
A
B
C
E
D
M
Potential Communication Paths
Path 1
Path 2 BA
Path 3
Path 4 DC
Path 5 EC CA
43. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 2: Flow Coordination
43
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MC
MB
MA
BA
DC
EC
CA
…
ready transmissions =
{(CA)}
D = 1
A
B
C
E
D
M
Potential Communication Paths
Path 1
Path 2
Path 3
Path 4
Path 5 CA
44. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 3: Reverse Scheduling
44
0 1 2 …
A
B
C
D
E
For Example:
Using forward scheduling, node A is blocked
in 3 slots, i.e., node A cannot be used for
scheduling other flows in time slots 0, 1, 2
• So far we have employed “forward scheduling”
—Forward Scheduling:
• We perform link scheduling starting from the flow generator
—Cannot effectively use the schedule combination technique
0 1 2 ..
c1
ME
MD
MC
MB
MA
BA
DC
EC
CA
……
A
B
C
E
D
M
45. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 3: Reverse Scheduling
45
—Forward Scheduling:
• The set of ready transmissions initially includes the transmissions that
origin from the flow generator
• Scheduling is started from time slot 0
Unfortunately, forward scheduling does not effectively benefit from the
schedule combination technique we proposed earlier
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MC
MB
MA
BA
DC
EC
CA
Transmissions MA and BA could be
scheduled in the same entry as that of CA
Blocking slots of A is
reduced from 3 to 1
46. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 3: Reverse Scheduling
46
• We propose “Reverse Scheduling” to improve schedule combination
—Reverse Scheduling:
• We perform link scheduling from the destination
… 5 6 7
A
B
C
D
E
For Example:
Using reverse scheduling, node A is
blocked in 1 slot only.
… 5 6 7
c1
ME
MD
MB
DC
EC
MC
MA
BA
CA
……
A
B
C
E
D
M
47. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 3: Reverse Scheduling
47
• To improve the efficiency of Flow Merging, we propose “Reverse Scheduling”
—Reverse Scheduling:
• The set of ready transmissions initially includes the transmissions that
deliver a flow to its destination
• Scheduling is started from the deadline of the flow
Forward
Scheduling
Reverse
Scheduling
48. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 3: Reverse Scheduling
48
0 1 2 3 4 5 6 7 8 9 10 …
c1
MA
BA
CA
…
ready transmissions =
{(CA), (BA), (MA)}
D = 1
D = 1
D = 1
Potential Communication Paths
A
B
C
E
D
M
Path 1 MA
Path 2 MB BA
Path 3 MC
Path 4 MD DC
Path 5 ME EC CA
49. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 3: Reverse Scheduling
49
0 1 2 3 4 5 6 7 8 9 10 …
c1
MB
DC
EC
MC
MA
BA
CA
…
ready transmissions =
{(MB), (DC), (EC), (MC)}
D = 2
D = 2
D = 2A
B
C
E
D
M
D = 2
Potential Communication Paths
Path 1
Path 2 MB
Path 3 MC
Path 4 MD DC
Path 5 ME EC
50. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Technique 3: Reverse Scheduling
50
0 1 2 3 4 5 6 7 8 9 10 …
c1
ME
MD
MB
DC
EC
MC
MA
BA
CA
…
ready transmissions =
{(ME), (MD)}
D = 3
D = 3
A
B
C
E
D
M
Potential Communication Paths
Path 1
Path 2
Path 3
Path 4 MD
Path 5 ME
51. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Slot Blocking: Forward and Reverse Scheduling
51
0 1 2 ..
c1
ME
MD
MC
MB
MA
BA
DC
EC
CA
……
0 1 2 …
A
B
C
D
E
Slot Blocking with “Forward Scheduling”
… 5 6 7
c1
ME
MD
MB
DC
EC
MC
MA
BA
CA
……
… 5 6 7
A
B
C
D
E
Slot Blocking with “Reverse Scheduling”
blocked in
3 slots
blocked in
1 slot
52. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Flow-Ordered Mobility-Aware Scheduling Algorithm (FO-MARS)
52
Request for Admission
Reserve bandwidth for:
new mobile node + existing nodes
Distribute the schedules for:
new mobile node + existing nodes
Reject
Approve
FO-MARS
Gateway
— Input:
• new mobile node’s flows +
existing flows
— Output:
• Approve: The algorithm has
scheduled all the flows
• Reject: The algorithm cannot
schedule all the flows
— Operation Summary:
• Schedule flows in the order of
their deadlines
• Employ the techniques we
proposed earlier
FO-MARS
53. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Algorithm may-schedule()
53Frequency-Time Division Multiple Access
In time slot s, what is the best
channel in which the given
transmission can be scheduled?
