KR20110106764A - Ubiquitous remote resource control method using distributed computing scheme and ubiquitous system - Google Patents

Abstract

Disclosed are a ubiquitous remote resource control method and a ubiquitous system using a distributed computation technique. The ubiquitous system converts individual sensor signals into common sensor signals irrelevant to the sensor characteristics, infers current situation information of the ubiquitous environment by analyzing common sensor signals, and individual control signals for controlling remote resources according to the inferred situation information. It includes a control (management / control portion) for generating, the remote resources are controlled based on the individual control signal. The control unit uses a common device interface module that receives individual sensor signals and converts them into a common sensor signal, a context-aware calculation module that generates context information using the common sensor signal, and a distributed computing platform that adopts a distributed computing technique. A ubiquitous distributed core operation module for determining a service to be performed on remote resources based on the generated service, generating individual control signals according to the determined service, and delivering the remote control resources to the remote resources, and common sensor signals and situation information, which are performed by the user terminal. It converts to be compatible with each application, and includes a common application interface module for providing the converted result to the user terminal. According to the present invention, the infrastructure of the ubiquitous city can be expanded at low cost by using the ubiquitous middleware that can operate in common regardless of the number of sensors and remote facilities.

Description

Ubiquitous remote resource control method using distributed computing scheme and ubiquitous system}

The present invention is part of the national research and development project, the project unique number: "10561", the research project name: "Seoul City industry-university cooperation project (2005 technology-based construction project)", the research title: "Intelligent for smart (ubiquitous) city City information convergence system development ".

The present invention is for a ubiquitous city (u-city), using an intelligent u-city middleware system (u-city) and u-city portal (u-city portal), U-city infrastructure It is related to the U-City system that can build the three-tier structure, manage and operate intelligently, and provide appropriate intelligent services according to the situation information.

U-City (Ubiquitous City) "A city that provides ubiquitous urban services anytime and anywhere through the ubiquitous urban infrastructure, which is built using ubiquitous urban technology to improve the competitiveness and quality of life of the city. From Article 1, Chapter 2 of the Act on the Construction, etc., ie u-city is a city that is created, managed and utilized through mediation between the telecommunications industry and the construction sector, urban planning and management engineering. U-City is usually controlled and managed by central management centers, has a platform, manages U-City through the latest U-City communication infrastructure, and manages U-City's various services. To provide.

Referring to the following paper [1], ubiquitous computing is "a post-desktop model of human-computer interaction, in which information processing is fully integrated into everyday objects and activities." The next generation computer information and communication environment that allows anyone to use the service anytime, anywhere, any-device, is called ubiquitous environment. Middleware has been developed to support the ubiquitous computing environment. They are designed to conveniently collect and provide functions for efficient use of the ubiquitous computing environment. Some examples include HAVi, Jini, UPnP, LonWork, RCSM, Gaia, Aura, SOCAM, CAMUS, Accord Gaia, SMART, CMQ.

U-City uses ubiquitous technologies as a foundation technology that provides various integrated services for U-City. These ubiquitous technologies are applied in various forms to manage urban elements of U-City and provide integrated services. This is true of online banking as an example, although online banking uses the basic technologies of a computer, but in its application can be attached to various additional technologies to provide magical online banking services. City uses ubiquitous basic technologies, but it is reborn as a completely new technology by attaching various additional technologies to provide various U-City integrated services. In addition, U-City must manage all functions and elements of the city fusion and provide integrated services incorporating city engineering technology. Therefore, ubiquitous middleware and methods and concepts cannot be applied. And ubiquitous cities are generally huge. As the scale grows, the constraints on providing integrated services for real-time u-city become increasingly severe. Thus, none of the prior art regarding ubiquitous middleware for relatively small ubiquitous equipment is suitable as middleware for large ubiquitous. In order to manage the whole city from the point of view of integration and convergence, and to provide convergence service, comprehensive judgment must be made using the information of the whole city while looking at the whole city. Necessary, not yet presented. In addition, since the characteristics of each city are different, a common methodology, apparatus, and system for managing and managing infrastructures having different characteristics are required to construct and operate a U-City. Furthermore, when connecting and operating these cities, there is a need for a common methodology, apparatus, and system that encompasses infrastructures having different characteristics in different cities, that is, they operate in common regardless of urban infrastructure characteristics. This patent proposes an intelligent middleware methodology, apparatus and system for u-City as a solution for this.

