On the Application of Social Internet of Things with Fog Computing: A New Paradigm for Traffic Information Sharing System

2018 ◽  
Author(s):  
Van Loc Tran ◽  
Anik Islam ◽  
Jeevan Kharel ◽  
Soo Young Shin
Keyword(s):  
Internet Of Things ◽  
Information Sharing ◽  
Fog Computing ◽  
Traffic Information ◽  
New Paradigm ◽  
Social Internet Of Things

scholarly journals A Novel Fog-IoT based Framework for Improving Performance of Cloud Computing

2019 ◽  
Vol 8 (12S) ◽  
pp. 889-895
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Secure Communication ◽  
Fog Computing ◽  
Cloud Service ◽  
Raspberry Pi ◽  
New Paradigm ◽  
Privacy And Security ◽  
Security Issues ◽  
Iot Devices

Internet-of-Things (IoT) has been considered as a fundamental part of our day by day existence with billions of IoT devices gathering information remotely and can interoperate within the current Internet framework. Fog computing is nothing but cloud computing to the extreme of network security. It provides computation and storage services via CSP (Cloud Service Provider) to end devices in the Internet of Things (IoT). Fog computing allows the data storing and processing any nearby network devices or nearby cloud endpoint continuum. Using fog computing, the designer can reduce the computation architecture of the IoT devices. Unfortunitily, this new paradigm IoT-Fog faces numerous new privacy and security issues, like authentication and authorization, secure communication, information confidentiality. Despite the fact that the customary cloud-based platform can even utilize heavyweight cryptosystem to upgrade security, it can't be performed on fog devices drectly due to reseource constraints. Additionally, a huge number of smart fog devices are fiercely disseminated and situated in various zones, which expands the danger of being undermined by some pernicious gatherings. Trait Based Encryption (ABE) is an open key encryption conspire that enables clients to scramble and unscramble messages dependent on client qualities, which ensures information classification and hearty information get to control. Be that as it may, its computational expense for encryption and unscrambling stage is straightforwardly corresponding to the multifaceted nature of the arrangements utilized. The points is to assess the planning, CPU burden, and memory burden, and system estimations all through each phase of the cloud-to-things continuum amid an analysis for deciding highlights from a finger tapping exercise for Parkinson's Disease patients. It will be appeared there are confinements to the proposed testbeds when endeavoring to deal with upwards of 35 customers at the same time. These discoveries lead us to a proper conveyance of handling the leaves the Intel NUC as the most suitable fog gadget. While the Intel Edison and Raspberry Pi locate a superior balance at in the edge layer, crossing over correspondence conventions and keeping up a self-mending network topology for "thing" devices in the individual territory organize.

scholarly journals Trust management in social Internet of vehicles: Factors, challenges, blockchain, and fog solutions

2019 ◽  
Vol 15 (1) ◽  
pp. 155014771982582 ◽  
Author(s):  
Razi Iqbal ◽  
Talal Ashraf Butt ◽  
Muhammad Afzaal ◽  
Khaled Salah
Keyword(s):  
Internet Of Things ◽  
Trust Management ◽  
Vehicular Networks ◽  
High Efficiency ◽  
Fog Computing ◽  
Trust Model ◽  
The Internet ◽  
Internet Of Vehicles ◽  
Social Internet Of Things ◽  
Trust Models

The Internet of things is the next stage in the evolution of the Internet that is being materialized with the integration of billions of smart objects. The state-of-the-art communication technologies have enabled the previously isolated devices to become an active part of the Internet. This constant connectivity opens new avenues for novel applications such as the realization of social Internet of things and its subdomain the social Internet of vehicles. Socializing requires sharing of information that entails trust, especially in an open and broad social environment. This article highlights the key factors involved in conceptualizing an efficient trust model for social Internet of vehicles. Furthermore, it focuses on the unique challenges involved in designing the trust models for social Internet of vehicles. Several trust models exist in literature; however, most of the existing trust models are specific to their domains, for example, Internet of things, social Internet of things, or general vehicular networks. This article presents a brief review of the trust models that have the potential to be implemented in Social Internet of vehicles. Finally, the authors present an overview of how trending concepts and emerging technologies like blockchain and fog computing can assist in developing a trust-based social Internet of vehicles model for high-efficiency, decentralized architecture and dynamic nature of vehicular networks.

scholarly journals An efficient fog computing for comprising approach to avoid data theft attack

2018 ◽  
Vol 7 (2.8) ◽  
pp. 680
Author(s):  
T Pavan Kumar ◽  
B Eswar ◽  
P Ayyappa Reddy ◽  
D Sindhu Bhargavi
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Paradigm Shift ◽  
Fog Computing ◽  
Edge Computing ◽  
New Paradigm ◽  
Computing Power ◽  
Data Theft

