Table of Content

    25 June 2015, Volume 13 Issue 2
    Download the whole issue (PDF)
    The whole issue of ZTE Communications June 2015, Vol. 13 No. 2
    2015, 13(2):  0. 
    Asbtract ( )   PDF (2239KB) ( )  
    Related Articles | Metrics
    Special Topic
    Using Artificial Intelligence in the Internet of Things
    Fuji Ren, Yu Gu
    2015, 13(2):  1-2. 
    Asbtract ( )   PDF (321KB) ( )  
    Related Articles | Metrics
    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 created by big data.

    This special issue deals with the technology and applications of AI in the IoT and is a forum for scientists, engineers, broadcasters, manufacturers, software developers, and other related professionals to discuss related issues. The topics addressed in this special issue include current research progress, real-world applications, and security issues related to AI in IoT. The call-for-papers attracted a number of excellent submissions. After two-round reviews, five papers were selected for publication. These papers are organized in three groups.

    The first group comprises one overview paper that outlines the technical progress of IoT. The second group comprises two papers addressing security issues in IoT. The last group comprises two papers that present some interesting real-world applications that will benefit daily life. The first paper,“I2oT: Advanced Direction of the Internet of Things,”gives an excellent vision of how AI technologies can be combined with IoT. The author introduces the principle and conceptual model of intelligent IoT (I2oT in short), which results from the integration of AI and IoT and is the most promising version of IoT. In the final section of the paper, the author makes recommendations for further study and standardization.

    The wireless sensor network (WSN) is a key enabler of IoT because of its great sensing ability and ability to generate and process big data. Using AI to handle big data in a WSN is a critical research topic and deserves much effort. The next two papers,“An Instance-Learning-Based Intrusion-Detection System for Wireless Sensor Networks”and“Forest Fire Detection Using Artificial Neural Network Algorithm Implemented in Wireless Sensor Networks”fall within this scope. The former addresses the intrusion-detection issue in WSNs and presents an instance-learningbased intrusion-detection system (IL-IDS) to protect the network from routing attacks. By mining historical data (instances), critical rules about attacks can be created to help build a routing mechanism that is more robust to malicious behaviour. The latter paper deals with a more specific application, i.e., forest fire detection using an artificial neural network algorithm in a WSN. Forest fires threaten forest resources, human lives, and surrounding environments. The authors build a forest fire detection system that takes advantage of the unique features of a WSN, such as easy deployment, efficient data collection and environmental monitoring. An artificial neural network algorithm is designed to improve multi - criteria detection, which helps decrease the possibility of false alarms the system cost.

    The last group comprises two papers about real-world applications of IoT:“We Watch: An Application for Watching Video Access Two Mobile Devices”and“A Parameter-Detection Algorithm for Moving Ships.”With the rapid development of wireless communications and embedded computing, IoT is no longer a concept but is gradually becoming a reality. One of the consequences of this trend is that people are surrounded by smart devices, which are changing almost every aspect of daily life. The former paper explores the blossoming of smart devices for a better viewing experience. It presents a unified platform based on Android where different devices can share screens. For instance, it allows a video to be played simultaneously on two devices that are close to each other. It provides a better way of watching videos by putting the screens of the two devices close together. However, the distance between the two screens needs to be accurately measured. This paper discusses a distancemeasuring mechanism based on Wi-Fi signal decay. By mining training data, the system can adaptively improve the measurement accuracy.

    The vision-based technique is a general AI technique that involves abstracting information from dynamic or static pictures. It is essential for the fast approach of IoT. In the latter paper, the authors propose an algorithm for detecting the parameters of a moving ship in an inland river. Numerous different vision-based parameter-detection approaches have been used in traffic monitoring systems; however, few have been applied to waterway transport because of complexities such as rippling water and lack of calibration objects. The authors discuss interactive calibration without a reference as well as detection of a moving ship using an optimized visual foregrounddetection algorithm. This reduces the likelihood of false detection in dynamic water-based scenarios and improves the detection of ship size, speed and flow. The traffic parameter detection algorithm has been trialled in the Beijing - Hangzhou Grand Canal and has an accuracy of more than 90% for all parameters.