The following documents are incorporated herein by reference in their entirety. [1] B. Hayes, "Cloud Computing", Communications of The ACM, July 2008, pp. 9-11. [2] I. Foster, Y. Zhao, I. Raicu, and S. Lu. "Cloud Computing and Grid Computing 360-Degree Compared". Grid Computing Environment Workshop (GCE'08), 2008. [3] R. Grossman. "The Case for Cloud Computing". ITPro, 2009, pp. 23-27. [4] G. DeCandia, D. Hastorun, M. Jampani, G. Kakulapati, A. Lakshman, A. Pilchin, S. Sivasubramanian, P. Vosshall, and W. Vogels. "Dynamo: Amazons highly available keyvalue store". In SOSP, 2007. [5] Amazon Elastic Compute Cloud (Amazon EC2) .http: //aws.amazon.com/ec2. [6] Google app engine web site, http://code.google.com/intl/appengine/. [7] H.S. Jung, C. S. Jeong, Y. W. Lee, and P. D. Hong, "An Intelligent Ubiquitous Middleware for U-City: SmartUM" JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 25, 2009, pp. 375-388. [8] H.S. Jung, J. K. Baek, C. S. Jeong, Y. W. Lee, and P. D. Hong, "Unified Ubiquitous Middleware for U-City", 2007 IEEE International Conference on Convergence Information Technology (2007 ICCIT), 2007. [9] H. Han, H. Jung, H. Y. Yeom, H. S. Kweon, and J. Lee "HVEM Grid: Experiences in Constructing an Electron Microscopy Grid", APWeb 2006, 2006. [10] NCMIR, http://www-ncmir.ucsd.edu/. [11] UHVEM, http://www.uhvem.osaka-u.ac.jp/. [12] NEES Inc, http://www.nees.org. [13] KOCED, http://www.koced.net/. [14] M. Weiser, "The Computer for the Twenty-First Century", Scientific American, 1991, pp. 94-101. [15] A. R. C. da Rocha, M. Endler, and T. S. de Siqueira. "Middleware for Ubiquitous Context-Awareness", MPAC, 2008. [16] C. Liao, Q. Liu, D. Kimber, P. Chiu, J. Foote, and L. Wilcox, "Shared interactive video for teleconferencing". MULTIMEDIA: Proceedings of the eleventh ACM international conference on Multimedia, 2003. [17] The globus toolkit, http://www.globus.org/tookit/ [18] I. Foster. "Globus Toolkit Version 4: Software for Service-Oriented Systems.". IFIP Int. Conf. on Network and Parallel Computing, Springer-Verlag LNCS 3779, 2006, pp 2-13. [19] Hanover, NH, "Ring Buffered Network Bus Technology Framework for Knowledge-Based System-of-Systems", RBNB DataTurbine Documents, Creare Inc. (unpublished), 2001. [20] Narada Broker, http://www.naradabrokering.org/. [21] National instruments LabVIEW, http://www.ni.com.

An object of the present invention is to provide a ubiquitous middleware for intelligently managing a large amount of remote facilities at low cost.

In addition, the present invention provides a method for providing a ubiquitous service that can expand the infrastructure of the ubiquitous city at low cost by using ubiquitous middleware that can operate in common regardless of the number of sensors and remote facilities by adopting a distributed computing technique It is.

One aspect of the present invention for achieving the above object is a ubiquitous remote resource based on individual sensor signals from a plurality of sensors operating in a ubiquitous environment and having individual sensor characteristics. It relates to a method for controlling them. In a ubiquitous remote resource control method according to an aspect of the present invention, a sensor signal receiving step of receiving individual sensor signals, converting the individual sensor signals into a common sensor signal irrelevant to sensor characteristics, and analyzing the common sensor signals A management / control step of inferring current context information of the ubiquitous environment, generating individual control signals for controlling remote resources according to the inferred context information, and remote resources based on the individual control signals. And a controlling step of controlling. In addition, the method according to the present invention provides a common sensor signal or context information to the user terminal, and further comprises a presentation step of receiving a user command from the user. In particular, the control step includes a common device interface step of receiving and converting individual sensor signals into a common sensor signal, a context-aware computing step of generating context information using the common sensor signal, and distribution It uses Distributed Computing Platform that adopts Distributed Computing Technique, determines the service to be performed on remote resources based on the situation information, and generates individual control signals according to the determined service Ubiquitous distributed core computing (Ubiquitous Distributed Core Computing) step to deliver resources, and common application interface to convert the common sensor signal and situation information to be compatible with each application running in the user terminal, and provide the converted result to the user terminal Including the Common Application Interface step . Further, the context aware operation step combines the common sensor signals and transforms the combined common sensor signal into a predefined context instance, and receives the context instance, and uses the predefined rules to A situation analysis step of inferring situation information by analyzing the received situation instance is included. In particular, the ubiquitous distributed core operation step may include a service discovery step of searching for a service to be performed from a service repository that stores services that can be performed based on context information, or receiving a service from a user to perform the service. Therefore, selecting the remote resources to be controlled, generating a common control signal (common control signal) for the selected remote resources, and converting the common control signal into individual control signals in consideration of the individual resource characteristics of the remote resources, and converts Generating an individual control signal to the remote resources. Preferably, the step of generating individual control signals comprises receiving a common control signal for selected remote resources, obtaining information about the properties of the selected remote resources from a resource repository, and the properties of the remote resources. And converting the common control signal into a separate control signal for each of the remote resources based on the information.

