WO2022045875A1

WO2022045875A1 - System and method for qualitative internet of things communications

Info

Publication number: WO2022045875A1
Application number: PCT/MY2020/050174
Authority: WO
Inventors: Hafizal Mohamad; Nuzli MOHAMAD ANAS
Original assignee: Mimos Berhad
Priority date: 2020-08-28
Filing date: 2020-11-27
Publication date: 2022-03-03

Abstract

The present invention provides a method for providing qualitative communication over Internet of Things (IoT) network having sensor nodes. The method comprises initiating (202) formation of communication links among all sensor nodes of the IoT network; identifying (204) packet types of packets from the sensor nodes; scanning (206) available channels and determining required bandwidth with a resource manager; employing (208) a network manager to determine channel quality indicator, CQI, received signal strength indicator, RSSI, and signal-to-noise ratio, SNR based on the packets; measuring (212) packets detection, node congestion, link and noise level; identifying (214) packets status classification and managing the current status of the packets by packet sorter; checking (216) if channel allocation and packet assignment are completed; and transmitting (218) IoT data assessed through the network manager and the qualitative module. A system therefore is also provided.

Description

SYSTEM AND METHOD FOR QUALITATIVE INTERNET OF THINGS COMMUNICATIONS

Field of the Invention

[0001 ] The present invention relates to internet of things, loT. More specifically, the present invention relates to a system and method for providing quality of loT communication.

Background

[0002] The booming popularity of electronic communication devices and the connectivity therefor have made Internet of Thing (loT) more useable in many applications. loT provides the capability of enhancing human live and improves business productivity by employing a number of smart sensors/devices to collect multiple data over a good period of time. Currently the number of connected devices is way more than the number of human populations on earth which make the date collected through the loT more meaningful.

[0003] US patent application no. US2007/0189235A1 entitled Quality of Service Based Resource Determination and Allocation Apparatus and Procedure in HSPA Evolution and LTE System discloses a process communication data in a hierarchy of processing including a physical layer, a medium access control layer and higher layers. It uses channel quality indicator only as determining factors to match QoS requirements.

[0004] US patent no. US10448409B2 discloses a system and method for allocating channel within a given band in a wireless communication system for internet of things. It also provides a method for allocating a channel based on the interference between system and a channel in a wireless system. It receives the channel allocation information and transmits a data signal through at least one channel. The system is provided with a channel quality indicator which may include a signal to noise ratio (SNR), a carrier to interference noise ratio (CINR) and a signal to noise ratio (SNR).

[0005] US patent no. US10491575B2 discloses a secure dynamic communication network and the internet of things devices to transfer packets of digital data in the wireless networks through appropriate channels. It also discloses the qualitative data transfer in the network. The data transfer is based on the data in the data field (level of criticality) and other limited parameters.

[0006] Internet of Things (loT) device and system consists of multiple data type, supports various applications, transports over different protocols, connectivity methods, etc. The multitude of different configurations, protocols and methods, however, lead to great challenge in managing the loT data packets properly.

[0007] It is therefore, there is a need to provide system and method to enable qualitative loT communications for new applications and services for improving reliability of loT data packets.

[0008] There is also a need for a system and method applicable for transmission between at least one sensor node and gateway for multiple type of data communications. The network needs to be configured to enable efficient transmission in response to different type of traffic, data exchange between sensor nodes and gateway, whereby the gateway and base-station are the aggregation points for the sensor nodes. Summary

[0009] In one aspect of the present invention, there is provided a method for providing qualitative communication over Internet of Things (loT) network having sensor nodes. The method comprises initiating formation of communication links among all sensor nodes of the loT network; identifying packet types of packets from the sensor nodes; scanning available channels and determining required bandwidth with a resource manager; employing a network manager to determine CQI, RSSI and SNR based on the received packets; measuring packets detection, node congestion, link and noise level; identifying packets status classification and managing the current status of the packets by packet sorter; checking if channel allocation and packet assignment are completed; transmitting loT data assessed through the network manager and the qualitative module.

[0010] In one embodiment, the method is carried out at network layer.

[0011] In another embodiment, the method further comprises allocating channel and assigning packet based on a level of significant of the packet.

[0012] In yet another embodiment, the packets are assigned with high level of significance are allocated to high quality channel.

[0013] In a further embodiment, wherein quality of the channel of the network is determined based on channel quality indicator, CQI, received signal strength indicator, RSSI, and signal-to-noise ratio, SNR.

