Strategic Thinking of the Internet of Things and M2M Services

Editor＇s Desk：The Internet of Things is an important part of the emerging high-tech industry and has been recognized as one of the important technologies for addressing global financial crisis and revitalizing the economy. Therefore, at the beginning of the new year, we are honored to have invited Mr. Samuel Qi （Qi Qingzhong）, a famous Chinese communication technology expert and GM of Shanghai Symphony Telecommunications Co., Ltd., to give his views on the development strategy of the Internet of Things and Machine to Machine （M2M） Communications.

Using Artificial Intelligence in the Internet of Things

The Internet of Things （IoT） has received much attention over the past decade. With the rapid increase in the use of smart devices, we are now able to collect big data on a daily basis. The data we are gathering （and related problems） are becoming more complex and uncertain. Researchers have therefore turned to artificial intelligence （AI） to efficiently deal with the problems ereated by big data.

Exploration on the Load Balancing Technique for Platform of Internet of Things

In recent years,the Internet of Things technology has developed rapidly,and smart Internet of Things devices have also been widely popularized.A large amount of data is generated every moment.Now we are in the era of big data in the Internet of Things.The rapid growth of massive data has brought great challenges to storage technology,which cannot be well coped with by traditional storage technology.The demand for massive data storage has given birth to cloud storage technology.Load balancing technology plays an important role in improving the performance and resource utilization of cloud storage systems.Therefore,it is of great practical significance to study how to improve the performance and resource utilization of cloud storage systems through load balancing technology.On the basis of studying the read strategy of Swift,this article proposes a reread strategy based on load balancing of storage resources to solve the problem of unbalanced read load between interruptions caused by random data copying in Swift.The storage asynchronously tracks the I/O conversion to select the storage with the smallest load for asynchronous reading.The experimental results indicate that the proposed strategy can achieve a better load balancing state in terms of storage I/O utilization and CPU utilization than the random read strategy index of Swift.

FUTURE OF LAW CONFERENCE： THE INTERNET OF THINGS, SMART CONTRACTS AND INTELLIGENT MACHINES

From 26 to 27 October 2017, the Centre for Cross-Border Commercial Law in Asia of Singapore Management University （SMU） Law School held an international conference entitled ＂Future of Law Conference： The Internet of Things, Smart Contracts and Intelligent Machines＂ in Singapore. The conference brought together the leading thinkers in academia and practice in the field of information technology law to discuss the legal and regulatory implications of recent technological developments. Associate Professor ZHANG Jiyu and Associate Professor DING Xiaodong of the Law and Technology Institute of Renmin Law School were invited to attend the conference.

5G and intelligence medicine—howthe next generation of wireless technology will reconstruct healthcare?

Despite intensive efforts,there are still enormous challenges in provision of healthcare services to the increasing aging population.Recent observations have raised concerns regarding the soaring costs of healthcare,the imbalance of medical resources,inefficient healthcare system administration,and inconvenient medical experiences.However,cutting-edge technologies are being developed to meet these challenges,including,but not limited to,Internet of Things(IoT),big data,artificial intelligence,and 5G wireless transmission technology to improve the patient experience and healthcare service quality,while cutting the total cost attributable to healthcare.This is not an unrealistic fantasy,as these emerging technologies are beginning to impact and reconstruct healthcare in subtleways.Although the technologies mentioned above are integrated,in this review we take a brief look at cases focusing on the application of 5G wireless transmission technology in healthcare.We also highlight the potential pitfalls to availability of 5G technologies.

Partially Distributed Channel and Power Management Based on Reinforcement Learning

This paper studies a dynamic multi-user wireless network,where users have no knowledge of the arrival rate and size of data block and suffer from a constraint on long-term average power consumption.Considering such a network,we address the problem of dynamically optimizing channel/power allocation,so as to minimize the long-term average data backlog.The design problem is shown to be a constrained Markov decision process.In order to solve the problem without knowledge on dynamics of the system,we introduce post-decision states and propose a resource allocation algorithm based on reinforcement learning.Since the channel/power allocation problem is coupled,the multiuser decision problem suffers from curses of dimensions(of state/action/outcome space).This makes centralized decision-making and optimization on channel/power allocation suffer from a long convergence time.As a countermeasure,a partially distributed resource allocation framework is proposed.The multiuser power allocation problem is decoupled into single-user decision problems,while channel allocation optimization is performed in a centralized manner.In order to further reduce computational complexity,we propose a low-complexity reinforcement learning method.Simulation results reveal that the proposed algorithm outperforms the state-of-the-art myopic optimizations in terms of energy efficiency and the backlog performance.

Data Secure Transmission Model Based on Compressed Sensing and Digital Watermarking Technology

Since the Internet of Things（IoT） secret information is easy to leak in data transfer,a data secure transmission model based on compressed sensing（CS） and digital watermarking technology is proposed here. Firstly, for node coding end, the digital watermarking technology is used to embed secret information in the conventional data carrier. Secondly, these data are reused to build the target transfer data by the CS algorithm which are called observed signals. Thirdly, these signals are transmitted to the base station through the wireless channel. After obtaining these observed signals, the decoder reconstructs the data carrier containing privacy information. Finally, the privacy information is obtained by digital watermark extraction algorithm to achieve the secret transmission of signals. By adopting the watermarking and compression sensing to hide secret information in the end of node code, the algorithm complexity and energy consumption are reduced. Meanwhile, the security of secret information is increased.The simulation results show that the method is able to accurately reconstruct the original signal and the energy consumption of the sensor node is also reduced significantly in consideration of the packet loss.