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Research Article A Data Processing Middleware Based on SOA forthe Internet of Things

Feng Wang, Liang Hu, Jin Zhou, and Kuo Zhao

College o Computer Science and echnology, Jilin University, Changchun , China

Correspondence should be addressed to Kuo Zhao; zhaokuo@jlu.edu.cn

Received September ; Revised January ; Accepted January

Academic Editor: Fei Yu

Copyright © Feng Wang et al. Tis is an open access article distributed under the Creative Commons Attribution License, whichpermits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Te Internet o Tings (Io) emphasizes on connecting every object around us by leveraging a variety o wireless communicationtechnologies. Heterogeneous data usion is widely considered to be a promising and urgent challenge in the data processing o theIo. In this study, we rst discuss the development o the concept o the Io and give a detailed description o the architecture o the Io. And then we design a middleware platorm based on service-oriented architecture (SOA) or integration o multisourceheterogeneous inormation. New research angle regarding exible heterogeneous inormation usion architecture or the Io is thetheme o this paper. Experiments using environmental monitoring sensor data derived rom indoor environment are perormedor system validation. Trough the theoretical analysis and experimental verication, the data processing middleware architecturerepresents better adaptation to multisensor and multistream application scenarios in the Io, which improves heterogeneous data

utilization value. Te data processing middleware based on SOA or the Io establishes a solid oundation o integration andinteraction or diverse networks data among heterogeneous systems in the uture, which simplies the complexity o integrationprocess and improves reusability o components in the system.

1. Introduction

Te concept o the Internet o Tings (Io) was rstly derived by the Automatic Identication (Auto-ID) Labs inthe Massachusetts Institute o echnology (MI) in . TeAuto-ID Labs simultaneously propose [] radio requency identication (RFID) systems that connect devices and trans-

mit inormation via radio requency to the Internet in orderto achieve intelligent identication and management. oormalize the concept o the “Internet o Tings,” the Interna-tional elecommunicationUnion (IU)released the report o “IU Internet reports : the Internet o Tings []” in theWorld Summit on Inormation Society (WSIS) held in unisin , in which the Io characteristics, related technicalchallenges, and uture market opportunities were introduced.

IU pointed out in the report [], “We are standing atthe edge o new times o communication, inormation andcommunication technology (IC) to achieve the objectiveshave been developed to meet the communication betweenpeople, and things, between things connection. Te coming

era o ubiquitousInternet o Tings make us a new dimensiono communication in the world o inormation and commu-nication technology (shown in Figure ), any time, any place,connected to anyone, expansion to connect things connectedto the Internet o Tings.”

With the rapid development o inormation and com-munication technology, just a oneold technology cannot

satisy the complex context-aware application requirements,in which resource inormation has been subject to outsideintererence, and people want to be able to obtain real-time and real-world inormation such as diverse sensory data acquisitions and human-computer interaction dataacquisitions and ultimately achieve efficient data acquisitionsbetween people and things, people, and things and things.

Te Io applications integrate with IntelliSense recog-nition technologies, pervasive computing, and ubiquitousnetworks, which are called the third wave o the inormationtechnology revolution ollowing the development o theinormation industry in the computer and the Internet. TeIo is an important part o the new generation o inormation

Hindawi Publishing CorporationJournal of SensorsVolume 2015, Article ID 827045, 8 pageshttp://dx.doi.org/10.1155/2015/827045

http://dx.doi.org/10.1155/2015/827045http://dx.doi.org/10.1155/2015/827045

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Any time

Any place

Any thing

Moving

Outside

Inside

NightDaytime

Without computer

Nearby computer

Human to human (H2H)

Human to things (H2)

Tings to things (2)

F : Connections in the Io.

technology. Te oundation o the Io is still the Internet andit is based on the extensionand expansiono Internet. Te Ioextends its client to anything and any person by the exchange

o inormation and communication though Internet. Te Ioconnects everything to the Internet.

Te Io incorporates RFID, wireless sensor networks,andubiquitous terminal equipment as the perception oundation,with a variety o wired or wireless communication and inte-gration o the Internet to achieve the perception data trans-erred and shared. By leveraging cloud computing and high-perormance computing technology or real-time inorma-tion process, management, and organization, we ultimately offer the upper application a variety o eedback decision-making processes or closed-loop control o the things.

