Low-diameter topic-based pub/sub overlay network construction with minimum–maximum node degree

Yumuşak, Semih; Layazali, Sina; Öztoprak, Kasım; Hassanpour, Reza

doi:10.7717/peerj-cs.538

Cited by 9 publications

(4 citation statements)

References 15 publications

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“…The Internet of Things (IoT) refers to the integration of the Internet with real-world items present in various areas, including environmental monitoring, smart homes, industrial processes, and health monitoring [1]. Blockchain, humanitarian logistics, cloud computing [2], machine learning [3][4][5], and artificial intelligence [6,7] are pivotal in the IoT ecosystem for boosting efficiency, security, and innovation. Blockchain ensures secure and transparent transactions among IoT devices [8], while humanitarian logistics utilizes IoT capabilities for coordinated aid delivery during emergencies [9].…”

Section: Introductionmentioning

confidence: 99%

Security and Privacy of Internet of Things: A Review of Challenges and Solutions

2023

JCSANDM

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The Internet of Things (IoT) is a global and comprehensive network that monitors and controls the physical world by collecting, processing, and analysing data derived from IoT devices. Globally, the IoT is emerging as a trend bringing intelligence and automation to a variety of application domains, presenting both opportunities and security challenges. It is used in various fields, including medical care, smart grids, home automation, smart cities, etc. As the number of devices connected to the IoT increases, there is an increased risk of cyber-attacks, data breaches, and other malicious activities. This means that it is essential to have secure protocols and encryption methods in place to protect the data being exchanged. This paper identifies and synthesizes security issues related to the IoT. Security threats across different layers of the IoT architecture are discussed first, followed by identifying prevalent security and privacy issues. A discussion is also provided on security countermeasures.

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Section: Introductionmentioning

confidence: 99%

Security and Privacy of Internet of Things: A Review of Challenges and Solutions

2023

JCSANDM

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“…Different service models are available in this model, allowing users to access resources on demand [2]. The convergence of Internet of Things (IoT) [3,4], artificial intelligence [5][6][7], differential equations [8], machine learning [9][10][11][12], smart grids [13], and Blockchain [14] has a profound impact on cloud computing, enabling enhanced connectivity, security, energy efficiency, data analytics, optimization, and intelligent decision-making capabilities, thereby revolutionizing the way resources are managed, services are delivered, and business operations are conducted in the digital era. The cloud paradigm requires a scheduling mechanism to provide on-demand access to cloud resources and provision of the resources needed by users [15].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Method Based on Gravitational Search and Genetic Algorithms for Task Scheduling in Cloud Computing

Zhang¹

2023

IJACSA

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Cloud computing has emerged as a novel technology that offers convenient and cost-effective access to a scalable pool of computing resources over the internet. Task scheduling plays a crucial role in optimizing the functionality of cloud services. However, inefficient scheduling practices can result in resource wastage or a decline in service quality due to under-or overloaded resources. To address this challenge, this research paper introduces a hybrid approach that combines gravitational search and genetic algorithms to tackle the task scheduling problem in cloud computing environments. The proposed method leverages the strengths of both gravitational search and genetic algorithms to achieve enhanced scheduling performance. By integrating the unique search capabilities of the gravitational search algorithm with the optimization and adaptation capabilities of the genetic algorithm, a more effective and efficient solution is achieved. The experimental results validate the superiority of the proposed method over existing approaches in terms of total cost optimization. The experimental evaluation demonstrates that the hybrid method outperforms previous scheduling methods in achieving optimal resource allocation and minimizing costs. The improved performance is attributed to the combined strengths of the gravitational search and genetic algorithms in effectively exploring and exploiting the solution space. These findings underscore the potential of the proposed hybrid method as a valuable tool for addressing the task scheduling problem in cloud computing, ultimately leading to improved resource utilization and enhanced service quality.

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“…Moreover, machine learning algorithms can learn from historical resource allocation patterns and optimize resource utilization, leading to enhanced efficiency and costeffectiveness [17]. These algorithms can identify resource bottlenecks, predict resource congestion, and dynamically allocate resources to alleviate these issues.…”

Section: Introductionmentioning

confidence: 99%

A Roadmap Towards Optimal Resource Allocation Approaches in the Internet of Things

Zhou¹

2023

IJACSA

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Introducing new technologies has facilitated people's lives more than ever. As one of these emerging technologies, the Internet of Things (IoT) enables objects we handle daily to interact with each other or humans and exchange information through the Internet by being equipped with sensors and communication technologies. IoT turns the physical world into a virtual world where heterogeneous objects and devices can be interconnected and controlled. IoT-based networks face numerous challenges, including energy and sensor transmission limitations. New technologies are needed to spread the IoT platform, optimize costs, cover heterogeneous connections, reduce power consumption, and diminish delays. Users of IoTbased systems typically use services that are integrated into these networks. Service providers provide users with on-demand services. The interrelationship between this request and response must be managed in a way that is done using a resource allocation strategy. Therefore, resource allocation plays a major role in these systems and networks. The allocation of resources involves matters such as how much, where, and when available resources should be provided to the user economically. The allocation of resources in the IoT environment is also subject to various challenges, including maintaining the quality of service, achieving a predetermined level of service, storing power, controlling congestion, and reducing costs. As the IoT resource allocation problem is an NP-Hard one, many research efforts have been conducted on this topic, and various algorithms have been developed. This paper reviews published publications on IoT resource allocation, outlining the underlying principles, the latest developments, and current trends.

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Low-diameter topic-based pub/sub overlay network construction with minimum–maximum node degree

Cited by 9 publications

References 15 publications

Security and Privacy of Internet of Things: A Review of Challenges and Solutions

Security and Privacy of Internet of Things: A Review of Challenges and Solutions

A Hybrid Method Based on Gravitational Search and Genetic Algorithms for Task Scheduling in Cloud Computing

A Roadmap Towards Optimal Resource Allocation Approaches in the Internet of Things

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