Another aspect of the present invention for achieving the above object is, a ubiquitous operating in a ubiquitous environment, comprising a plurality of sensors having individual sensor characteristics and generating individual sensor signals and a plurality of ubiquitous remote resources having individual resource characteristics It is about the system. The ubiquitous system according to the present invention converts individual sensor signals into common sensor signals irrelevant to sensor characteristics, infers current situation information of the ubiquitous environment by analyzing common sensor signals, and controls remote resources according to the inferred situation information. A management / control portion for generating a separate control signal for the remote resources, the remote resources being controlled based on the individual control signal. Furthermore, the ubiquitous system according to the present invention provides a common sensor signal or situation information to a user terminal, and further includes a presentation portion for receiving a user command from the user. In particular, the control unit uses a common device interface module for receiving and converting individual sensor signals into a common sensor signal, a context-aware calculation module for generating context information using the common sensor signal, and a distributed computing platform employing a distributed calculation technique. A ubiquitous distributed core operation module that determines a service to perform on remote resources based on context information, generates individual control signals according to the determined service, and delivers them to the remote resources, and common sensor signals and context information at a user terminal. It converts to be compatible with each application to be performed, and includes a common application interface module for providing the converted result to the user terminal. Furthermore, the context aware arithmetic module receives a context converter for combining a common sensor signal and converting the combined common sensor signal into a predefined situation instance, and a context instance, and using the predefined rules. It includes a context analyzer to infer the context information by analyzing the received context instance. In addition, the ubiquitous distributed core operation module may search for a service to be performed from a service repository that stores services that can be performed based on contextual information, or a service discovery unit that receives a service to be performed from a user, and may be controlled according to a service. A resource manager for selecting remote resources, generating a common control signal for the selected remote resources, and converting the common control signal into an individual control signal in consideration of individual resource characteristics of the remote resources, and converting the converted individual control It includes a resource agent that delivers signals to remote resources. Preferably, the resource agent receives a common control signal for the selected remote resources, obtains information on the characteristics of the selected remote resources from the resource repository, and remotely controls the common control signal based on the information on the characteristics of the remote resources. And adapted to convert to a separate control signal for each of the resources.

According to the present invention, since intelligent middleware operating independently of a sensor and a remote facility is provided, the cost of implementing a ubiquitous city can be greatly reduced, and management costs can be reduced.

In addition, since the ubiquitous middleware according to the present invention adopts a distributed computing technique, a large amount of sensor information can be processed in real time at a low cost, and a user can control remote devices as if they control local resources. .

1 is a flowchart conceptually illustrating a ubiquitous remote resource control method according to an aspect of the present invention.
2 is a block diagram conceptually illustrating an embodiment of a ubiquitous system according to another aspect of the present invention.
3 is a diagram conceptually illustrating a remote management model implemented in the present invention.
4 is a block diagram conceptually illustrating another embodiment of a ubiquitous system according to another aspect of the present invention.
5 is a graph illustrating a signal received from a sensor.
6 is a pseudo-code illustrating an inference rule for inferring situation information.
7 is a diagram illustrating a remote control portal displayed on the user terminal.
8 is a block diagram conceptually illustrating an operation of a ubiquitous system according to another aspect of the present invention.
9 is a diagram illustrating a service ontology used by the present invention.

In order to fully understand the present invention, the operational advantages of the present invention, and the objects achieved by the practice of the present invention, reference should be made to the accompanying drawings which illustrate preferred embodiments of the present invention and the contents described in the accompanying drawings.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. As those skilled in the art would realize, the described embodiments may be modified in various different ways, all without departing from the spirit or scope of the present invention. In addition, in order to clearly describe the present invention, parts irrelevant to the description are omitted, and the same reference numerals in the drawings indicate the same members.

