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Über dieses Buch

This book constitutes the refereed proceedings of the 4th EAI International Conference on Industrial Networks and Intelligent Systems, INISCOM 2018, held in Da Nang, Vietnam, in August 2018. The 26 full papers were selected from 38 submissions and are organized thematically in tracks: Telecommunications Systems and Networks; Industrial Networks and Applications; Hardware and Software Design and Development; Information Processing and Data Analysis; Signal Processing; Security and Privacy.

Inhaltsverzeichnis

Frontmatter

Optimal Beamforming for Multiuser Secure SWIPT Systems (Invited Paper)

Abstract
In this paper, we study the beamforming design for simultaneous wireless information and power transfer (SWIPT) downlink systems. The design is formulated as a non-convex optimization problem which takes into account the quality of service (QoS) requirements of communication security and minimum harvested power. In particular, the proposed design advocates the dual use of energy signal to enable secure communication and efficient WPT. The globally optimal solution of the optimization problem is obtained via the semidefinite programming relaxation (SDR). Our simulation results show that there exists a non-trivial tradeoff between the achievable data rate and the total harvested power in the system. Besides, our proposed optimal scheme provides a substantial performance gain compared to a simple suboptimal scheme based on the maximum ratio transmission (MRT).
Yuqing Su, Derrick Wing Kwan Ng

Logarithmic Spiral Based Local Search in Artificial Bee Colony Algorithm

Abstract
Artificial bee colony (ABC) algorithm is recent swarm intelligence based meta-heuristic that is developed to solve complex real problems which are difficult to solve by the available deterministic strategies. It mimics the natural behaviour of real honey bees while searching for food sources. The performance of ABC depends on the size of step during position update process, that is a combination of the arbitrary component \(\phi _{ij}\) and a difference vector between the current solution and an arbitrarily identified solution. The high value of \(\phi _{ij}\) and high difference between the vectors in the step generation process may generate the large size step which may leads to the skipping of true solution. Therefore, to avoid this situation a logarithmic spiral based local search strategy, namely logarithmic spiral local search (LSLS) is planned and incorporated with the ABC. The proposed hybridized ABC is named as logarithmic spiral based ABC (LSABC). To demonstrate the efficiency and accurateness of the LSABC, it is tested over 10 popular benchmarks functions and outcomes are equated with ABC, Modified ABC, and Best-so-far ABC. The reported results showed that the proposed LSABC is a new viable variation of ABC algorithm.
Sonal Sharma, Sandeep Kumar, Anand Nayyar

Outage Performance Analysis of Energy Harvesting DF Cooperative NOMA Networks over Nakagami-m Fading Channels

Abstract
In this paper, we investigate the energy harvesting decode-and-forward cooperative non-orthogonal multiple access (NOMA) networks. We study the case of the better user play a role of relay to forward information to the worse user. Specifically, one source node wishes to transmit two symbols to two respective destinations directly and via the help of energy constraint node (better user) with applying the NOMA technique over Nakagami fading channels. In order to evaluate the performance of this considered system, we derive the closed-form expressions for the outage probability (OP) at each user based on the statistical characteristics of signal-to-noise ratio (SNR) and signal-to-interference-plus-noise ratio (SINR). Our analysis is confirmed by Monte Carlo simulation. Finally, in order to look insight this system, we also investigate the effect of several parameters, such as transmit power, power splitting ratio and the location of relay nodes to the outage performance of entire system.
Van-Long Nguyen, Dac-Binh Ha

Multi-path Routing for Mission Critical Applications in Software-Defined Networks

Abstract
Mission critical applications depends on the communication among other systems and/or users and thus, the traffic/flows generated by these applications could bring profound consequences in sectors such as military, hospital, automotive safety and air-traffic control systems. These critical flows require stringent QoS requirements on parameters such as throughput, packet loss, latency, jitter and redundancy. Network operators must have tools that allow them to provide special treatment to such mission-critical flows based on specific application requirements. Due to the constraints of traditional networks, we should seek for solutions supported by de-centralised approaches offered by SDN.
In this paper, we propose a solution to achieve the stringent QoS requirement of such mission critical flows in multi-path environments based on SDN. This solution allows the network operator to prioritise traffic between specific end points. Also, using the overall view of the network, the solution allows evaluation of the path loads between two endpoints and to opt for the less congested path. Moreover, this paper tries to demonstrate a satisfactory network performance by presenting trade-offs between throughput and the number of hops within a multi-path network. The proposed solution is implemented in the application and control layer of the OpenDaylight Controller. The networking devices were simulated using Mininet simulator and background traffic was generated using Iperf.
Ramon Carreras Ramirez, Quoc-Tuan Vien, Ramona Trestian, Leonardo Mostarda, Purav Shah