[0014] In another aspect of the present invention, there is provided a system for providing qualitative communication over Internet of Things, loT, network. The system comprises a network manager adapted to obtain and extract network related parameter of the packets, that include channel quality indicator, CQI, received signal strength indicator, RSSI, and signal-to-noise ratio, SNR; a qualitative module adapted to identify types of the packets for assigning appropriate channel.

[0015] In one embodiment, the network manager further comprises a significant packet detector for determining significant level of the packets; a congestion node evaluator assesses activity level and capacity of gateways of the network; and a link noise and interference level detector the link noise the interference level detector is adapted to determine and manage multiple link status and evaluate interference between various network elements.

[0016] In another embodiment, the qualitative module further comprises a packet status classification and sorter for classifying and sorting the packets; and a channel allocation and packet assignment for assigning the packets to appropriate channel.

[0017] In yet another embodiment, the significant level comprises a low, medium and high levels. A packet with significant level of high level can be assigned to high quality channel.

Brief Description of the Drawings

[0018] This invention will be described by way of non-limiting embodiments of the present invention, with reference to the accompanying drawings, in which:

[0019] FIG. 1 illustrates a block diagram of the system according to an embodiment of the present invention; and [0020] FIG. 2 illustrates a flow diagram for managing qualitative Internet of

Things communication in wireless network in accordance with an embodiment of the present invention.

Detailed Description

[0021] In line with the above summary, the following description of a number of specific and alternative embodiments are provided to understand the inventive features of the present invention. It shall be apparent to one skilled in the art, however that this invention may be practiced without such specific details. Some of the details may not be described at length so as not to obscure the invention. For ease of reference, common reference numerals will be used throughout the figures when referring to the same or similar features common to the figures.

[0022] Embodiments of the present invention include various steps, which will be described below. The steps may be performed by hardware components or may be embodied in machine-executable instructions, which may be used to cause a general- purpose or special-purpose processor programmed with the instructions to perform steps. Alternatively, steps may be performed by a combination of hardware, software, firmware, and/or by human operators.

[0023] Various methods described herein may be practiced by combining one or more machine -readable storage media containing the code according to the present invention with appropriate standard computer hardware to execute the code contained therein. An apparatus for practicing various embodiments of the present invention may involve one or more computers (or one or more processors within a single computer) and storage systems containing or having network access to computer program(s) coded in accordance with various methods described herein, and the method steps of the invention could be accomplished by modules, routines, subroutines, or subparts of a computer program product. [0024] The present invention is implementable on both local and remote computing device. A local computer include a personal computer or a handheld mobile device. A remote computer may be a remote server or cloud computing device, which includes virtual machine, which generally refers to a self-contained operating environment that behaves as if it is a separate computer even though is part of a separate computer or may be virtualized using resources form multiple computers.

[0025] In one embodiment, software applications can be developed based on available platforms or platform products to build new functionality as an extension to the existing functionality. For example, a platform can be provided by a third party, e.g. a cloud computing platform that allows provisioning of the software application in a cloud environment.

[0026] Cloud computing is an internet-based computing that provides shared processing of resources and data to computers and other devices based on demand. The cloud computing provides access to the resources like networks, servers, storage, applications and services. These resources can be rapidly provisioned and released with minimal management effort in the cloud computing.

[0027] In this application, Internet of Things (loT) and the devices therefore may refer to any system and device (e.g., an appliance, a sensor, etc.) that has an addressable interface (e.g., an Internet protocol (IP) address, a Bluetooth identifier (ID), a near-field communication (NFC) ID, etc.) and can transmit information to one or more other devices over a wired or wireless connection. The loT device may have a passive communication interface, such as a quick response (QR) code, a radio-frequency identification (RFID) tag, an NFC tag, or the like, or an active communication interface, such as a modem, a transceiver, a transmitter-receiver, or the like. The loT device can have a particular set of attributes (e.g., a device state or status, such as whether the loT device is on or off, open or closed, idle or active, available for task execution or busy, and so on, a cooling or heating function, an environmental monitoring or recording function, a light-emitting function, a sound-emitting function, etc.) that can be embedded in and/or controlled/monitored by a computing unit configured for connection to an loT network. The loT network may be comprised of a combination of “legacy” Internet- accessible devices (e.g., laptop or desktop computers, cell phones, etc.) in addition to devices that do not typically have Internet-connectivity (e.g., dishwashers, etc.). The loT network includes a local ad-hoc network or the Internet.