Throughout the specification, when a part is said to "include" a certain component, it means that it may further include other components, without excluding the other components unless otherwise stated. In addition, the terms "... unit", "... unit", "module", "block", etc. described in the specification mean a unit for processing at least one function or operation, which means hardware, software, or hardware. And software.

1 is a flowchart conceptually illustrating a ubiquitous remote resource control method according to an aspect of the present invention.

First, individual sensor signals are received from sensors operating in a ubiquitous environment (S110). In the present specification, the ubiquitous environment means that a plurality of sensors and remote resources having various characteristics are connected to a central control unit or a central server that provides ubiquitous service through various communication methods. The central server is provided with a distributed arithmetic ubiquitous middleware, which will be described later, to process a large amount of sensor information and to control remote resources according to the current situation information. In addition, the characteristics of the sensor in the present invention refers to the unique properties of each sensor, such as the physical characteristics of the sensor, the communication protocol applied to the signal transmitted by the sensor, and the physical characteristics of the sensor signal. Sensors that transmit sensor signals using the same communication protocol may be connected to the same Ubiquitous Sensor Network (USN), but the present invention is not limited thereto, and various sensors using various communication protocols may be commonly connected to a central server. In addition, in the present specification, a remote equipment or a remote resource refers to various devices operated to implement a service determined according to context information. For example, if the service determines that the gate should be opened, the remote resource could be the gate drive. Each remote facility also has unique physical characteristics, like sensors, that can communicate with a central server through a unique communication protocol. The physical characteristics of the control signal for controlling the remote facility may also be included in the properties of the remote facility. For example, more power is consumed to control a hydro gate opening and closing for a larger gate than a hydro gate driving device for opening and closing a small gate. In the present invention, a signal for controlling all remote facilities is called a common control signal for clarity, and a specific signal for controlling each remote facility is called an individual control signal. For example, the control signal instructing the small and large hydro gate devices to open the gate 50% is a common control signal, and based on the common control signal, each of the small and large hydro gate devices operates the hydro gate motor. The specific physical signal to make is an individual control signal.

When the individual sensor signal is received, the received individual sensor signal is converted into a common sensor signal irrelevant to the sensor characteristic (S120). The reason for converting individual sensor signals into common sensor signals is to interpret the sensor signals in the middleware independently of the characteristics of each sensor. For example, even when exposed to the same amount of light, the amount of light detected by cameras with different CCD sizes is inevitably different. At this time, the absolute magnitude of the amount of light received by each camera becomes a separate sensor signal, and the ratio of the current light amount to the maximum received light amount of each camera may be a common sensor signal. As such, the operation of generating a common sensor signal may be regarded as an operation of normalizing an individual sensor signal in consideration of characteristics of each sensor. As such, since the ubiquitous remote resource control method according to the present invention uses a common sensor signal independent of each sensor characteristic, the ubiquitous remote resource control method can operate independently regardless of specific characteristics of the sensors, and simply add sensors as needed. Can be.

When the common sensor signal is received, the received common sensor signals are analyzed to infer current context information of the ubiquitous environment (S130). A specific process of inferring the situation information will be described later in detail in the relevant part of the present specification.

When the contextual information is inferred, a distributed computing platform adopting a distributed computing technique is used, and a service to be performed on remote resources is determined based on the contextual information (S140). At this time, the service to be performed may be retrieved from a service repository that stores services that can be performed based on the received context information, or a specific command may be obtained from the user.

When the service to be determined is determined, the remote resources to be controlled are selected according to the determined service, and a common control signal for the selected remote resources is generated (S150). As described above, the common control signal is generated regardless of the characteristics of the remote facility to be controlled. Then, the common control signal is converted into the individual control signal in consideration of the individual resource characteristics of the remote resources (S160). In order to generate individual control signals, information about characteristics of remote resources to be controlled may be read from a resource repository.

When the individual control signal is generated, the remote resources are controlled using the generated individual control signal (S170).

In addition, the common sensor signal or situation information is provided to the user terminal so that the user may monitor the situation information of the current ubiquitous environment (S180). In this case, a user command may be received through the user terminal.

As such, the ubiquitous remote resource control method according to the present invention can generate situation information and control the remote facility in a unified manner regardless of the characteristics of the individual sensor and the individual remote facility.

2 is a block diagram conceptually illustrating an embodiment of a ubiquitous system according to another aspect of the present invention.

