Ismail Ahmedy

Spectrum sensing in cognitive vehicular network

Vehicular Ad Hoc Network (VANET) is envisaged to play an important role in the safety of drivers and passengers when moving on the roads. However, VANET still faces many challenges before it could be deployed. One such challenge is shortage of radio frequency spectrum channels. VANET has been allocated 7 channels for dedicated short range communication at 5.9GHz band. The 7 channels are likely to get congested in high vehicle densities when many vehicles are contending for the same medium. Consequently, affecting the transmission of safety and emergency messages. To alleviate the problem of scarcity channels, dynamic spectrum access (DSA) through cognitive radio (CR) technology has been proposed. One of the core functions of a CR is to identify spectrum holes in licensed frequency bands that can be accessed by unlicensed users through spectrum sensing. In VANET, spectrum sensing is challenging because of the mobility nature of vehicles, dynamic topological changes as well as other unique characteristics not found in other networks. However, these challenges have not been fully studied and how they affect spectrum sensing in cognitive vehicular network (CVN). In this paper, we discuss challenges associated with spectrum sensing in CVN. We describe the primary system activity model used by many schemes proposed in literature. Furthermore, we present an in depth analysis of state-of-art cooperative spectrum sensing techniques for CVN from 2010 to May 2016. In addition, we present some of the open issues in spectrum sensing for CVN.

A review on wireless sensor networks routing protocol: Challenge in energy perspective

Wireless sensor networks (WSNs) technology consists of a number of sensor nodes that are dispersed in a geographically distributed area usually for monitoring purposes. The widespread applications of WSN have fueled the emergence and acceptance of this technology as a frontrunner. However, the success of the wireless sensor network applications highly depends on the reliable communication among the sensor nodes. One of the major problems in wireless sensor network environments is the limitation of the physical resource that is energy resources. The node energy is a critical constraint that needs addressing in order to achieve the demanding goals of wireless sensor network applications. High energy consumption in the sensor node occurs when data is disseminated to the other nodes in wireless sensor networks. Data delivery in specific time slot holds the key position for the successful completion of tasks assigned to sensor nodes and hence the application those sensors are serving. The wireless sensor network applications are in high demand nowadays. Time delay in packet delivery can save lives. The data in WSN hops from one node to another in order to reach the destination if the receiver node is not in a direct radio range of the sender. This paper provides a critical analysis on the impact of the previous methods on the reliability and energy efficiency for routing protocol in multi-hop wireless sensor networks. At the end of this paper, a characterized comparison has been forwarded on these methods based on the analysis outcome.

A Novel Method to Water Level Prediction using RBF and FFA

Water level prediction of rivers, especially in flood prone countries, can be helpful to reduce losses from flooding. A precise prediction method can issue a forewarning of the impending flood, to implement early evacuation measures, for residents near the river, when is required. To this end, we design a new method to predict water level of river. This approach relies on a novel method for prediction of water level named as RBF-FFA that is designed by utilizing firefly algorithm (FFA) to train the radial basis function (RBF) and (FFA) is used to interpolation RBF to predict the best solution. The predictions accuracy of the proposed RBF–FFA model is validated compared to those of support vector machine (SVM) and multilayer perceptron (MLP) models. In order to assess the models’ performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results show that the developed RBF–FFA model provides more precise predictions compared to different ANNs, namely support vector machine (SVM) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real time water stage measurements. The results specify that the developed RBF–FFA model can be used as an efficient technique for accurate prediction of water stage of river.

Using Captchas to Mitigate the VoIP Spam Problem

Voice over Internet Protocol (VoIP) is one of the emerging technologies today. This application offers the user a service by which one can call another person at a low cost as compare with traditional phone services. One drawback to the Internet is spam, which are unsolicited or unwanted objects which often appear as unwanted messages in various email applications. For VoIP, spam refers to unsolicited and unwanted calls by the VoIP user. In this paper, we have purposed a solution to prevent the spam in VoIP. The CAPTCHA (Completely Automated Public Turing Test to Tell Computers and Human Apart) method aims to determine whether the call is coming from a human or a machine. The key contribution of this paper is a proof-of-concept implementation of a CAPTCHA mechanism to prevent VoIP Spam.

An Estimation of QoS for Classified Based Approach and Nonclassified Based Approach of Wireless Agriculture Monitoring Network Using a Network Model

Wireless Sensor Network (WSN) can facilitate the process of monitoring the crops through agriculture monitoring network. However, it is challenging to implement the agriculture monitoring network in large scale and large distributed area. Typically, a large and dense network as a form of multihop network is used to establish communication between source and destination. This network continuously monitors the crops without sensitivity classification that can lead to message collision and packets drop. Retransmissions of drop messages can increase the energy consumption and delay. Therefore, to ensure a high quality of service (QoS), we propose an agriculture monitoring network that monitors the crops based on their sensitivity conditions wherein the crops with higher sensitivity are monitored constantly, while less sensitive crops are monitored occasionally. This approach selects a set of nodes rather than utilizing all the nodes in the network which reduces the power consumption in each node and network delay. The QoS of the proposed classified based approach is compared with the nonclassified approach in two scenarios; the backoff periods are changed in the first scenario while the numbers of nodes are changed in the second scenario. The simulation results demonstrate that the proposed approach outperforms the nonclassified approach on different test scenarios.

