Sentiment Analysis of Chinese Microblog Based on Stacked Bidirectional LSTM

Journal
Junhao Zhou, Yue Lu, Hong-Ning Dai, Hao Wang, Hong Xiao
IEEE Access, vol. 7, pp. 38856-38866, 2019
Publication year: 2019

Sentiment analysis on Chinese microblogs has received extensive attention recently. Most previous studies focus on identifying sentiment orientation by encoding as many word properties as possible while they fail to consider contextual features (e.g., the long-range dependencies of words), which are, however, essentially important in the sentiment analysis. In this paper, we propose a Chinese sentiment analysis method by incorporating a word2vec model and a stacked bidirectional long short-term memory (Stacked Bi-LSTM) model. We first employ the word2vec model to capture semantic features of words and transfer words into high-dimensional word vectors. We evaluate the performance of two typical word2vec models: continuous bag-of-words (CBOW) and skip-gram. We then use the Stacked Bi-LSTM model to conduct the feature extraction of sequential word vectors. We next apply a binary softmax classifier to predict the sentiment orientation by using semantic and contextual features. Moreover, we also conduct extensive experiments on the real dataset collected from Weibo (i.e., one of the most popular Chinese microblogs). The experimental results show that our proposed approach achieves better performance than other machine-learning models.

Secure and Flexible Economic Data Sharing Protocol Based on ID-based Dynamic Exclusive Broadcast Encryption in Economic System

Journal
Xiaofen Wang, Hong-Ning Dai, Ke Zhang
Future Generation Computer Systems (early access)
Publication year: 2019

Sharing economic data is paramount for improving quality and developing more efficient ways to produce statistics, and making better economic decisions. The economic data is of great importance to the corporations and governments, and they must be protected against the outsiders. Unfortunately, in an economic administration system, a few users may be malicious, or they are at high risk to leak information to the outsiders. Therefore, the economic data must also be protected against these users. The traditional broadcast encryption can provide protected data sharing among honest users. However, it is not efficient when most of the users are honest, and only a small amount of users are malicious. The traditional method is not cost effective, and does not fit to the situation where the set of malicious users dynamically changes either. Meanwhile, in traditional broadcast encryption, the authorized users’ identities need to be sent with the ciphertext. The valid users’ anonymity is not provided. To solve these problems, in this work, we present a novel cryptographic primitive, i.e. ID-based Dynamic Exclusive Broadcast Encryption (IBDEBE), and based on a hybrid framework (the combination of the exponent-inversion framework and the commutative-blinding framework) we propose an IBDEBE scheme with constant-size private keys and ciphertexts. The IBDEBE scheme is proved to be semi-adaptively semantically secure in the random oracle model. By applying the IBDEBE scheme, a secure economic data sharing protocol is devised, which is efficient and flexible in dynamic honest user groups, and it provides good security properties, i.e. source authenticity, data integrity protection, data access control, resistance to collusion attack and anonymity. We evaluate the performance of our solution with experiments and the results show good computation efficiency.

SCTSC: A Semicentralized Traffic Signal Control Mode With Attribute-Based Blockchain in IoVs

Journal
Lichen Cheng, Jiqiang Liu, Guangquan Xu, Zonghua Zhang, Hao Wang, Hong-Ning Dai, Yulei Wu, Wei Wang
IEEE Transactions on Computational Social Systems (early access)
Publication year: 2019

Assisting traffic control is one of the most important applications on the Internet of Vehicles (IoVs). Traffic information provided by vehicles is desired since drivers or vehicle sensors are sensitive in perceiving or detecting nuances on roads. However, the availability and privacy preservation of this information are critical while conflicted with each other in the vehicular communication. In this paper, we propose a semicentralized mode with attribute-based blockchain in IoVs to balance the tradeoff between the availability and the privacy preservation. In this mode, a method of control-by-vehicles is used to control signals of traffic lights to increase traffic efficiency. Users are grouped their attributes such as locations and directions before starting the communication. The users reach an agreement on determining a temporary signal timing by interacting with each other without leaking privacy. Final decisions are verifiable to all users, even if they have no a priori agreement and processes of consensus. The mode not only achieves the aim of privacy preservation but also supports responsibility investigation for historical agreements via ciphertext-policy attribute-based encryption (CP-ABE) and blockchain technology. Extensive experimental results demonstrated that our mode is efficient and practical.

