SPECIAL SECTION ON BIG DATA SERVICES AND COMPUTATIONAL INTELLIGENCEFOR INDUSTRIAL SYSTEMS

Received October 10, 2015, accepted October 20, 2015, date of publication October 26, 2015, date of current version October 29, 2015.

Digital Object Identifier 10.1109/ACCESS.2015.2493890

From Internet to Smart WorldHUANSHENG NING1, (Senior Member, IEEE), HONG LIU2, (Member, IEEE),JIANHUA MA3, (Member, IEEE), LAURENCE T. YANG4,5, (Senior Member, IEEE),YUELIANG WAN2, XIAOZHEN YE1, RUNHE HUANG3, (Member, IEEE)1School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China2Research Institute, Run Technologies Company, Ltd., Beijing 100192, China3Faculty of Computer and Information Sciences, Hosei University, Tokyo 102-8160, Japan4School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China5Department of Computer Science, St. Francis Xavier University, Antigonish, NS B2G 2W5, Canada

Corresponding author: H. Ning (ninghuansheng@ustb.edu.cn)

This work was supported in part by the Science and Technology Foundation of Beijing under Grant Z141100002714003, in part by theFundamental Research Funds for the Central Universities under Grant 06105031, in part by the National Natural Science Foundation ofChina under Grant 61471035, and in part by the Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research underGrant 25330270 and Grant 26330350.

ABSTRACT The development of informationization and intelligentization prompts Internet developingtoward a new era. A deep fusion among cyber space, physical space, social space, and thinking spacebrings a quaternionic cyber-physical-social-thinking hyperspace, based on which an embryo of smart worldis being established through heterogeneous spaces. The smart world is expected to be an attractive perspectiveinvolving ubiquitous sensing, computing, and communication to achieve comprehensive interconnections ofphysical perception, cyber interaction, social correlation, and cognitive thinking. In this paper, evolutionof the smart world is briefly introduced, and physical-based coordination, social-inspired interactivity,brain-abstracted cooperativity, and cyber-enabled homogeneity are, respectively, discussed as the maincharacteristics of the smart world.

INDEX TERMS Smart world, Internet of Things, cyber-physical-social system, hyperspace.

I. INTRODUCTIONThe development of informationization and intelligentizationhas brought a global digital revolution in recent decades,several research areas (e.g., Internet of Things (IoT), socialcomputing, and brain informatics) emerge to launch signi-ficative influences for academia and industry. The IoT asa representative system paradigm aims to realize interac-tions among ubiquitous things through heterogeneous spaces,and is characterized by comprehensive sensing, reliabletransmission, and intelligent processing to achieve pervasiveinterconnections, intelligence, and efficiency [1], [2]. Socialcomputing highlights socialized intelligence by capturingsocial dynamics, appointing social agents, and managingsocial knowledge to develop beyond personal computing,facilitating collaboration and social interactions. Braininformatics is based on web intelligence centric informa-tion technologies to enhance human brain data, information,and knowledge interactions. It brings an inevitable recon-figurable combination of emerging technologies to promptInternet developing into a new era, called smart world,in which the ubiquitous things establish dynamical and seam-less interconnections in the cyber-physical-social-thinkinghyperspace [3].

The smart world originates with an appearance ofcomputer networks, and Internet subsequently emerges

to address cyber entities’ interconnections in the cyberspace. Considering wireless networking and mobilecommunications being involved into the Internet, physicalobjects establish interactions with the cyber entities viastandard communication protocols. Accordingly, cyber-physical system appears as an integration of ubiquitousprocessing, networking, and computing, and realizes that thephysical objects are mapped into the cyber space as the cyberentities for more convenient interactions. Thereafter,social attributes (e.g., ownerships, and affiliation rela-tionships) are highlighted to address the human orientedinterconnections to establish the cyber-physical-socialsystem.