The ubiquitous system 200 shown in FIG. 2 is composed of three tiers: a feeling tier 210, a middleware tier 220, and a presentation tier 230. Filling tier 210 includes various devices such as networked sensors, video cameras, microphones, GPS sensors, and related devices. The middleware tier 220 includes a common device interface layer 240, a context-aware computing layer 250, a ubiquitous distributed core computing layer 260, and common. It includes four layers of a common application interface layer (270). In addition, the context aware operation layer 250 includes a context converter 252, a context analyzer 254, a context repository 256, and a context provider 258, and a ubiquitous cloud core compute layer 260 includes a ubiquitous computing platform 262 and a cloud computing platform 264.

The middleware tier 220 is a core technology for providing various integrated services for u-city [14]. Marked with [.] In this specification refers to the aforementioned non-patent documents. Decisions to operate ubiquitous cities must be made by individuals or groups working together efficiently, and timely relevant data in U-City must be processed in real time. The middleware tier 220 serves as an intermediary platform function between the ubiquitous applications for the ubiquitous city and the infrastructure function of the ubiquitous city, and is composed of services that enable various ubiquitous applications to manage the ubiquitous city. In addition, the middleware tier 220 has a cloud platform concept so that application programs do not need to consider the details of the middleware tier. That is, since applications for U-City use a common ubiquitous middleware 220, it reduces time and cost in developing U-City application, enables better systematic and effective operation and management of U-City, and Provide consistency.

In the embodiment shown in FIG. 2, individual sensor signals received from each sensor are communicated to a common device interface layer 240 of the middleware tier 220. Then, the common device interface layer 240 converts individual sensor signals into common sensor signals in consideration of their respective sensor characteristics and transmits them to the context aware operation layer 250. That is, the common device interface layer 240 is connected to various kinds of devices, but provides a consistent and unified interface to the context aware operation layer 250 and the ubiquitous cloud core operation layer 260. That is, since the middleware tier 220 according to the present invention supports sensor network data sinks and protocols, the middleware tier 220 may be used as a general gateway for various types of sensors and ubiquitous sensor networks that collect sensed data. The filling tier 210 is composed of heterogeneous sensors that collect data in a u-city environment.

The middleware tier 220 operates as a platform-as-a-service (PaaS) to perform intelligent context awareness processing using an ontology. The common sensor signal from the common device interface layer 240 is passed to the context aware operation layer 250. The context converter 252 then converts the received common sensor signal into a context instance, making it available to other components. The situation instance is passed to the situation analyzer 254, which infers the situation information from the pre-determined domain ontology by applying the inference rules stored in the situation store 256. Here, the context analyzer 254 uses an ontology-based intelligent reasoning engine, and uses a domain ontology predetermined to manage context data. The inferred contextual information is then communicated by the context provider 258 to the ubiquitous cloud core computing layer 260.

Ubiquitous cloud core compute layer 260 is an automated service based on context inferred from context-aware compute layer 250 to provide an automated computing environment and make applications or services available anywhere in a timely and collaborative manner. Perform intelligent services such as discovery, automatic service distribution and automatic service execution. By providing predefined services in your application, you can integrate information from other devices or environments.

The ubiquitous computing platform 262 may receive context information provided from the context provider 258, and select a service to be performed from the service ontology using the context information. The service ontology may be implemented as illustrated in FIG. 9. The cloud computing platform 264 also provides a user-transparent service through the presentation tier 230. In other words, the cloud computing platform 264 provides computing power to applications requiring real-time, high performance computing power using computational grid technology. In addition, the cloud computing platform 264 provides a Computer Supported Cooperative Work (CSCW) service using an access grid technology. Accordingly, the cloud computing platform 264 allows real-time control of a vast amount of remote devices such as firewalls, emergency equipment, remote cameras, and the like.

The common application interface layer 270 converts common sensor signals and situation information common to different types of applications such as fire management applications and traffic accident management applications to the presentation tier 230. The common application interface layer 270 converts the common sensor signal and the context information to the presentation tier 230 so as to be compatible with different user terminals as well as different applications executed in the same user terminal. That is, through the common application interface layer 270, a user may execute various applications on various user terminals to read current situation information of the ubiquitous environment and issue necessary user commands.

The presentation tier 230 may provide intelligent services, computing power, and infrastructure to various kinds of applications used by a user. In addition, the presentation tier 230 may provide a portal for various applications, a portal for remote device control, and a portal for managing situational awareness. The user can conveniently and easily use the ubiquitous service and the cloud service using the presentation tier 230.

