scholarly journals Structural Balance of Social Internet of Things Networks with Ambiguous Relationships

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Hongfei Zhang ◽  
Li Zhu ◽  
Haifeng Du ◽  
Li Zhang ◽  
Kaiqi Zhang ◽  
...  
Keyword(s):  
Social Networks ◽  
Internet Of Things ◽  
Structural Changes ◽  
Dynamical Evolution ◽  
Human Beings ◽  
Smart Objects ◽  
Service Matching ◽  
Signed Networks ◽  
Structural Balance ◽  
Social Internet Of Things

In the social Internet of Things, social networks can be built among smart objects or between smart objects and people just like human beings. One of the factors that determines the effect and efficiency of service matching in SIoT is the structure of social networks. In this paper, we exploit the theory of structural balance in signed networks to optimize SIoT network structures to provide a friendly and stable environment as well as a solid foundation for service matching of social Internet of Things. Next, besides being friends or enemies, which are traditional relationships of structural balance or structural changes in signed networks, in our research, we introduce the ambiguous relationship which is the certain state between the hostile and the friendly status and we discuss the meaning and significance of ambiguous relationship in dynamical changes of structural balance in SIoT networks. Based on previous studies, we apply an enhanced objective function and a modified approach concerning the ambiguous relationship towards the dynamical change process. Experiments show that our approach is more effective and efficient than former studies in optimizing dynamical evolution of structural balance in signed networks of SIoT.

Social Internet of Things in Healthcare

2017 ◽  
pp. 88-111 ◽  
Author(s):  
Cristina Elena Turcu ◽  
Corneliu Octavian Turcu
Keyword(s):  
Social Networks ◽  
Internet Of Things ◽  
Agent Technology ◽  
Smart Devices ◽  
Collaborative Environments ◽  
The Social ◽  
Social Internet Of Things ◽  
New Applications ◽  
Future Vision

This chapter presents a future vision for healthcare, which will involve smart devices, Internet of Things, and social networks, that make this vision a reality. The authors present the necessary background by introducing the Social Internet of Things paradigm. Agent technology seems to be a promising approach in the adoption of the Social Internet of Things in collaborative environments with increased autonomy and agility, like healthcare is. Also, it is examined challenges to the adoption of the Social Internet of Things in healthcare in order to facilitate new applications and services in more effective and efficient ways.

scholarly journals Towards a Social Internet of Things Enabled Framework for Supply Community Networks

2019 ◽  
Vol 13 (1) ◽  
pp. 121
Author(s):  
Mohamed Omar ◽  
Paul Mason
Keyword(s):  
Social Networks ◽  
Internet Of Things ◽  
Current Literature ◽  
Community Networks ◽  
Matlab Simulation ◽  
Community Network ◽  
Baked Goods ◽  
Social Internet Of Things ◽  
Autonomous Objects ◽  
A Chain

Social Internet of Things (SIoT) is one of several emerging internet paradigms, signaling the inevitable fusion of Internet of Things with Social Networks. This paper demonstrates the feasibility of applying an existing SIoT framework to Supply Community Networks (SCN). a term we use to describe the changing pattern of supply chains whose morphology continues to evolve from traditional linear continuums, into ostensibly mesh-like structures. Specifically, we identify an appropriate SIoT architecture from current literature which was used as a basis for realizing the notion of SCN, where in this case the ‘members’ are autonomous objects (Supply Community Agents, or SCA) working on behalf of member organizations (suppliers, manufacturers, retailers, etc.) and whose generic object architecture we extended by specifying interfaces to various member functions that all such agents must possess to engage in the exchange of goods/services information and remittance one would expect whether part of a chain or as here, a network (or networks). We substantiate our claims of feasibility using stochastic MATLAB simulation of a baked-goods SCN scenario. Results showed that the modified SIoT framework exhibited the flexibility required by SCAs when operating as part of a Supply Community Network so that they can effectively discharge their responsibilities in delivering the services needed by other member agents of a SCN.