Deep and Embedded Learning Approach for Traffic Flow Prediction in Urban Informatics

Journal
Zibin Zheng, Yatao Yang, Jiahao Liu, Hong-Ning Dai, Yan Zhang
IEEE Transactions on Intelligent Transportation Systems (accepted to appear)
Publication year: 2019

Traffic flow prediction has received extensive attention recently since it is a key step to prevent and mitigate traffic congestion in urban areas. However, most previous studies on traffic flow prediction fail to capture fine-grained traffic information (like link-level traffic) and ignore the impacts from other factors such as route structure and weather conditions. In this paper, we propose a Deep and Embedding Learning Approach (DELA) that can explicitly learn from fine-grained traffic information, route structure and weather conditions. In particular, our DELA consists of an embedding component, a Convolutional Neural Networks (CNN) component and a Long Short-term Memory (LSTM) component. The embedding component can capture the categorical feature information and identify correlated features. Meanwhile, the CNN component can learn the 2-Dimensional (2-D) traffic flow data while the LSTM component has the benefits of maintaining a long-term memory of historical data. The integration of the three models together can improve the prediction accuracy of traffic flow. We conduct extensive experiments on realistic traffic flow dataset to evaluate the performance of our DELA and make comparison with other existing models. The experimental results show that the proposed DELA outperforms existing methods in terms of prediction accuracy.

A Hybrid Computing Solution and Resource Scheduling Strategy for Edge Computing in Smart Manufacturing

Journal
Xiaomin Li, Jiafu Wan, Hong-Ning Dai, Muhammad Imran, Min Xia, Antonio Celesti
IEEE Transactions on Industrial Informatics (early access)
Publication year: 2019

At present, smart manufacturing computing framework has faced many challenges such as the lack of an effective framework of fusing computing historical heritages and resource scheduling strategy to guarantee the low latency requirement. In this paper, we propose a hybrid computing framework and design an intelligent resource scheduling strategy to fulfill the real-time requirement in smart manufacturing with edge computing support. First, a four-layer computing system in a smart manufacturing environment is provided to support the AI task operation with the network perspective. Then, a two-phase algorithm for scheduling the computing resources in the edge layer is designed based on greedy and threshold strategies with latency constraints. Finally, a prototype platform was developed. We conducted experiments on the prototype to evaluate the performance of the proposed framework with a comparison of the traditionally-used methods. The proposed strategies have demonstrated the excellent real-time, satisfaction degree and energy consumption performance of computing services in smart manufacturing with edge computing.

Wide & Deep Convolutional Neural Networks for Electricity-Theft Detection to Secure Smart Grids

Journal
Zibin Zheng, Yatao Yang, Xiangdong Niu, Hong-Ning Dai, Yuren Zhou
IEEE Transactions on Industrial Informatics,vol. 14, no. 4, pp. 1606-1615, April 2018
Publication year: 2018

Electricity theft can be harmful to power grid suppliers and cause economic losses. Integrating information flows with energy flows, smart grids can help to solve the problem of electricity theft owning to the availability of massive data generated from smart grids. The data analysis on the data of smart grids is helpful in detecting electricity theft because of the abnormal electricity consumption pattern of energy thieves. However, the existing methods have poor detection accuracy of electricity-theft since most of them were conducted on one dimensional (1-D) electricity consumption data and failed to capture the periodicity of electricity consumption. In this paper, we originally propose a novel electricity-theft detection method based on Wide & Deep Convolutional Neural Networks (CNN) model to address the above concerns. In particular, Wide & Deep CNN model consists of two components: the Wide component and the Deep CNN component. The Deep CNN component can accurately identify the non-periodicity of electricity-theft and the periodicity of normal electricity usage based on two dimensional (2-D) electricity consumption data. Meanwhile, the Wide component can capture the global features of 1-D electricity consumption data. As a result, Wide & Deep CNN model can achieve the excellent performance in electricity-theft detection. Extensive experiments based on realistic dataset show that Wide & Deep CNN model outperforms other existing methods.

