Mobile edge computing has risen as a promising technology for augmenting the computational capabilities of mobile devices Meanwhile, in-network caching has become a natural trend of the solution of handling exponentially increasing Internet traffic The important issues in these two networking paradigms are computation offloading and content caching strategies, respectively In order to jointly tackle these issues in wireless cellular networks with mobile edge computing, we formulate the computation offloading decision, resource allocation and content caching strategy as an optimization problem, considering the total revenue of the network Furthermore, we transform the original problem into a convex problem and then decompose it in order to solve it in a distributed and efficient way Finally, with recent advances in distributed convex optimization, we develop an alternating direction method of multipliers-based algorithm to solve the optimization problem The effectiveness of the proposed scheme is demonstrated by simulation results with different system parameters

Computation Offloading and Resource Allocation in Wireless Cellular Networks With Mobile Edge Computing

The Internet of Things (IoT) has recently advanced from an experimental technology to what will become the backbone of future customer value for both product and service sector businesses. This underscores the cardinal role of IoT on the journey toward the fifth generation of wireless communication systems. IoT technologies augmented with intelligent and big data analytics are expected to rapidly change the landscape of myriads of application domains ranging from health care to smart cities and industrial automations. The emergence of multi-access edge computing (MEC) technology aims at extending cloud computing capabilities to the edge of the radio access network, hence providing real-time, high-bandwidth, low-latency access to radio network resources. IoT is identified as a key use case of MEC, given MEC’s ability to provide cloud platform and gateway services at the network edge. MEC will inspire the development of myriads of applications and services with demand for ultralow latency and high quality of service due to its dense geographical distribution and wide support for mobility. MEC is therefore an important enabler of IoT applications and services which require real-time operations. In this survey, we provide a holistic overview on the exploitation of MEC technology for the realization of IoT applications and their synergies. We further discuss the technical aspects of enabling MEC in IoT and provide some insight into various other integration technologies therein.

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Survey on Multi-Access Edge Computing for Internet of Things Realization

Enabling technologies for fog computing in healthcare IoT systems

Path planning techniques for unmanned aerial vehicles: A review, solutions, and challenges

This paper provides an overview of the Industrial Internet with the emphasis on the architecture, enabling technologies, applications, and existing challenges. The Industrial Internet is enabled by recent rising sensing, communication, cloud computing, and big data analytic technologies, and has been receiving much attention in the industrial section due to its potential for smarter and more efficient industrial productions. With the merge of intelligent devices, intelligent systems, and intelligent decisioning with the latest information technologies, the Industrial Internet will enhance the productivity, reduce cost and wastes through the entire industrial economy. This paper starts by investigating the brief history of the Industrial Internet. We then present the 5C architecture that is widely adopted to characterize the Industrial Internet systems. Then, we investigate the enabling technologies of each layer that cover from industrial networking, industrial intelligent sensing, cloud computing, big data, smart control, and security management. This provides the foundations for those who are interested in understanding the essence and key enablers of the Industrial Internet. Moreover, we discuss the application domains that are gradually transformed by the Industrial Internet technologies, including energy, health care, manufacturing, public section, and transportation. Finally, we present the current technological challenges in developing Industrial Internet systems to illustrate open research questions that need to be addressed to fully realize the potential of future Industrial Internet systems.

Industrial Internet: A Survey on the Enabling Technologies, Applications, and Challenges

In this paper, we study the automatic ground map building and efficient path planning in unmanned aerial/ground vehicle (UAV/UGV) cooperative systems. Using the UAV, a ground image can be obtained from the aerial vision, which is then processed with image denoising, image correction, and obstacle recognition to construct the ground map automatically. Image correction is used to help the UGV improve the recognition accuracy of obstacles. Based on the constructed ground map, a hybrid path planning algorithm is proposed to optimize the planned path. A genetic algorithm is used for global path planning, and a local rolling optimization is used to constantly optimize the results of the genetic algorithm. Experiments are performed to evaluate the performance of the proposed schemes. The evaluation results show that our proposed approach can obtain a much less costly path compared to the traditional path planning algorithms such as the genetic algorithm and the A-star algorithm and can run in real-time to support the UAV/UGV systems.

A Hybrid Path Planning Method in Unmanned Air/Ground Vehicle (UAV/UGV) Cooperative Systems

Electrocardiogram (ECG) signal is a direct and effective way to find cardiovascular disease timely, which can intuitively reflect changes of the heart beat and activities of different parts Due to the noise interference from surroundings, acquisition of real-time and high-quality ECG signal is a big challenge for portable mobile medical systems Integer coefficients infinite impulse response (IIR) digital filter is suitable for portable mobile platform, but it will be a little bit of distortion So, an improved integer IIR filter for portable ECG monitors is presented in this paper The proposed IIR filter can instantaneously and effectively eliminate baseline drift of main interference frequency band and 50-Hz power frequency interference in ECG signal The method is verified by a specific example and MIT/BIH Arrhythmia Database The improved integer coefficients IIR filter was applied in a portable mobile medical system It can meet the requirements of ECG filtering in real-time and filtering performance

Design of a Real-Time ECG Filter for Portable Mobile Medical Systems

Linear induction motors (LIMs) are being gradually applied in the urban rail transit due to their simplified mechanical structure and feasibility for both low-speed and high-speed operations. Direct-torque control (DTC) is a classical control scheme that can be readily extended to LIMs. However, due to the high thrust ripple and poor dynamic performance for the low-speed operation, control performance of DTC is not satisfactory. This paper is to propose an explicit model predictive control to be combined with the DTC scheme. First, the LIM model is presented and discretized. Then, the LIM drive and its operating principle are discussed. Thirdly, the controller design, including control variables, and the objective function are depicted. Finally, both the simulation and the experiment are engaged for verifying the proposed control algorithm.

Continuous-Behavior and Discrete-Time Combined Control for Linear Induction Motor-Based Urban Rail Transit

With increasingly fierce competition for jobs, the pressures on people have risen in recent years, leading to lifestyle and diet disorders that result in significantly higher risks of cardiovascular disease Hypertension is one of the common chronic cardiovascular diseases; however, mainstream blood pressure measurement devices are relatively heavy When multiple measurements are required, the user experience and the measurement results may be unsatisfactory In this paper, we describe the design of a signal collection module that collects pulse waves and electrocardiograph (ECG) signals The collected signals are input into a signal processing module to filter the noise and amplify the useful physiological signals Then, we use a wavelet transform to eliminate baseline drift noise and detect the feature points of the pulse waves and ECG signals We propose the concept of detecting the wave shape associated with an instance, an approach that minimizes the impact of atypical pulse waves on blood pressure measurements Finally, we propose an improved method for measuring blood pressure based on pulse wave velocity that improves the accuracy of blood pressure measurements by 58% Moreover, the results meet the american medical instrument promotion association standards, which demonstrate the feasibility of our measurement system

Genqiang Deng

Papers

Industrial Internet: A Survey on the Enabling Technologies, Applications, and Challenges

A Hybrid Path Planning Method in Unmanned Air/Ground Vehicle (UAV/UGV) Cooperative Systems

Design of a Real-Time ECG Filter for Portable Mobile Medical Systems

Continuous-Behavior and Discrete-Time Combined Control for Linear Induction Motor-Based Urban Rail Transit

Design of a Continuous Blood Pressure Measurement System Based on Pulse Wave and ECG Signals