scholarly journals High-Capacity Robust Behavioral Steganography Method Based on Timestamp Modulation across Social Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Mingliang Zhang ◽  
Xiangyang Luo ◽  
Pei Zhang ◽  
Hao Li ◽  
Yi Zhang ◽  
...  
Keyword(s):  
Social Networks ◽  
Internet Of Things ◽  
Data Privacy ◽  
Common Property ◽  
High Capacity ◽  
Secret Message ◽  
Embedding Capacity ◽  
Social Internet Of Things ◽  
High Embedding Capacity ◽  
Interaction Behaviors

Social Internet of Things (SIoT) is an emerging field that combines IoT and Internet, which can provide many novel and convenient application scenarios but still faces challenges in data privacy protection. In this paper, we propose a robust behavioral steganography method with high embedding capacity across social networks based on timestamp modulation. Firstly, the IoT devices on the sending end modulate the secret message to be embedded into a timestamp by using the common property on social networks. Secondly, the accounts of multiple social networks are used as the vertices, and the timestamp mapping relationship generated by the interaction behaviors between them is used as the edges to construct a directed secret message graph across social networks. Then, the frequency of interaction behaviors generated by users of mainstream social networks is analyzed; the corresponding timestamps and social networks are used to implement interaction behaviors based on the secret message graph and the frequency of interaction behaviors. Next, we analyze the frequency of interaction behaviors generated by users in mainstream social networks, implement the interaction behaviors according to the secret message graph and the frequency of interaction behaviors in the corresponding timestamps and social networks, and combine the redundant mapping control to complete the embedding of secret message. Finally, the receiver constructs the timestamp mapping relationship through the shared account, key, and other parameters to achieve the extraction of secret message. The algorithm is robust and does not have the problem that existing multimedia-based steganography methods are difficult to extract the embedded messages completely. Compared with existing graph theory-based social network steganography methods, using timestamps and behaviors frequencies to hide message in multiple social networks increases the cost of detecting covert communication and improves concealment of steganography. At the same time, the algorithm uses a directed secret message graph to increase the number of bits carried by each behavior and improves the embedding capacity. A large number of tests have been conducted on mainstream social networks such as Facebook, Twitter, and Weibo. The results show that the proposed method successfully distributes secret message to multiple social networks and achieves complete extraction of embedded message at the receiving end. The embedding capacity is increased by 1.98–4.89 times compared with the existing methods SSN, NGTASS, and SGSIR.

scholarly journals Social Internet of Things: vision, challenges, and trends

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Mozhgan Malekshahi Rad ◽  
Amir Masoud Rahmani ◽  
Amir Sahafi ◽  
Nooruldeen Nasih Qader
Keyword(s):  
Social Networks ◽  
Internet Of Things ◽  
Trust Management ◽  
Process Time ◽  
New Paradigm ◽  
Simulation Tools ◽  
Social Internet Of Things ◽  
Common Goals ◽  
Main Components ◽  
Evaluation Parameters

AbstractIoT describes a new world of billions of objects that intelligently communicate and interact with each other. One of the important areas in this field is a new paradigm-Social Internet of Things (SIoT), a new concept of combining social networks with IoT. SIoT is an imitation of social networks between humans and objects. Objects like humans are considered intelligent and social. They create their social network to achieve their common goals, such as improving functionality, performance, and efficiency and satisfying their required services. Our article’s primary purpose is to present a comprehensive review article from the SIoT system to analyze and evaluate the recent works done in this area. Therefore, our study concentrated on the main components of the SIoT (Architecture, Relation Management, Trust Management, web services, and information), features, parameters, and challenges. To gather enough information for better analysis, we have reviewed the articles published between 2011 and December 2019. The strengths and weaknesses of each article are examined, and effective evaluation parameters, approaches, and the most used simulation tools in this field are discussed. For this purpose, we provide a scientific taxonomy for the final SIoT structure based on the academic contributions we have studied. Ultimately we observed that the evaluation parameters are different in each element of the SIoT ecosystem, for example for Relation Management, scalability 29% and navigability 22% are the most concentrated metrics, in Trust Management, accuracy 25%, and resiliency 25% is more important, in the web service process, time 23% and scalability 16% are the most mentioned and finally in information processing, throughput and time 25% are the most investigated factor. Also, Java-based tools like Eclipse has the most percentage in simulation tools in reviewed literature with 28%, and SWIM has 13% of usage for simulation.