We publish the dataset used in this paper to promote the research in this area. The dataset can be found through this link: https://github.com/henryRDlab/ElectricityTheftDetection/

Detection Performance of Packet Arrival under Downclocking for Mobile Edge Computing

Journal
Zhimin wang, Qinglin Zhao, Fangxin Xu, Hong-Ning Dai, Yujun Zhang
Wireless Communications and Mobile Computing, 2018
Publication year: 2018

Mobile edge computing (MEC) enables battery-powered mobile nodes to acquire information technology services at the network edge. These nodes desire to enjoy their service under power saving. The sampling rate invariant detection (SRID) is the first downclocking WiFi technique that can achieve this objective. With SRID, a node detects one packet arrival at a downclocked rate. Upon a successful detection, the node reverts to a full-clocked rate to receive the packet immediately. To ensure that a node acquires its service immediately, the detection performance (namely, the miss-detection probability and the false-alarm probability) of SRID is of importance. This paper is the first one to theoretically study the crucial impact of SRID attributes (e.g., tolerance threshold, correlation threshold, and energy ratio threshold) on the packet detection performance. Extensive Monte Carlo experiments show that our theoretical model is very accurate. This study can help system developers set reasonable system parameters for WiFi downclocking.

Data Analysis on Video Streaming QoE over Mobile Networks

Journal
Qingyong Wang, Hong-Ning Dai, Di Wu, Hong Xiao
EURASIP Journal on Wireless Communications and Networking, 2018
Publication year: 2018

One of recent proposals on standardizing quality of user experience (QoE) of video streaming over mobile network is is video Mean Opinion Score (vMOS), which can model QoE of video streaming in 5 discrete grades. However, there are few studies on quantifying vMOS and investigating the relationship between vMOS and other Quality of Service (QoS) parameters. In this paper, we address this concern by proposing a novel data analytical framework based on video streaming QoE data. In particular, our analytical model consists of K-means clustering and logistic regression. This model integrates the benefits of both these two models. Moreover, we conduct extensive experiments on realistic dataset and verify the accuracy of our proposed model. The results show that our proposed framework outperforms other existing methods in terms of prediction accuracy. Moreover, our results also show that vMOS is essentially affected by many QoS parameters such as initial buffering latency, stalling ratio and stalling times. Our results offer a number of insights in improving QoE of video streaming over mobile networks.

We publish the dataset used in this paper to promote the research in this area. The dataset can be found in https://github.com/henryRDlab/VMOS.

 

Connectivity of Underlay Cognitive Radio Networks with Directional Antennas

Journal
Qiu Wang, Hong-Ning Dai, Orestis Georgiou, Zhiguo Shi, Wei Zhang
IEEE Transactions on Vehicular Technology, Vol 67, pp. 7003 - 7017, Aug. 2018
Publication year: 2018

In underlay cognitive radio networks (CRNs), the connectivity of secondary users (SUs) is difficult to be guaranteed due to the existence of primary users (PUs). Most prior studies only consider cognitive radio networks equipped with omni-directional antennas causing high interference at SUs. We name such CRNs with omni-directional antennas as Omn-CRNs. Compared with an omni-directional antenna, a directional antenna can concentrate the transmitting/receiving capability at a certain direction, consequently resulting in the less interference. In this paper, we investigate the connectivity of SUs in CRNs with directional antennas (named as Dir-CRNs). In particular, we derive closed-form expressions of the connectivity of SUs of both Dir-CRNs and Omn-CRNs, thus enabling tractability. We show that the connectivity of SUs is mainly affected by two constraints: the spectrum availability of SUs and the topological connectivity of SUs. Extensive simulations validate the accuracy of our proposed models. Meanwhile, we also show that Dir-CRNs can have higher connectivity than Omn-CRNs mainly due to the lower interference, the higher spectrum availability and the higher topological connectivity brought by directional antennas. Moreover, we also extend our analysis with consideration transmission power efficiency. The simulation results show that Dir-CRNs require less transmission power to establish links than Omn-CRNs. We further investigate the throughput capacity of SUs, which is shown to heavily depend on the connectivity of SUs.

Connectivity of Cognitive Radio Ad Hoc Networks with Directional Antennas

Journal
Yuanyuan Wang, Qiu Wang, Hong-Ning Dai, Haibo Wang, Zhiguo Shi
Wireless Networks, Volume 24, Issue 8, Pages 3045–3061, November
Publication year: 2018

In cognitive radio ad hoc networks, omni-directional antennas are typically used at both primary users (PUs) and secondary users (SUs), which can cause high interference. We name such cognitive radio ad hoc networks with omni-directional antennas as OMN-CRAHNs. Different from omni-directional antennas, directional antennas can concentrate the transmission on desired directions and can consequently reduce interference in undesired directions. In this paper, we investigate both the local connectivity and the overall connectivity of cognitive radio ad hoc networks with directional antennas (DIR-CRAHNs), in which both PUs and SUs are equipped with directional antennas. In particular, we establish a theoretical framework to analyze both the probability of node isolation and the probability of connectivity of DIR-CRAHNs and OMN-CRAHNs. Our analytical results show that DIR-CRAHNs can have higher connectivity than OMN-CRAHNs.

