2017. 4th Issue
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PAPERS FROM OPEN CALL
Bowei Zhang, Xin Hu, Weinong Wu, Jie Huang, Jing Wang and Wenjiang Feng
Retrospective Interference Neutralization for the Two-Cell MIMO Interfering Multiple Access Channel
The world of Industrial IoT (Internet of Things) generates different challenges for every company. For the small and medium-size enterprises these challenges involve material and special human resource constraints. For these enterprises, the complex solutions may not be feasible due to financial reasons, so individual solutions and individual IT support must be provided for them. Still, generally accepted architectural principles, protocols, data analysis solutions are available as building blocks for solutions tailored for smaller enterprises.
In order to offer good examples for such individual solutions, this paper presents various infocommunication technologies and environment as a complex infrastructure background. This setup has already been used in two different wood industrial companies to improve the effectivenes of their productivity.
Pavel Masek, Zhaleh Sadreddini, Tugrul Cavdar and Jiri Hosek
On the Performance of Spectrum Handoff Framework for Next-generation 5G Networks
The lack of available radio spectrum and inefficiency in its usage necessitate a new communication paradigm requiring to exploit the existing spectrum opportunistically. One of the perspective spectrum sharing methods, which is currently under a heavy investigation by academia and industry as well across whole Europe, is called Licensed Shared Access (LSA). This novel technology allows for controlled sharing of spectrum between an original owner (primary user, incumbent) and a licensee (secondary user), such as the mobile network operators (MNOs), which coexist geographically. Despite certain benefits, there are still several issues to be solved before the LSA framework will be implemented in commercial infrastructure. One of them is the need to move secondary users (SUs) from the rented LSA band whenever the incumbent needs it. The potential solution for this problem is represented by spectrum handoff, which aims to help SUs to vacate the occupied licensed spectrum and find suitable network resources to resume the unfinished transmissions somewhere else in order to keep SUs satisfaction in terms of quality of experience (QoE) at negotiated quality of service (QoS) level. Inspired by this, we propose a decision making model considering several SUs attributes (RSSI, RSRP, RSRQ, SINR) in order to efficiently implement the handoff procedure and treat SUs to maximize total service time, spectrum utilization and SUs' satisfaction. As an input for our simulation model, we have used the set of measurements performed in real 3GPP LTE-A indoor cellular system located at Brno University of Technology, Czech republic. Our achieved simulation results evaluate the spectrum utilization of three 3GPP LTE-A cells and provide the total service time for each active SU, while different values of primary user's activity ratio are considered for each cell. Authors would like to recall that this paper represents extended version of their previously published work at TSP 2017 conference.
On Sensitive and Weighted Routing and Placement Schemes for Network Function Virtualization
Virtualization is a fast-growing technology that is being widely adopted to help improve network and datacenter resource manageability and usage optimization. However, given increasing deployments, new challenges are starting to arise, e.g., such as management complexity. Hence in order to deliver a higher degree of service provisioning flexibility, two key technologies have attracted attention, namely network function virtualization (NFV) and software defined networking (SDN). The former enables the implementation of network functions (NFs) via top-of-the-shelf commodity servers in datacenters. The latter decouples the data and control planes, centralizing flow rules definitions in a controller system to facilitate management and routing. Although recent NFV studies have focused on minimizing resource usage to satisfy a set of requested NFs, they do not consider scenarios with limited resources. Hence this paper presents an optimization-based solution for the joint routing and placement of virtual NFs. In particular, the scheme tries to maximize the number of satisfied requests as well as well minimize routing and deployment costs. The model also introduces weighting factors to allow operators to select cost preferences. However findings indicate that the proposed optimization solution can only be solved for smaller networks. Hence a more scalable greedy heuristic scheme is also developed.
PAPERS OF APPLIED RESEARCH
Zoltán Pödör, Attila Gludovátz, László Bacsárdi, Imre Erdei and Ferenc Nandor Janky
Industrial IoT techniques and solutions in wood industrial manufactures
The world of Industrial IoT (Internet of Things) generates different challenges for every company. For the small and medium-size enterprises these challenges involve material and special human resource constraints. For these enterprises, the complex solutions may not be feasible due to financial reasons, so individual solutions and individual IT support must be provided for them. Still, generally accepted architectural principles, protocols, data analysis solutions are available as building blocks for solutions tailored for smaller enterprises. In order to offer good examples for such individual solutions, this paper presents various infocommunication technologies and environment as a complex infrastructure background. This setup has already been used in two different wood industrial companies to improve the effectiveness of their productivity.
