本文選題：物聯(lián)網(wǎng) + 資源管理��； 參考：《北京郵電大學》2014年博士論文

【摘要】：目前,物聯(lián)網(wǎng)的應(yīng)用模式還停留在Intranet of Things階段,大多數(shù)物聯(lián)網(wǎng)應(yīng)用模式都是豎井式的,這種應(yīng)用模式通常是：專用的設(shè)備和感知延伸網(wǎng)絡(luò)用于專門的應(yīng)用,底層的感知資源和感知數(shù)據(jù)被封鎖在了一個個的應(yīng)用中,得不到進一步的共享和重用。這些系統(tǒng)之間是相互隔離的,彼此的信息不能夠互聯(lián)互通,導(dǎo)致了信息孤島的產(chǎn)生,造成了大量的傳感資源和數(shù)據(jù)的浪費,也阻礙了進一步的跨系統(tǒng)的智能數(shù)據(jù)融合。此外,這種豎井式應(yīng)用模式無法支持更加“普適性”和大規(guī)模的應(yīng)用方案。本文主要關(guān)注的是支持從Intranet of Things過渡到Internet of Things所需要的中間件基礎(chǔ)設(shè)施,以及構(gòu)建這種基礎(chǔ)設(shè)施存在的部分技術(shù)問題及其解決方案。 本文提出了一個物聯(lián)網(wǎng)服務(wù)提供框架。框架在保證資源提供者本身應(yīng)用的實時性和可靠性前提下,為可定制的開放和共享資源提供了基礎(chǔ)設(shè)施。框架中包含多級資源管理平臺,作為資源管理平臺的體系架構(gòu),而資源管理平臺是框架的核心,作為整個基礎(chǔ)設(shè)施的功能載體。從大的方面來講,平臺的目標是為從豎井式應(yīng)用模式過渡到水平式模式提供基礎(chǔ)中間件,進而以開放的方式將底層資源的能力提供出來,從而實現(xiàn)資源和數(shù)據(jù)的跨系統(tǒng)共享和重用。從功能上來說,平臺提供了一個中間件來接入異構(gòu)資源、形式化的描述資源和實體,并將它們的輸出以"well-understood、machine-processible"的方式開放給不同的應(yīng)用。 針對物聯(lián)網(wǎng)資源的異構(gòu)性問題,資源管理平臺主要解決協(xié)議的異構(gòu)性和數(shù)據(jù)模型異構(gòu)性兩個方面。對于協(xié)議的異構(gòu)性,平臺底層借助于UDA (Unified Device Access)統(tǒng)一接入層來適配底層設(shè)備協(xié)議的異構(gòu)性。UDA的核心功能是協(xié)議棧框架,協(xié)議�？蚣芑贠SGi技術(shù),并采用Dependency-Inversion的協(xié)議棧設(shè)計模式�？傮w來說,協(xié)議棧框架有兩大特點：支持協(xié)議的動態(tài)熱插拔,即協(xié)議是即插即用的,可以動態(tài)的安裝、修改和卸載；協(xié)議的自適配,即協(xié)議棧框架能夠支持異構(gòu)協(xié)議的自適配,能夠自動選擇協(xié)議�；蛘邉討B(tài)組裝協(xié)議棧來解析未知數(shù)據(jù)包,不需要手工逐一配置。此外,協(xié)議�？蚣苤胁煌膮f(xié)議都以組件的形式維護在協(xié)議容器中,協(xié)議容器提供了維護、管理和配置協(xié)議的圖形化管理工具,因此可以規(guī)范的管理已有協(xié)議。經(jīng)過一系列的性能測試,實驗結(jié)果表明UDA的性能可以勝任一些對實時性要求比較高的應(yīng)用場景。 對于數(shù)據(jù)模型的異構(gòu)性,本文提出了基于語義本體的多層次、多維度信息模型。異構(gòu)資源通過UDA接入進平臺后,通過信息模型對資源和數(shù)據(jù)進行統(tǒng)一建模描述。多層次信息模型的理念首先從模型這個角度將上層應(yīng)用與底層傳感器資源解耦,上下層模型通過資源-實體綁定進行關(guān)聯(lián)。資源和實體關(guān)聯(lián)后,資源就可以觀測或者控制實體的具體屬性,原本無意義的觀測數(shù)據(jù)也變成了具備具體應(yīng)用意義的情景數(shù)據(jù)。一個應(yīng)用場景中的實體模型可以關(guān)聯(lián)不同資源提供者的資源模型,這意味著從模型的角度應(yīng)用程序可以共享和重用傳感器資源。同時,信息模型提供了模型的關(guān)聯(lián)和映射機制,通過這種機制,系統(tǒng)之間的數(shù)據(jù)或者來自感知層的數(shù)據(jù)能夠以上層應(yīng)用可理解的方式提供給它們。此外,本文提出了多維度的思想,通過多個特征維度的資源模型來描述資源。根據(jù)多維度模型,資源匹配算法可以根據(jù)每個維度的特性準確的匹配資源。此外,我們實現(xiàn)了一個基于領(lǐng)域模板的建模工具,能夠有效地創(chuàng)建、組織和維護這些模型并支持模板的復(fù)用。信息模型已在“西門子智能交通系統(tǒng)”等系統(tǒng)中得到了應(yīng)用。 平臺接入大量的異構(gòu)感知資源后,將它們能力以輕量級服務(wù)的方式開放出來。針對物聯(lián)網(wǎng)服務(wù)的大規(guī)模性、動態(tài)性和情景的復(fù)雜性,本文提出了基于語義相似度的功能性服務(wù)推薦和基于協(xié)同過濾的QoS-based服務(wù)推薦算法,根據(jù)用戶的需求,結(jié)合當前被監(jiān)控實體的情景,為用戶自動或者半自動的推薦合適的服務(wù)。算法的作用主要定位在兩方面：協(xié)助用戶從大量的可用服務(wù)集中選擇合適的服務(wù),降低用戶的工作量；當資源或者被測實體情景發(fā)生改變,動態(tài)為被測實體匹配資源,找到與實體當前情景相符的感控服務(wù),保證了服務(wù)的連續(xù)性。實驗結(jié)果表明文中提出服務(wù)推薦算法是適合物聯(lián)網(wǎng)環(huán)境特性的,它在較短的計算時問內(nèi)盡量保證了推薦的準確率和召回率性能。
[Abstract]:At present, the application mode of the Internet of things is still in the Intranet of Things stage, most of the application modes of the Internet of things are vertical wells. This application mode is usually used for special applications and perceptual extension networks, and the underlying perceptual resources and perceptual data are locked in a number of applications. Sharing and reuse. These systems are isolated from each other, the information of each other can not be interconnected, resulting in the production of information islands, causing a large amount of waste of sensing resources and data, and also hindering further cross system intelligent data fusion. In addition, this type of vertical application model can not support more "universality" and larger. Scale applications. This article focuses on the middleware infrastructure needed to support the transition from Intranet of Things to Internet of Things, as well as some of the technical problems and solutions that exist in the construction of such infrastructure.
This paper presents a framework for the service of the Internet of things. The framework provides the infrastructure for customizable open and shared resources under the premise of the real-time and reliability of the resource provider itself. The framework includes a multilevel resource management platform as the architecture of the resource management platform, and the resource management platform is the core of the framework. As a function carrier for the entire infrastructure, the goal of the platform is to provide the basic middleware for the transition from the shaft type application mode to the horizontal mode, and then to provide the ability of the underlying resources in an open way, so as to realize the cross system sharing and reuse of resources and data. It provides a middleware to access heterogeneous resources, formally describe resources and entities, and open their output to different applications in a "well-understood, machine-processible" way.