BRAINS: Joint Bandwidth-Relay Allocation in Multi-Homing Cooperative D2D Networks

Journal
Long Chen, Jigang Wu, Hong-Ning Dai, Xiaoxia Huang
IEEE Transactions on Vehicular Technology, Vol 67, pp. 5387 - 5398, June 2018
Publication year: 2018

Devices with multi-homing capability can access multiple wireless access networks simultaneously. As an emerging technique, cooperative device to device (CD2D) communication has been considered to be a solution to capacity shortage problem. Combining multi-homing and CD2D techniques together can potentially improve network performance. We propose a novel multi-homing CD2D (MH-CD2D) network, in which multiple homing mobile devices (MMDs) act as relays for the cooperative communications of ordinary mobile devices (OMDs). We formulate such joint bandwidth-relay allocation problem as a two-stage game, in order to deal with two challenges: 1) how to design incentive mechanisms motivating MMDs to lease spare bandwidths to OMDs; 2) how to help OMDs to choose appropriate MMD relays. In the first stage, we use a non-cooperative game to model the competition between MMDs in terms of shared bandwidth and price. In the second stage, we model the behavior of OMDs selecting MMDs by an evolutionary game. We prove that there exists Nash equilibrium in the game and propose a distributed incentive scheme named IMES to solve the joint bandwidth-relay allocation problem. Extensive simulation results show that the equilibrium can be achieved and the best response price of one MMD increases with the other’s best price in the Stackelberg game. The utility of MMDs increases with the number of OMDs in each OMD group at the evolutionary equilibrium. The proposed algorithms are able to reduce the average service delay by more than 25% in comparison to the randomized scheme which is frequently used in the most existing works. On average, IMES outperforms existing scheme by about 20.37% in terms of utility of MMDs.

Blockchain Challenges and Opportunities: A Survey

Journal
Zibin Zheng, Shaoan Xie, Hong-Ning Dai, Huaimin Wang and Xiangping Chen
International Journal of Web and Grid Services (IJWGS), Vol. 14, No. 4, 2018
Publication year: 2018

Blockchain has numerous benefits such as decentralization, persistency, anonymity and auditability. There is a wide spectrum of blockchain applications ranging from cryptocurrency, financial services, risk management, Internet of Things to public and social services. Although a number of studies focus on using the blockchain technology in various application aspects, there is no comprehensive survey on the blockchain technology in both technological and application perspectives. To fill this gap, we conduct a comprehensive survey on the blockchain technology. In particular, this paper gives the blockchain taxonomy, introduces typical blockchain consensus algorithms, reviews blockchain applications and discusses technical challenges as well as recent advances in tackling the challenges. Moreover, this paper also points out the future directions in the blockchain technology.

 

[This is the first comprehensive survey on blockchain from technological and application perspectives. This paper was essentially completed in 2016 and formally published by International Journal of Web and Grid Services (IJWGS) in Oct. 2018). http://dx.doi.org/10.1504/IJWGS.2018.095647]

A Novel Friendly Jamming Scheme in Industrial Crowdsensing Networks against Eavesdropping Attack

Journal
Xuran Li, Qiu Wang, Hong-Ning Dai, Hao Wang
Sensors, 2018
Publication year: 2018

Eavesdropping attack is one of the most serious threats in red industrial crowdsensing networks. In this paper, we propose a novel anti-eavesdropping scheme by introducing friendly jammers to an red industrial crowdsensing network. In particular, we establish a theoretical framework considering both the probability of eavesdropping attacks and the probability of successful transmission to evaluate the effectiveness of our scheme. Our framework takes into account various channel conditions such as path loss, Rayleigh fading, and the antenna type of friendly jammers. Our results show that using jammers in red industrial crowdsensing networks can effectively reduce the eavesdropping risk while having no significant influence on legitimate communications.

On Connectivity of Wireless Sensor Networks with Directional Antennas

Journal
Qiu Wang, Hong-Ning Dai, Zibin Zheng, Muhammad Imran, Athanasios V. Vasilakos
Sensors, vol. 17, no. 1, 2017
Publication year: 2017

In this paper, we investigate the network connectivity of wireless sensor networks with directional antennas. In particular, we establish a general framework to analyze the network connectivity while considering various antenna models and the channel randomness. Since existing directional antenna models have their pros and cons in the accuracy of reflecting realistic antennas and the computational complexity, we propose a new analytical directional antenna model called the iris model to balance the accuracy against the complexity. We conduct extensive simulations to evaluate the analytical framework. Our results show that our proposed analytical model on the network connectivity is accurate, and our iris antenna model can provide a better approximation to realistic directional antennas than other existing antenna models.

