scholarly journals A Game-Based Scheme for Resource Purchasing and Pricing in MEC for Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yajing Leng ◽  
Ming Wang ◽  
Bowen Ma ◽  
Ying Chen ◽  
Jiwei Huang
Keyword(s):  
Internet Of Things ◽  
Stackelberg Game ◽  
Incentive Compatibility ◽  
Experimental Results ◽  
Stackelberg Equilibrium ◽  
Optimal Solutions ◽  
Challenging Problem ◽  
Simulation Experiments ◽  
Iot Devices ◽  
The Individual

Mobile edge computing (MEC) is emerging as a promising paradigm to support the applications of Internet of Things (IoT). The edge servers bring computing resources to the edge of the network, so as to meet the delay requirements of the IoT devices’ service requests. At the same time, the edge servers can gain profit by leasing computing resources to IoT users and realize the allocation of computing resources. How to determine a reasonable resource leasing price for the edge servers and how to determine the number of resource purchased by users with different needs is a challenging problem. In order to solve the problem, this paper proposes a game-based scheme for resource purchasing and pricing aiming at maximizing user utility and server profit. The interaction between users and the edge servers is modeled based on Stackelberg game theory. The properties of incentive compatibility and envy freeness are theoretically proved, and the existence of Stackelberg equilibrium is also proved. A game-based user resource purchasing algorithm called GURP and a game-based server resource pricing algorithm called GSRP are proposed. It is theoretically proven that solutions of the proposed algorithms satisfy the individual rationality property. Finally, simulation experiments are carried out, and the experimental results show that the GURP algorithm and the GSRP algorithm can quickly converge to the optimal solutions. Comparison experiments with the benchmark algorithms are also carried out, and the experimental results show that the GURP algorithm and the GSRP algorithm can maximize user utility and server profit.

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 Optimal Game-Based Energy Management with Renewable Energy for Secure Electric Vehicles Charging in Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Huwei Chen ◽  
Shijun Chen ◽  
Shanhe Jiang
Keyword(s):  
Renewable Energy ◽  
Internet Of Things ◽  
Electric Vehicles ◽  
Energy Demand ◽  
Stackelberg Game ◽  
Scheduling Algorithm ◽  
Optimal Solution ◽  
Stackelberg Equilibrium ◽  
Charging System ◽  
Game Theoretic

The integration of smart grid and Internet of Things (IoT) has been facilitated with the proliferation of electric vehicles (EVs). However, due to EVs’ random mobility and different interests of energy demand, there exists a significant challenge to optimally schedule energy supply in IoT. In this paper, we propose a secure game theoretic scheme for charging EVs supplied by mobile charging stations (MCSs) in IoT, considering the dynamic renewable energy source. Firstly, the charging system composed of MCSs is developed to implement the charging service. Secondly, when the secure charging scheme of EV users is designed, the utility function of each entity in the charging system is formulated to express the trading relationship between EV users and MCSs. Moreover, with consideration of the competition and cooperation, we propose a Stackelberg game framework with sub-noncooperative optimization. Thirdly, the existence and uniqueness of both Stackelberg equilibrium (SE) and Nash equilibrium (NE) are theoretically analyzed and proved. Through the presented distributed energy scheduling algorithm, we can achieve the optimal solution. Finally, numerical results demonstrate the effectiveness and efficiency of our proposal through comparison with other existing schemes.

scholarly journals COISA: A Compact OpenISA virtual platform for IoT devices

2015 ◽  
Author(s):  
Carlos Eduardo Millani ◽  
Alisson Linhares ◽  
Rafael Auler ◽  
Edson Borin
Keyword(s):  
Internet Of Things ◽  
Virtual Machines ◽  
Experimental Results ◽  
The Internet ◽  
Instruction Set ◽  
Promising Technology ◽  
Iot Devices ◽  
Virtual Platform ◽  
Hardware Platforms ◽  
The Internet Of Things

In face of the high number of different hardware platforms that we need to program in the Internet-of-Things (IoT), Virtual Machines (VMs) pose as a promising technology to allow a program once, deploy everywhere strategy. Unfortunately, many existing VMs are very heavy to work on resourceconstrained IoT devices. We present COISA, a compact virtual platform that relies on OpenISA, an Instruction Set Architecture (ISA) that strives for easy emulation, to allow a single program to be deployed on many platforms, including tiny microcontrollers. Our experimental results indicate that COISA is easily portable and is capable of running unmodified guest applications in highly heterogeneous host platforms, including one with only 2 kB of RAM.

scholarly journals Two-parametric game-theoretic model of concession in communal heating