Natural Disaster and Environmental Threat Monitoring System: Design and Implementation

Abstract
Nowadays, climate change is mainly caused by human activities. As a consequence, natural disasters such as flooding, storm, and drought are attacking people at high frequency and extreme damage. In addition, many megacities have been facing the rapid urbanization problem of the increase in carbon emission, noise, dust, and temperature that seriously impacts on the living conditions of the people. In this paper, we design and implement a monitoring system for early detecting and warning the natural disasters and the environmental threats of the rapid urbanization in two typical provinces in the Central Vietnam, i.e., Quang Nam and Da Nang. The system will sense, communicate, store, process, and display the important information including precipitation, wind speed and direction, water level, and landslide/earthquake in Quang Nam and CO\(_2\) emission, temperature, dust, and noise in Da Nang. The experimental results can help the local government and citizens with better management of natural disasters and environmental threats in the future.
Ba-Cuong Huynh, Thanh-Hieu Nguyen, Thanh-Duong Vu, Nguyen-Son Vo, Trung Q. Duong

Sport News Semantic Search with Natural Language Questions

Abstract
An increasingly huge amount of sport news published from a number of heterogeneous sources on the Web brings challenges to the traditional searching method using keywords. Providing an expressive way to retrieve news items and exploiting the advantages of semantic search technique in the development of Web-based sports news aggregation system is within our consideration. This paper presents a method to translate natural language questions into queries in SPARQL, the standard query language recommended by W3C for semantic data. Our contribution consists mainly of the construction of a semantic model representing a question, the detection of ontology vocabularies and knowledge base elements in question, and their mapping to generate a query. We evaluate the method based on a set of natural language questions and the results show that the proposed method achieves good performance with respect to precision.
Quang-Minh Nguyen, Son-Hong Ngo, Tuan-Dung Cao

Smart City Total Transport-Managing System

(A Vision Including the Cooperating, Contract-Based and Priority Transport Management)
Abstract
Today’s nations are facing numerous challenges in transforming living environments in a way better-serving people’s demands of the future. The principal point in this transformation is reinventing cities as smart cities that combine their data, their resources, their infrastructure and their people to continually focus on improving livability while minimizing the use of resources. The usage data and sensor network is the primary characteristics of any smart city. However, just having data is not enough, data points themselves are only information. It is good to have, but hardly useful by themselves.
This paper gives a short overview of the concepts for transport management system in the smart city and proposes a new transport management approach that is contract-based and priority transport management. These methods allow to estimate and control traffic efficiently. Based on these concepts, the authors propose a new transport management system that is working as a single system. This proposed system has three layers: physical, info-communication and control generation. The system deals with four different classes of tasks: (i) handling the non-cooperative vehicle, (ii) traffic management based on the cooperative vehicle information, (iii) contract-based traffic management, (iv) priority transport management. Some benefits of implementing this system are also expected in this paper.
Nguyen Dinh Dung, Jozsef Rohacs

Shinobi: A Novel Approach for Context-Driven Testing (CDT) Using Heuristics and Machine Learning for Web Applications

Abstract
Context-Driven Testing is widely used in the Agile World. It optimizes the testing value and provides an effective way to detect unexpected bugs. Context-driven testing requires the testing team to leverage the full knowledge and skills to solve the problem or to make a decision. In this paper, we propose an approach for Context-Driven Testing using Heuristics and Machine Learning for web applications with a framework called Shinobi. The framework can detect web controls, suggest a set of heuristic values, recognize the meaningful input data, and detect changes of application to recommend test ideas. In the context of improvising the testing performance, Shinobi is considered as Test Assistant for context-driven testers. Shinobi is a PoC to prove the idea of using Machine Learning to develop a Virtual Tester to improve the test quality and train junior testers as responsible testers. The framework is well integrated into all eCommerce projects at MeU Solutions which is a value-added advantage for testing.
Duc-Man Nguyen, Hoang-Nhat Do, Quyet-Thang Huynh, Dinh-Thien Vo, Nhu-Hang Ha