On Capacity and Delay of Multi-channel Wireless Networks with Infrastructure Support

Journal
Hong-Ning Dai, Raymond Chi-Wing Wong, Hao Wang
IEEE Transactions on Vehicular Technology, vol. 66, no. 2, pp. 1589-1604, Feb. 2017
Publication year: 2017

In this paper, we propose a novel multichannel network with infrastructure support, which is called an MC-IS network, that has not been studied in the literature. To the best of our knowledge, we are the first to study such an MC-IS network. Our proposed MC-IS network has a number of advantages over three existing conventional networks: a single-channel wireless ad hoc network (called an SC-AH network), a multichannel wireless ad hoc network (called an MC-AH network), and a single-channel network with infrastructure support (called an SC-IS network). In particular, the network capacity of our proposed MC-IS network is √n log n times higher than that of an SC-AH network and an MC-AH network and the same as that of an SC-IS network, where n is the number of nodes in the network. The average delay of our MC-IS network is √log n/n times lower than that of an SC-AH network and an MC-AH network and min {CI, m} times lower than the average delay of an SC-IS network, where CI and m denote the number of channels dedicated for infrastructure communications and the number of interfaces mounted at each infrastructure node, respectively. Our analysis on an MC-IS network equipped with omnidirectional antennas has been extended to an MC-IS network equipped with directional antennas only, which are named as an MC-IS-DA network. We show that an MC-IS-DA network has an even lower delay of c/(⌊2π/θ⌋ · CI) compared with an SC-IS network and our MC-IS network. For example, when CI = 12 and θ = π/12, an MC-IS-DA can further reduce the delay by 24 times lower than that of an MC-IS network and by 288 times lower than that of an SC-IS network.

Link Connectivity and Coverage of Underwater Cognitive Acoustic Networks under Spectrum Constraint

Journal
Qiu Wang, Hong-Ning Dai, Chak Fong Cheang, Hao Wang
Sensors 2017, 17(12), 2839
Publication year: 2017

Extensive attention has been given to the use of cognitive radio technology in underwater acoustic networks since the acoustic spectrum became scarce due to the proliferation of human aquatic activities. Most of the recent studies on underwater cognitive acoustic networks (UCANs) mainly focus on spectrum management or protocol design. Few efforts have addressed the quality-of-service (QoS) of UCANs. In UCANs, secondary users (SUs) have lower priority to use acoustic spectrum than primary users (PUs) with higher priority to access spectrum. As a result, the QoS of SUs is difficult to ensure in UCANs. This paper proposes an analytical model to investigate the link connectivity and the probability of coverage of SUs in UCANs. In particular, this model takes both topological connectivity and spectrum availability into account, though spectrum availability has been ignored in most recent studies. We conduct extensive simulations to evaluate the effectiveness and the accuracy of our proposed model. Simulation results show that our proposed model is quite accurate. Besides, our results also imply that the link connectivity and the probability of coverage of SUs heavily depend on both the underwater acoustic channel conditions and the activities of PUs.

A Smart MCDM Framework to Evaluate Impact of Air Pollution on City Sustainability: A Case Study from China

Journal
Qingyong Wang, Hong-Ning Dai, Hao Wang
Sustainability, vol. 9, no. 6
Publication year: 2017

Air pollution has become one of the key environmental concerns in the urban sustainable development. It is important to evaluate the impact of air pollution on socioeconomic development since it is the prerequisite to enforce an effective prevention policy of air pollution. In this paper, we model the impact of air pollution on the urban economic development as a Multiple Criteria Decision Making (MCDM) problem. In particular, we propose a novel Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) analysis framework to evaluate multiple factors of air pollutants and economic development. Our method can overcome the drawbacks of conventional TOPSIS methods by using Bayesian regularization and the Back-Propagation (BP) neural network to optimize the weight training process. We have conducted a case study to evaluate our proposed framework.