In order to control the remote device, the user should not feel the difference between the remote device and the local device, in order to achieve this object, the middleware tier 220 according to the present invention performs remote control using cloud computing. do. Distributed operations to perform remote control must satisfy the following conditions.

New standard user interface for remote use over the network, replacing the interface provided by traditional control software

Standard control protocol for local control of remote devices

-Remote observation system that enables device management to be performed and data generated by devices and observation sensors can be viewed in real time from a remote location.

-Software that enables automated management even in remote locations when complex management behavior processes must be programmed in advance.

-Tools for exchanging information in real time across multiple physically separated managers and administrator communities

The reason for using the distributed computing technique in the present invention is that it is a technique that can effectively manage a large-scale sensor network and a remote facility network at a low cost, which is expected to bring innovation in the next generation IT field.

Hereinafter, a remote management model adopted by the present invention will be described with reference to FIG. 3.

3 is a diagram conceptually illustrating a remote management model implemented in the present invention.

For remote control, Gbus (Globus Tele Control Protocol) is used as the remote control protocol in Globus Toolkit 4 (see [17] [18]). GTCP provides methods such as openSession, closeSession, propose, execute, and cancel.

In addition, a real-time monitoring system for remote equipment is provided for remote monitoring. The remote monitoring module provides video images to show the status of the equipment and the data measured from each sensor. For data streaming services, the Network for Earthquake Engineering Simulation Grid (NEESgrid) (see [7]) plays this role with the Ring Buffer Network Bus (RBNB) Data Turbine (see [10]) and HVEMgrid (High-Voltage Electron). Microscopy Grid (see [11]) is run by software called NaradaBroker (see [12]).

The user interface for remote control, remote monitoring, and collaboration can be implemented in various forms, but is preferably provided in the form of a web portal. gridsphere provides user interface functionality in the form of portlets, a standard for the JSR-168 specification. In addition, the control points and sensors of the device are dynamically expressed on the web using Java Script-based Web 2.0 technology, so that users can easily use them.

4 is a block diagram conceptually illustrating another embodiment of a ubiquitous system according to another aspect of the present invention.

The ubiquitous system 400 shown in FIG. 4 includes a filling tier 410, a middleware tier 420, and a ubiquitous cloud portal tier 430.

Filling tier 410 operates in a ubiquitous environment and includes a plurality of sensors having individual sensor characteristics and generating individual sensor signals, and a plurality of ubiquitous remote resources having individual resource characteristics. More specifically, each remote USN has a LabVIEW (see [21]), Server Daemon, DaqToNarada, and Control Daemon in it. The filling tier takes data from sensors, video cameras, and audio to work with each other to process them and deliver the data to NaradaBroker within a common device interface in Tier 2.

The Server Daemon in a remote system receives individual sensor signals from the sensors through LabVIEW. Server Daemon then sends the data received to DaqToNarada. Then, DaqToNarada in the remote system sends data to the Narada Broker. DaqToNarada and Narada Broker work together to stream data. In addition, the control daemon receives a control signal from the GTCP-Plugin included in the ubiquitous cloud core computing layer 460. The Control Daemon controls remote devices by request from the ubiquitous cloud portal tier 430 or by commands by emergency scenarios in the middleware tier 420. In this case, the control daemon controls the remote facilities according to the common control signal irrespective of the characteristics of the individual remote facilities as described above.

One example of a sensor signal from the filling tier is shown in FIG. 5.

5 is a graph illustrating a signal received from a sensor.

5 shows the simulation results in a test bed for a remote control experiment. The testbeds are located in two geographically separated locations more than 30 kilometers apart. In place A, the small stream is configured to allow water to flow from high to low by means of an electric pump. The river is equipped with a sensor for measuring the electrical conductivity of the water to determine the contamination of the flowing water. Place B is equipped with a cloud platform server. 5 shows the change in electrical conductivity measured at the sensor when contaminants were found in the water. If the value of the conductivity is higher than the value already defined, the pump will automatically operate to provide more water to the stream to neutralize the contamination of the water. The threshold already defined is 800 uS / cm. 5, it can be seen that after the predefined threshold the pump is operated by the cloud platform to reduce contamination.

Referring back to FIG. 4, the middleware tier 420 includes a common device interface 440, a context aware computing layer 450, a ubiquitous cloud core computing layer 460, and a common application interface layer 470.

The context converter included in the context aware operation layer 440 converts raw data values, which are input through Narada Broker from various types of remote devices, into specific context instances. This transformed situation instance is stored in a domain ontology of information classes. Here, one context data is like an individual instance of the context domain ontology model. This changed situation information is used by other components for intelligent situational cloud computing.

