scholarly journals Cooperative Edge Computing Task Offloading Strategy for Urban Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Bo Wang ◽  
Mingchu Li
Keyword(s):  
Internet Of Things ◽  
Stackelberg Game ◽  
Edge Computing ◽  
Smart Devices ◽  
Smart Device ◽  
Cloud Data Center ◽  
Two Stage ◽  
Cloud Data ◽  
Internet Of Things Technology ◽  
Task Offloading

With the continuous progress of edge computing technology and the development of the Internet of Things technology, scenarios such as smart transportation, smart home, and smart medical care enable people to enjoy the smart era’s convenience. Simultaneously, with the addition of many smart devices, a large number of tasks are submitted to the edge server, making the edge server unable to meet the needs of completing tasks submitted by the smart device. Besides, if the task is submitted to the remote cloud data center, it increases the user’s additional delay and cost. Therefore, it is necessary to improve the task offloading strategy and resource allocation scheme to solve these problems. This paper first proposes a new task offloading mechanism and then proposes a two-stage Stackelberg game model to solve each participant’s interaction problem in the task offloading mechanism and ensure the maximization of their respective interests. Finally, a theoretical analysis proves the equilibrium of the two-stage Stackelberg game. Experiments are used to prove the effectiveness of the proposed mechanism. Comparative experimental results show that the proposed model can achieve better results regarding delay and energy consumption.

scholarly journals CrowdBox: Crowdsourced Network-in-Box Recruitment for Edge Computing-Enabled Industrial Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Pengfei Wang ◽  
Chi Lin ◽  
Zhen Yu ◽  
Leyou Yang ◽  
Qiang Zhang
Keyword(s):  
Internet Of Things ◽  
Stackelberg Game ◽  
Edge Computing ◽  
Stackelberg Equilibrium ◽  
Smart Devices ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Communication Demands ◽  
Edge Layer ◽  
Optimal Reward

The rapidly increasing number of smart devices deployed in the Industrial Internet of Things (IIoT) environment has been witnessed. To improve communication efficiency, edge computing-enabled Industrial Internet of Things (E-IIoT) has gained attention recently. Nevertheless, E-IIoT still cannot conquer the rapidly increasing communication demands when hundreds of millions of IIoT devices are connected at the same time. Considering the future 6G environment where smart network-in-box (NIB) nodes are everywhere (e.g., deployed in vehicles, buses, backpacks, etc.), we propose a crowdsourcing-based recruitment framework, leveraging the power of the crowd to provide extra communication resources and enhance the communication capabilities. We creatively treat NIB nodes as edge layer devices, and CrowdBox is devised using a Stackelberg game where the E-IIoT system is the leader, and the NIB nodes are the followers. CrowdBox can calculate the optimal reward to reach the unique Stackelberg equilibrium where the utility of E-IIoT can be maximized while none of the NIB nodes can improve its utility by deviating from its strategy. Finally, we evaluate the performance of CrowdBox with extensive simulations with various settings, and it shows that CrowdBox outperforms the compared algorithms in improving system utility and attracting more NIB nodes.

scholarly journals Mobile edge computing resource allocation: A joint Stackelberg game and matching strategy

2019 ◽  
Vol 15 (7) ◽  
pp. 155014771986155 ◽  
Author(s):  
Shaoyong Guo ◽  
Xing Hu ◽  
Gangsong Dong ◽  
Wencui Li ◽  
Xuesong Qiu
Keyword(s):  
Resource Allocation ◽  
Internet Of Things ◽  
Smart Home ◽  
Stackelberg Game ◽  
Edge Computing ◽  
Hierarchical Architecture ◽  
Smart Devices ◽  
Low Latency ◽  
Mobile Edge Computing ◽  
Computing Resource

Mobile edge computing has attracted great interests in the popularity of fifth-generation (5G) networks and Internet of Things. It aims to supply low-latency and high-interaction services for delay-sensitive applications. Utilizing mobile edge computing with Smart Home, which is one of the most important fields of Internet of Things, is a method to satisfy users’ demand for higher computing power and storage capacity. However, due to limited computing resource, how to improve efficiency of resource allocation is a challenge. In this article, we propose a hierarchical architecture in Smart Home with mobile edge computing, providing low-latency services and promoting edge process for smart devices. Based on that, a Stackelberg Game is designed in order to allocate computing resource to devices efficiently. Then, one-to-many matching is established to handle resource allocation problems. It is proved that the allocation strategy can optimize the utility of mobile edge computing server and improve allocating efficiency. Simulation results show the effectiveness of the proposed strategy compared with schemes based on auction game, and present performance with different changing system parameters.