Consequently, the growing popularity o the Io willinevitably lead to a new wave o development o various

industries, such as smart home, intelligent monitoring, smartgrid, and other new concepts o things technology. So ar,the Io has been launched as a variety o demonstrationapplications in different domains (shown in Figure ), such asintelligent industry [], intelligent agriculture [], intelligentlogistics [], intelligent transportation [], smart grid [],environmental protection [], security protection [], intel-ligent medical care [, ], and smart home [].

Te rest o the paper is organized as ollows. In Section ,the Io concepts are reviewed. Te description o the archi-tecture o the Io is detailed in Section  . In Section , wepropose a middleware ramework based on SOA or Io. Weconclude the paper and point out uture work in Section .

2. Related Work 

Te Io will be a promising acility o uture network which has sel-conguration ability in global dynamic net-work based on standard and interoperable communicationprotocols. In the network, all real and virtual items havespecic identication and physical sensory data in order toachieve the goal o inormation sharing through seamlessconnection o intelligent interace [, ]. Tese intelligentinteraces connect and communicate with users, society, andenvironment context on the basis o the agreed protocols. Itis an extension and expansion o the network based on the

Internet to achieve intelligent identiying, locating, tracking,monitoring, and managing.

From an alternative perspective beyond the initial con-cept o the Io and the denitions o it as abovementioned,the Io is a network connecting things to things or achievingintelligent identication and management o the items in a

broad sense; it can be seen as a usion o the inormationspace and physical space. Trough that way, everythingis digitized and networked, which results in realizing anefficient inormation interactive mode between items, itemsand people, and people and environment. Afer that, variousdiversities o inormation are merged into social networksand integrated into human society in a higher realm. Forrealization o inormation usion in the Io, the middlewaretechnology is suitable to be adopted as a concrete solution.

Middleware as computer sofware provides connection o different sofware components and applications. It consists o a set o enabling services that allow multiple processes run-ning on one or more machines to interact across a network.

Atzori et al. [] summarized the relationship as three visionso the Io, that is, things-oriented visions, semantic-oriented

 visions, and Internet-oriented visions. According to the threecharacteristics, middleware in the Io shall be able to addressthings issues and Internet issues, deal with the semanticsgap, such as interoperability across heterogeneous devices,context awareness, and device discovery, manage resourcesconstrained embedded devices and scalability, manage largedata volumes and privacy, and cope with semantic data andso orth.

Several studies have been published that have exploredways to design middleware or the Io. In [], R ̈omer et al.summarized the unctions and the nature o the middle-

ware or wireless sensor network. In [], Wang et al. havereviewed middleware or WSN and a detailed analysis o theapproachesand techniques offered by themiddleware to meetthe requirements o the WSN has been presented. It alsodiscusses generic components o the middleware and reer-ence model o WSN based middleware. In [], middlewarehas been surveyed rom adaptability perspective in whichSadjadi and McKinley presents taxonomy or adaptive mid-dleware and their application domains and provides detailsor one o each middleware category. Te context-awarenessmiddleware also has been studied. Te survey in [] isbased on the architectural aspects and provides taxonomy o the eatures o the generic context-aware middleware.

A survey reported in [] evaluates several context-awarearchitectures based on some relevant criteria rom ubiquitousor pervasive computing perspective. In [], Bandyopadhyay et al. provides a survey o middleware system or the Io.

3. The Architecture of the IoT

Heterogeneous inormation sources are the most importantcharacters o the Io. In order to achieve interconnection,intercommunication, and interoperability between heteroge-neous inormation, the uture architecture o the Io needsto be open, layered, and scalable []. Te Io architectureis generally divided into our layers that are perception

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Access network Access network 

Access gateway 

Sensor gateway 

Sensor nodes

Sensor gateway 

Sensor gateway 

Mobile RFIDreader

RFID reader

Access network Access network Access network  

Directory server Management

Context modelingand management

Contentmanagement

Spatial informationmanagement

RemoteAgriculture control Disaster rescue Digitized battleeld elemedicine

Logistic and supplychain management

Ubiquitous service

monitoring

F : Layered ramework in the Io.

layer, network layer, middleware layer, and application layer(shown in Figure ).