On Performance Analysis of Protective Jamming Schemes in Wireless Sensor Networks

Journal
Xuran Li, Hong-Ning Dai, Hao Wang, Hong Xiao
Sensors, vol. 16, no. 12, 2016
Publication year: 2016

Wireless sensor networks (WSNs) play an important role in Cyber Physical Social Sensing (CPSS) systems. An eavesdropping attack is one of the most serious threats to WSNs since it is a prerequisite for other malicious attacks. In this paper, we propose a novel anti-eavesdropping mechanism by introducing friendly jammers to wireless sensor networks (WSNs). In particular, we establish a theoretical framework to evaluate the eavesdropping risk of WSNs with friendly jammers and that of WSNs without jammers. Our theoretical model takes into account various channel conditions such as the path loss and Rayleigh fading, the placement schemes of jammers and the power controlling schemes of jammers. Extensive results show that using jammers in WSNs can effectively reduce the eavesdropping risk. Besides, our results also show that the appropriate placement of jammers and the proper assignment of emitting power of jammers can not only mitigate the eavesdropping risk but also may have no significant impairment to the legitimate communications.

On Modeling Eavesdropping Attacks in Underwater Acoustic Sensor Networks

Journal
Qiu Wang, Hong-Ning Dai, Xuran Li, Hao Wang, Hong Xiao
Sensors, vol. 16, no. 5, 2016
Publication year: 2016

The security and privacy of underwater acoustic sensor networks has received extensive attention recently due to the proliferation of underwater activities. This paper proposes an analytical model to investigate the eavesdropping attacks in underwater acoustic sensor networks. Our analytical framework considers the impacts of various underwater acoustic channel conditions (such as the acoustic signal frequency, spreading factor and wind speed) and different hydrophones (isotropic hydrophones and array hydrophones) in terms of network nodes and eavesdroppers. We also conduct extensive simulations to evaluate the effectiveness and the accuracy of our proposed model. Empirical results show that our proposed model is quite accurate. In addition, our results also imply that the eavesdropping probability heavily depends on both the underwater acoustic channel conditions and the features of hydrophones.

Underwater; Sensor Networks; Security

 

An Analytical Study on Eavesdropping Attacks in Wireless Nets of Things

Journal
Xuran Li, Hao Wang, Hong-Ning Dai, Yuanyuan Wang, Qinglin Zhao
Mobile Information Systems, Volume 2016 (2016), Article ID 4313475, 10 pages
Publication year: 2016

The security of Internet of Things (IoT) has received extensive attention recently. This paper presents a novel analytical model to investigate the eavesdropping attacks in Wireless Net of Things (WNoT). Our model considers various channel conditions, including the path loss, the shadow fading effect, and Rayleigh fading effect. Besides, we also consider the eavesdroppers in WNoT equipped with either omnidirectional antennas or directional antennas. Extensive simulation results show that our model is accurate and effective to model the eavesdropping attacks in WNoT. Besides, our results also indicate that the probability of eavesdropping attacks heavily depends on the shadow fading effect, the path loss effect, Rayleigh fading effect, and the antenna models. In particular, we find that the shadow fading effect is beneficial to the eavesdropping attacks while both the path loss effect and Rayleigh fading effect are detrimental. Besides, using directional antennas at eavesdroppers can also increase the eavesdropping probability. Our results offer some useful implications on designing antieavesdropping schemes in WNoT.

On the Delay Reduction of Wireless Ad Hoc Networks with Directional Antennas

Journal
Hong-Ning Dai, Qinglin Zhao
EURASIP Journal on Wireless Communications and Networking, Jan. 2015
Publication year: 2015

It is shown that the throughput capacity of wireless ad hoc networks using omni-directional antennas (OMN networks) is significantly decreased with the increased number of nodes. One major reason lies in the interference caused by using omni-directional antennas, which just broadcast radio signal in all directions. Thus, a communication with multipleshort-rangedhops is suggested in such networks to avoid interference and improve the throughput. However, the multi-hop transmission can also significantly increase the end-to-end delay.

In this paper, we investigate the throughput improvement and the delay reduction by using directional antennas in wireless ad hoc networks. We call such wireless ad hoc networks using directional antennas as DIR networks. In particular, we investigate the effective transmission range of directional antennas with consideration of various channel conditions, such as the large scale path loss and the shadow fading effect. We have found that directional antennas can significantly increase the transmission range compared with omni-directional antennas even under the same channel condition. Besides, we derive the throughput and the delay of a DIRnetwork by constructing a routing scheme and a time-division multi-access (TDMA) scheme. We have found that using directional antennas not only can increase the throughput capacity but also can decrease the delay by reducing the number of hops.