Stackelberg game‐based task offloading in vehicular edge computing networks

2021 ◽  
Author(s):  
Shuang Liu ◽  
Jie Tian ◽  
Xiaofang Deng ◽  
Yuan Zhi ◽  
Ji Bian
Keyword(s):  
Stackelberg Game ◽  
Edge Computing ◽  
Task Offloading

Smart cities: existing security problems and their solutions

2020 ◽  
Vol 60 (11) ◽  
pp. 16-20
Author(s):  
Vugar Hajimahmud Abdullayev ◽  
◽  
Vusala Alyag Abuzarova ◽  
Keyword(s):  
Internet Of Things ◽  
Cyber Security ◽  
Smart City ◽  
Information Technologies ◽  
New Technologies ◽  
Smart Cities ◽  
Smart Devices ◽  
The Internet ◽  
It Industry ◽  
Internet Of Things Technology

The article is devoted to the study of cyber security problems in the Smart Cities system. The development of the IT industry has led to the introduction of new technologies into our lives. One of these technologies is the Internet of Things technology. The application of IoT technology has increased in recent years. One of the most important areas in which Internet of Things technology is applied is the Smart Cities system. The main difference between smart cities and other cities is that their components are connected to each other via the Internet. All these smart devices create a smart city system in general. One of the biggest and most important problems in many areas where the Internet is used is security. The article looks at possible security problems in the system of smart cities and solutions to ensure cyber security. Key words: Smart city; Internet of Things; Information technologies; Security; Cyber security

scholarly journals Method of Resource Estimation Based on QoS in Edge Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Guangshun Li ◽  
Jianrong Song ◽  
Junhua Wu ◽  
Jiping Wang
Keyword(s):  
Markov Chain ◽  
Prediction Method ◽  
Edge Computing ◽  
Resource Estimation ◽  
Matching Method ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Delay Sensitive ◽  
Penalty Factor

With the development of Internet of Things, the number of network devices is increasing, and the cloud data center load increases; some delay-sensitive services cannot be responded to timely, which results in a decreased quality of service (QoS). In this paper, we propose a method of resource estimation based on QoS in edge computing to solve this problem. Firstly, the resources are classified and matched according to the weighted Euclidean distance similarity. The penalty factor and Grey incidence matrix are introduced to correct the similarity matching function. Then, we use regression-Markov chain prediction method to analyze the change of the load state of the candidate resources and select the suitable resource. Finally, we analyze the precision and recall of the matching method through simulation experiment, validate the effectiveness of the matching method, and prove that regression-Markov chain prediction method can improve the prediction accuracy.

scholarly journals A Risk-Sensitive Task Offloading Strategy for Edge Computing in Industrial Internet of Things

2021 ◽  
Author(s):  
Xiaoyu Hao ◽  
Ruohai Zhao ◽  
Tao Yang ◽  
Yulin Hu ◽  
Bo Hu ◽  
...  
Keyword(s):  
At Risk ◽  
Internet Of Things ◽  
Value At Risk ◽  
Communication Systems ◽  
Edge Computing ◽  
Conditional Value At Risk ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
End To End ◽  
Task Offloading

Abstract Edge computing has become one of the key enablers for ultra-reliable and low-latency communications in the industrial Internet of Things in the fifth generation communication systems, and is also a promising technology in the future sixth generation communication systems. In this work, we consider the application of edge computing to smart factories for mission-critical task offloading through wireless links. In such scenarios, although high end-to-end delays from the generation to completion of tasks happen with low probability, they may incur severe casualties and property loss, and should be seriously treated. Inspired by the risk management theory widely used in finance, we adopt the Conditional Value at Risk to capture the tail of the delay distribution. An upper bound of the Conditional Value at Risk is derived through analysis of the queues both at the devices and the edge computing servers. We aim to find out the optimal offloading policy taking into consideration both the average and the worst case delay performance of the system. Given that the formulated optimization problem is a non-convex mixed integer non-linear programming problem, a decomposition into sub-problems is performed and a two-stage heuristic algorithm is proposed. Simulation results validate our analysis and indicate that the proposed algorithm can reduce the risk in both the queueing and end-to-end delay.

scholarly journals Research on Intelligent Scheduling Mechanism in Edge Network for Industrial Internet of Things