    We thank all authors for their valuable contributions and we express our sincere gratitude to all the reviewers for their timely and insightful expert reviews. It is hoped that the contents in this special issue are informative and useful from the aspects of technology, standardization, and implementation.
    I2oT: Advanced Direction of the Internet of Things
    Yixin Zhong
    2015, 13(2):  3-6.  doi:10.3969/j.issn.1673-5188.2015.02.001
    Asbtract ( )   PDF (357KB) ( )  
    Related Articles | Metrics
    The Internet of Things (IoT) is still in its infancy because of the limited capability of its embedded processor. In the meantime, research on artificial intelligence (AI) has made plenty of progress. The application of AI to IoT will significantly increase the capabilities of IoT, and this will benefit both economic and social development. In this paper, the elementary concepts and key technologies of AI are explained, and the model and principle of intelligent IoT, denoted I2oT, resulting from the integration of AI and IoT are discussed. I2oT will be the most promising version of IoT. Finally, recommendations for further study and standardization of I2oT are made.
    An Instance-Learning-Based Intrusion-Detection System forWireless Sensor Networks
    Shuai Fu, Xiaoyan Wang, Jie Li
    2015, 13(2):  7-11.  doi:10.3969/j.issn.1673-5188.2015.02.002
    Asbtract ( )   PDF (390KB) ( )  
    Related Articles | Metrics
    This paper proposes an instance-learning-based intrusion-detection system (IL-IDS) for wireless sensor networks (WSNs). The goal of the proposed system is to detect routing attacks on a WSN. Taking an existing instance-learning algorithm for wired networks as our basis, we propose IL-IDS for handling routing security problems in a WSN. Attacks on a routing protocol for a WSN include black hole attack and sinkhole attack. The basic idea of our system is to differentiate the changes between secure instances and attack instances. Considering the limited resources of sensor nodes, the existing algorithm cannot be used directly in a WSN. Our system mainly comprises four parts: feature vector selection, threshold selection, instance data processing, and instance determination. We create a feature vector form composed of the attributes that changes obviously when an attack occurs within the network. For the data processing in resource-constrained sensor nodes, we propose a data-reduction scheme based on the clustering algorithm. For instance determination, we provide a threshold-selection scheme and describe the concrete-instance-determination mechanism of the system. Finally, we simulate and evaluate the proposed IL-IDS for different types of attacks.
    Forest Fire Detection Using Artificial Neural Network Algorithm Implemented in Wireless Sensor Networks
    Yongsheng Liu, Yansong Yang, Chang Liu, Yu Gu
    2015, 13(2):  12-16.  doi:10.3969/j.issn.1673-5188.2015.02.003
    Asbtract ( )   PDF (356KB) ( )  
    Related Articles | Metrics
    A forest fire is a severe threat to forest resources and human life. In this paper, we propose a forest-fire detection system that has an artificial neural network algorithm implemented in a wireless sensor network (WSN). The proposed detection system mitigates the threat of forest fires by provide accurate fire alarm with low maintenance cost. The accuracy is increased by the novel multicriteria detection, referred to as an alarm decision depends on multiple attributes of a forest fire. The multi-criteria detection is implemented by the artificial neural network algorithm. Meanwhile, we have developed a prototype of the proposed system consisting of the solar batter module, the fire detection module and the user interface module.
    WeWatch:An Application for Watching Video Across Two Mobile Devices
    Fuji Ren, Mengni Chen, Yu Gu
    2015, 13(2):  17-22.  doi:10.3969/j.issn.1673-5188.2015.02.004
    Asbtract ( )   PDF (459KB) ( )  
    Related Articles | Metrics
    In recent years, high-resolution video has developed rapidly and widescreen smart devices have become popular. We present an Android application called WeWatch that enables high-resolution video to be shared across two mobile devices when they are close to each other. This concept has its inspiration in machine-to-machine connections in the Internet of Things (loT). We ensure that the two parts of the video are the same size over both screens and are synchronous. Further, a user can play, pause, or stop the video by moving one device a certain distance from the other. We decide on appropriate distances through experimentation. We implemented WeWatch on Android operating system and then optimize Watch so battery consumption is reduced. The user experience provided by WeWatch was evaluated by students through a questionnaire, and the reviews indicated that WeWatch does improve the viewing experience.
    A Parameter-Detection Algorithm for Moving Ships
    Yaduan Ruan, Juan Liao, Jiang Wang, Bo Li, Qimei Chen
    2015, 13(2):  23-27.  doi:10.3969/j.issn.1673-5188.2015.02.005
    Asbtract ( )   PDF (427KB) ( )  
    Related Articles | Metrics
    In traffic-monitoring systems, numerous vision-based approaches have been used to detect vehicle parameters. However, few of these approaches have been used in waterway transport because of the complexity created by factors such as rippling water and lack of calibration object. In this paper, we present an approach to detecting the parameters of a moving ship in an inland river. This approach involves interactive calibration without a calibration reference. We detect a moving ship using an optimized visual foreground detection algorithm that eliminates false detection in dynamic water scenarios, and we detect ship length, width, speed, and flow. We trialed our parameter-detection technique in the Beijing-Hangzhou Grand Canal and found that detection accuracy was greater than 90% for all parameters.