DOA Estimation of Underwater Acoustic Signals Using Non-uniform Linear Arrays

Abstract
This paper proposes to use the multiple signal classification (MUSIC) algorithm applied to non-uniform linear array (NLA) to estimate the direction of arrival (DOA) for passive sonar systems. The performance of the DOA estimation obtained by the MUSIC algorithm is investigated by applying different configurations of the antenna array parameters. For the purpose of comparison, uniform linear arrays (ULAs) are also considered. With same number of elements and antenna parameter configuration, the simulation results show, that the NLA significantly provides a better performance in terms of DOA estimation than that obtained by the ULA. In addition, the accuracy and resolution of the DOA, as well as the number of detectable signal sources can be increased, if we enlarge the antenna spacing as well as the number of the antenna elements.
Sang Van Doan, Trang Cong Tran, Van Duc Nguyen

Performance Analysis of the Access Link of Drone Base Station Networks with LoS/NLoS Transmissions

Abstract
In this paper, we provide performance analysis for drone base station (DBS)-enabled wireless communication networks. The lower bound performance of such networks has been previously obtained in the literature, assuming DBSs are statically hovering and randomly distributed according to a homogeneous Poisson point process (HPPP). We derive the upper bound performance of such networks assuming a teleportation mode, i.e., DBSs can instantaneously move to the positions directly overhead ground users (UEs). By considering both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions in the access links between DBSs and ground UEs, coverage probability and area spectral efficiency (ASE) are derived in closed-form expressions based on stochastic geometry analysis. The characterization of both the lower and upper bound performances of DBS networks indicates the performance region of practical DBS network operations. Moreover, our analytical and simulation results in this paper provide guidelines for performance optimization of further DBS networks.
Huazhou Li, Ming Ding, David López-Pérez, Azade Fotouhi, Zihuai Lin, Mahbub Hassan

Development of the Rules for Transformation of UML Sequence Diagrams into Queueing Petri Nets

Abstract
Sequence diagrams (SDs) are an abstraction of communication modeling between different entities, objects or classes. SDs are used to describe an execution trace of a particular system at a particular point in time. Queueing Petri Nets (QPNs) are graphical formalisms, at a lower level of abstraction, for which efficient and mature simulation-based solution techniques are available. This paper defines and explains the relationship between sequence diagrams and QPNs. Our approach can be used to transform sequence diagrams into QPNs. We presented the development of the model transformation solution to translate UML Sequence Diagrams (SDs) into equivalent QPNs. A case study of a new account opening for banking management system is used to illustrate the transformation rules.
Vu Van Doc, Huynh Quyet Thang, Nguyen Trong Bach

HHUSI: An Efficient Algorithm for Hiding Sensitive High Utility Itemsets

Abstract
Itemset hiding is a technique that modifies data in order to remove sensitive itemsets from a database. The traditional frequent itemset hiding algorithms cannot be applied directly into high utility itemset hiding problem. In order to solve this problem, Tseng et al. [8] proposed HHUIF and MSICF algorithms. The important target of high utility itemset hiding process is to minimize the side effects caused by data distortion, including missing itemsets, ghost itemsets, remaining sensitive itemsets, and database accuracy. In this paper, we propose an algorithm, named HHUSI, for hiding high utility sensitive itemsets. The method consists of two steps: (1) identify victim transaction and victim item and (2) modify internal utility of the victim item in the victim transaction. Experiment shows that the performance of this method is better than HHUIF and MSICF.
Vy Huynh Trieu, Chau Truong Ngoc, Hai Le Quoc, Long Nguyen Thanh

Converting the Vietnamese Television News into 3D Sign Language Animations for the Deaf

