AU2020101430A4 - Low delay communication between cyber physical systems of iot applications using fog nodes - Google Patents

Low delay communication between cyber physical systems of iot applications using fog nodes Download PDF

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AU2020101430A4
AU2020101430A4 AU2020101430A AU2020101430A AU2020101430A4 AU 2020101430 A4 AU2020101430 A4 AU 2020101430A4 AU 2020101430 A AU2020101430 A AU 2020101430A AU 2020101430 A AU2020101430 A AU 2020101430A AU 2020101430 A4 AU2020101430 A4 AU 2020101430A4
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fog
cyber
applications
iot
physical
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AU2020101430A
Inventor
Joel Devadass Daniel D. J.
Madhusudhan K. N.
Jayalekshmi M.B.
Nagaratna P. Hegde
Senthil T.
Jeyasheela Y.
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D J Joel Devadass Daniel Mr
MB Jayalekshmi Dr
P Hegde Nagaratna Dr
T Senthil Dr
Y Jeyasheela Dr
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D J Joel Devadass Daniel Mr
M B Jayalekshmi Dr
P Hegde Nagaratna Dr
T Senthil Dr
Y Jeyasheela Dr
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/50—Network services
    • H04L67/60—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
    • H04L67/61—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources taking into account QoS or priority requirements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5061—Partitioning or combining of resources
    • G06F9/5077—Logical partitioning of resources; Management or configuration of virtualized resources
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/70—Services for machine-to-machine communication [M2M] or machine type communication [MTC]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Software Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)

Abstract

LOW DELAY COMMUNICATION BETWEEN CYBER PHYSICAL SYSTEMS OF IOT APPLICATIONS USING FOG NODES Abstract The cyber-physical system (CPS) in Cloud platforms have developed as a progressive and secure approach to promoting the collaboration of Internet of Things (IoT) systems. The CPS assimilates, investigates, and expresses analyzed relevant data between Internet of Things networks. With vastly increased communication challenges, centralized and cost-effective networking facilities and the optimal usage of optical facilities are intended to build advanced technologies. Fog computing is the fundamental framework for the deployment of a cyber-physical system (CPS) applications that entail ultra-low latency. This proposal promotes efficient communication among cyber-physical systems of IoT applications using Fog computing to reduce the latency. The Fog-RAN (F-RAN) with persistence and edge computing facilities assures compatibility and interoperability with minimal cost. F RAN used along with SDN and NFV, which is deployed to accommodate empirically centralized supervision strategy and efficient distribution and allocation of resources. Emerging solutions currently encounter a wide variety of obstacles, such as low - latency, maximum bandwidth, and reduced energy usage to endorse applications. 1| P a g e LOW DELAY COMMUNICATION BETWEEN CYBER PHYSICAL SYSTEMS OF IOT APPLICATIONS USING FOG NODES Diagram DATA CENTERS tasknn-PS based fog nodes -A Fig 1: Dataflow diagram 1| P a g e