2020 ◽  
Vol 14 (1) ◽  
pp. 55-68
Author(s):  
Alexander Khutoretskii ◽  
Vladimir Nefedkin
Keyword(s):  
Thermal Energy ◽  
Incentive Compatibility ◽  
Random Variable ◽  
Heat Energy ◽  
Stackelberg Equilibrium ◽  
Theoretic Model ◽  
Daily Average ◽  
The One ◽  
The Individual ◽  
Two Parameter

In this study, we propose to model the operation of a service concession arrangement in the economic area of municipal heat supply utilities. We offer a scheme of interaction between the concedent and concessionaire in this concessionary arrangement. Currently, the existing regulations regarding the temperature of coolant focusses on the daily average outdoor temperature, and the determination of a “normative” demand for heat energy. On any day of the heating period, this demand is a random variable, whose distribution can be described through the distribution of daily average air temperature. In our model, heat energy is paid for at a fixed price, and the concessionaire pays a penalty for each unit of unsatisfied normative demand. The price and penalty values are the concession parameters, and are determined by the concedent. The concedent’s goal is to minimise the thermal energy cost; the concessionaire’s purpose is to maximise profit. The interaction is formalised as a two-move game model. First, the concedent determines the price and the value of the penalty. Then the concessionaire selects the capacity to be created. The concession’s parameters should be set so that the individual rationality and incentive compatibility conditions are met. Our results prove the existence of Stackelberg equilibrium, and we derive the relevant formulas for computing its parameters. In equilibrium, the optimum capacity for the concessionaire provides a sufficient probability of meeting demand. The price of thermal energy is minimal under this condition. We also formulate a one-parameter model (thermal energy price as a parameter), which is based on a typical concession scheme. In the two-parameter model, the equilibrium capacity and price do not exceed the corresponding parameters of the one-parameter model. The main advantage of the two-parameter model is an “embedded” economic mechanism that prevents the concessionaire’s opportunistic behaviour. By contrast, in the one-parameter model there is no such mechanism. The proposed approach can be applied to a concession for the production of any good or service, provided the concerned parties are interested in the availability and reliability of meeting a corresponding need, which may be described as a random variable. However, typical concession schemes do not penalise unsatisfied demand, so the implementation of our two-parametric model is possible only after modification of the pertinent concession legislation.

Bringing Security to The Smallest Embedded Systems

2017 ◽  
Author(s):  
JOSEPH YIU
Keyword(s):  
Internet Of Things ◽  
Embedded Systems ◽  
Low Cost ◽  
Security Requirements ◽  
The Internet ◽  
Security Measures ◽  
Significant Challenge ◽  
Iot Devices

The increasing need for security in microcontrollers Security has long been a significant challenge in microcontroller applications(MCUs). Traditionally, many microcontroller systems did not have strong security measures against remote attacks as most of them are not connected to the Internet, and many microcontrollers are deemed to be cheap and simple. With the growth of IoT (Internet of Things), security in low cost microcontrollers moved toward the spotlight and the security requirements of these IoT devices are now just as critical as high-end systems due to:

Agricultural Application of Web of Things Architecture

Impact ◽  
2019 ◽  
Vol 2019 (10) ◽  
pp. 61-63 ◽  
Author(s):  
Akihiro Fujii
Keyword(s):  
Internet Of Things ◽  
Agricultural Sector ◽  
Electronic Device ◽  
Specific Work ◽  
Science And Engineering ◽  
Unique Identifier ◽  
Agricultural Application ◽  
Iot Devices ◽  
The Internet Of Things ◽  
Type Pressure

The Internet of Things (IoT) is a term that describes a system of computing devices, digital machines, objects, animals or people that are interrelated. Each of the interrelated 'things' are given a unique identifier and the ability to transfer data over a network that does not require human-to-human or human-to-computer interaction. Examples of IoT in practice include a human with a heart monitor implant, an animal with a biochip transponder (an electronic device inserted under the skin that gives the animal a unique identification number) and a car that has built-in sensors which can alert the driver about any problems, such as when the type pressure is low. The concept of a network of devices was established as early as 1982, although the term 'Internet of Things' was almost certainly first coined by Kevin Ashton in 1999. Since then, IoT devices have become ubiquitous, certainly in some parts of the world. Although there have been significant developments in the technology associated with IoT, the concept is far from being fully realised. Indeed, the potential for the reach of IoT extends to areas which some would find surprising. Researchers at the Faculty of Science and Engineering, Hosei University in Japan, are exploring using IoT in the agricultural sector, with some specific work on the production of melons. For the advancement of IoT in agriculture, difficult and important issues are implementation of subtle activities into computers procedure. The researchers challenges are going on.

scholarly journals Internet of things issues related to psychiatry

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Scott Monteith ◽  
Tasha Glenn ◽  
John Geddes ◽  
Emanuel Severus ◽  
Peter C. Whybrow ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Cognitive Abilities ◽  
Healthcare Providers ◽  
Emotional Reactions ◽  
The Body ◽  
Psychiatric Research ◽  
Main Body ◽  
Personal Safety ◽  
Healthcare Organizations ◽  
Iot Devices

