The Internet of Things (IoT) is a large-scale network of devices capable of sensing, data processing, and communicating with each other through different communication protocols. In today's technology ecosystem, I...The Internet of Things (IoT) is a large-scale network of devices capable of sensing, data processing, and communicating with each other through different communication protocols. In today's technology ecosystem, IoT interacts with many application areas such as smart city, smart building, security, traffic, remote monitoring, health, energy, disaster, agriculture, industry. The IoT network in these scenarios comprises tiny devices, gateways, and cloud platforms. An IoT network is able to keep these fundamental components in transmission under many conditions with lightweight communication protocols taking into account the limited hardware features (memory, processor, energy, etc.) of tiny devices. These lightweight communication protocols affect the network traffic, reliability, bandwidth, and energy consumption of the IoT application. Therefore, determining the most proper communication protocol for application developers emerges as an important engineering problem. This paper presents a straightforward overview of the lightweight communication protocols, technological advancements in application layer for the IoT ecosystem. The survey then analyzes various recent lightweight communication protocols and reviews their strengths and limitations. In addition, the paper explains the experimental comparison of Constrained Applications Protocol (CoAP), Message Queuing Telemetry (MQTT), and WebSocket protocols, more convenient for tiny IoT devices. Finally, we discuss future research directions of communication protocols for IoT.展开更多
More devices in the Intelligent Internet of Things(AIoT)result in an increased number of tasks that require low latency and real-time responsiveness,leading to an increased demand for computational resources.Cloud com...More devices in the Intelligent Internet of Things(AIoT)result in an increased number of tasks that require low latency and real-time responsiveness,leading to an increased demand for computational resources.Cloud computing’s low-latency performance issues in AIoT scenarios have led researchers to explore fog computing as a complementary extension.However,the effective allocation of resources for task execution within fog environments,characterized by limitations and heterogeneity in computational resources,remains a formidable challenge.To tackle this challenge,in this study,we integrate fog computing and cloud computing.We begin by establishing a fog-cloud environment framework,followed by the formulation of a mathematical model for task scheduling.Lastly,we introduce an enhanced hybrid Equilibrium Optimizer(EHEO)tailored for AIoT task scheduling.The overarching objective is to decrease both the makespan and energy consumption of the fog-cloud system while accounting for task deadlines.The proposed EHEO method undergoes a thorough evaluation against multiple benchmark algorithms,encompassing metrics likemakespan,total energy consumption,success rate,and average waiting time.Comprehensive experimental results unequivocally demonstrate the superior performance of EHEO across all assessed metrics.Notably,in the most favorable conditions,EHEO significantly diminishes both the makespan and energy consumption by approximately 50%and 35.5%,respectively,compared to the secondbest performing approach,which affirms its efficacy in advancing the efficiency of AIoT task scheduling within fog-cloud networks.展开更多
The Internet of Things(IoT)has the characteristics of limited resources and wide range of points.Aiming at the problems of policy centralization and single point of failure in traditional access control schemes,a dist...The Internet of Things(IoT)has the characteristics of limited resources and wide range of points.Aiming at the problems of policy centralization and single point of failure in traditional access control schemes,a distributed access control method based on adaptive trust evaluation and smart contract is proposed to provide fine-grained,flexible and scalable authorization for IoT devices with limited resources.Firstly,a modular access control architecture with integrated blockchain is proposed to achieve hierarchical management of IoT devices.Secondly,an IoT trust evaluation model called AITTE based on adaptive fusion weights is designed to effectively improve the identification of illegal access requests from malicious nodes.Finally,an attribute-based access control model using smart contract called AACSC which is built,which consists of attribute set contract(ASC),registration contract(RC),state judgment contract(SJC),authority permission management contract(AMC),and access control contract(ACC).As experimental results show,the scheme can effectively solve the problem of access security in resource-constrained IoT environments.Moreover,it also ensures the reliability and efficiency of the access control implementation process.展开更多
文摘The Internet of Things (IoT) is a large-scale network of devices capable of sensing, data processing, and communicating with each other through different communication protocols. In today's technology ecosystem, IoT interacts with many application areas such as smart city, smart building, security, traffic, remote monitoring, health, energy, disaster, agriculture, industry. The IoT network in these scenarios comprises tiny devices, gateways, and cloud platforms. An IoT network is able to keep these fundamental components in transmission under many conditions with lightweight communication protocols taking into account the limited hardware features (memory, processor, energy, etc.) of tiny devices. These lightweight communication protocols affect the network traffic, reliability, bandwidth, and energy consumption of the IoT application. Therefore, determining the most proper communication protocol for application developers emerges as an important engineering problem. This paper presents a straightforward overview of the lightweight communication protocols, technological advancements in application layer for the IoT ecosystem. The survey then analyzes various recent lightweight communication protocols and reviews their strengths and limitations. In addition, the paper explains the experimental comparison of Constrained Applications Protocol (CoAP), Message Queuing Telemetry (MQTT), and WebSocket protocols, more convenient for tiny IoT devices. Finally, we discuss future research directions of communication protocols for IoT.
基金in part by the Hubei Natural Science and Research Project under Grant 2020418in part by the 2021 Light of Taihu Science and Technology Projectin part by the 2022 Wuxi Science and Technology Innovation and Entrepreneurship Program.
文摘More devices in the Intelligent Internet of Things(AIoT)result in an increased number of tasks that require low latency and real-time responsiveness,leading to an increased demand for computational resources.Cloud computing’s low-latency performance issues in AIoT scenarios have led researchers to explore fog computing as a complementary extension.However,the effective allocation of resources for task execution within fog environments,characterized by limitations and heterogeneity in computational resources,remains a formidable challenge.To tackle this challenge,in this study,we integrate fog computing and cloud computing.We begin by establishing a fog-cloud environment framework,followed by the formulation of a mathematical model for task scheduling.Lastly,we introduce an enhanced hybrid Equilibrium Optimizer(EHEO)tailored for AIoT task scheduling.The overarching objective is to decrease both the makespan and energy consumption of the fog-cloud system while accounting for task deadlines.The proposed EHEO method undergoes a thorough evaluation against multiple benchmark algorithms,encompassing metrics likemakespan,total energy consumption,success rate,and average waiting time.Comprehensive experimental results unequivocally demonstrate the superior performance of EHEO across all assessed metrics.Notably,in the most favorable conditions,EHEO significantly diminishes both the makespan and energy consumption by approximately 50%and 35.5%,respectively,compared to the secondbest performing approach,which affirms its efficacy in advancing the efficiency of AIoT task scheduling within fog-cloud networks.
基金This work was supported by the Ministry of Education Industry-University Cooperation Collaborative Education Projects of China(202102119036 and 202102082013).
文摘The Internet of Things(IoT)has the characteristics of limited resources and wide range of points.Aiming at the problems of policy centralization and single point of failure in traditional access control schemes,a distributed access control method based on adaptive trust evaluation and smart contract is proposed to provide fine-grained,flexible and scalable authorization for IoT devices with limited resources.Firstly,a modular access control architecture with integrated blockchain is proposed to achieve hierarchical management of IoT devices.Secondly,an IoT trust evaluation model called AITTE based on adaptive fusion weights is designed to effectively improve the identification of illegal access requests from malicious nodes.Finally,an attribute-based access control model using smart contract called AACSC which is built,which consists of attribute set contract(ASC),registration contract(RC),state judgment contract(SJC),authority permission management contract(AMC),and access control contract(ACC).As experimental results show,the scheme can effectively solve the problem of access security in resource-constrained IoT environments.Moreover,it also ensures the reliability and efficiency of the access control implementation process.
