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Journal of Telecommunications and Information Technology (JTIT) - 1/2017

Joanna Kołodziej
Preface
[ Bibtex Plain ]
Mohammed Zidane, Said Safi and Mohamed Sabri
Compensation of Fading Channels Using Partial Combining Equalizer in MC-CDMA Systems
In this paper the performance of a partial combining equalizer for Multi-Carrier Code Division Multiple Access (MC-CDMA) systems is analytically and numerically evaluated. In the part of channel identification, authors propose a blind algorithm based on Higher Order Cumulants (HOC) for identifying the parameters representing the indoor scenario of Broadband Radio Access Networks (BRAN A) channel model normalized for MC-CDMA systems. Theoretical analysis and numerical simulation results, in noisy environment and for different Signal to Noise Ratio (SNR), are presented to illustrate the performance of the proposed algorithm in the one hand, and the other hand the impact of partial combining equalizer on the performance of MC-CDMA systems.
[ Bibtex Plain ]
Noureddine Lachachi
Unsupervised Phoneme Segmentation Based on Main Energy Change for Arabic Speech
In this paper, a new method for segmenting speech at the phoneme level is presented. For this purpose, author uses the short-time Fourier transform of the speech signal. The goal is to identify the locations of main energy changes in frequency over time, which can be described as phoneme boundaries. A frequency range analysis and search for energy changes in individual area is applied to obtain further precision to identify speech segments that carry out vowel and consonant segment confined in small number of narrow spectral areas. This method merely utilizes the power spectrum of the signal for segmentation. There is no need for any adaptation of the parameters or training for different speakers in advance. In addition, no transcript information, neither any prior linguistic knowledge about the phonemes is needed, or voiced/unvoiced decision making is required. Segmentation results with proposed method have been compared with a manual segmentation, and compared with three same kinds of segmentation methods. These results show that 81% of the boundaries are successfully identified. This research aims to improve the acoustic parameters for all the processing systems of the Arab speech.
[ Bibtex Plain ]
Subhajit Chatterjee, Swaham Dutta, Partha Pratim Bhattacharya and Jibendu Sekhar Roy
Optimization of Spectrum Sensing Parameters in Cognitive Radio Using Adaptive Genetic Algorithm
Quality of service parameters of cognitive radio, like, bandwidth, throughput and spectral efficiency are optimized using adaptive and demand based genetic algorithm. Simulation results show that the proposed method gives better real life solution to the cognitive radio network than other known approach.
[ Bibtex Plain ]
Vincenzo Conti and Salvatore Vitabile
Design Exploration of AES Accelerators on FPGAs and GPUs
The embedded systems are increasingly becoming a key technological component of all kinds of complex technical systems and an exhaustive analysis of the state of the art of all current performance with respect to architectures, design methodologies, test and applications could be very interesting. The Advanced Encryption Standard (AES), based on the well-known algorithm Rijndael, is designed to be easily implemented in hardware and software platforms. General purpose computing on graphics processing unit (GPGPU) is an alternative to recon gurable accelerators based on FPGA devices. This paper presents a direct comparison between FPGA and GPU used as accelerators for the AES cipher. The results achieved on both platforms and their analysis has been compared to several others in order to establish which device is best at playing the role of hardware accelerator by each solution showing interesting considerations in terms of throughput, speedup factor, and resource usage. This analysis suggests that, while hardware design on FPGA remains the natural choice for consumer-product design, GPUs are nowadays the preferable choice for PC based accelerators, especially when the processing routines are highly parallelizable.
[ Bibtex Plain ]
Shiva Rowshanrad, Sahar Namvarasl and Manijeh Keshtgari
A Queue Monitoring System in OpenFlow Software Defi ned Networks
Real-time trac characteristic is di erent and it is very sensitive to delay. To meet trac speci cations in real time, monitoring systems are used as an important part of networking. Many monitoring systems are deployed to have an update view of the network QoS parameters and performance. Most of these systems are implemented to measure QoS parameters in links. Here, in this paper, a system for monitoring queues in each link by means of Software Defined Networks is proposed. The monitoring system is implemented by extending Floodlight controller, which uses OpenFlow as southbound protocol. The controller has a centralized view of the network. By the help of OpenFlow it also can provide flow level statistics. Using these advantages, the proposed system can monitor delay and available bandwidth of a queue on a link or path. Despite of monitoring systems in traditional networks, the proposed monitoring system makes a low overhead in network thanks to OpenFlow protocol messages. It is also integrated into the network controller, which enables QoS and trac engineering applications to use the system's reports for automatic trac management and QoS setup. The experimental results show a 99% accuracy of the proposed system for monitoring of both bandwidth and delay.
[ Bibtex Plain ]
Sheena Kohli and Partha Pratim Bhattacharya
Sensor Hop-based Energy Efficient Networking Approach for Routing in Underwater Acoustic Communication
Underwater Wireless Sensor Networks are deployed to explore the world under the water, measure different parameters and communicate the data to the surface, in the widespread applications. The main operating technology of these networks is the acoustic communication. The communication among the sensors and finally to the surface station requires a routing protocol. The sensors being battery limited and unfeasible to be replaced under the water requires an energy efficient routing protocol. Clustering imparted in routing is an energy saving technique in sensor networks. The routing may involve single or multi hop communication in the sensor networks. The paper gives a comparative study of the benchmark protocol multi-hop LEACH with the proposed Sensor Hop-based Energy Efficient Networking Approach (SHEENA) for the shallow as well as deep water in three dimensional Underwater Wireless Sensor Networks. The network energy model for the Underwater Wireless Sensor Networks is based among the different acoustic channel characteristics. The proposed approach is found to give better response.