Description

LOW DELAY COMMUNICATION BETWEEN CYBER PHYSICAL SYSTEMS OF IOT APPLICATIONS USING FOG NODES
Diagram
DATA CENTERS
tasknn-PS based
fog nodes
-A
Fig 1: Dataflow diagram
1| P a g e
LOW DELAY COMMUNICATION BETWEEN CYBER PHYSICAL SYSTEMS OF IOT APPLICATIONS USING FOG NODES
Description
Field of Invention:
Wireless sensor entities and actuators associated with the Internet of Things (IoT) are essential to the development of sophisticated cyber-physical systems (CPSs). This invention helps to reduce the latency of communication among IoT devices using fog computing. The emerging framework outlines technical challenges, including a massive desire for elevated robustness and reduced latency in real-time deployment by using optical infrastructure as edge devices combined with software-defined networking in the 5 G technologies. A novel Virtual Fog node is projected to develop virtual space nearby IoT systems by using F-RAN, thus producing an ultra-low latency, reducing power utilization.
Background and prior art of the invention:
Ku et al. outlined the updated technologies and technical concerns in the hybrid fog-cloud framework to remain enforced in the 5 G wireless networks. Also, the convergence of the analytical and interaction facilities to be employed in the 5 G network was achieved by promoting the validation and emulation of the GPP approach. Consequently, the GPP framework was integrated with the F-RAN infrastructure for incentivizing low-latency processes in the 5 G technology.
F. Arriba-Perez et al. described the IoT-enabled healthcare tracking devices, which are generally offered health technologies like early detection and prevention for patients by integrating data acquisition from the patient, data processing, and predictive analytics. The framework is diverse in evolution, varying from simple to detailed remote monitoring. For simplistic IoT-based surveillance systems, only data acquiring, transmission, and analysis for patients is carried out, but no observations or interprets of the patient's health status are documented. oT-based surveillance
11 P a g e systems are, therefore, inadequate for pervasive tracking, quantitative, and decision-making. Even these, essential IoT-based sensor networks are inadequate for widespread observing, adding extensive analytical and decision-making.
Yang has suggested a smart framework that uses the decentralized and core detectable flow process to determine the critical essential detectable activities in the CPS along with fog computing. The efficiency of the conceptual method was evidenced by the deployment of a sophisticated specialized task and yields improved research findings.
Z. Tao et al. formulated the LTE technology that has been enhanced to assist CPS access for computer-restricted systems and digital vehicles in recent decades. All over the current time, fog computing achieves popularity as an efficient strategy for personalized and approaching-edge computing, which enables real-world privacy processing. Fog nodes synchronize between themselves to unload computation than less skilled or overwhelmed components, eradicate evaluation impediments, certify the reliability of equipment, and promote self-configuration for prolonged network security.
Donovan et al. described an automotive CPS with a developing fog computing model. It facilitated manufacturing components and mechanisms to be firmly attached to hold out self-configuring processes. The conceptual model has been examined with sophisticated machine learning applications for data analytics and computation in the online world.
Peng et al. discussed a sophisticated prototype system premised on the F-RAN interaction strategy to ensure sufficient power density and high performance in the 5th Generation wireless networks. This architecture described vulnerable problems regarding of edge caching, SDN, and virtualization of networking devices.
A. Botta et al. explained cloud-based IoT technology that provides reasonable quality and effectiveness to enable non-safety and delay-sensitive applications. Examples of these services are a range of commercial and smart city applications. Even so, remote health monitoring systems entail a relatively high level of consistency, affordability, and compactness. Moreover, the simplistic adaptation of the traditional client-server model used on the internet and included "information" is not appropriate for a broad range of IoT applications, which is the objective of this investigation.
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Sood and Mahajan have introduced a technique to identify, recognize, and control mosquito-borne disorders, highly contagious cases. The prototype system combined IoT devices, cloud infrastructure, and cloud management with the CPS indoctrination, evaluation, and exchanging of healthcare-relevant data between individuals and healthcare professionals.
Hong, K et al. presented the IoT applications with high-level programming model over cloud and fog. Researches in the computation area have proposed to enable dispersed fog nodes to perform parts of numerical computations. The activities are associated with the tool which is providing by neighboring fog nodes.
Zeng et al. have constructed a cyber-physical fog system that has been successful energy effective property configuration in load handling. They posited a heuristic strategy to reduce mixed-integer linear computing and demonstrated to be an NP-hard renewable energy issue. The outcome of the simulation studies demonstrated the elevated power utilization of the cyber-physical system.
Yang et al. recommended an SDN-based architecture that endorsed not merely cloud-fog multi operation but also optimized excellence of experience and efficient use of computing properties. A scenario that is investigating the effectiveness and implications of the developed system has been afforded prospective evaluation challenges for 5 G cellular networks.
Summary of the invention:
The cost-efficient technology for high-bandwidth networking in the cloud and fog computing environment is Optical transmission. The passive optical network utilizes optical line terminals and optical network components to provide cloud-based services accurately. Incorporating this innovation with modern communications technology, the Internet of Things, cloud and fog computing, 5th Generation wireless communication and emerging intelligent systems have immense expertise to facilitate the innovative applications that ensure a massive quantity of information to be managed remotely and assertions are functioning with minimal delay and internet congestion.
This innovative proposal promotes the advanced technologies for low delay communication among cyber-physical systems of IoT applications using fog and cloud computing platforms.
31Page
CPS facilitates the incorporation of digital components, such as computers, sensors, and control units, and networking equipment, into physical components by attaching them to the network and with each other.
CPS has exhibited enormous accomplishments in several aspects such as telecommunications, medical care, software development, electronic components, transportation, defense, and so on. It has also persuaded numerous inventive and quickest-growing initiatives in the field of cloud and fog computing applications. CPS demands an innovative, safe, high-quality centralized, and ultra dense fog computing technology in the diverse network to strengthen its importance on the wireless connection in the upcoming 5 G phase.
The innovative idea is the edge-assisted Cyber-Physical System, which is recommended for the Internet of Things applications in the 5th Generation wireless network. This technology employs the Software Definition Network (SDN) with ONV and optical fog layer to develop CPS-based applications.
Physical devices like sensors, electronic types of equipment, and actuators are interconnected via the internet to the gateway for various applications. The cyber-physical system contains a physical phase which is operated by an application platform to perform complex processes in real-time. It acquires all information from IoT devices and progresses to cyberspace for subsequent analysis and artificial intelligence process.
The optical fog layer exploits the power of the optical network for real-time transmission and serves as a link between the physical space and the cloud layer. Computing resources across the optical fog layer are handled by building the OpticalFog node using the SDN and Optical Network Virtualization (ONV). A task placement algorithm called the Binpack algorithm is proposed for CPS-based tasks that effectively utilize resources for CPS and non-CPS tasks.
The Free available resources are used to build a virtualization layer that incorporates the widely affordable services of the optical network services on the optical fog layer. Although network switches and routers have scarce resources, only optical elements such as ONUs and OLTs are employed for implementing free available resources. In the present network scenario, the virtual components are used for specific computation, caching, and interoperability.
41Page
The radio access network (F-RAN) interconnects various fog nodes in the optical fog layer, which contains SDN and ONV. ONV converts the free available resources into the cloud services. Binpack task placement strategy that places the process based on the least available memory. In the Binpack method, the new process demanded is a non-CPS task; it may be explicitly assigned to the cloud. This innovative idea reduces the low latency communication among cyber-physical systems, minimizes energy utilization, and enhances the bandwidth.
The objective of the invention:
The main objective is to promote the ultra-low- level delay among communication between IoT devices using fog computing. The objectives are
* To promote sensors and actuators for real-time evaluation monitoring of physical systems. * To guarantee Quality of Service and quality of experience of end-users for varied real-time IoT-based applications by using optical Fog-layer. * To build a fog network, including the collection of distinct and operational aggregated nodes and are configured in a cooperative framework to mitigate interaction and computation latency in the network system.
Statement of the invention:
Most experts and capitalists have initiated proposals on stepping stones for the next evolution of cellular and communication technologies. It affords the forum for technologies focused on cyber physical systems (CPS), augmented reality, remote driving, emergency prevention, intelligent IoT systems. The physical systems for various applications are interconnected, and software applications are used for further processing and data analysis. The end-user performs their processing, analysis, and various services in each fog node. The fog nodes are connected to the virtual layer, and tasks can be categorized as non-CPS, and the CPS task and cyber-physical tasks are processed by using SDN and ONV. The optical line terminals are used for a passive optical network that is connected to the cloud server. The free available resources are processed by centric SDN that reduces the communication delay between cyber-physical systems and increases the bandwidth.
1P a g e
Brief description of the Drawings:
Fig 1: Data flow Diagram
Fig 2: virtual optical fog layer
A detailed description of the drawing:
Figure 1 illustrates the dataflow diagram of an innovative proposed system using fog computing. The bottom layer represents the physical devices such as sensors, processing elements, and actuators. The physical layer information is processed in end devices called edge computing devices. The optical fog layer comprises software definition network (SDN) and optical network virtualization (ONV) for processing free available resources. The SDN processes the CPS from the optimal path, and ONU converts this task into cloud services. The non-CPS task is assigned directly to the cloud server. The fog-RAN is proposed to communicate the different fog nodes. Thus the proposal reduces the communication delay among IoT applications.
Figure 2 explains the virtual optical fog layer, which comprises optical network units and optical network terminals and a passive optical network.
61Page