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2017. 3rd Issue
Full issue (6,5 MB)
PAPERS FROM OPEN CALL
István Pelle, Felicián Németh and András Gulyás
A Little Less Interaction, A Little More Action: A Modular Framework for Network Troubleshooting
Requirements of an ideal network troubleshooting system dictate that it should monitor the whole network at once, feed results to a knowledge-based decision making system and suggest actions to operators or correct the failure, all these automatically. Reality is quite the contrary, though: operators separated in their cubicles try to track down complex networking failures in their own way, which is generally a long sequence of manually edited parallel shell commands calling rudimentary tools. This process requires operators to be "masters of com- plexity" (which they often are) and continuous interaction. In this paper we aim at narrowing this huge gap between vision and reality by introducing a modular framework capable of (i) formalizing troubleshooting processes as the concatenation of executable functions [called troubleshooting graphs (TSGs)], (ii) executing these graphs via an interpreter, (iii) evaluating and navigating between the outputs of the functions and (iv) sharing troubleshooting know-hows in a formalized manner.
Sagar Arun More and Pramod Jagan Deore
View-Invariant Person Identification by Orthogonal View Gait Signature and Fusion of Classifiers
In this paper, we proposed the use of three orthogo- nal views of gait signature for view-invariant person identification system. We also experimented the fusions of classifiers in order to improve the recognition performance. Two classifiers used corresponding to two LDA spaces. The first classifier used for angle classification followed by second classifier for person identification. The proposed mechanism of selective kNN (s-kNN) has boosted the recognition performance and found very effective. We got 97.07% maximum rank-1 angle classification accuracy and 93% maximum rank-1 person identification accuracy.
Haiqing Liu, Shuhua Hao, Yuancheng Li, Xiang Li and Jie Ma
Live face detection method based on local binary pattern and bandelet
Face recognition system is exposed to video replay attacks and photo spoofing attacks along with the extensive use of identity authentication technology. Spoofing attack happens when an attacker tries to disguise as a legitimate user with permissions to spoof authentication system by replaying the recorded videos of legitimate users or utilizing the printed photos of legitimate users. Inspired by the differences between image acquisition and playback, printing properties, and light emission models, this paper proposes a live face detection method based on local binary pattern and Bandelet. The replayed video images and the printed face images usually contain characteristics that are easy to be detected by texture detection and frequency domain analysis. The proposed method analyzes the differences between live faces and photo faces in texture, at the same time it utilizes Bandelet to analyze face images with multi-scale analysis and extracts the high-frequency sub band coefficients as feature vectors to train Extreme Learning Machine (ELM) to classify and recognize. The algorithm is verified on the public CASIA_FASD, print-attack and replay-attack datasets, well known Face Anti-Spoofing Databases, and the experimental results show that the method reduces the computational complexity and improves the detection accuracy.
PAPERS OF APPLIED RESEARCH
Tamás Helfenbein, Roland Király, Márton Törőcsik, Emil Tóth and Sándor Király
Extension of RFID Based Indoor Localization Systems With Smart Transponders
The indoor localization problem is a method of identifying and finding position (co-ordinates) of requested objects in a well defined area of interest (AoI) in buildings. Beside identification, localization is an important task in several complex industrial environments. Assigning unique Radio Frequency IDentifier (RFID) tags to the objects both the identification and the localization problem can be solved.
In this paper, RFID based indoor localization systems, methods, and protocols are analysed. A novel Smart Tag platform called Blackforest with integrated self localization capabilities is introduced. This device can be in either transmitter or receiver role to ensure fast prototyping of localization environments. Higher temporal positioning possibilities and sensor fusion techniques are introduced using the BlackForest nodes. The radiofrequency (RF) characteristcs of the device were analyzed and a localization system was built using Blackforrest nodes. The localization architecture, methods and system configurations are described. After calibration, the suitable accuracy of RFID indoor localization using BlackForest Smart Tags is proven in an indoor office scenario.
A hierarchical localization protocol stack is introduced in order to extend existing indoor RFID localization systems using intelligent and co-operative antenna systems with novel Smart-Tags.
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