If social attributes are regarded as a person’s exter-nal elements, thinking related issues (e.g., emotion, self-awareness, and subconsciousness) will be a person’s internalelements. Considering a person’s both external and inter-nal elements, the cyber-physical-social space is requiredto evolve towards a wiser ecosystem with thinking partic-ipation. Human cognitive capacities (e.g. logic reasoning,and attention distribution) and society principles areinvolved for designing a harmonious ecosystem [4],and cyber-physical-social-thinking (CPST) hyperspace isestablished by merging the thinking space into thecyber-physical-social space. Human cognition along with

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interactions of data, information, knowledge and intelligenceare through the CPST hyperspace.

An embryo of the smart world is associated with a conceptof hyperworld, which originally refers to real-digital directmappings between physical space and cyber space involvinghyper-connected multi-worlds [5]. The hyperworld resem-bles a preliminary cyber-physical-social system, in whichthe social attributes address complicated interconnectionsthrough the cyber-physical-social space. Thereafter, the smartworld focuses on ubiquitous intelligence of things beingattached, embedded or blended with sensors, actuators,middlewares, interfaces, and other network components inpractical applications [6]. It covers dynamic contexts ofcomplex physical, human, social environments and the asso-ciated cyber space. A digital copy or counterpart of a realindividual (i.e., Real-I) is defined as a cyber individual(i.e., Cyber-I), and comprehensive mapping relationships areestablished between a Real-I and the corresponding oneor multiple Cyber-Is [7]. Along with distributed comput-ing developing towards cloud based web computing, mobilecommunication based mobile computing, and contextsbased social computing, the smart world becomes a cyberspace driven hyperspace to address the holographic data,information, knowledge, and wisdom oriented physical per-ception, cyber interaction, social correlation, and cognitivethinking.

FIGURE 1. The cyber-physical-social-thinking hyperspace.

II. THE CYBER-PHYSICAL-SOCIAL-THINKINGHYPERSPACEFig. 1 illustrates CPST hyperspace model involvingquaternionic cyber-physical-social-thinking dimensions.

• Physical space refers to natural and human-madesystems operated in applications, in which physicalobjects are perceived and controlled by ubiquitoussensors and actuators to establish interactions via infor-mation, communication and networking technologies(e.g., remote collaboration, real-time localization, andautonomy maintenance). The physical space mainlyaddresses the issues such as network infrastructures,heterogeneous interfaces, and interactive environments,in which semantic sensors, cooperative actuators,context-aware networks alongwith energy consumption,electromagnetic spectrum compatibility, and space-time

consistency should be considered to achieve seamlessmapping between physical space and cyber space.

• Cyber space is characterized by the discrete, logical,and switched computation, communication, and control.It refers to the generalized information resources,including digital abstractions to achieve interconnec-tions among the cyber entities. The cyber infrastructuresare required to support uniform standards and protocols,and to transform the cyber space into an intelligent infor-mation ecosystem. The holographic data management,on-demand resource management, and spontaneousservice management are required to support cyberinteractions.

• Social space is an integration of social attributes andsocial intra-/inter- relationships owned by human beingsand other physical objects/cyber entities. The socialspace is formally described in semantic representationsto address issues such as ownership control manage-ment, affiliation relationship modeling, trustworthinessevaluation, and human behavior formalization. Humanlearning principles (e.g., cognitive psychology, anddecision neuroscience) and social rules are introducedto enhance human-nature coexistence.

• Thinking space focuses on cognition issues of humanbeings and other things, which are reflections of humanbrains’ activities and things’ observations on objec-tive existences in the hyperspace. The thinking spacemainly addresses the processes of analysis, synthesis,judgment, and reasoning based on representationsand abstract conceptions. A concept of Internet ofThinking (IoTk) was first presented on an open forum‘‘Top 10 Questions in Intelligent Informatics/Computing’’ in World Intelligence Congress for TuringYear [8]. The IoTk is expected that human, nature,and society are collaborative beyond space-time con-straints, and human subjective initiative may breakcyber-physical-social limitations.