The Context Analyzer provides inference contextual information based on domain ontology using contextual inference engines. Multiple reasoning engines can work with the context analyzer to provide different reasoning results. The Context Analyzer's inference engine has the ability to provide inferential contextual information based on direct contexts and to infer content differences and conflicts in the context knowledge database. In order to infer the current situation information, a predetermined rule-based method is used.

FIG. 6 is a pseudo-code inferring pollution levels of water used by the Context Analyzer and illustrating inference rules stored in the context store for determining the operation of the pump.

If the electrical conductivity of water exceeds 800, then it is inferred that water is contaminated by poisons. The water pump is then activated by the inferred result. The Context Analyzer in the ubiquitous cloud core compute layer 460 infers whether water is currently contaminated and sends a special warning message from the service ontology to the pump activation service or related manager using the inferred contextual information from the service discoverer (not shown). Discover services and more.

9 is a diagram illustrating a service ontology used by the present invention.

The context provider provides context information inferred to the ubiquitous cloud core computing layer 460 for service discovery. The discovered services are run by cloud computing platforms or ubiquitous computing platforms. The Context Repository also stores context, ontology, context instance, rules illustrated in FIG. 6, and inferred context information. Using the context repository, other components can query, add, delete, and modify context knowledge.

The four main components in middleware tier 420, Broker Manager, Resource Manager, GTCP Server, and GTCP Plugin, cooperate with each other to implement remote management. The Broker Manager determines which of the remote control services is given to the remote device. The determined service may be displayed on the user's screen through the ubiquitous school portal tier 430, and may perform an already defined action. The Broker Manager is alerted by the Context Provider when the Context Analyzer detects an exceptional situation. Broker Manage sends the decision to the resource manager. The GTCP server and the GTCP plugin work in concert to perform remote control on decision and can use GT4 (see [17]). GTCP service receives user's instruction from cloud portal and delivers it to GTCP Plugin.

Hereinafter, a portal provided by the ubiquitous cloud portal tier 430 will be described with reference to FIG. 7.

7 is a diagram illustrating a remote control portal displayed on the user terminal.

Users access the ubiquitous cloud platform through the ubiquitous cloud portal. Through these portals, users can detect the status of remote devices and site conditions at remote locations, control remote devices, change emergency scenarios, change situational awareness rules, access situation information, retrieve necessary information, and There are many other useful actions you can do.

8 is a block diagram conceptually illustrating an operation of a ubiquitous system according to another aspect of the present invention.

The data measured by the sensor and the video / audio image from the video / audio device are collected by Server Daemon on the computer where the sensor is connected. Server Daemon then sends the information to DaqToNarada on the same computer. DaqToNarada then sends the collected data to NaradaBroker. NaradaBroker then sends the measured data to the Context Converter. Video data is sent directly by NaradaBroker to the real-time view portlet of the ubiquitous cloud portal.

The Context Converter converts the measured data into an ontology instance and passes it to the Context Analyzer. The inference engine of the Context Analyzer infers a predefined situation using the received ontology instance and predefined rules. The Context Analyzer communicates the inferred situation to the Broker Manager. The Broker Manager receives the inferred situation and sends it to the ubiquitous cloud portal as a real-time view portlet. If the received context information requires some particular service, the service discoverer finds a suitable service.

If the found service needs to control a remote device, the Broker Manager then sends a request for the found service to the Resource Manager. Resource Manager works in concert with GTCP to send control commands to the Control Daemon in the remote computer that is connected to the remote device. And the designated remote device is controlled by Control Daemon.

As described above, the ubiquitous service providing method according to the present invention uses a cloud computing platform and is implemented in a three-tier structure. Thus, the user is provided with user-transparence that does not need to have an awareness of the infrastructure and does not need to know the details of the remote control principle. In addition, since the present invention uses the concept of PaaS, a device located at a remote location can be felt and controlled by virtualizing as a local device. While the remote control models according to the prior art control only one specified remote device, the remote control method according to the present invention can manage various kinds of heterogeneous remote devices.

Although the present invention has been described with reference to the embodiments shown in the drawings, this is merely exemplary, and it will be understood by those skilled in the art that various modifications and equivalent other embodiments are possible.

Therefore, the true technical protection scope of the present invention will be defined by the technical spirit of the appended claims.

The present invention can be applied to the ubiquitous system for processing the sensor signal from the large-scale sensor network in real time to infer the situation information in real time, and control the remote facilities according to the inference result.