Abstract
Sign language (SL) is based on the movement of hands, body gestures and motions to express information instead of speech or written forms. SL has been used since 384-322 BC and developed in many countries, including Vietnam. In some countries, there are several applications of using technology to develop SL and communicate within the deaf community. However, there is lack of studies in these areas in Vietnam. This study is approaching of using 3D avatar of the HamNoSys and building a dictionary for Vietnamese SL animation. The study builds a data set and applies the machine learning decision tree (ID3) to convert the Vietnamese normal sentences into the short sentences of the deaf. The conversion process generates SiGML language to express the SL by a virtual signer leading to present the television news. The assessment results by experts in SL institutions indicate high precision of proposed solution and show the needs of the study.
Quach Luyl Da, Nguyen Hua Duy Khang, Nguyen Chi Ngon

Outage Performance of the Downlink NOMA Relay Networks with RF Energy Harvesting and Buffer Aided Relay

Abstract
In this paper, we investigate performance of a decode-and-forward Non-Orthogonal Multiple Access (NOMA) relay system using Simultaneous Information and Power Transfer (SWIPT). In the considered system a source node transmits data in the downlink simultaneously to two destination nodes via an energy-harvesting relay node. In order to cope with fading channels the relay is assumed to have an infinite capacity buffer to store data if the transmission link is in outage. We analyze outage performance of the system and obtain the closed-form expressions for the system outage probability for two cases, i.e. the relay is equipped and not equipped with the buffer. Numerical results are provided to demonstrate the merit of using the buffer-aided relay.
Xuan Nam Tran, Tran Manh Hoang, Nguyen Ba Cao, Le The Dung

Analyzing Seismic Signal Using Support Vector Machine for Vehicle Motion Detection

Abstract
A system to process seismic signals of vehicles passing between two sensor stations had been developed and experimented. To evaluate the feasibility of the system before field test with a real vehicle and to support the classification model with artificial data later, the input seismic data were simulated from Green’s method function that accounts only for Rayleigh surface wave. The system using the Machine Learning Classification method SVM to classify data collected from two stations at any time have the state of passed or not. By processing the signal, the system could detect whether the vehicle had passed the crossing line or not with the accuracy of 99.10% for simulated data and 94.22% for experiment data. The experiment and results suggested that processing seismic signals to monitor control lines is feasible.
Thang Duong Nhat, Mai Nguyen Thi Phuong

Smart-IoUT 1.0: A Smart Aquatic Monitoring Network Based on Internet of Underwater Things (IoUT)

Abstract
Internet of Underwater Things (IoUT) is defined as a network of smart interconnected underwater objects for monitoring/carrying out underwater operations. IoUT enables a system of autonomous underwater vehicles (AUV) communicating with each other, sensing, collecting and transmitting data to control centers above the surface at regular Internet speeds. The information could be a great source to carry out a wide range of tasks like crash surveying, shipwrecks discovery, detection of tsunamis early signs, animal health monitoring as well as collecting real-time aquatic information, archaeological expeditions etc. This paper analyzes the complete terminology of IoUT - Concept, Architecture and challenges. In addition to this, a novel IoUT based working prototype, i.e. Smart IoUT 1.0 is proposed for sensing and collecting underwater information. Smart IoUT 1.0 is equipped with 2 sensing nodes containing 4 different sensors - EZO Dissolved Oxygen Sensor, DS18B20 Temperature sensor, pH analog and Water Turbidity Sensor for acquiring live data and access it anywhere via Internet using Thingspeak.com. The paper provides strong base ground for researchers to tackle serious challenges posed by IoUT as extending the concept of IoT to underwater is completely different.
Anand Nayyar, Cuong Huynh Ba, Nguyen Pham Cong Duc, Ha Dac Binh

Wireless Power Transfer Under Secure Communication with Multiple Antennas and Eavesdroppers

Abstract
In this paper, we analyze the physical layer secrecy performance of a 5G radio frequency energy harvesting (RF-EH) network in the presence of multiple passive eavesdroppers. In this system, the source is considered as an energy-limited node, hence it harvests energy from RF signals generated by a power transfer station to use for information transmission. Additionally, in order to enhance the energy harvesting and system performance, the source is equipped with multiple antennas and employs maximal ratio combining (MRC) and transmit antenna selection (TAS) techniques to exploit the benefits of spatial diversity. Given these settings, the exact close-form expressions of existence probability of secrecy capacity and secrecy outage probability are derived. Furthermore, the obtained results indicate that multiple antennas technique applied at the source not only facilitates energy harvesting but also improves secrecy performance of the investigated network. Finally, Monte-Carlo simulation is provided to confirm our analytical results.
Duc-Dung Tran, Dac-Binh Ha, Anand Nayyar