The CPST hyperspace emphasizes convergence tofacilitate integration, interconnection, and interaction in theheterogeneous environments. Seamless data, information,knowledge, and wisdom exchanging measurement forthe geographically dispersed individuals is anticipatedto enhance human thoughts to realize an aggregatedfunctionality. The quaternionic hyperspace convergence issignificative for the self-organization of cognitive thinking,and it is an attractive perspective of ‘‘thinking being accessed,transferred, discovered, and shared’’ like other cyber,physical and social resources.

III. MAIN CHARACTERISTICS AND CHALLENGESOF THE SMART WORLDThe smart world is established based on the cyber-physical-social-thinking hyperspace, and there are four maincharacteristics including physical-based coordination,social-inspired interactivity, brain-abstracted cooperativity,and cyber-enabled homogeneity, as shown in Fig. 2.

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FIGURE 2. The main characteristics of the smart world.

A. PHYSICAL-BASED COORDINATIONPhysical-based coordination means that the physicalobjects establish mutual assistance relationships involvingcritical infrastructures, heterogeneous interfaces, andinteractive environments. During the physical objects’coordination, there are several challenging issues. How todeal with an ultimate limit of Moore’s Law? How to guar-antee the time-space consistent between physical objects andthe corresponding cyber entities under the heterogeneoussensing, communication, and storage environments?How to realize exascale computing by breaking through thebottlenecks including memory, communication, reliability,and energy? The physical-based coordination includes thefollowing main aspects.

• ID-objects and nID-objects coordination: The identifierbased objects (i.e., ID-objects) and non-identifiers basedobjects (i.e., nID-objects) establish cooperativerelationships [9]. The non-identifiers mainly referto spatiotemporal, biometric and physicochemicalattributes, which are used for object recognition based ontemporal and spatial uniqueness, physiological attributes(e.g., fingerprint, hand geometry, iris, and palm vein),behavioral attributes (e.g., typing rhythm, and gait), andother nonunique attributes (e.g., frequency spectrum,and electromagnetic scattering). Note that thenID-objects as necessary supplements for ID-objectshave no available identifiers for direct identification,authentication, and addressing.

• Sensors and actuators coordination: The wirelesssensor-actuator networks are typical forms of sen-sors and actuators coordination with motivations ofautomation covering broad domains with real-timerequirements. The sensors act as detectors and con-verters to capture physical data for perception, andsemantic sensors should be designed to providesemantic-integration context awareness for supportingmeta-service based adaptability and scalability. Theactuators convert the received physical data intoaction commands to realize enhanced efficiency inself-adaptive modes, and collaborative actuators shouldbe organized in interconnected ecosystems to achieveaggregated functionality.

• Networks and contexts coordination: Networks andcontexts coordination propels context-aware networks,referring to network architectures, protocols, services,communications and applications. Information centricnetwork emerges as a context-aware paradigm [10],which applies content identifiers for enabling context-based operations through information centric channelaccess, adaptive routing, packet switching and resolu-tion functions. Network middlewares facilitate context-aware services such as social services, migratoryservices, location services, and multimedia services inheterogeneous networks.

B. SOCIAL-INSPIRED INTERACTIVITYSocial-inspired interactivity addresses the human beingsoriented applications in both physical and cyber spaces,in which a person is a comprehensive peer with othernetworked persons for unrestricted interaction and resourcesharing. During the data driven interconnections, Real-Is andCyber-Is are assigned with the capabilities of accessing trans-parency, dynamic participation, and accountability.

• Interactivity between a Real-I and a Cyber-I : Cyber-Iis a digital copy or counterpart of a Real-I with socialattribute considerations, and aims to achieve the perfectcopy of an individual’s internal behaviors. It is a com-prehensive digital organism to describe the mappingbetween a Real-I in the physical space and the cor-responding Cyber-Is in the cyber space. Interactivitybetween a Real-I and a Cyber-I is established, and theReal-I owns inherent and acquired relationships withother Real-Is or Cyber-Is. The Cyber-I is regarded asanother self in the cyber space, and adopts data aggrega-tions to address individual modeling in individual-awareapplications. The main interactive relationships includethe following aspects [7]: 1) enabling a Real-I to ownone or more Cyber-Is with symbiotic relationships in thecyber space; 2) enabling comprehensive human model-ing involving individual thinking cognition; 3) enablingcustomized services (e.g., individual-aware servicerecommendations) and other ubiquitous applications(e.g., service discovery).