2022 ◽  
Vol 2022 ◽  
pp. 1-14
Author(s):  
Zhenzhong Zhang ◽  
Wei Sun ◽  
Yanliang Yu
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Internet Of Things ◽  
Task Scheduling ◽  
Edge Computing ◽  
The Internet ◽  
Computing Technology ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Internet Of Things Technology

With the vigorous development of the Internet of Things, the Internet, cloud computing, and mobile terminals, edge computing has emerged as a new type of Internet of Things technology, which is one of the important components of the Industrial Internet of Things. In the face of large-scale data processing and calculations, traditional cloud computing is facing tremendous pressure, and the demand for new low-latency computing technologies is imminent. As a supplementary expansion of cloud computing technology, mobile edge computing will sink the computing power from the previous cloud to a network edge node. Through the mutual cooperation between computing nodes, the number of nodes that can be calculated is more, the types are more comprehensive, and the computing range is even greater. Broadly, it makes up for the shortcomings of cloud computing technology. Although edge computing technology has many advantages and has certain research and application results, how to allocate a large number of computing tasks and computing resources to computing nodes and how to schedule computing tasks at edge nodes are still challenges for edge computing. In view of the problems encountered by edge computing technology in resource allocation and task scheduling, this paper designs a dynamic task scheduling strategy for edge computing with delay-aware characteristics, which realizes the reasonable utilization of computing resources and is required for edge computing systems. This paper proposes a resource allocation scheme combined with the simulated annealing algorithm, which minimizes the overall performance loss of the system while keeping the system low delay. Finally, it is verified through experiments that the task scheduling and resource allocation methods proposed in this paper can significantly reduce the response delay of the application.

Privacy in the Internet of Things

2019 ◽  
pp. 1569-1584
Author(s):  
Jayashree Kanniappan ◽  
Babu Rajendiran
Keyword(s):  
Data Collection ◽  
Internet Of Things ◽  
Personal Life ◽  
Smart Devices ◽  
The Internet ◽  
Privacy Threats ◽  
And Performance ◽  
Internet Of Things Technology ◽  
Privacy Issues ◽  
The Internet Of Things

Internet of Things technology is rapidly gaining popularity, not only in industrial and commercial environments, but also in personal life by means of smart devices at home. The Internet of Things (IoT) spawn new businesses and make buildings, cities and transport smarter. The IoT allows for ubiquitous data collection or tracking, but these useful features are also examples of privacy threats that are already limiting the success of the IoT vision when not implemented correctly. Privacy should be protected in the device, in storage, during communication, and at processing. The privacy of users and their data protection have been identified as one of the important challenges that need to be addressed in the IoT. The chapter presents the IoT technology, the various applications, and privacy issues. Various other issues such as security and performance are also addressed.

scholarly journals Exploiting Small World Problems in a SIoT Environment

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2089 ◽  
Author(s):  
Rehman Abdul ◽  
Anand Paul ◽  
Junaid Gul M. ◽  
Won-Hwa Hong ◽  
Hyuncheol Seo
Keyword(s):  
Internet Of Things ◽  
Small World ◽  
Research Society ◽  
Virtual Object ◽  
Smart Devices ◽  
Smart Device ◽  
Social Agent ◽  
The Social ◽  
Iot Devices ◽  
The Right

Internet of Things (IoT) has been at the center of attention among researchers for the last two decades. Their aim was to convert each real-world object into a virtual object. Recently, a new idea of integrating the Social Networking concept into the Internet of Things has merged and is gaining popularity and attention in the research society due to its vast and flexible nature. It comprises of the potential to provide a platform for innovative applications and network services with efficient and effective manners. In this paper, we provide the sustenance for the Social Internet of Things (SIoT) paradigm to jump to the next level. Currently, the SIoT technique has been proven to be efficient, but heterogeneous smart devices are growing exponentially. This can develop a problematic scenario while searching for the right objects or services from billions of devices. Small world phenomena have revealed some interesting facts and motivated many researchers to find the hidden links between acquaintances in order to reach someone across the world. The contribution of this research is to integrate the SIoT paradigm with the small world concept. By integrating the small world properties in SIoT smart devices, we empower the Smart Social Agent (SSA). The Smart Social Agent ensures the finding of appropriate friends (i.e., the IoT devices used by our friend circle) and services that are required by the user, without human intervention. The Smart Social Agent can be any smart device in SIoTs, e.g., mobile phones.

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