A major part o perception layer is wireless sensornodes. A generic sensor node aims to take measurements o physical environment []. It may be equipped with a variety o devices which can measure various physical attributessuch as light, temperature, humidity, barometric pressure,acceleration, acoustics, magnetic eld, and carbon dioxideconcentration. In addition to the sensors, perception layeralso consists o a large amount o inormation generatedequipment, including RFID and positioning systems, anda variety o smart devices, such as smart phones, PDAs,multimedia players, netbooks, and laptops. It can be seen that

the diversity o generated inormation is an emerging andimportant eature o the Io.

IPv addresses the major deect o the limit on thenumber o terminal pieces o equipment to access Internet.Te main idea o network layer is leveraging the existingInternet as the main dissemination o inormation by virtueo a variety o wireless accesses. Every wireless access methodhas its own characteristics and application scenarios. Wi-Fiand other wireless broadband technologies possess broadercoverage, aster transmission, reliable high-speed, and lowercost and circumvent the obstacles. Te low-speed wirelessnetworks, such as ZigBee, Bluetooth, and inrared low-speednetwork protocols, are adapted to resource constrained node,

which has the characteristics o the low communicationradius, low computing power, and low energy consumption.Mobile communication network will become an effectiveplatorm or “a comprehensive, anytime, anywhere.”

Middleware layer tackles the inormation heterogeneity issues by intelligent interaces. Te unctional solutions o middleware layer mainly consist o data storage (databaseand mass storage technology), heterogeneous data retrieval(search engine), data mining, data security, and privacy protection.

In application layer, traditional Internet has gone throughdata-centric to people-centric conversion; typical onlineapplications include le transer, e-mail, the World Wide

Web, e-commerce, online gaming, and social networking. Inthe application o Io, things or physical world areconsideredas the center, typical Io applications covering item tracking,context-aware, intelligent logistics, intelligent transportation,smart grid, and so orth. Te Io application is currently in aperiod o rapid growth.

4. The Implementation of MiddlewareBased on SOA for IoT

Te Io research mainly pays more attention to network layer recently, such as the Io network coding, identica-tion and anticollision technology. However, data processing

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inrastructure continues to be overwhelmed by the mass o heterogeneous inormation rom the number o terminalsin the Io. Te exible architecture that is based on SOAor heterogeneous inormation usion in the Io offers theopportunity to employ mitigation measures. It is criticalor the ultimate success o the Io application or better

utilization o the integration o a wide range o services rommultiple sources and provides more personalized service tobusinesses or individuals [].

.. Service-Oriented Application Architecture Description.SOA (service-oriented architecture) is a component modeland links different unctional units (called services) o theapplication through well-dened interaces and contractsbetween these services. Interace is dened by a neutral man-ner and it should be independent o implementation services,hardware platorms, operating systems, and programminglanguages. Tis allows the service to be built in a variety o such systems to interact in a uniorm and general way 

[]. Te service is the basis o the SOA; thereby, they canbe applied directly and effectively depending on system andinteraction o sofware agents.

ypically, business operations running in an SOA com-prise a number o different components, which are ofen in anevent-driven or asynchronous ashion that reects the under-lying business process needs []. In the context o the Io,original and emerging resources are in the orm o servicesandare opening on Internet. Consequently, the studyo SOA-based usion application technology is o great value [].

SOA architecture consists o ve main parts, depicted asbelow:

() Consumer: acquires the inormation rom producers’

entities that provide services, such as mobile termi-nals and web clients.

() Application: provides application interaces or differ-entdegrees o loosely coupled services, such as mobileapplications, web applications, and rich client.

() Service: the implementation o the entities involvedin a specic task, such as data center and enterpriseinormation center.

() Service Support: SOA specic application back-ground support unctions, such as security, manage-ment, and semantic analysis.

() Producer: an entity to provide specic services or

unctions.