Impact of Opportunistic Transmission on MCIK-OFDM: Diversity and Coding Gains

Abstract
This work proposes an opportunistic scheduling scheme for Multi-Carrier Index Keying - Orthogonal Frequency Division Multiplexing (MCIK-OFDM), which is termed as OS-MCIK-OFDM. Particularly, in every transmission, the proposed scheme allows only one machine whose worst sub-channel is the maximum among several machines’ worst sub-channels, to communicate with the central device, employing MCIK-OFDM technique. As a result, OS-MCIK-OFDM can harvest the multi-user diversity gain to enhance the reliability of MCIK-OFDM, especially when the number of machines increases. For performance analysis, we derive the closed-form expression for the symbol error probability (SEP), which is then asymptotically analyzed to develop unique features that can address achievable diversity and coding gains, as well as impacts of system parameters. Finally, simulation results are presented to validate the accuracy of the derived SEP performance of OS-MCIK-OFDM and specifically its superiority over the opportunistic scheduling OFDM.
Thien Van Luong, Youngwook Ko

An Improved Occlusion Detection with Constraints Approach for Video Processing

Abstract
The accurate understanding of occlusion region is critical for trustworthy estimation of optical flow to prevent the negative influence of occluded pixels on disocclusion regions. However, occlusion is the result of motion. In contrast, estimating accurate optical flow is necessary to locate reliable occlusions. Hence, one of the key challenges that required further exploration and research is the accuracy at the boundaries of the moving objects. This paper presents the work in process approach that can detect occlusion regions by using some constraints such as pixel-wise coherence, segment-wise confidence and edge-motion coherence. Comparing to the previous methods, our method achieves the same efficiency by solving only one Partial Differential Equation (PDE) problem. The proposed method is faster and provides better coverage rates for occlusion regions than variation techniques in various numbers of benchmark datasets. With these improved results, we can apply and extend our approach to a wider range of applications in computer vision, such as: motion estimation, object detection and tracking, robot navigation, 3D reconstruction, image registration.
Tuan-Anh Vu, Hung Ngoc Phan, Tu Kha Huynh, Synh Viet-Uyen Ha

Development and Deployment of an IoT-Based Reconfigurable System: A Case Study for Smart Garden

Abstract
Nowadays, Internet of Things (IoT) is not only a hot research topic but also plays a vital role in the development and deployment of many different domains, e.g., industry, transportation, education, health and agriculture as well. However, the development and deployment of real-time IoT-based systems requires stringent technical challenges on the scalability, the availability and the dynamic adaptability of the IoTs systems and applications. In this paper, we present an IoT-based architecture with a reconfigurable approach to deal with those technical challenges, and the proposed IoT-based reconfigurable system is applied for the environmental monitoring in a Smart Garden application as a case study. By implementing the load-balanced infrastructure and the over-the-air (OTA) programming, our system fulfils the large deployment of many wireless sensor devices. In addition, we have also presented and discussed the empirical results related to the resource usage, the packet transmission and the energy consumption during the reconfiguration and lay out tentative approaches on the application of our proposed system to different application domains.
Dang Huynh-Van, Ngan Le-Thi-Chau, Khoa Ngo-Khanh, Quan Le-Trung

Secure Cooperative Systems with Jamming and Unreliable Backhaul over Nakagami-m Fading Channels

Abstract
In this paper, the secrecy performance of cooperative networks with jamming signals of eavesdroppers are studied under the impacts of unreliable backhaul networks. By proposing a two-phase transmitter/relay selection scheme, the desired signal-to-noise ratio (SNR) of relays is maximized by selected the best transmitter, meanwhile, the jamming signal-to-interference-plus-noise ratio (SINR) of the eavesdroppers is minimized by selected the best relay. The secrecy outage probability is derived in closed-form expressions by following some useful lemmas and theorems. Furthermore, the analysis of asymptotic secrecy outage probability is also performed to explicitly reveal the impacts of unreliable backhaul links on the secrecy performance. By the impact of imperfect backhaul links, the diversity gain is limited as shown in our results.
Michael Stewart, Long D. Nguyen, Cheng Yin, Emiliano Garcia-Palacios, Sang Q. Nguyen