Claims (7)

LOW DELAY COMMUNICATION BETWEEN CYBER PHYSICAL SYSTEMS OF IOT APPLICATIONS USING FOG NODES Claims We claim that,
1. Sensors are used for sensing the information from various applications, and actuators are used for controlling purposes.
2. Gateways which act between the physical devices and fog layer for interconnection.
3. Fog nodes are deployed as edge computing entities that encourage fog utilities to be embedded and encompass at least one or more physical devices with computing and detecting functionality.
4. An electronic device with a touch screen such as a smartphone, laptop, tablet, etc. with high-speed internet or Wi-Fi.
5. Virtual fog layer which comprises the software network definition and Optical network virtualization for implementing the optical fog nodes to find optimal paths for further processing.
6. ECS Task placement algorithm like Binpack for placing the task based on the free available resources.
7. Cloud server such as IBM, AWS to store the computed data in an encrypted format.
1| P a g e
LOW DELAY COMMUNICATION BETWEEN CYBER PHYSICAL 21 Jul 2020
SYSTEMS OF IOT APPLICATIONS USING FOG NODES
Diagram 2020101430
Fig 1: Dataflow diagram
1|Page
Fig 2: virtual optical fog layer
2|Page
AU2020101430A 2020-07-21 2020-07-21 Low delay communication between cyber physical systems of iot applications using fog nodes Ceased AU2020101430A4 (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112416603A (en) * 2020-12-09 2021-02-26 北方工业大学 Combined optimization system and method based on fog calculation
CN113098891A (en) * 2021-04-19 2021-07-09 广东技术师范大学 Method and system for network transmission control based on medical big data
CN117544513A (en) * 2024-01-02 2024-02-09 杭州海康威视数字技术股份有限公司 Novel Internet of things customized service providing method and device based on fog resources

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112416603A (en) * 2020-12-09 2021-02-26 北方工业大学 Combined optimization system and method based on fog calculation
CN112416603B (en) * 2020-12-09 2023-04-07 北方工业大学 Combined optimization system and method based on fog calculation
CN113098891A (en) * 2021-04-19 2021-07-09 广东技术师范大学 Method and system for network transmission control based on medical big data
CN113098891B (en) * 2021-04-19 2023-04-07 广东技术师范大学 Method and system for network transmission control based on medical big data
CN117544513A (en) * 2024-01-02 2024-02-09 杭州海康威视数字技术股份有限公司 Novel Internet of things customized service providing method and device based on fog resources
CN117544513B (en) * 2024-01-02 2024-04-02 杭州海康威视数字技术股份有限公司 Novel Internet of things customized service providing method and device based on fog resources

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