Claims (12)

A method for controlling ubiquitous remote resources based on individual sensor signals from a plurality of sensors operating in a ubiquitous environment and having individual sensor characteristics, the method comprising:
A sensor signal receiving step of receiving the individual sensor signals;
The individual sensor signal is converted into a general sensor signal irrelevant to the sensor characteristic, the common sensor signals are analyzed to infer the current context information of the ubiquitous environment, and the inferred context information A management / control step of generating individual control signals for controlling the remote resources accordingly; And
And controlling the remote resources based on the individual control signals. The method of claim 1,
And providing a common sensor signal or the situation information to a user terminal and receiving a user command from a user. The method of claim 2, wherein the controlling step,
A common device interface receiving the individual sensor signals and converting the individual sensor signals into the common sensor signal;
A context-aware computing operation of generating the context information using the common sensor signal;
It uses a distributed computing platform that adopts a distributed computing technique, determines a service to be performed on the remote resources based on the context information, and determines the individual control signal according to the determined service. A ubiquitous distributed core computing step of generating and delivering to the remote resources; And
A ubiquitous step of converting the common sensor signal and the context information to be compatible with each application executed in the user terminal and providing the converted result to the user terminal. Remote resource control method. The method of claim 3, wherein the context aware operation comprises:
A context transformation step of combining the common sensor signals and converting the combined common sensor signals into a predefined context instance; And
And a situation analysis step of receiving the situation instance and inferring situation information by analyzing the received situation instance using a predefined rule. The method of claim 3, wherein the ubiquitous distributed core operation step,
A service discovery step of searching for a service to be performed from a service repository storing services that can be performed based on the context information or receiving a service to be performed from a user;
Selecting remote resources to be controlled according to the service and generating the common control signal for the selected remote resources; And
A ubiquitous remote resource comprising converting the common control signal into an individual control signal in consideration of individual resource characteristics of the remote resources, and transferring the converted individual control signal to the remote resources. Control method. The method of claim 5, wherein generating the individual control signal,
Receiving the common control signal for selected remote resources;
Obtaining information about characteristics of the selected remote resources from a resource repository; And
And converting the common control signal into a separate control signal for each of the remote resources based on the information on the characteristics of the remote resources. In a ubiquitous system operating in a ubiquitous environment and comprising a plurality of sensors having individual sensor characteristics and generating individual sensor signals and a plurality of ubiquitous remote resources having individual resource characteristics,
Converting the individual sensor signal into a common sensor signal irrelevant to the sensor characteristic, analyzing the common sensor signals to infer the current situation information of the ubiquitous environment, and controlling the remote resources according to the inferred situation information. It includes a control (control / control portion) for generating a control signal,
And the remote resources are controlled based on the individual control signal. The method of claim 7, wherein
And a presentation portion for providing the common sensor signal or the situation information to a user terminal and receiving a user command from a user. The method of claim 8, wherein the control unit,
A common device interface module for receiving the individual sensor signals and converting them into the common sensor signals;
A situation recognition calculation module configured to generate the situation information using the common sensor signal;
A distributed computing platform employing a distributed computing technique employs a distributed computing platform, and determines a service to be performed on the remote resources based on the contextual information, and generates and transmits the individual control signal to the remote resources according to the determined service. Ubiquitous distributed core computing module; And
And a common application interface module for converting the common sensor signal and the contextual information to be compatible with each application executed in the user terminal, and providing the converted result to the user terminal. The method of claim 9, wherein the situation recognition operation module comprises:
A context converter for combining the common sensor signals and converting the combined common sensor signals into a predefined situation instance; And
And a context analyzer configured to receive the context instance and infer context information by analyzing the received context instance by using a predefined rule. 10. The method of claim 9, wherein the ubiquitous distributed core calculation module,
A service discovery unit for searching for a service to be performed or receiving a service to be performed from a user from a service repository storing services that can be performed based on the context information;
A resource manager for selecting remote resources to be controlled according to the service and generating the common control signal for the selected remote resources; And
A ubiquitous system, comprising: a resource agent converting the common control signal into an individual control signal in consideration of individual resource characteristics of the remote resources, and transferring the converted individual control signal to the remote resources. . The method of claim 11, wherein the resource agent,
Receive the common control signal for selected remote resources, obtain information about the characteristics of the selected remote resources from a resource repository, and transmit the common control signal based on the information about the characteristics of the remote resources to each of the remote resources Ubiquitous system, characterized in that it is adapted to convert to a separate control signal for.

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