Cloud computing has become a new paradigm shift in the IT world because of its revolutionary model of computing. It provides flexibility, scalability, and reliability and decreased operational and support expenses for an organization. The Enterprise edition software’s are very costly and maintaining a separate IT team and maintaining their own servers is very expensive and that’s the reason why most of the companies are opting for Cloud computing over enterprise edition of the software. However, few organization cloud customers are not willing to step to cloud computing up on a big scale because of the safety problems present in cloud computing. One more disadvantage of Cloud is it’s not suitable for another revolutionary technology i.e.IoT(Internet of things)In this paper we are going to present the Advantages of Fog Computing and Decoy technology to address the security in cloud computing by extending it into fog computing.Fog Computing is a new paradigm in which the computing power moves to the edge of the network. So, it’s also called as Edge Computing.

scholarly journals Decision Making in Internet of Things (IoT) : A Systematic Literature Review

2020 ◽  
Vol 5 (1) ◽  
pp. 51-65
Author(s):  
Hespri Yomeldi
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Research Question ◽  
Fog Computing ◽  
The Internet ◽  
New Paradigm ◽  
Decision Making Factors ◽  
Decision Making System ◽  
Machine Communication ◽  
Support Decision Making

Today’s internet technologies support everything that human do. By using integrated technologies the things that connected to internet can provide data. The Internet of Things (IoT) is the new paradigm in provide the data without human communicated. The IoT system support machine to machine communication that can be used to develop smart services that can generate a lot of data. This exponential data can support a decision making. The decision making system depend on availability and reliability of data. This study focus to how the Internet of Thing support decision making system. With a survey of literature to understand the trends, models and factors of decision making in IoT based on previous research. This survey following step by conduct the research question (RQ), then search and observation the previous research from database journal. Based on reviewing 26 articles, this study conclude that the trends of decision making in IoT are implemented on Manufacturing and Industry, Healthcare, Agriculture and Transportation. Besides that the decision model that can support by IoT used Fog Computing,  Fuzzy, Game Theoritic, Clustering Based on Multimodal Data Correlation, etc. Meanwhile the decision making factors that influenced by IoT like Latency, data-driven, security, data reliability and accurate.  The integrated of model and point of interest on decision making in IoT should be improved.  It will be the opportunities and challenge in IoT to support decision making in future.

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.

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.

scholarly journals Novel Resource Allocation Algorithms for the Social Internet of Things Based Fog Computing Paradigm

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Sungwook Kim
Keyword(s):  
Resource Allocation ◽  
Internet Of Things ◽  
Mobile Devices ◽  
Fog Computing ◽  
Nash Bargaining ◽  
Bargaining Solution ◽  
Research Issues ◽  
The Social ◽  
Social Internet Of Things ◽  
Allocation Algorithms

Social Internet of Things (SIoT) is a control paradigm by the integration of social networking concepts into the Internet of Things, and Fog Computing (FC) is an emerging technology that is aimed at moving the cloud computing facilities to the access network. Recently, the SIoT and FC models are combined by using complementary features, and a new Social Fog IoT (SFIoT) paradigm has been developed. In this paper, we design novel resource allocation algorithms for the SFIoT system. Considering the social relationship and each preference, mobile devices in the SFIoT effectively share the limited computation and communication resources of FC operators. To formulate the interaction among mobile devices and FC operator, we adopt the basic concept of two game models: voting and bargaining games. Bicooperative voting approach can make control decisions for the resource allocation method, and Nash bargaining solution is used to effectively distribute the computation resource to different application tasks. Based on the two-phase game model, the proposed scheme takes various benefits in a fair-efficient way. Through the extensive simulation experiments, we can validate the superiority of our proposed approach by the fact that it produces a mutually acceptable agreement among game players and significantly outperforms the existing protocols. Last, we point out the further challenges and future research issues about the SFIoT paradigm opportunities.

scholarly journals Internet of Things Framework for Home Care Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Biljana Risteska Stojkoska ◽  
Kire Trivodaliev ◽  
Danco Davcev
Keyword(s):  
Internet Of Things ◽  
Home Care ◽  
Detection System ◽  
Fog Computing ◽  
Fire Detection ◽  
New Paradigm ◽  
Case Scenario ◽  
Distributed Approach ◽  
Care Systems ◽  
Fuzzy Logic Approach

The increasing average age of the population in most industrialized countries imposes a necessity for developing advanced and practical services using state-of-the-art technologies, dedicated to personal living spaces. In this paper, we introduce a hierarchical distributed approach for home care systems based on a new paradigm known as Internet of Things (IoT). The proposed generic framework is supported by a three-level data management model composed of dew computing, fog computing, and cloud computing for efficient data flow in IoT based home care systems. We examine the proposed model through a real case scenario of an early fire detection system using a distributed fuzzy logic approach. The obtained results prove that such implementation of dew and fog computing provides high accuracy in fire detection IoT systems, while achieving minimum data latency.

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