Social Internet of Things: Applications, architectures and protocols

Social Internet of Things: Applications, architectures and protocols

Future Generation Computer Systems 92 (2019) 959–960 Contents lists available at ScienceDirect Future Generation Computer Systems journal homepage: ...

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Future Generation Computer Systems 92 (2019) 959–960

Contents lists available at ScienceDirect

Future Generation Computer Systems journal homepage:


Social Internet of Things: Applications, architectures and protocols ∗

Seungmin Rho a , , Yu Chen b a b

Department of Media Software, Sungkyul University, Anyang-si, Korea State University of New York, Binghamton, USA

a b s t r a c t Enabling autonomous interactions between social networks and Internet of Things (IoTs) is an emerging interdisciplinary area and is leveraging modern promising paradigm of Social Internet of Things (SIoTs). Among other extensions of IoTs, SIoTs is among the latest hot topics. It provides a platform for worldwide interconnected objects to establish social relationships by trading-off their individuality for common interests and better services to users. This relationship among objects can be of co-location, co-work, parental, social or co-ownership. Due to the all-in-one nature of SIoTs, its architectural design, implementation, and operational manageability and maintenance are raising numerous prevalent concerns that are the challenges for researchers, academicians, engineers, standardization bodies and other market players. We have selected eleven research papers whose topics are closely related to this special issue. © 2018 Published by Elsevier B.V.

1. Introduction As a core technology of the fourth Industrial Revolution, development and spread of IoTs technology have exponentially increased connectivity between human to human, human to object, object to object, reinforcing an entry to hyper-connected society [1]. According to [2], a new value of fusion services is expected to appear afterward over the interconnection of billions of smart devices. In other words, in the hyper-connected society, intellectualized objects will not only apprehend what kind of situation human is in, understand what they want and in need (Context Aware), by itself (autonomous), offer and suggest what’s the best information to oneself, but also support to take control measures in the way that human wants (Enhance quality of life as an individual level, efficiency of organizational value chain) [3]. A field that enables creating a new innovative service (New Value) at a rapid pace, surpassing the improvement of existing service (Tapped Value) is a Social Internet of Things technology. According to [4], the Social Internet of Things (SIoT) is defined as an IoT where things are capable of establishing social relationships with other objects, autonomously with respect to humans. Also, The SIoT paradigm represents an ecosystem which allows people and smart objects to interact within a social structure of relationships [5]. SIoT environment surrounding an individual or organization supports obtaining variety and plenty of information and collected ∗ Corresponding author. E-mail addresses: [email protected] (S. Rho), [email protected] (Y. Chen). 0167-739X/© 2018 Published by Elsevier B.V.

Fig. 1. Social Internet of Things.

information (Big Data) gets to be an intelligent service through the process of sophisticated interference [6]. This signifies the dynamic form of mutual information in accordance with the purpose of the desired service, going beyond of simple sharing and level of reading regarding text, image and etc. in the existing Social Network Service. Moreover, with the range of Social Network Service being expanded from individual targeted to corporation targeted and being connected (United) with Internet of Things enables a business functional collaboration [7]. SIoTs is being accelerated to becoming one of the most popular future application paradigms by many state-of-the-art, quickly developing technologies, just name a few: IP-enabled embedded devices and smart objects, short range and long range communication technologies, data collection, analysis, processing and visualization tools from big market giants and its multifaceted advantages in network navigability, scalability, evaluation of objects’ trustworthiness, service composition, object discovery, behavior classification and prediction (see Fig. 1).