On Modeling Eavesdropping Attacks in Wireless Networks

Journal
Xuran Li, Jianlong Xu, Hong-Ning Dai, Qinglin Zhao, Chak Fong Cheang, Qiu Wang
Journal of Computational Science, Vol. 11, Pages 196 - 204, November 2015
Publication year: 2015

This paper concerns the eavesdropping attacks from the eavesdroppers’ perspective, which is new since most of current studies consider the problem from the good nodes’ perspective. In this paper, we originally propose an analytical framework to quantify the effective area and the probability of the eavesdropping attacks. This framework enables us to theoretically evaluate the impact of node density, antenna model, and wireless channel model on the eavesdropping attacks. We verify via extensive simulations that the proposed analytical framework is very accurate. Our results show that the probability of eavesdropping attacks significantly vary, depending on the wireless environments (such as shadow fading effect, node density, and antenna types). This study lays the foundation toward preventing the eavesdropping attacks in more effective and more economical ways.

SPTF: Smart Photo-Tagging Framework on Smart Phones

Journal
Hao Xu, Hong-Ning Dai, Walter Hon-Wai Lau
International Journal of Multimedia and Ubiquitous Engineering (IJMUE), Vol.9, No.9, 2014
Publication year: 2014

Smart phones, as one of the most important platforms for personal communications and mobile computing, have evolved with various embedded devices, such as cameras, Wi-Fi transceivers, Bluetooth transceivers and sensors. Specifically, the photos taken by a smart phone has the approximate or even equivalent image quality to that of a professional camera. As a result, smart phones have become the first choice for people to take photos to record their ordinary life. However, how to manage thousands of photos on a smart phone becomes a challenge. In this paper, we propose a new architecture in terms of Smart Photo-Tagging Framework (SPTF) to manage the substantial number of photos taken by smart phones. In particular, our SPTF collects the ambient data obtained from various embedded sensors on a smart phone when a photo is taken. After processing and analyzing the ambient data, SPTF can accurately record both the ambient tags and the face tags of the photo, which will be used for auto-tagging photos and searching photos. We also implement SPTF and verify its effectiveness by conducting a number of realistic experiments.

Performance Evaluation of the Delayed-DCF Scheme in Wireless LANs

Journal
Qinglin Zhao, Zhijie Ma, Hong-Ning Dai
International Journal of Future Computer and Communication (IJFCC), Vol. 2, No. 5, October 2013
Publication year: 2013

On Eavesdropping Attacks in Wireless Sensor Networks with Directional Antennas

Journal
Hong-Ning Dai, Qiu Wang, Dong Li, Raymond Chi-Wing Wong
International Journal of Distributed Sensor Networks, Vol. 2013
Publication year: 2013

The eavesdropping attack is a serious security threat to a wireless sensor network (WSN) since the eavesdropping attack is a prerequisite for other attacks. Conventional WSNs consist of wireless nodes equipped with omnidirectional antennas, which broadcast radio signals in all directions and are consequently prone to the eavesdropping attacks. Different from omnidirectional antennas, directional antennas radiate radio signals on desired directions and potentially reduce the possibility of the eavesdropping attacks. In this paper, we propose a model to analyze the eavesdropping probability in both single-hop WSNs and multihop WSNs with omnidirectional antennas and directional antennas. We verify the correctness of our analytical model by conducting extensive simulations. We have found that using directional antennas in either single-hop WSNs or multihop WSNs can significantly reduce the eavesdropping probability. The reason of the improved security of WSNs with directional antennas lies in (i) the smaller exposure region of a directional antenna and (ii) the fewer hops to route a packet due to the longer transmission range of a directional antenna. Our results have also shown that the security improvement factor heavily depends on the node density, the antenna beamwidth, and the signal path loss factor.

On Busy-Tone based MAC Protocol for Wireless Networks with Directional Antennas

Journal
Hong-Ning Dai, Kam-Wing Ng, Min-You Wu
Wireless Personal Communications, Vol. 73, Issue 3, pp. 611 - 636, 2013
Publication year: 2013

The application of directional antennas in wireless ad hoc networks offers numerous benefits, such as the extended communication range, the increased spatial reuse, the improved capacity and the suppressed interference. However, directional antennas can cause new location-dependent carrier sensing problems, such as new hidden terminal and deafness problems, which can severely degrade the network performance. Recently, a few schemes have been proposed to address these problems. However, most of these existing methods can only partially solve the hidden terminal and deafness problems. Some of them even bring significant performance overhead. In this paper, we propose a novel MAC protocol, in terms of the busy-tone based directional medium access control (BT-DMAC) protocol. In BT-DMAC, when the transmission is in progress, the sender and the receiver will turn on their omni-directional busy tones to protect the on-going transmission. Integrating with the directional network allocation vector (DNAV), the scheme can almost mitigate the hidden terminal problem and the deafness problem completely. We then propose an analytical model to investigate the throughput performance of BT-DMAC. The numerical results show that BT-DMAC outperforms other existing directional MAC schemes. We next evaluate the performance of BT-DMAC through extensive simulation experiments. The results show that our proposed BT-DMAC scheme has superior performance to other existing solutions, in terms of higher throughput.