[0028] Through the present invention, the reliability of loT data packets can be improved. Embodiments of the present invention enable qualitative Internet of Things communications by exploiting statistical behaviour of loT data packet. The system provides the reliable loT packet data communication between sensor nodes and non- stationary gateway.

[0029] FIG. 1 illustrates a block diagram of the system according to an embodiment of the present invention. The present invention is deployed at the network layer of the loT to assess and evaluate parameters 105 of packages from the sensors and devices of the physical (PHY) layer 180, which include modulation, coding, and space-time block code (STBC), and etc. The parameters 105 include channel quality indicator (CQI), received signal strength indicator (RSSI) and signal-to-noise ratio (SNR) of the packages. The CQI indicates a suitable downlink transmission data rate, i.e. a Modulation and Coding Scheme (MCS) value. The RSSI indicates a quality of received signal strength at the receiver side. The SNR indicate a ratio between the level of the signal to the background noise level. These measures are apparent to one skilled in the art, and no further details will be provided herein. The system comprises a network manager 110 and a qualitative module 150. The network manager 110 is adapted to obtain and extract network related parameter of the packets. The qualitative module 150 on the other hand is adapted to identify types of packets and assigning the packet to an appropriate channel.

[0030] The network manager 110 comprises a significant packet detector 112, a congestion node evaluator 114, a link noise and interference level detector 116, and database 118. The network manager 110 operates at a network level/layer to perform several functions.

[0031] Operationally, the CQI is processed by the significant packet detector 112 to determine the respective packet’s significant level. The significant packet detector 112 examines a level of criticality or significance of the packet and evaluate the trending values of the sensors. The number of levels of significance can be adapted according to the application. In one embodiment, it can be classified with three levels: low, medium and high. In another embodiment, the resolution of significant level can be increased to ten or any number, depending on the deployment requirements.

[0032] For example, a flood monitoring system with an early warning system may adapt a three levels of significance whereby a green level indicates normal, a yellow level triggers the early warning, and a red indicates flood has occurred. For instance, temperature values that exceed certain threshold can be classified as significant packet.

[0033] For the purposes of the present invention, the packet refers to a network packet that is a formatted unit of data transmitted through network. The packet types may include, but not limited to, email, audio file, video, and/or all other sensor note format files.

[0034] The RSSI is processed by the congestion node evaluator 114 to fast assessment on level of activity for gateways in the network. The level of activity includes the data traffic across the network and the number of connections between the gateway and sensor nodes. Capacity of the gateway is also evaluated. In one embodiment, the capacity of a gateway is not fixed, i.e. dynamic, according to the deployment needs, such as coverage area, nature of geographical area, and so on. For example, a flood monitoring system over a riverbank in cities are distinct from that deployment in rural areas. Hence, different gateway capacity.

[0035] The SNR is processed by the link noise and interference level detector 116 to determine and manage multiple link status and evaluate interference between various network elements. The link noise and interference level detector 116 is adapted to handle multiple frequencies utilized by the sensor nodes that include those that operates in unlicensed band.

[0036] The qualitative module 150 comprises a packet status classifier and sorter 152, and a channel allocation and packet assignor 154. The packet status classifier and sorter 152 manages the current status of the packet and the channel allocation and packet assignor 154 provides the right packet to the suitable transmission channel.

[0037] A database 118 is provided for storing information relating the gateway and the sensor nodes of the network, for facilitating the three modules 112, 114, 116 of the network manager 110. The stored information includes the sensed information, such as RSSI and SNR, and the packet related information, such as packet type, packet status, packet load etc. Furthermore, the database 118 also stored the channel quality information to assist the qualitative module on decision making.

[0038] In one embodiment, the packet status can be categorized by the details included in that message, such as information packet, redirection packet, server error packet, client error packet, client error packet and success packet, etc. These statuses are available in the internet protocol. The packets are then sorted based on the packet types, packet load and other metrics that well suited for the implementation. In one embodiment, packets are sorted according to the significant level of the packet. Priority is given to packet with the high level of criticality to be transmitted to the base station using high quality loT communication medium, in which identified by the Qualitative Module 150.

[0039] In relation to the channel allocation and packet assignment, there are known method that can be deployed therefor among loT data packets. The method typically accounts the bandwidth requirements, node congestions, link and noise level that are suitable to the specific packet type.