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• Interactivity among multiple Cyber-Is: Social attributesreflect direct/indirect correlations so that socializedrelationships exist among multiple Cyber-Is such ascollaboration, ownership, communal sharing, equalitymatching, and authority ranking. A social network gameis an online community covering the main componentsof multi-identifier, status control, assets management,relationship management, resource management, andtrustworthiness management. Interactivity amongmultiple Cyber-Is are organized in autonomous modesto improve social intelligence, and socialized servicesbecome noteworthy for the Cyber-Is with socialawareness (e.g., social relationships and interactions)considerations. From the perspective of social network-ing services, the Cyber-Is’ interactivity can be analyzedfor identifying local and global social patterns, deter-mining influential entities, and monitoring social rela-tionship topology dynamics.

C. BRAIN-ABSTRACTED COOPERATIVITYBrain-abstracted cooperativity is a reflect of the IoTk,in which cognitive thinking is regarded as the control ofassociating including the process of analysis, synthesis,judgment, and reasoning based on representations andabstract conceptions. Cognitive thinking aims to perceive,interpret, represent and model the surrounding environmentsand contexts for decision-making and forecasting, and refersto thinking activities to establish direct mappings of cyber-thinking spaces [3]. Human physiological and mental char-acteristics (e.g., conditioned reflex, attention allocation, andemotional control) are applied for designing more spiritualinteractive mechanisms.

Emerging sensing technologies are applied for brainelectrical signal identification, brain information acquisition,human consciousness extraction, and human behaviortendency prediction. Comprehensive human brain datacollection realizes to copy and refine cognitive thinkingdata to support intelligent interactions. Meanwhile, cogni-tive thinking data collection is achieve for inter-mappingthrough cyber-physical-social spaces, in which human bodysensors are popular for detecting human brain wave andother parameters. Heterogeneous human body area networkcommunications are established for interconnections amongmultiple individuals. Brain-abstracted cooperativity servicesare provided to achieve synergetic thinking, and thinkingcoordination activities are launched to facilitate an optimuminteraction in the distributed environments. Brain-abstractedcooperativity promotes creative behaviors, activities, andevents for human society to achieve aggregated intelligentservices.

Meanwhile, Cyber-Is and other things also have brains toachieve ubiquitous intelligence, which brings several ethicalissues. For instance, how to realize harmonious interactionsbetween Real-Is’ real brain and Cyber-Is’ virtual brains?How to perform communication among a Real-I’s multipleCyber-Is’ brains? How to establish consistent interactions

FIGURE 3. The main aspects of cyber-enabled homogeneity.

between a person’s brain and a thing’s brain? Will be a cyberbrain more smarter than a real brain?Will does a thing’s braincontrol a person’s brain?

D. CYBER-ENABLED HOMOGENEITYCyber-enabled homogeneity refers to ubiquitous things withdifferent features developing towards an unity of the samenature driven in the cyber space. Almost all cyber entitiesare formalized by specific rules, models, and semantics.Existing approaches such as object oriented modeling,resource description framework (RDF), web ontologylanguage (OWL), and physical markup language (PML) withparticular applicability have emerged as dominant perspec-tives, and there is less unified cyber entity oriented model-ing framework for universal applications. During a physicalobject mapping into the cyber space as one or multiplecyber entities, the physical object’s behaviors, tendencies,and events should be associated with the corresponding cyberentities in dynamic representations. Fig. 3 shows the mainaspects of cyber-enabled homogeneity.