Social Internet of Things in Healthcare

2017 ◽  
pp. 266-295
Author(s):  
Cristina Elena Turcu ◽  
Corneliu Octavian Turcu
Keyword(s):  
Social Networks ◽  
Internet Of Things ◽  
Agent Technology ◽  
Smart Devices ◽  
Collaborative Environments ◽  
The Social ◽  
Social Internet Of Things ◽  
New Applications ◽  
Future Vision

This chapter presents a future vision for healthcare, which will involve smart devices, Internet of Things, and social networks, that make this vision a reality. The authors present the necessary background by introducing the Social Internet of Things paradigm. Agent technology seems to be a promising approach in the adoption of the Social Internet of Things in collaborative environments with increased autonomy and agility, like healthcare is. Also, it is examined challenges to the adoption of the Social Internet of Things in healthcare in order to facilitate new applications and services in more effective and efficient ways.

scholarly journals Busca de Serviços Baseada em Perfis Sociais dos Objetos em uma Rede SIoT Urbana

2019 ◽  
Author(s):  
Iury Rogerio Sales de Araujo ◽  
Mikaelly Felicio Pedrosa ◽  
Eudisley Gomes dos Anjos ◽  
Fernando Menezes Matos
Keyword(s):  
Social Networks ◽  
Internet Of Things ◽  
Service Discovery ◽  
Ad Hoc ◽  
Social Internet Of Things ◽  
Service Interaction ◽  
The Creation ◽  
Social Profiles

The service interaction provided by objects in IoT networks enables the creation of advanced services to answer application requests. However, the growing number of objects into the IoT network, besides its ad hoc structure, are disturbing some functionalities, such as service discovery. Therefore, when searching for services, the navigability is impaired because the system needs to sweep a great quantity of objects without a previous organization. Social Internet of Things (SIoT) emerged as an alternative to solve several problems faced by IoT through the concept of social networks. In SIoT each object has its own social profile, which contains its characteristics and information, and are organize by relationships. Thus, this research propose a solution for service discovery in a SIoT network. This solution uses the relationships between objects to improve the discovery scalability and considers their social profiles to meet more satisfactorily the requisitions. Simulated results demonstrates the solution performance to answer service requisitions in an urban SIoT network.

Enabling smart objects discovery via constructing hypergraphs of heterogeneous IoT interactions

2016 ◽  
Vol 44 (1) ◽  
pp. 110-124 ◽  
Author(s):  
Jooik Jung ◽  
Sejin Chun ◽  
Xiongnan Jin ◽  
Kyong-Ho Lee
Keyword(s):  
Internet Of Things ◽  
Social Relationships ◽  
Social Relations ◽  
Smart Home ◽  
New Paradigm ◽  
Sensors And Actuators ◽  
Smart Objects ◽  
The Social ◽  
Social Internet Of Things ◽  
The Internet Of Things

Recent advances in the Internet of Things (IoT) have led to the rise of a new paradigm: Social Internet of Things (SIoT). However, the new paradigm, as inspired by the idea that smart objects will soon have a certain degree of social consciousness, is still in its infant state for several reasons. Most of the related works are far from embracing the social aspects of smart objects and the dynamicity of inter-object social relations. Furthermore, there is yet to be a coherent structure for organising and managing IoT objects that elicit social-like features. To fully understand how and to what extent these objects mimic the behaviours of humans, we first model SIoT by scrutinising the distinct characteristics and structural facets of human-centric social networks. To elaborate, we describe the process of profiling the IoT objects that become social and classify various inter-object social relationships. Afterwards, a novel discovery mechanism, which utilises our hypergraph-based overlay network model, is proposed. To test the feasibility of the proposed approach, we have performed several experiments on our smart home automation demo box built with various sensors and actuators.

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