Abdül Halim Zaim

A Novel Energy Efficient Routing Protocol in Wireless Sensor Networks

For terrestrial positioning, some applications require three dimensional coordinates. The Dilution of precisions (DOPs) for position systems using range measurement is reviewed and the average values of DOPs for different deployments of base station geometries are examined. It is shown that to obtain the lowest DOPs, the base stations for different types of positioning systems need to be deployed differently. Changing the N-sided regular polygon to an (N – 1)-sided polygon with one base station in the centre of the polygon can decrease the value of DOP in general for a pseudorange time of arrival (TOA) system but not for an absolute range TOA system. The height of the base station in the centre can also change the DOP significantly. The finding can be used to optimize the deployment of the base stations for range measurement positioning systems.

A Multichannel Cross-Layer Architecture for Multimedia Sensor Networks

Depending upon the technological developments, the same fast evolution has occurred in the structures of sensor networks, their composing devices which are sensor nodes, and their application areas. Those tiny, energy-constrained, mostly non-real-time data transmitting sensor nodes have evolved to more energy-containing, camera-adapted, real-time multimedia-data-transmitting devices. Developments in the usage areas and the capabilities have revealed some other problems such as time limited data transmission. In this paper, we propose a multichannel cross-layer architecture for Quality of Service (QoS) constrained multimedia sensor networks. The proposed architecture considers both the time and energy efficiency concepts. Energy efficiency is succeeded by ensuring the fair load distribution among the nodes during a real-time multimedia packet stream transmission. Besides ensuring the fair load distribution, on-time packet transmission is also assured by constructing the paths with a hard reservation technique depending on the predetermined QoS constraints. Simulations show that the proposed architecture provides higher performance than the Greedy approach and the LEERA scheme.

A new dynamic bandwidth allocation algorithm based on online-offline mode for EPON

In parallel with the enormous spread of Internet usage, the tendency of users for high capacity applications (HDTV, Online Games, P2P File Transfer) are rising. This increase in needs of data communication, compel the service providers to act to end users better than before. At this point, Passive Optical Networks (PONs) distinguish in access network solutions due to its capability of carrying high amount of data over longer distances. Although they are still in development, existing electronic based data communication techniques (ADSL, double twisted copper telephony systems like VDSL, cable modem coaxial cable CATV systems) can operate over short distances and have large amount of energy consumption. In this paper, basic schemes of dynamic bandwidth allocation algorithms on EPON have been presented and a novel online-offline based method called hcDBA (Half Cycling Dynamic Bandwidth Allocation) has been introduced. In addition, hcDBA algorithm has been improved with early prediction mechanism (p-hcDBA). By the simulation studies, it has been investigated that hcDBA algorithm performs better than existing mechanism in terms of byte loss ratio and access delays criteria. p-hcDBA also improved the performance in terms of access delay. In this study, we stated that when the bandwidth increases the prediction approached has more impact of the overall performance.

Towards green and secure vehicle-to-vehicle communications: A protocol for establishing the network

In this study, initial part of establishing a Green and Secure Vehicle-to-Vehicle Communications Network (GSV2VCN) is proposed. Different from IEEE 1609.3, the protocol proposed focuses solely on a universal control channel (CC) to agree on a master of the group of close-by nodes within the same physical region. Also, unlike IEEE 1609.3, the proposed protocol does not take advantage of multi-channel transceiver mode. Instead, once the master is agreed on, the slave nodes switch to a specific service channel (SC) decided by the master. An object-oriented simulation framework is designed and run to obtain statistics for the proposed protocol. Results are provided along with the relevant discussions. Future work towards GSV2VCN is given as well.

Deep Learning Approaches for Predictive Masquerade Detection

In computer security, masquerade detection is a special type of intrusion detection problem. Effective and early intrusion detection is a crucial factor for computer security. Although considerable work has been focused on masquerade detection for more than a decade, achieving a high level of accuracy and a comparatively low false alarm rate is still a big challenge. In this paper, we present a comprehensive empirical study in the area of anomaly-based masquerade detection using three deep learning models, namely, Deep Neural Networks (DNN), Long Short-Term Memory Recurrent Neural Networks (LSTM-RNN), and Convolutional Neural Networks (CNN). In order to surpass previous studies on this subject, we used three UNIX command line-based datasets, with six variant data configurations implemented from them. Furthermore, static and dynamic masquerade detection approaches were utilized in this study. In a static approach, DNN and LSTM-RNN models are used along with a Particle Swarm Optimization-based algorithm for their hyperparameters selection. On the other hand, a CNN model is employed in a dynamic approach. Moreover, twelve well-known evaluation metrics are used to assess model performance in each of the data configurations. Finally, intensive quantitative and ROC curves analyses of results are provided at the end of this paper. The results not only show that deep learning models outperform all traditional machine learning methods in the literature but also prove their ability to enhance masquerade detection on the used datasets significantly.

An Efficient Big Data Anonymization Algorithm Based on Chaos and Perturbation Techniques

The topic of big data has attracted increasing interest in recent years. The emergence of big data leads to new difficulties in terms of protection models used for data privacy, which is of necessity for sharing and processing data. Protecting individuals’ sensitive information while maintaining the usability of the data set published is the most important challenge in privacy preserving. In this regard, data anonymization methods are utilized in order to protect data against identity disclosure and linking attacks. In this study, a novel data anonymization algorithm based on chaos and perturbation has been proposed for privacy and utility preserving in big data. The performance of the proposed algorithm is evaluated in terms of Kullback–Leibler divergence, probabilistic anonymity, classification accuracy, F-measure and execution time. The experimental results have shown that the proposed algorithm is efficient and performs better in terms of Kullback–Leibler divergence, classification accuracy and F-measure compared to most of the existing algorithms using the same data set. Resulting from applying chaos to perturb data, such successful algorithm is promising to be used in privacy preserving data mining and data publishing.

Implementation of Variants in Component Based Software Production

We created and implemented an algebraic framework to automatically generate component variants out of specifications. In this paper we provide the definition of this approach with its operators and operands, and show how expressions can be parsed, translated and processed for production of component variants. We created a Java application which is widely based on sets, to show the approach can be implemented properly and efficiently.

Identification of shadowed fast fading interference in celullar mobile radio systems

In this study, a method that identifies shadowed fast fading interference is proposed on downlink transmission for frequency division duplexing (FDD)-based cellular mobile radio communications systems. The method proposed exploits the independence of shadowing and fast-fading processes along with the difference between their occurrence scales in spatial dimension and provides an analytical approach to identify the interference with the aid of a metric defined.

How Variability Helps to Make Components More Flexible and Reusable

Cross-project and cross-market reusability is the basis for the existence of a component-based development paradigm for the establishment of a software industry based on reusability and conservation of expertise. In this paradigm producer is in need to enhance components’ functional capabilities and increase the audiences for successful marketing, so they tend to add extra features to widen the reuse spectrum. However, this in return is recompensed by the component consumers in means of higher prices for unneeded features, overflowing functionality and superfluous code. The component producers need more flexibility to generate specific patterns of components to deal with the changing requests of consumers. In this paper we provide a basis for more flexible components.