• Resource homogeneity: Resources refer to heteroge-neous elements of limited availability, and can beaccessed to support practical applications as essentialcomponents during network connections and datainteractions. Physical objects and other components areinvolved in the cyber space to ensure interactive resourcecross-sharing and cross-utilization. Network infrastruc-tures, communication channels, computing capabilities,memory storage, and frequency spectrum are typicalresources, for which on-demand strategies should bemore generalized with negligible differences in thesmart world. For instance, frequency spectrum resourcesare almost fully exploited and utilized, which may beaddressed by aggregate programming based on comput-ing and communication resources; Dynamic spectrumallocation may be efficiently addressed according to thesimilar algorithms as existing energy allocation.

• Service homogeneity: The service explosion is anoutcome of cloud computing, in which anything as aservice (XaaS) covers almost all forms of availableresources. Such heterogeneous resources are essentiallythe same, and service management confronts resourcesrelated issues including semantic resource description,on-demand resource allocation, spontaneous resourcediscovery, and cooperative resource sharing. Webservices apply simple object access protocol (SOAP),

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Web services description language (WSDL), universaldescription discovery and integration (UDDI) to sup-port dynamic service provisioning, and configuration ofcloud service infrastructures approaches homogeneousto deal with heterogeneous and dynamic requirements.Due to cloud data centers located in different geograph-ical locations, cloud services become homogeneousin user-centric web environments. Complex distributedservices should be suitably encapsulated, modulated,and invoked via building-block APIs.

• Functionality homogeneity: Though the things’ func-tions become more refined, core functions becomemore generalized. For instance, wearable devices havethe functions including sensing an individual’s data(e.g., human body signs, and tracking) based onshort-range wireless communication technologies(e.g., Bluetooth, WiFi, and near field communica-tion (NFC)), data analysis is performed for intelli-gent support and social interaction. Similarly, advancedmetering infrastructure (AMI) is an intelligent deviceto automatically measure, collect, store, and analyzepower information for supply-demand balance. In asense, wearable devices and AMI can be regardedas functionality homogeneous due to the commondata acquisition, information processing, knowledgeextraction, intelligent computing, and remote cloudstorage.

Considering increasing data center sizes restrict thesustainable growth of the remote and geographicallydistributed cloud services and network operators along withexplosive expansion of connections. Network architectures,topologies, and routing protocols have been designed toenhance network capacity and efficiency, and softwaredefined networks (SDN) emerge to manage network servicesthrough abstraction of lower-level functionality. TheSDN differ from network virtualization (NV) and networkfunctions virtualization (NFV), which create virtual tunnelsand functions to physical networks. While, the SDN essen-tially change physical networks to promote cyber-enabledhomogeneity, and bring the homogeneity of hardware com-ponents due to a centralized control plane separated from thetraffic forwarding or switching plane.

IV. CONCLUSIONIn this work, a quaternionic cyber-physical-social-thinkinghyperspace has been identified, and an embryo of smartworld is presented based on the heterogeneous spaces. Thesmart world is described according to the main characteristicsincluding physical-based coordination, social-inspired inter-activity, brain-abstracted cooperativity, and cyber-enabledhomogeneity, in which the challenging issues are accordinglydiscussed in the field of smart world. It indicates that thesmart world will be an attractive perspective to achieve aperfect convergence of cyber-physical-social-thinking hyper-space, and launches comprehensive interactions of data,information, knowledge and intelligence.

REFERENCES[1] R. Want, B. N. Schilit, and S. Jenson, ‘‘Enabling the Internet of Things,’’

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CRC Press, 2013.[3] H. Ning, H. Liu, J. Ma, L. T. Yang, and R. Huang, ‘‘Cybermat-

ics: Cyber–physical–social–thinking hyperspace based science and tech-nology,’’ Future Generat. Comput. Syst., 2015. [Online]. Available:http://dx.doi.org/10.1016/j.future.2015.07.012

[4] H. Ning and Z. Wang, ‘‘Future Internet of Things architecture: Likemankind neural system or social organization framework?’’ IEEECommun. Lett., vol. 15, no. 4, pp. 461–463, Apr. 2011.

[5] T. Kunii, J. Ma, and R. Huang, ‘‘Hyperworld modeling,’’ in Proc. Int. Conf.Vis. Inf. Syst., 1996, pp. 1–8.