[0040] FIG. 2 illustrates a flow diagram for managing qualitative Internet of Things communication in wireless network in accordance with an embodiment of the present invention. The method comprises initiating formation of communication links among all sensor nodes in the network at step 202; identifying different packet types from the sensor nodes at step 204, scanning available channel and the required bandwidth with a resource manager at step 206, employing network manager to determine signal qualities in the network based on data from sensors at step 208, measuring detected packet, node congestion, link and noise level at step 212, identifying a packet status classification and packet sorter manages the current status of the packet at step 214, checking if channel allocation and packet assignment is completed at step 216, if not, the process returns to step 212, and if the channel allocation and packet assignment is completed, transmitting loT data based on network manager and qualitative module parameters at step 218.

[0041] The require bandwidth refers to required data transfer rate of a network connection. It measures how much data need to be sent over a specific connection in a given amount of time.

[0042] Operationally, the network manager 110 initialises the communication links connecting the sensors of the network at the step 202. The qualitative module 150 identifies the packet types from the sensor nodes and classifies the same accordingly at the step 204.

[0043] The qualitative module 150 keep tracks on the network traffic for a good period of time to optimize the loT communication, in which, the data packets are handled accordingly based on their level of significant. Through the qualitative module 150, data packet with high priority level pre-empts the other packets in that instant, thus increase the quality of information disseminated.

[0044] Operationally, when the level of significant of the packets are observed, it facilitates the channel allocation and packet assignor 154 to carry out the channel allocation. As the packets are observed over time, the observed statuses of the packets that are stored on the database 118 can be used to predict the next events. Through the qualitative module 150, the present embodiment provides a learning and decision making mechanism to manage the channel allocation and packet assignment in a qualitative manner. [0045] In the present embodiment, the channel allocation and packet assignment 154 provides a single channel allocation based on CQI of the sensor devices to preserve high quality loT communications.

[0046] Embodiments of the present invention operatively tracking and monitoring the transmitted packets and traffic across the network nodes and gateways to provide qualitative channel allocations and packet assignments over the loT communication. Desirably, the network manager 110 collects the CQI, RSSI and SNR parameters of the data from sensors to identify a good quality of channel to be allocated for the data packet that has high level of significances. The two modules 110 and 150 in the qualitative function chooses data packet that needs to be allocated to the high quality channel, whilst the less significant packet may use other normal channel allocation. Thus, significant data packet from sensor can be transmitted at instant.

[0047] While specific embodiments have been described and illustrated, it is understood that many changes, modifications, variations and combinations thereof could be made to the present invention without departing from the scope of the invention.

Claims

1. A method for providing qualitative communication over Internet of Things, loT network having sensor nodes, characterized in that the method comprising: initiating (202) formation of communication links among all sensor nodes of the loT network; identifying (204) packet types of packets from the sensor nodes; scanning (206) available channels and determining required bandwidth with a resource manager; employing (208) a network manager to determine channel quality indicator, CQI, received signal strength indicator, RSSI, and signal-to-noise ratio, SNR, (105) based on the packets; measuring (212) packets detection, node congestion, link and noise level; identifying (214) packets status classification and managing a current status of the packets by packet sorter; checking (216) if channel allocation and packet assignment are completed; transmitting (218) loT data assessed through the network manager (110) and a qualitative module (150).

2. The method according to claim 1, wherein the method is carried out at network layer.

3. The method according to claim 1, further comprising allocating channel and assigning packet based on a level of significant of the packet.

4. The method according to claim 3, wherein the packets assigned with high level of significance are allocated to high quality channel.

5. The method according to claim 4, wherein the quality of the channel of the network is determined based on channel quality indicator, CQI, received signal strength indicator , RSSI, and signal-to-noise ratio, SNR.

6. A system for providing qualitative communication over Internet of Things, loT, network, characterized in that the system comprising: a network manager (110) adapted to obtain and extract network related parameter of packets, that include channel quality indicator, CQI, received signal strength indicator, RSSI, and signal-to-noise ratio, SNR (105); and a qualitative module (150) adapted to identify types of the packets for assigning appropriate channel.

7. The system according to claim 6, wherein the network manager (110) further comprising: a significant packet detector (112) for determining significant level of the packets; a congestion node evaluator (114) to assess activity level and capacity of gateways of the network; and a link noise and interference level detector (116) is adapted to determine and manage multiple link status and evaluate interference between various network elements.

8. The system according to claim 6, wherein the qualitative module (150) further comprising: a packet status classification and sorter (152) for classifying and sorting the packets; and a channel allocation and packet assignment (154) for assigning the packets to appropriate channel. 16

9. The system according to claim 7, wherein the significant level comprises a low, medium and high levels.

10. The system according to claim 9, wherein a packet with significant level of high level is assigned to high quality channel.