This is the best channel found
Based on the rules presented earlier
Scheduling
Matrix
Start
sender | receiver | flow: i | slot | scheduling matrix: S
sender or
receiver used
for scheduling
another flow?
A channel in
which sender or
receiver have
been used?
A channel in which
a transmission of
flow i has been
scheduled?
return
None
return
channel
Yes
Yes
No No
return
channel
Yes
An empty
channel?
return
channel
Yes
No
No
54. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Flow-Ordered Mobility-Aware Real-Time Scheduling (FO-MARS)
54
• Schedules one flow at a time
• The order of flow scheduling is based on flows’ deadlines
NOTE: Scheduling a flow with longer period may reduce the schedulability
chance of flows with shorter periods…
EXAMPLE:
• f1:<m1, 32, 32> requires 4 transmissions
• f2:<m2, 8, 8> requires 4 transmissions
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
We cannot
schedule f2 here
Ordering 1: f1:<m1, 32, 32> , then f2:<m2, 8, 8>
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
Ordering 2: f2:<m2, 8, 8>, then f1:<m1, 32, 32>
55. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Flow-Ordered Mobility-Aware Real-Time Scheduling (FO-MARS)
55
Two shortcomings of FO-MARS:
1. When a request for bandwidth reservation is received, all the existing
flows with shorter period must also be rescheduled
Significant control data dissemination
Long node join delay
2. A newly received schedule can be used at the beginning of the next
hyper period
Long node join delay
56. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Flow-Ordered Mobility-Aware Real-Time Scheduling (FO-MARS)
56
We cannot switch to a new scheduling matrix at any time
✦ Example:
… s-1 s s+1 s+2 …
*
… s-1 s s+1 s+2 …
*
Reception of new
scheduling matrix
Existing Scheduling Matrix New Scheduling Matrix
Switch to the new
scheduling matrix
Transmission * never happens
because that is scheduled for slot
s in the new scheduling matrix
57. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Flow-Ordered Mobility-Aware Scheduling Algorithm (FO-MARS)
57
Request for Admission
Reserve bandwidth for:
new mobile node + existing nodes
Distribute the schedules for:
new mobile node + existing nodes
Reject
Approve
FO-MARS
Gateway
Request for
Node Admission
All the red schedules
should be disseminated
LONG
Node Admission Delay
Problem
58. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Additive Mobility-Aware Real-Time Scheduling (A-MARS)
58
Request for Admission
Reserve bandwidth for:
new mobile node
Distribute the schedules for:
new mobile node
Reject
Approve
A-MARS
Gateway
Request for
Node Admission
Only the red schedules
should be disseminated
SHORT
Node Admission DelayProblem Solved
59. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Challenge of Additive Scheduling
59
time
The flows of each node should be scheduled
so that future mobile nodes can be scheduled as well
A B C
We need a smart bandwidth reservation algorithm that
predicts the future to enhance the schedulability of future flows
60. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Challenge of Additive Scheduling
60
• Assume Pγ = 16 and Pβ = 8
• γ and β require 5 transmissions
• γ and β cannot be scheduled using the same time slots
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
nth Period of flow γ (Scheduling ok!)
γ γ γ γ γ
nth Period of flow β (scheduling ok!) n+1th Period of flow β (scheduling fail!)
β β β β β γ γ γ γ γ
Failed admission of flow β
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
nth Period of flow γ (Scheduling ok!)
γ γ γ γ γ
nth Period of flow β (scheduling ok!) n+1th Period of flow β (scheduling ok!)
β β β β β γ γ β β β β β γ γ γ
Successful admission of flow β
How to know which slots should be used for scheduling a flow?
61. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Flow Classes and Slot Prioritization
61
• Assume the network services a set of flow classes γ, β, α,…
• All the flows in a flow class have similar period and deadline
• We prepare a prioritized list of slots for scheduling each flow class
How using a slot for
scheduling γ would affect
the schedulability of β and α
Prepare a prioritized list of
slots for scheduling a flow γ
For flow class γ : Flow
Class
Period/
Deadline
Heart
Rate
γ Pγ, Dγ
Pulse
Oximetry
β Pβ , Dβ
Blood
Pressure
α Pα, Dα
Dα < Dβ < Dγ
62. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Frequency-Time Division Multiple Access
Slot Prioritization
62
• We propose the notion of Potential Utilization (PU) to measure the
effect of choosing each slot
Time Slots 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
nth Period of flow β n+1th Period of flow β
PU for class β 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31
Time Slots 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
nth Period of flow β n+1th Period of flow β
PU for class β 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31
Choose slot 7 and update PU
choosing from these slots:
increase PU by 0.31
choosing from these slots:
increase PU by 0.39
demand = percentage of flows belonging to class β x #required transmissions
available slots
(0.5 X 5)/8
63. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Performance Evaluation
63
64. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
• Correctness depends on both functionality and timeliness
• Real-time networks are required for mission-critical applications
• Mission-critical applications:
• Industrial process control
• Clinical patient monitoring
• …
• Several organizations: HART, ISA, WINA, ZigBee
Setup
64
Mobility Paths
Links of the Routing Graph
Infrastructure Nodes
Gateway
• Trace-driven simulator using exhaustive floor plan measurements
• Realistic and repeatable experimentation
Performance Evaluation
65. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Flow Period [second]
(a)
0.64 1.28 2.56 5.12
MaxMobil
0
50
100
Flow Period [second]
(b)
0.64,1.28,2.56 0.64,1.28,5.12 0.64,2.56,5.12 1.28,2.56,5.12
MaxMobileNodesSupported
0
10
20
30
40
50
60
70
80
90
100
Performance Evaluation
Scalability: How Many Mobile Nodes can be Supported?
65
Mobile nodes generate
reports with different rates
FO-MARS vs SRS
14x
5.12
LLF-SRS
LLF-ESRS
LLF-CERS
FO-MARS
A-MARS
SRS: Designed for Static Networks
ESRS: SRS + Flow Coordination
CERS: SRS + Flow Coordination + Schedule Combination
Proposed Algorithms
66. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Performance Evaluation
Admission Delay
66
Number of Mobile Nodes
(a)
10 20 30 40 50
AdmissionDelay[s]
0
50
100
150
200
250
Flow Period = 1:28
Number of Mobile Nodes
(b)
50 100 150
AdmissionDelay[s]
0
50
100
150
200
250
Flow Period = 5:12
Number of Mobile Nodes
(c)
10 20 30 40 50
AdmissionDelay[s]
0
100
200
300
400
Flow Period 2f0:64; 1:28; 2:56g
Number of Mobile Nodes
(d)
20 40 60 80 100
AdmissionDelay[s]
0
100
200
300
400
Flow Period 2f1:28; 2:56; 5:12g
SRS: Designed for Static Networks
ESRS: SRS + Flow Coordination
CERS: SRS + Flow Coordination + Schedule Combination
= 1:28
missionDelay[s]
50
100
150
200
250
Flow Period = 5:12
LLF-SRS
LLF-ESRS
LLF-CERS
FO-MARS
A-MARS
Proposed Algorithms
A-MARS’S Admission delay
< 20 seconds
67. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Performance Evaluation
Network Lifetime
67
SRS: Designed for Static Networks
ESRS: SRS + Flow Coordination
CERS: SRS + Flow Coordination + Schedule Combination
= 1:28
missionDelay[s]
50
100
150
200
250
Flow Period = 5:12
LLF-SRS
LLF-ESRS
LLF-CERS
FO-MARS
A-MARS
Proposed Algorithms
odes
70
Number of Mobile Nodes
(b)
10 20 30 40
NodeLifetime[hour]
500
1000
1500
2000
2500
3000
3500
Pdata 2f64; 128; 256g
Number of Mobile Nodes
(c)
10 20 30 40 50 60
NodeLifetime[hour]
0
1000
2000
3000
4000
5000
6000
7000
Flow Period 2f1:28; 2:56; 5:12g
LLF-ESRS LLF-CERS FO-MARS A-MARS
Higher network lifetime
achieved with
FO-MARS and A-MARS
68. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Conclusion
68
• Real-time wireless networks can be used in mission-critical
applications such as industrial process control and medical
monitoring
• Existing real-time networks do not efficiently handle network
dynamics such as mobility and flow addition/removal
• We proposed scheduling techniques for efficient bandwidth
reservation for mobile nodes
• We proposed an additive scheduling algorithm for effective
handling of flow admission and removal
• Compared to the algorithms designed for stationary real-time
networks, our proposed network admits a significantly higher
number of mobile nodes, archives short admission delay, and
handles network dynamics efficiently
69. Behnam Dezfouli | Mobile Sensing Laboratory :: Department of Computer Science :: The University of Iowa
Acknowledgement
69
Behnam Dezfouli
University of Iowa
Iowa City, IA, USA
Marjan Radi
University of Iowa
Iowa City, IA, USA
Octav Chipara
University of Iowa
Iowa City, IA, USA
This work was supported by
the National Science Foundation and
the Roy J. Carver Charitable Trust