scholarly journals An Agent-Based Model of Task-Allocation and Resource-Sharing for Social Internet of Things

IoT ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 187-204
Author(s):  
Kashif Zia ◽  
Umar Farooq ◽  
Muhammad Shafi ◽  
Muhammad Arshad

The things in the Internet of Things are becoming more and more socially aware. What social means for these things (more often termed as “social objects”) is predominately determined by how and when objects interact with each other. In this paper, an agent-based model for Social Internet of Things is proposed, which features the realization of various interaction modalities, along with possible network structures and mobility modes, thus providing a novel model to ask interesting “what-if” questions. The scenario used, which is the acquisition of shared resources in a common spatial and temporal world, demands agents to have ad-hoc communication and a willingness to cooperate with others. The model was simulated for all possible combinations of input parameters to study the implications of competitive vs. cooperative social behavior while agents try to acquire shared resources/services in a peer-to-peer fashion. However, the main focus of the paper was to analyze the impact of profile-based mobility, which has an underpinning on parameters of extent and scale of a mobility profile. The simulation results, in addition to others, reveal that there are substantial and systematic differences among different combinations of values for extent and scale.

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3257
Author(s):  
Arne Bochem ◽  
Benjamin Leiding

Today, increasing Internet of Things devices are deployed, and the field of applications for decentralized, self-organizing networks keeps growing. The growth also makes these systems more attractive to attackers. Sybil attacks are a common issue, especially in decentralized networks and networks that are deployed in scenarios with irregular or unreliable Internet connectivity. The lack of a central authority that can be contacted at any time allows attackers to introduce arbitrary amounts of nodes into the network and manipulate its behavior according to the attacker’s goals, by posing as a majority participant. Depending on the structure of the network, employing Sybil node detection schemes may be difficult, and low powered Internet of Things devices are usually unable to perform impactful amounts of work for proof-of-work based schemes. In this paper, we present Rechained, a scheme that monetarily disincentivizes the creation of Sybil identities for networks that can operate with intermittent or no Internet connectivity. We introduce a new revocation mechanism for identities, tie them into the concepts of self-sovereign identities, and decentralized identifiers. Case-studies are used to discuss upper- and lower-bounds for the costs of Sybil identities and, therefore, the provided security level. Furthermore, we formalize the protocol using Colored Petri Nets to analyze its correctness and suitability. Proof-of-concept implementations are used to evaluate the performance of our scheme on low powered hardware as it might be found in Internet of Things applications.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jonatan Almagor ◽  
Stefano Picascia

AbstractA contact-tracing strategy has been deemed necessary to contain the spread of COVID-19 following the relaxation of lockdown measures. Using an agent-based model, we explore one of the technology-based strategies proposed, a contact-tracing smartphone app. The model simulates the spread of COVID-19 in a population of agents on an urban scale. Agents are heterogeneous in their characteristics and are linked in a multi-layered network representing the social structure—including households, friendships, employment and schools. We explore the interplay of various adoption rates of the contact-tracing app, different levels of testing capacity, and behavioural factors to assess the impact on the epidemic. Results suggest that a contact tracing app can contribute substantially to reducing infection rates in the population when accompanied by a sufficient testing capacity or when the testing policy prioritises symptomatic cases. As user rate increases, prevalence of infection decreases. With that, when symptomatic cases are not prioritised for testing, a high rate of app users can generate an extensive increase in the demand for testing, which, if not met with adequate supply, may render the app counterproductive. This points to the crucial role of an efficient testing policy and the necessity to upscale testing capacity.


2020 ◽  
Vol 24 (5) ◽  
pp. 82-90
Author(s):  
A. Mikryukov ◽  
V. M. Trembach ◽  
A. V. Danilov