Editorial / Future Generation Computer Systems 92 (2019) 959–960

Based on these attributes of SIoT, a variety of research [8–10] is being discussed regarding a designing platform for the construction of SIoT service environment as well as vitalizations of application is being discussed. Also, other relevant research is being actively conducted, such as research [5,11] conducting an interference or classification of conclusion based on research about data collection within the SIoT environment and collected big data, and research [12,13] for maintaining a credibility of information and protection. Accordingly, this study examines core technology and consideration required in the perspective of technical elements (Architecture and Protocol) and service elements (Application) that these kinds of SIoT environmental change can bring. Firstly, the future platform technology required for construction of SIoT service environment is addressed in the study [14–18], quality of service and application service field is in the study [19–24]. 2. Conclusion Finally, the guest editors’ special thanks go to Prof. Peter Sloot and all editorial staffs for their valuable supports throughout the preparation and publication of this special issue. We would like to thank all authors for their contributions to this special issue. We also extend our thanks to the external reviewers for their time and efforts in reviewing the manuscripts. References [1] Xuanxia Yao, Zhi Chen, Ye Tian, A lightweight attribute-based encryption scheme for the internet of things, Future Gener. Comput. Syst. (2015) http: // [2] I. Farrisa, L. Militano, L. Nitti, A. Ieraa, MIFaaS: A mobile-IoT-federation-as-aservice model for dynamic cooperation of IoT cloud providers, Future Gener. Comput. Syst. (2017) [3] Zheng Yan, Jun Liu, Athanasios V. Vasilakos, Laurence T. Yang, Trustworthy data fusion and mining in internet of things, Future Gener. Comput. Syst. (2015). [4] L. Atzori, A. Iera, G. Morabito, M. Nitti, The social internet of things (siot)– when social networks meet the internet of things: concept, architecture and network characterization, Comput. Netw. 56 (16) (2012) 3594–3608. [5] Ruixin Ma, Kai Wang, Tie Qiua, Arun Kumar Sangaiah, Dan Lin, Hannan Bin Liaqat, Feature-based compositing memory networks for aspect-based sentiment classification in social internet of things, Future Gener. Comput. Syst. 92 (2019) 879–888, [6] Muhammad Babar, Fahim Arif, Smart urban planning using big data analytics to contend with the interoperability in internet of things, Future Gener. Comput. Syst. (2017) [7] Bo Yuan, Lu Liu, Nick Antonopoulos, Efficient service discovery in decentralized online social networks, Future Gener. Comput. Syst. (2017) http://dx.doi. org/10.1016/j.future.2017.04.022. [8] Bilal Afzal, Muhammad Umair, Ghalib Asadullah Shah, Ejaz Ahmed, Enabling IoT platforms for social IoT applications: Vision, feature mapping, and challenges, Future Gener. Comput. Syst. 92 (2019) 718–731, 1016/j.future.2017.12.002. [9] Fadi Al-Turjman, 5G-enabled devices and smart-spaces in social-IoT: An overview, Future Gener. Comput. Syst. 92 (2019) 732–744, 10.1016/j.future.2017.11.035. [10] Son N. Han, Noel Crespi, Semantic service provisioning for smart objects: Integrating IoT applications into the web, Future Gener. Comput. Syst. (2019) [11] Mohammed Zaki Hasan, Fadi Al-Turjman, SWARM-based data delivery in social internet of things, Future Gener. Comput. Syst. 92 (2019) 821–836, [12] Vishal Sharma, Ilsun You, Dushantha Nalin K. Jayakody, Mohammed Atiquzzaman, Cooperative trust relaying and privacy preservation via edgecrowdsourcing in social internet of things, Future Gener. Comput. Syst. 92 (2019) 758–776, [13] Javier Lopez, Ruben Rios, Feng Bao, Guilin Ang volving privacy: From sensors to the Internet of Things, Future Gener. Comput. Syst. (2017) http://dx.doi. org/10.1016/j.future.2017.04.045. [14] Hao Wu, Kun Yue, Bo Li, Binbin Zhang, Ching-Hsien Hsu, Collaborative QoS prediction with context-sensitive matrix factorization, Future Gener. Comput. Syst. (2017)