    Inter-WBAN Coexistence and Interference Mitigation
    Bin Liu, Xiaosong Zhao, Lei Zou, Chang Wen Chen
    2015, 13(2):  28-35.  doi:10.3969/j.issn.1673-5188.2015.02.006
    Asbtract ( )   PDF (416KB) ( )  
    Related Articles | Metrics
    With promising applications in e-health and entertainment, wireless body area networks (WBANs) have attracted the interest of both academia and industry. If WBANs are densely deployed within a small area, serious problems may arise between the WBANs. In this paper, we discuss issues related to the coexistence of WBANs and investigate the main factors that cause inter-WBAN interference. We survey inter-WBAN interference mitigation strategies and track recent research developments. We also discuss unresolved issues related to inter-WBAN interference mitigation and propose future research directions.
    Research Paper
    A Visual Lossless Image-Recompression Framework
    Ping Lu, Xia Jia, Hengliang Zhu, Ming Liu, Shouhong Ding, Lizhuang Ma
    2015, 13(2):  36-40.  doi:10.3969/j.issn.1673-5188.2015.02.007
    Asbtract ( )   PDF (405KB) ( )  
    Related Articles | Metrics
    In this paper, we propose a novel image recompression framework and image quality assessment (IQA) method to efficiently recompress Internet images. With this framework image size is significantly reduced without affecting spatial resolution or perceptible quality of the image. With the help of IQA, the relationship between image quality and image evaluation scores can be quickly established, and the optimal quality factor can be obtained quickly and accurately within a pre determined perceptual quality range. This process ensures the image’s perceptual quality, which is applied to each input image. The test results show that, using the proposed method, the file size of images can be reduced by about 45%-60% without affecting their visual quality. Moreover, our new image-recompression framework can be used in to many different application scenarios.
    Channel Modeling for Air-to-Ground Wireless Communication
    Yingcheng Shi, Di He, Bin Li, Jianwu Dou
    2015, 13(2):  41-45.  doi:10.3969/j.issn.1673-5188.2015.02.008
    Asbtract ( )   PDF (502KB) ( )  
    Related Articles | Metrics
    In this paper, we discuss several large-scale fading models for different environments. The COST231-Hata model is adapted for air-to-ground modeling. We propose two criteria for air-toground channel modelling based on test data derived from field testing in Beijing. We develop a new propagation model that is more suitable for air-to-ground communication that previous models. We focus on improving this propagation model using the field test data.
    Terminal-to-Terminal Calling for GEO Broadband Mobile Satellite Communication
    Qing Wang,Minjiong Zhu,Jie Zhou,Zhen Gao,, Jinsheng Yang
    2015, 13(2):  46-52.  doi:10.3969/j.issn.1673-5188.2015.02.009
    Asbtract ( )   PDF (428KB) ( )  
    Related Articles | Metrics
    Satellite and terrestrial components of IMT-Advanced need to be integrated so that the traditional strengths of each component can be fully exploited. LTE/LTE-A is now a recognized foundation of terrestrial 4G networks, and mobile satellite networks should be based on it. Long transmission delay is one of the main disadvantages of satellite communication, especially in a GEO system, and terminal-to-terminal (TtT) design reduces this delay. In this paper, we propose a protocol architecture based on LTE/LTE-A for GEO mobile satellite communication. We propose a detailed call procedure and four TtT modes for this architecture. We describe the division of tasks between the satellite gateway (SAT-GW) and satellite as well as TtT processing in the physical layer of the satellite in order to reduce delay and ensure compatibility with a terrestrial LTE/LTE-A system.
    Community Discovery with Location-Interaction Disparity in Mobile Social Networks
    Danmeng Liu, Wei Wei, Guojie Song, Ping Lu
    2015, 13(2):  53-61.  doi:10.3969/j.issn.1673-5188.2015.02.010
    Asbtract ( )   PDF (538KB) ( )  
    Related Articles | Metrics
    With the fast-growth of mobile social network, people’s interactions are frequently marked with location information, such as longitude and latitude of visited base station. This boom of data has led to considerable interest in research fields such as user behavior mining, trajectory discovery and social demographics. However, there is little research on community discovery in mobile social networks, and this is the problem this work tackles with. In this work, we take advantage of one simple property that people in different locations often belong to different social circles in order to discover communities in these networks. Based on this property, which we referred to as Location-Interaction Disparity (LID), we proposed a state network and then define a quality function evaluating community detection results. We also propose a hybrid communitydetection algorithm using LID for discovering location-based communities effectively and efficiently. Experiments on synthesis networks show that this algorithm can run effectively in time and discover communities with high precision. In realworld networks, the method reveals people’s different social circles in different places with high efficiency.