Abstract Background Internet of Things (IoT) devices for remote monitoring, diagnosis, and treatment are widely viewed as an important future direction for medicine, including for bipolar disorder and other mental illness. The number of smart, connected devices is expanding rapidly. IoT devices are being introduced in all aspects of everyday life, including devices in the home and wearables on the body. IoT devices are increasingly used in psychiatric research, and in the future may help to detect emotional reactions, mood states, stress, and cognitive abilities. This narrative review discusses some of the important fundamental issues related to the rapid growth of IoT devices. Main body Articles were searched between December 2019 and February 2020. Topics discussed include background on the growth of IoT, the security, safety and privacy issues related to IoT devices, and the new roles in the IoT economy for manufacturers, patients, and healthcare organizations. Conclusions The use of IoT devices will increase throughout psychiatry. The scale, complexity and passive nature of data collection with IoT devices presents unique challenges related to security, privacy and personal safety. While the IoT offers many potential benefits, there are risks associated with IoT devices, and from the connectivity between patients, healthcare providers, and device makers. Security, privacy and personal safety issues related to IoT devices are changing the roles of manufacturers, patients, physicians and healthcare IT organizations. Effective and safe use of IoT devices in psychiatry requires an understanding of these changes.

scholarly journals An efficient pruning scheme of deep neural networks for Internet of Things applications

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Chen Qi ◽  
Shibo Shen ◽  
Rongpeng Li ◽  
Zhifeng Zhao ◽  
Qing Liu ◽  
...  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Internet Of Things ◽  
Deep Neural Networks ◽  
Computational Cost ◽  
Superior Performance ◽  
Compact Structure ◽  
Resource Limited ◽  
Benchmark Datasets ◽  
Iot Devices

AbstractNowadays, deep neural networks (DNNs) have been rapidly deployed to realize a number of functionalities like sensing, imaging, classification, recognition, etc. However, the computational-intensive requirement of DNNs makes it difficult to be applicable for resource-limited Internet of Things (IoT) devices. In this paper, we propose a novel pruning-based paradigm that aims to reduce the computational cost of DNNs, by uncovering a more compact structure and learning the effective weights therein, on the basis of not compromising the expressive capability of DNNs. In particular, our algorithm can achieve efficient end-to-end training that transfers a redundant neural network to a compact one with a specifically targeted compression rate directly. We comprehensively evaluate our approach on various representative benchmark datasets and compared with typical advanced convolutional neural network (CNN) architectures. The experimental results verify the superior performance and robust effectiveness of our scheme. For example, when pruning VGG on CIFAR-10, our proposed scheme is able to significantly reduce its FLOPs (floating-point operations) and number of parameters with a proportion of 76.2% and 94.1%, respectively, while still maintaining a satisfactory accuracy. To sum up, our scheme could facilitate the integration of DNNs into the common machine-learning-based IoT framework and establish distributed training of neural networks in both cloud and edge.

scholarly journals Practical Cross-Layer Radio Frequency-Based Authentication Scheme for Internet of Things

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4034
Author(s):  
Arie Haenel ◽  
Yoram Haddad ◽  
Maryline Laurent ◽  
Zonghua Zhang
Keyword(s):  
Internet Of Things ◽  
Radio Frequency ◽  
Real Life ◽  
Computation Time ◽  
Cost Effective ◽  
Battery Life ◽  
Cross Layer ◽  
Security Level ◽  
Cost Of Energy ◽  
Iot Devices

The Internet of Things world is in need of practical solutions for its security. Existing security mechanisms for IoT are mostly not implemented due to complexity, budget, and energy-saving issues. This is especially true for IoT devices that are battery powered, and they should be cost effective to be deployed extensively in the field. In this work, we propose a new cross-layer approach combining existing authentication protocols and existing Physical Layer Radio Frequency Fingerprinting technologies to provide hybrid authentication mechanisms that are practically proved efficient in the field. Even though several Radio Frequency Fingerprinting methods have been proposed so far, as a support for multi-factor authentication or even on their own, practical solutions are still a challenge. The accuracy results achieved with even the best systems using expensive equipment are still not sufficient on real-life systems. Our approach proposes a hybrid protocol that can save energy and computation time on the IoT devices side, proportionally to the accuracy of the Radio Frequency Fingerprinting used, which has a measurable benefit while keeping an acceptable security level. We implemented a full system operating in real time and achieved an accuracy of 99.8% for the additional cost of energy, leading to a decrease of only ~20% in battery life.

Sign in / Sign up

Export Citation Format

Share Document