[15] Bo-Wei Chen, Nik Nailah Binti Abdullah, Sangoh Park, Y. Gu, Efficient multiple incremental computation based on kernel ridge regression with bayesian uncertainty modeling, Future Gener. Comput. Syst. (2017) 10.1016/j.future.2017.08.053. [16] Guangjie Han, Lina Zhou, Hao Wang, Wenbo Zhang, Sammy Chan, A source location protection protocol based on dynamic routing in wsns for the social internet of things, Future Gener. Comput. Syst. (2017) 1016/j.future.2017.08.044. [17] Caifeng Zou, Huifang Deng, Jiafu Wan, Zhongren Wang, Pan Deng, Mining and updating association rules based on fuzzy concept lattice, Future Gener. Comput. Syst. (2017) [18] Bindiya Jain, Gursewak Brar, Jyoteesh Malhotra, Shalli Rani, Gurbinder Singh Brar, Syed Hassan Ahmed, A cross-layer protocol for traffic management in social internet of vehicles, Future Gener. Comput. Syst. (2017) http://dx.doi. org/10.1016/j.future.2017.11.019. [19] Awais Ahmad, Murad Khan, Anand Paul, Sadia Din, M. Mazhar Rathore, Gwanggil Jeon, Gyu Sang Choi, Towards modeling and optimization of features selection in big data based social internet of things, Future Gener. Comput. Syst. (2017) [20] Jianqi Liu, Jiafu Wan, Qinruo Wang, Bi Zeng, Shaoliang Fang, A lightweight and robust two-factor authentication scheme for personalised healthcare systems using wireless medical sensor networks, Future Gener. Comput. Syst. (2017) in press. [21] Zheng Yan, Haomeng Xie, Peng Zhang, Brij B. Gupta, Flexible data access control in d2d communications, Future Gener. Comput. Syst. (2017) http: // [22] Seokcheol Lee, Sungjin Kim, Ken Choi, Taeshik Shon, Game theory-based security vulnerability quantification for social internet of things, Future Gener. Comput. Syst. (2017) [23] Abebe Abeshu Diro, Naveen Chilamkurti, Distributed attack detection scheme using deep learning approach for internet of things, Future Gener. Comput. Syst. (2017) [24] Seungwan Hong, Sangho Park, Lee Won Park, Minseo Jeon, Hangbae Chang, An analysis of security systems for electronic information for establishing secure internet of things environments: Focusing on research trends in the security field in South Korea, Future Gener. Comput. Syst. (2017) 1016/j.future.2017.10.019.

Dr. Seungmin Rho is currently a faculty of Department of Multimedia at Sungkyul University. He received his Ph.D. degree in Computer Science from Ajou University, Korea in 2008. In 2008-2009, he was a Postdoctoral Research Fellow at the Computer Music Lab of the School of Computer Science in Carnegie Mellon University. His current research interests include database, big data analysis, music retrieval, multimedia systems, machine learning, knowledge management as well as computational intelligence. He has published more than 200 papers in refereed journals and conference proceedings in these areas. He has been involved in more than 20 conferences and workshops as various chairs and more than 30 conferences/workshops as a program committee member. He has been appointed as an Editor-in-Chief in Journal of Platform Technology since 2013. He has edited a number of international journal special issues as a guest editor, such as Enterprise Information Systems, Multimedia Systems, Information Fusion, ACM Transactions on Embedded Computing, Journal of Real-Time Image Processing, Future Generation Computer Systems, Engineering Applications of Artificial Intelligence, New Review of Hypermedia and Multimedia, Multimedia Tools and Applications, Personal and Ubiquitous Computing, Telecommunication Systems, Ad Hoc & Sensor Wireless. Dr. Yu Chen is an Associate Professor and the Graduate Program Director of Electrical and Computer Engineering Department at the Binghamton University - State University of New York (SUNY). He received the Ph.D. in Electrical Engineering from the University of Southern California (USC) in 2006. Leading the Ubiquitous Smart & Sustainable Computing (US2C) Lab, his research interest lies in Security of Internet of Things; Cloud/Fog Computing; and Smart Surveillance. He has authored or co-authored more than 100 research papers in refereed journals, conferences, and book chapters. His research has been funded by NSF, DoD, AFOSR, AFRL, New York State, and industrial partners. He has served as reviewer for NSF panels and for international journals, and on the Technical Program Committee (TPC) of prestigious conferences. He is a member of ACM, IEEE (Computer Society & Communication Society), and SPIE.