.. Te Io Middleware Design.   Inspired by the character-istics o data in the Io, the design o middleware with theservice-oriented architecture was employed in this paper,and integration services, compatible with various types o data and the agreement has been divided. Consequently,this paper presents the basic ramework o SOA-based Ioapplications as shown in Figure . In Figure , the three-layerstructure o the original SOA is broken down into a ve-layersystem. Service providers (producers) use o various types o environmental sensing technology. Data processing platorm

Users

Securityplatform

Service

Dataprocessingplatform

Device

Applicationusers

Service access security andauthentication

Application universal interface

Data universal interface

Devicemanagement

Serviceagent

Communicationagent

Consistency and standardization of heterogeneous data

Data validation and decontamination

Producer

Middle-ware

Consumer

F : Te Io middleware architecture based on SOA.

is responsible or data processing, data ltering, and dataintegrity. It provides XML scheme or data unication andmetadata consistency and standardization o heterogeneousdata processing.

Security platorm is a security barrier between the serviceplatorm and data platorm, which is responsible or thesaety o the equipment and data. Service layer aims atproviding a range o generic interaces and agency serviceswhich are responsible or data parsing in order to coordinatedifferent data ormats and are also advantageous or dis-tributed deployment o a variety o databases. Te purpose o universal interace is to achieve compatible communication

protocols, which are used by different types o users, toperorm unied data exchanging with the upper consumers.

Te key part o the service layer is to orm a bridgebetween the data processing and the upper application. Teservice layer also aces different problems that are encoun-tered in the Io application such as network connection,resource-constrained nodes, and different application plat-orm. Because the underlying device is extremely rich inthe Io, the SOA system to provide network services needsto consider the problem o transmission delay and resourcescheduling and network services need to provide a variety o routing or delay tolerant network technology to deal with.SOA systems also need a balanced scheduling algorithm and

balanced network resources. Different application platormsrequire more generic SOA system design patterns; we willrst consider the standard between different devices and theupper users between different access platorms.

As it can be seen rom Figure , the basic ramework o SOA application is on the basis o the data stream generatedby the perceive network rom the physical world, whichis with the basic physical properties o the world romthe underlying environmental sensing. In SOA architecture,these vast amounts o real context-aware data orm the basiso the entire application.

Since heterogeneous data processing is inevitably linkedto the Io middleware architecture based on SOA, a concrete

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Client

Data integration service layerOnline heterogeneous data

source bottom layer

Application

Operatingparser

Resultbuilder

Data deletion

Data query 

Data modication

Data query 

Upper services Lower services

Services based onXML data format

Services based onXML data format

XMLdocuments

XMLdocuments

Network database(structured data)

Sensor resources(semistructured data and

unstructured data)

F : Te Io data integration middleware based on SOA.

solution is proposed orthe metadata integration o heteroge-neous data which is as shown in Figure . Tis architecture isdivided into three basic processes, which rom top to bottomare the client application layer, the data integration layer, andthe Io heterogeneous data sources, as shown in Figure .

Te client applications include users unied access inter-ace ordata manipulation, which canbe a specic applicationor a web browser.

Data integration service layer [] is the core o thearchitecture and also the key to heterogeneous data integra-tion. In order to increase the intelligence and scalability o architecture and alleviate the burden on users, we design astructure that contains the upper and lower levels o service.Metadata ormat vary greatly since which are grounded inheterogeneous sensor sources []. o circumvent this obsta-cle, we express various types o data into XML ormat and setup rules to make operations on the metadata. Consequently,we rst converted the heterogeneous data in a unied XMLormat, on this basis, and then created the underlying data

integration services layer. Te upper layer services built ontop o the lower layer services and the underlying servicesare developed in an XML document based on the underlyingheterogeneous data sources.

Services o lower levels achieve our data access unc-tions: add, modiy, query, and delete and the upper serviceunction extracts the same unctionality rom the underlyingservice to the same service according to the data then ormsthe integrated data service unction. Application layer callcorresponding upper services according to the operationalrequirements, and then underlying data manipulation isspecied by the upper service based on data parameters romthe client calls; thus, whenthe underlying heterogeneous data

source changes, we simply update the underlying service andmap to the upper applications rather than make any changesto upper layers. Data integration implementation process iscompletely transparent to the user, which is compatible andinteroperable in different systems.