[6] J. Ma, L. T. Yang, B. O. Apduhan, R. Huang, L. Barolli, and M. Takizawa,‘‘Towards a smart world and ubiquitous intelligence: A walkthroughfrom smart things to smart hyperspaces and UbicKids,’’ Int. J. PervasiveComput. Commun., vol. 1, no. 1, pp. 53–68, 2005.

[7] J. Ma, J. Wen, R. Huang, and B. Huang, ‘‘Cyber-individual meets braininformatics,’’ IEEE Intell. Syst., vol. 26, no. 5, pp. 30–37, Sep./Oct. 2011.

[8] Top 10 Questions Voting Result, The Open Forum on Top 10 Ques-tions in Intelligent Informatics/Computing. [Online]. Available: http://wi-consortium.org/blog/top10qi/, accessed 2015.

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HUANSHENG NING (SM’13) received theB.S. degree from Anhui University, in 1996,and the Ph.D. degree from Beihang University,in 2001. He is currently a Professor with theSchool of Computer and Communication Engi-neering, University of Science and TechnologyBeijing, China. He has authored over 50 papers injournals and international conferences/workshops.His current research interests include Internet ofThings, cybermatics, and electromagnetic sensing

and computing.

HONG LIU received the Ph.D. degree from theSchool of Electronic and Information Engineer-ing, Beihang University, China. She is currentlya Research Fellow with the Research Institute,Run Technologies Company, Ltd., Beijing, China.She focuses on the security and privacy issues inwearable devices, vehicle-to-grid networks, andInternet of Things. Her research interests includeauthentication protocol design, and securityformal modeling and analysis.

JIANHUA MA had 15 years’ working experiencewith the National University of Defense Tech-nology, Xidian University, and the University ofAizu, Japan. He is currently a Professor with theDepartment of Digital Media, Faculty of Com-puter and Information Sciences, Hosei University,Japan. He has authored over 200 papers, and editedover 20 books/proceedings and over 20 journalspecial issues. His research interests include mul-timedia, networks, ubiquitous computing, social

computing, and cyber intelligence. He is the Co-Founder of the IEEE Inter-national Conference on Ubiquitous Intelligence and Computing, the IEEEInternational Conference on Cyber, Physical and Social Computing, and theIEEE International Conference on Internet of Things.

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LAURENCE T. YANG received the B.E. degreein computer science from Tsinghua University,China, and the Ph.D. degree in computer sciencefrom the University of Victoria, Canada. He iscurrently a Professor with the School of ComputerScience and Technology, Huazhong University ofScience and Technology, China, and the Depart-ment of Computer Science, St. Francis XavierUniversity, Canada. His research interests includeparallel and distributed computing, and embed-

ded and ubiquitous/pervasive computing. His research is supported bythe National Sciences and Engineering Research Council and the CanadaFoundation for Innovation.

YUELIANG WAN received the Ph.D. degree fromthe School of Computer Science, Beijing Instituteof Technology, China. He is currently the Directorof the Research Institute with Run TechnologiesCompany, Ltd., Beijing, China. He focuses on thecontent security in Internet, multimedia analysis,and Internet search and mining. His research inter-ests include Internet multimedia retrieval, privacyprotection, and data center network.

XIAOZHEN YE received the B.E. degree from theSchool of Computer and Communication Engi-neering, University of Science and TechnologyBeijing, China, where she is currently pursuing thePh.D. degree. She focuses on visual target detec-tion and tracking. Her research interests includeselective sensing and virtual reality.

RUNHE HUANG received the Ph.D. degree incomputer science and mathematics from the Uni-versity of the West of England, in 1993. She hasbeen involved in the field of computer scienceand engineering since 1982. She is currentlya Professor with the Faculty of Computer andInformation Sciences, Hosei University, Japan.Her research fields include artificial intelligenceand its applications, distributed intelligence com-puting, big data mining and service computing,

mobile computing, ubiquitous intelligence computing, cloud computing, andhyper-world modeling. She is a member of ACM.

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