Outage Probability of Cognitive Heterogeneous Networks with Multiple Primary Users and Unreliable Backhaul Connections

Abstract
A cognitive heterogeneous network with unreliable backhaul connections is studied in this paper. In this system, a macro-base station connected to cloud transmits information to multiple small cells via backhaul links. In addition, multiple small cells acting as secondary transmitters send information to a receiver by sharing the same spectrum with multiple primary users. Bernoulli process is adopted to model the backhaul reliability. Selection combining protocol is used at the receiver side to maximize the received signal-to-noise ratio. We investigate the impacts of the number of small-cells, the number of primary users as well as the backhaul reliability on the system performance, i.e., outage probability in Rayleigh fading channels. Closed-form expressions are derived and asymptotic analysis is also provided.
Cheng Yin, Jingxian Xie, Emiliano Garcia-Palacios, Hien M. Nguyen

Impact of Direct Communications on the Performance of Cooperative Spectrum-Sharing with Two-Way Relays and Maximal Ratio Combining

Abstract
In this paper, we investigate a three-phase two-way (TW) amplify-and-forward (AF) relaying for cognitive radio networks. By utilizing the direct communications, the end user can employ maximal ratio combining to achieve the full diversity. We derive the closed-form and asymptotic expressions for user and system outage probabilities which allow us to highlight the advantage of cooperative cognitive communications. The numerical results, obtained through compact forms of these outage probabilities, yield that the cognitive TW AF relaying scheme can significantly enhance the reliability of unlicensed networks in which the transmit power at each secondary user is strictly governed.
Tu Lam Thanh, Tiep M. Hoang, Vo Nguyen Quoc Bao, Hien M. Nguyen

Energy Efficiency Maximization with Per-Antenna Power Constraints for Multicell Networks Using D.C. Programming

Abstract
This paper studies the energy efficiency (EE) optimization problem in multicell wireless networks in which each base station (BS) equipped with multiple antennas serves multiple users at the same time and in the same frequency. The problem of interest is to design the precoders to maximize the network EE subject to practical power constraints at physical layers. The resultant optimization design problem is nonconvex fractional programming and, thus, finding its optimal solution is mathematically challenging. In this paper, we use a combination of difference of convex (d.c.) programming and the Dinkelbach algorithm to iteratively solve the optimization problem. Then, by numerical simulations, we verify the convergence characteristics of the iterative algorithm and examine the EE performance of the system as compared to an spectral efficiency (SE) approach.
Le Ty Khanh, Ha Hoang Kha, Nguyen Minh Hoang

Development of a Positioning Solution Using FUKS Based on RTS Smoother Combined with FUKF for Vehicle Management Systems

Abstract
This article introduces a new way to improve accuracy of trajectory in transportation management systems, in which it describes a design for integrated INS/GPS device mounted on vehicle and algorithms for trajectories at the station. The significant features of this system are the ways to process data at station by using a flexible unscented Kalman filter algorithm, and a backward retrieval calculation algorithm based on Rauch-Tung-Striebel smoother, called flexible unscented Kalman smoother. This system has the capability of receiving the information in order to locate, monitor hybrid buses more exactly and manage some other motion parameters to improve the quality of monitoring and management transportation system, and also to evaluate driving style of drivers in services and support for smart cities.
Binh Thanh Ngo, Michele Zucchelli, Francesco Biral

Modeling Spatially-Correlated Cellular Networks by Using Inhomogeneous Poisson Point Processes

Abstract
In this paper, we introduce the Inhomogeneous Double Thinning (IDT) approach, which allows us to analyze the performance of downlink cellular networks in which the Base Stations (BSs) constitute a stationary Point Process (PP) that exhibits some degree of spatial repulsion (i.e., inhibition). The accuracy of the proposed IDT approach is substantiated by using empirical data for the spatial distribution of the BSs.
Marco Di Renzo, Shanshan Wang, Xiaojun XI

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