[ Bibtex Plain ]
Priya Mishra, Charu Gandhi and Buddha Singh
An Improved Greedy Forwarding Scheme in MANETs
Position-based routing protocols are widely accepted efficient solution for routing in MANETs. The main feature of position-based routing protocols is to use greedy forwarding methods to route data. The greedy forwarding methods select a node, either having maximum progress towards destination (distance-based principle) or minimum deviation with line between source and destination (direction-based strategy). The first method minimizes the hopcount in a path and on the other hand, second method minimizes the spatial distance between source and destination. The distance-based routing has a great impact on the selection of reliable node and the direction based routing plays a major role to increase the stability of route towards destination. Therefore, in this paper authors propose a weighted forwarding method, which combines both the selection, schemes to select an optimal next forwarding node in a range. The simulation results show that the proposed scheme performs better than existing position-based routing protocols.
[ Bibtex Plain ]
Agnieszka Jakóbik, Daniel Grzonka, Joanna Kołodziej, Adriana E. Chis and Horacio González-Vélez
Energy Efficient Scheduling Methods for Computational Grids and Clouds
This paper presents an overview of techniques developed to improve energy efficiency of grid and cloud computing. Power consumption models and energy usage pro les are presented together with energy efficiency measuring methods. Modeling of computing dynamics is discussed from the viewpoint of system identi cation theory, indicating basic experiment design problems and challenges. Novel approaches to cluster and network-wide energy usage optimization are surveyed, including multi-level power and software control systems, energy-aware task scheduling, resource allocation algorithms and frameworks for backbone networks management. Software-development techniques and tools are also presented as a new promising way to reduce power consumption at the computing node level. Finally,  energy-aware control mechanisms are presented. In addition, this paper introduces the example of batch scheduler based on ETC matrix approach.
[ Bibtex Plain ]
Jamal Raiyn
Introduction to Big Data Management Based on Agent Oriented Cyber Security
This paper deals with information security and safety issues in public open spaces. Public open spaces include high streets, street markets, shopping centers, community gardens, parks, and playgrounds, each of which plays a vital role in the social, cultural and economic life of a community. Those outdoor public places are mashed up with various ICT tools, such as video surveillance, smartphone apps, Internet of Things (IoT) technologies, and biometric big data (called Cyber Parks). Security and safety in public places may include video surveillance of movement and the securing of personalized information and location-based services. The article introduces technologies used in Cyber Parks to achieve information security in big data era.
[ Bibtex Plain ]
Agnieszka Jakóbik and Andrzej Wilczyński
Using Polymatrix Extensive Stackelberg Games in Security – Aware Resource Allocation and Task Scheduling in Computational Clouds
In this paper, the Stackelberg game models are used for supporting the decisions on task scheduling and resource utilization in computational clouds. Stackelberg games are asymmetric games, where a specific group of players’ acts first as leaders, and the rest of the players follow the leaders’ decisions and make their decisions based on the leader’s actions. In the proposed model, the optimal schedules are generated under the security criteria along with the generation of the optimal virtual machines set for the scheduled batch of tasks. The security criteria are defined as security requirements for mapping tasks onto virtual machines with specified trust level. The effectiveness of the proposed method has been verified in the realistic use cases with in the cloud environment with OpenStack and Amazon Cloud standards.
[ Bibtex Plain ]
Piotr Szuster
Data Fixing Algorithm in Radiosonde Monitoring Process
Earth surface monitoring can give information that may be used in complex analysis of the air conditions, temperature, humidity etc. Data from a vertical profile of the atmosphere is also essential for accurate thunderstorm forecasting. That data is collected by radiosondes – telemetry instruments carried into the atmosphere usually by balloons. Sometimes, due to the hostile conditions of upper troposphere, incorrect data can be generated by radiosonde sensors. In this paper, a new algorithm is developed for fixing the incorrect data, i.e. missing or out of specific range values. The proposed algorithm was tested both on benchmarks and real data generated by radiosondes. About 70% of significantly damaged test data volume was recovered. Up to 100% of real data was fixed.
[ Bibtex Plain ]
Catalin-Constantin Usurelu and Florin Pop
My City Dashboard: Real-time Data Processing Platform for Smart Cities
In recent years, with the increasing popularity of IoT, the rapid growth of smartphone usage enabled by the increase adoption of Internet services and the continuously decreasing costs of these devices and services has led to a huge increase in the volume of data that governments can use in the context of smart city initiatives. The need for analytics is becoming a requirement for smart city projects such as city dashboards to provide citizens with an easy to understand overview of the city. As such, data should be analyzed, reduced and presented in such a way that citizens can easily understand various aspects of the city and use this information to increase quality of life. In this paper, we firstly present the context and the start of the design and implementation of proposed solution for real-time data processing in smart cities, mainly an analytics processing pipeline and a dashboard prototype for this solution, named My City Dashboard. We focus on high scalability and modularity of this platform.
[ Bibtex Plain ]