In view of the heterogeneity of the Internet of things, the resource management platform mainly solves the heterogeneity of the protocol and the heterogeneity of the data model. For the heterogeneity of the protocol, the core function of the UDA (Unified Device Access) unified access layer to adapt the heterogeneous.UDA of the underlying device protocol is the protocol stack framework and the protocol stack. The framework is based on OSGi technology and adopts the protocol stack design pattern of Dependency-Inversion. In general, the framework of the protocol stack has two major features: dynamic hot plug in the protocol, that is, the protocol is plug and play, can be installed dynamically, modified and unloaded; the self adaptation of the protocol, that is, the protocol stack framework can support the self adaptation of heterogeneous protocols. Automatic selection protocol stack or dynamic assembly protocol stack to parse unknown data packets without manual configuration. In addition, different protocols in the protocol stack are maintained in the protocol container in the form of components, and protocol containers provide graphical management tools for maintenance, management, and configuration protocols, so it can be managed in a standardized way. After a series of performance tests, the experimental results show that the performance of UDA can be applied to some application scenarios with high real-time requirements.
For the heterogeneity of the data model, this paper presents a multi-level and multi-dimensional information model based on semantic ontology. After the heterogeneous resources are connected to the platform through UDA, the information model is used to describe the resources and data. The concept of multi level information model first from the angle of the model to solve the upper application and the underlying sensor resource solution. Coupled, upper and lower layers are associated by resource entity binding. After resources and entities are associated, the resources can observe or control the specific properties of the entity. The original meaningless observation data also becomes scenario data with specific application significance. An entity model in an application scene can relate to the resources of different resource providers. The model, which means that the application of the model can share and reuse the sensor resources. At the same time, the information model provides the association and mapping mechanism of the model, through which the data between the systems, or the data from the perceptual layer, can be provided to them in an understandable way. According to the multi-dimensional model, the resource matching algorithm can match the resources accurately according to the characteristics of each dimension. In addition, we implement a modeling tool based on the domain template, which can effectively create, organize and maintain these models and support the reuse of the template. The information model has been applied in the system of SIEMENS intelligent transportation system.
After the platform has access to a large number of heterogeneous perceived resources, the platform opens up their capabilities in a lightweight service. In view of the large-scale, dynamic and situational complexity of the Internet of things services, this paper proposes a functional service recommendation based on semantic similarity and a collaborative filtering based QoS-based service recommendation algorithm based on user requirements. The role of the algorithm is mainly in two aspects: assisting the user to select the appropriate service from a large number of available services, reducing the user's workload, and dynamically matching the measured entity when the resource or the measured entity situation changes. The results show that the service recommendation algorithm is suitable for the environment of the Internet of things, which ensures the accuracy and recall performance in the short calculation.
【學位授予單位】：北京郵電大學
【學位級別】：博士
【學位授予年份】：2014
【分類號】：TP391.44;TN929.5

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本文編號：2075136