Channel Allocation in Wireless Networks with Directional Antennas

Journal
Hong-Ning Dai, Kam-Wing Ng, Min-You Wu
Journal of Sensor and Actuator Networks, 2(2), pp. 213 - 234, 2013
Publication year: 2013

In this paper, we study the channel allocation in multi-channel wireless ad hoc networks with directional antennas. In particular, we investigate the problem: given a set of wireless nodes equipped with directional antennas, how many channels are needed to ensure collision-free communications? We derive the upper bounds on the number of channels, which heavily depend on the node density and the interference ratio (i.e., the ratio of the interference range to the transmission range). We construct several scenarios to examine the tightness of the derived bounds. We also take the side-lobes and back-lobes as well as the signal path loss into our analysis. Our results can be used to estimate the number of channels required for a practical wireless network (e.g., wireless sensor network) with directional antennas.

An Overview of Using Directional Antennas in Wireless Networks

Journal
Hong-Ning Dai, Kam-Wing Ng, Minglu Li, Min-You Wu
Vol. 26, Issue 4, pp. 413 - 448, 2013
Publication year: 2013

Compared with omni-directional antennas, directional antennas have many merits, such as lower interference, better spatial reuse, longer transmission range, and improved network capacity. Directional antennas enable numerous emerging outdoor and indoor applications, which have been addressed in many recent studies. Despite the advances in wireless networks with directional antennas (DAWNs), there are many research challenges in all layers of DAWNs. This paper presents a detailed study on recent advances and open research issues on DAWNs. Firstly, we briefly introduce the classification of directional antennas, antenna radiation patterns, antenna modes, and the challenges in the physical layer of DAWNs. We then present research issues on the medium access control (MAC) layer, followed by the current solutions as well as open research problems on the MAC layer of DAWNs. In addition, we also discuss the research issues on the routing layer and the transport layer. Moreover, other research challenges on the performance evaluation of DAWNs and a brief introduction of indoor DAWNs are given in this paper as well. In conclusion, we summarize the current research issues on DAWNs as well as prospects in the future.

Collision-Tolerant Transmission with Narrow-beam Antennas

Journal
Hong-Ning Dai, Kam-Wing Ng, Min-You Wu, Bo Li
International Journal of Communications, Network and System Sciences, Vol. 1, No. 4 (Nov. 2008)
Publication year: 2008

The application of directional antennas in wireless ad hoc networks brings numerous benefits, such as increased spatial reuse and mitigated interference. Most MAC protocols with directional antennas are based on the RTS/CTS mechanism which works well in wireless ad hoc networks using omni-directional antennas. However, RTS/CTS frames cannot mitigate the interference completely. Besides, they also contribute a lot to the performance overhead. This paper studies the problem from a new perspective. We have found that the transmission success probability under directional transmission and directional reception is quite high when the antenna beamwidth is quite narrow. Motivated by the analytical results, we design a lightweight MAC protocol without RTS/CTS frames. The evaluation results demonstrate that this new protocol performs better than MAC protocols based on the RTS/CTS mechanism. The results also show that a collision-tolerant transmission is feasible under the narrow beam configuration.

A Visual Editor System for Non-structured Data

Journal
Hong-Ning Dai, GuihuaWen, Yuehua Ding, Chonggui Fan
Research of Computer Application, June 2003
Publication year: 2003

Analyses of the Tree-decomposable Reminding Process

Journal
GuihuaWen, Hong-Ning Dai, Weiqiang Guo
Journal of South China University of Technology (Natural Science Edition), Vol.30, No.5, 2002
Publication year: 2002

A Framework for Product Creative Design Platform

Journal
Guihua Wen, Yuehua Ding, Hong-Ning Dai, Weiping Tu
Mechanical and Electronics Engineering, Vol.31, No.6, 2002
Publication year: 2002