Purpose of research. The aim of the research is to form modules of organizational and technical systems (OTS) using a cognitive approach to solve problems of adaptation of cyberphysical systems. Currently, there is a rapid development of elements of the Internet of things. New tasks related to self-organization and adaptation in a rapidly changing external environment are brought to the fore. These tasks occur when new elements appear in the telecommunications computer network, they fail, change the mode, new tasks occur, etc. To work out these tasks, the possibilities of approaches to support and decision-making such as situational, cognitive, and semiotic are considered. The authors consider the cognitive approach in more detail. Within the framework of the cognitive paradigm, the article describes the use of the cognitive approach for solving problems of adaptation of cyberphysical systems. To solve this problem on the basis of an agent-based approach, the structure of a cyberphysical system with the possibility of adaptation is presented and the functions of its agents are described. The main stages of solving problems of adaptation of cyberphysical systems are presented. An adaptation algorithm using the planning mechanism is presented. The demo example shows a knowledge base for solving the problem of adapting cyberphysical systems using a cognitive planning mechanism.Materials and methods of research. New approaches and methods are required to address adaptation issues in planning. The cognitive approach is one of the developing directions in solving many problems of the Internet of things. One of these tasks is the ability to adapt OTS modules in a rapidly changing external environment based on the planning mechanism. To solve the planning problem, we use the algorithm described by Aristotle more than 2,350 years ago and implemented in the GPS program. This algorithm can be considered the first description of the cognitive mechanism that a person uses. The knowledge base uses an integrated approach to knowledge representation. When developing OTS modules, an agent-based approach was used to solve the problem of adaptation.Results. The existing and developing approaches and methods for decision support and decision-making are considered for decisionmaking in newly emerging situations in OTS modules. The main provisions of such significant approaches as situational, cognitive and semiotic are presented. A cognitive approach to the adaptation of intelligent systems is proposed. The solution of the problem of adaptation of cyberphysical systems is considered within the framework of the cognitive paradigm. The structure of a cyberphysical system capable of solving adaptation problems is shown. The functions of OTS modules based on agent-oriented technology are described. A description of the adaptation algorithm using the cognitive planning mechanism is given. The main stages of solving problems of adaptation of cyberphysical systems are presented. A demo example of solving the problem of adaptation by a cyberphysical system-a cooking robot – is shown.Conclusion. Using the modular architecture of an intelligent system allows you to solve many problems. One of these tasks is to configure elements of the Internet of things when they deviate from their main function. The planning mechanisms proposed for parametric adaptation can be repeatedly applied in OTS modules as separate agents. This approach is relevant for elements of the Internet of things. In the case of expanding the functionality of the OTS modules of Internet of things, it is advisable to apply machine learning with fixing the results in the knowledge base of planning agents.


2022 ◽  
Vol 2 (1) ◽  
pp. 34-43
Author(s):  
ADITYA ZULMI RAHMAWAN ◽  
ZAENURIYAH EFFENDI

The COVID-19 pandemic poses problems in various sectors. The most vulnerable sector in this situation is the social sector, especially education. Problems such as the learning process make the continuity of education a concern. This is a challenge for the community in the era of society 5.0 in the hope of overcoming the problems that arise due to the Covid-19 pandemic. The use of big data, artificial intelligence, and the internet of things is an alternative effort to help deal with the impact of the pandemic in accordance with the conditions in this disruptive era. This study aims to determine the policies and strategies of society 5.0 in the learning process as an effort to handle the impact of the pandemic. This study uses a systematic review research method of literature published by scientific journals in the period January 2010 to December 2021. The data used comes from published journals related to the topics studied and from various electronic media. The results of the study can find out strategies in the learning process in the implementation of society 5.0 in policies in the field of education as an effort to deal with the impact of the covid-19 pandemic. ABSTRAKPandemi covid-19 memberikan permasalahan di berbagai sektor. Sektor yang paling rentan dalam situasi ini adalah sektor sosial terutama pada pendidikan. Permasalahan seperti proses pembelajaran membuat keberlangsungan pendidikan menuai kekhawatiran. Hal ini menjadi sebuah tantangan bagi masyarakat di era society 5.0 dengan harapan dapat mengatasi permasalahan yang timbul akibat pandemi Covid-19. Pemanfaatan big data, artificial intelligent, dan internet of things menjadi upaya alternatif dalam membantu menangani dampak pandemi yang sesuai dengan keadaan di era disruptif ini. Penelitian ini bertujuan untuk mengetahui kebijakan dan strategi society 5.0 dalam proses pembelajaran sebagai upaya penanganan dampak pandemi. Penelitian ini menggunakan metode penelitian tinjauan sistematis terhadap literatur yang diterbitkan oleh jurnal ilmiah pada periode Januari tahun 2010 hingga Desember 2021. Sumber yang digunakan berasal dari jurnal-jurnal yang sudah dipublikasikan terkait dengan topik yang dikaji dan dari berbagai media elektronik. Hasil penelitian dapat mengetahui strategi dalam proses pembelajaran dalam implementasi society 5.0 pada kebijakan di bidang pendidikan sebagai upaya menghadapi dampak pandemi covid-19.


2014 ◽  
Vol 104 (7) ◽  
pp. 1196-1203 ◽  
Author(s):  
Yong Yang ◽  
Ana Diez-Roux ◽  
Kelly R. Evenson ◽  
Natalie Colabianchi

Author(s):  
William J. Gibbs

In this chapter, I examine trends in today's news-orientated interfaces and the impact of digital interfaces on news consumption. Digital interfaces will be differentiated from traditional informational sources such as newspapers and television news. Additionally, I will explore several major characteristics or trends germane to today's news interfaces and their implications for how people consume news and, more generally, for how they transform information services: a) rapid innovation, b) interactivity, c) social, d) standardization, e) scale, f) media convergence and, g) the Internet of Things and Big Data.


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