A Multivariant Stream Analysis Approach to Detect and Mitigate DDoS Attacks in Vehicular Ad Hoc Networks

Vehicular Ad Hoc Networks (VANETs) are rapidly gaining attention due to the diversity of services that they can potentially offer. However, VANET communication is vulnerable to numerous security threats such as Distributed Denial of Service (DDoS) attacks. Dealing with these attacks in VANET is a challenging problem. Most of the existing DDoS detection techniques suffer from poor accuracy and high computational overhead. To cope with these problems, we present a novel Multivariant Stream Analysis (MVSA) approach. The proposed MVSA approach maintains the multiple stages for detection DDoS attack in network. The Multivariant Stream Analysis gives unique result based on the Vehicle-to-Vehicle communication through Road Side Unit. The approach observes the traffic in different situations and time frames and maintains different rules for various traffic classes in various time windows. The performance of the MVSA is evaluated using an NS2 simulator. Simulation results demonstrate the effectiveness and efficiency of the MVSA regarding detection accuracy and reducing the impact on VANET communication.

A Localization-Free Interference and Energy Holes Minimization Routing for Underwater Wireless Sensor Networks

Interference and energy holes formation in underwater wireless sensor networks (UWSNs) threaten the reliable delivery of data packets from a source to a destination. Interference also causes inefficient utilization of the limited battery power of the sensor nodes in that more power is consumed in the retransmission of the lost packets. Energy holes are dead nodes close to the surface of water, and their early death interrupts data delivery even when the network has live nodes. This paper proposes a localization-free interference and energy holes minimization (LF-IEHM) routing protocol for UWSNs. The proposed algorithm overcomes interference during data packet forwarding by defining a unique packet holding time for every sensor node. The energy holes formation is mitigated by a variable transmission range of the sensor nodes. As compared to the conventional routing protocols, the proposed protocol does not require the localization information of the sensor nodes, which is cumbersome and difficult to obtain, as nodes change their positions with water currents. Simulation results show superior performance of the proposed scheme in terms of packets received at the final destination and end-to-end delay.

Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP)

In this paper, we propose an extended multi-objective version of single objective optimization algorithm called sperm swarm optimization algorithm. The proposed multi-objective optimization algorithm based on sperm fertilization procedure (MOSFP) operates based on Pareto dominance and a crowding factor, that crowd and filter out the list of the best sperms (global best values). We divide the sperm swarm into three equal parts, after that, different types of turbulence (mutation) operators are applied on these parts, such as uniform mutation, non-uniform mutation, and without any mutation. Our algorithm is compared against three well-known algorithms in the field of optimization. These algorithms are NSGA-II, SPEA2, and OMOPSO. These algorithms are compared using a very popular benchmark function suites called Zitzler-Deb-Thiele (ZDT) and Walking-Fish-Group (WFG). We also adopt three quality metrics to compare the convergence, accuracy, and diversity of these algorithms, including, inverted generational distance (IGD), spread (SP), and epsilon (∈). The experimental results show that the performance of the proposed MOSFP is highly competitive, which outperformed OMOPSO in solving problems such as ZDT3, WFG5, and WFG8. In addition, the proposed MOSFP outperformed both of NSGA-II or SPEA2 algorithms in solving all the problems.

Review of hardware implementation of Speech-To-Text Engine for Jawi Character

Jawi is a Malay writing script based on the Arabic script which adds six extra characters to accommodate Malay vocal sounds. Real-Time Speech-To-Text Engine for Jawi Character aims to help students to read Jawi more effectively. In this paper, we investigate the suitable method and device that best for speech-to-text hardware implementation. A complete set of Jawi Speech-To-Text tools will be implements by integrating the hardware with a microphone and Jawi word processor. The speech recognition will use Linear Predictive Coding (LPC) as feature extraction and Neural Network (NN) with Backpropagation will be use as a pattern classification. The implementation of this system will be tested using Xilinx Field Programmable Gate Array (FPGA) board.

Impact of multipath fading on spectrum sensing in vehicular communication environment

Dynamic spectrum access (DSA) has received much attention in research community recently. DSA is the concept in which communication devices of unlicensed users are allowed to access underutilized spectrum in licensed frequency bands. DSA relies on cognitive radio (CR) technology to identify the free spectrum bands in licensed channels through spectrum sensing. In vehicular communications, spectrum sensing is affected by the speed of vehicles, multipath fading and shadowing. In this paper, we show the impact of fading on spectrum sensing in vehicular communications. Understanding how the fading environment affects spectrum sensing will help in developing sensing techniques that can prevent interference in licensed channels while allowing for utmost reuse of radio frequency through DSA.