.. Evaluation.  In order to test the Io middleware archi-tecture based on SOA, we set up an indoor temperaturemonitoring system in practical environment. We deploy sensor nodes in three rooms, to monitor the indoor tempera-tures. Afer collection o the sensor data, the data is deliveredby a wireless multihop network rom sensor nodes to a basestation which is connected to a cluster.

In experiments, clusters include common PCs that are-core . GHzdesktop computerwith GB RAMand Ubun-tu operating system or the runtime environment. Althoughthey are generic computers, they satisy the requirements.

In the paper, the sensor nodes are IRIS nodes. IRIS nodesare produced by Crossbow echnology Inc. Tese sensorsare based on the Atmegal microprocessing chip and aRF RF chip which are working at . GHz and supportingthe IEEE ... communication protocol. Te nodes havethree times radio range and twice the program memory o MICA Motes and outdoor line-o-sight tests have a range asgreat as metersbetween nodes without amplication. TeIRIS not only has a longer transmission distance but also hasultralow power consumption and a longer battery lie.

In the test, equipment used is shown in Figure     andthe portal o the Io system or environment monitoring isshown in Figure . Some example o the collected sensory data is as shown in able   . Te monitoring system con-tinues evaluating or three months and collects about ve

million o the sensor data items. During the test period,we have supplemented and changed several types o thesensors without interrupting the system. When we add thenew equipment, some new proles will be added to themiddleware ramework while the system is still running.

We can draw some conclusions rom the result o theexperiment.

First, the SOA-based data processing middleware archi-tecture represents better adaptation to the Io multisensorand multistream application scenarios, which improve theheterogeneous data reusability and utilization value.

Second, the experiment result demonstrates the decou-pling power o middleware which makes it easier to establish

a unied heterogeneous inormation processing platorm ora diversity o applications in the Io.

Tird, the distributed deployment o middleware bringsbetter perormance optimization and achieves better loadbalancing in the cluster.

5. Conclusion

Tis paper discusses the development o the concept o theIo and gives a detailed description o the architecture o the Io. Based on characteristics o the architecture andchallenges o inormation usion in the Io, the paper designsa middleware platorm based on SOA architecture or the

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: Some examples o the collected sensory data.

Node ID Parent Board ID Voltage Humid hum temp pr temp Press accel    accel     accel     ime

. . :.

. . :.

  −   − . . :.

  −   − . . :.   −   − . . :.

  − . . :.

  − . . :.

. . :.

. . :.

. . :.

. . :.

F : Te equipment used in the demo.

F : Te portal o the Io system or environment monitoring.

integration o multisource heterogeneous inormation. Aferthat, we use the SOA data processing middleware to buildan environmentalmonitoring system or validation veriying.Trough theoretical analysis and experimental verication,the SOA pattern-based processing middleware architecturedesign is better adapted to the Io multisensor and multi-stream application scenarios, which improve the sensing datautilization value. Te SOA data processing middleware haslaid a solid oundation or data integration and interactionbetween different networking systems, simpliying the com-plexity o the system integration process and improving thereuse o components in the uture. In order to achieve better

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interaction between the different large-scale Io applications,the criteria with regard to unied data ormat are widely considered to be made or coordination o different systemsin relevant international organizations, research institutions,and enterprises.

Conflict of Interests

Te authors declare that there is no conict o interestsregarding the publication o this paper.

 Acknowledgments

Tis work is unded by the European Framework Pro-gram (FP) under Grant no. FP-PEOPLE--IRSES, theNational Natural Science Foundation o China under Grantnos. and and , the National Highechnology R&D Program o China under Grant no.AA, the NationalKey echnology R&D Program o 

China under Grant no. SQGXE-F, the NationalScience and echnology Major Projects o China underGrant nos. SinoProbe--- and ZX---,the Key Science echnology Program o Jilin Province o China under Grant no. ZDGG, the Key Scientic andechnological Project o Jilin Province o China under Grantno. GX, and the Fundamental Research Fundsor Central Universities o China under Grant no. JCKY-QKJC.

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