Ali Safa Sadiq

Beaconing Approaches in Vehicular Ad Hoc Networks: A Survey

A vehicular ad hoc network (VANET) is a type of wireless ad hoc network that facilitates ubiquitous connectivity between vehicles in the absence of fixed infrastructure. Beaconing approaches is an important research challenge in high mobility vehicular networks with enabling safety applications. In this article, we perform a survey and a comparative study of state-of-the-art adaptive beaconing approaches in VANET, that explores the main advantages and drawbacks behind their design. The survey part of the paper presents a review of existing adaptive beaconing approaches such as adaptive beacon transmission power, beacon rate adaptation, contention window size adjustment and Hybrid adaptation beaconing techniques. The comparative study of the paper compares the representatives of adaptive beaconing approaches in terms of their objective of study, summary of their study, the utilized simulator and the type of vehicular scenario. After implementing the representatives of beaconing approaches, we analysed the simulation results and discussed the strengths and weaknesses of these beaconing approaches with regard to their suitability to vehicular networks. Finally, we discussed the open issues and research directions related to VANET adaptive beaconing approaches.

An Intelligent Vertical Handover Scheme for Audio and Video Streaming in Heterogeneous Vehicular Networks

In heterogeneous vehicular networks, the most challenging issue is obtaining an efficient vertical handover during the vehicle roaming process. Efficient network selection process can achieve satisfactory Quality-of-Service for ongoing applications. In this paper, we propose an Intelligent Network Selection (INS) scheme based on maximization scoring function to efficiently rank available wireless network candidates. Three input parameters were utilized to develop a maximization scoring function that collected data from each network candidate during the selection process. These parameters are: Faded Signal-to-Noise Ratio, Residual Channel Capacity, and Connection Life Time. The results show that the proposed INS scheme is more efficient at decreasing handover delays, End-to-End delays for VoIP and Video applications, packet loss ratios as well as increasing the efficiency of network selection processes in comparison with the state of the arts.

A Fuzzy Logic Approach for Reducing Handover Latency in Wireless Networks

Existing wireless networks aim to provide information communication services between mobile nodes. When a mobile node moves between different radio networks, a handover process is needed to change its point of attachment to the predicted radio network. Since traditional (based on one metric Received Signal Strength Indicator) predictions of handover decisions do not perform well, it is imperative that we develop an intelligent approach to facilitate the handover prediction process, thus yielding seamless handovers. In this article, a Fuzzy logic-based Hand-off Decision (FHD) approach is proposed for wireless networks. The parameters include a Received Signal Strength Indicator and the relative direction of a Mobile Node toward an access point, which are considered as inputs to the fuzzy logic system in order to facilitate the handover decision process and a switch to the best preferable access point. To achieve a fair comparison with a standard handover procedure, we have implemented a fuzzy logic-based hand-off decision approach in Omnet++. Our simulation results show that the proposed approach is able to reduce the handover latency. More precisely, the results show that by using the proposed method, the performance improved significantly the wireless access media delay (link-layer).

A smart handover prediction system based on curve fitting model for Fast Mobile IPv6 in wireless networks

Seamless handover process is essential in order to provide efficient communication between mobile nodes in wireless local area networks. Despite the importance of a signal strength prediction model to provide seamless handovers, it is not embedded in standard mobility management protocols. In this article, we propose a smart handover prediction system based on curve fitting model to perform the handover CHP algorithm. The received signal strength indicator parameter, from scanning phase, is considered as an input to the CHP in order to provide a prediction technique for a mobile node to estimate the received signal strength value for the access points in the neighborhood and to select the best candidate access point from them in an intelligent way. We implemented the proposed approach and compared it with standard protocols and linear regression-based handover prediction approach. Simulation results in complex wireless environments show that our CHP approach performs the best by predicting the received signal strength value with up to 800ms in advance from real obtained value via scanning phase. Moreover, our CHP approach is the best in terms of layer2 and overall handover latency, in comparison with standard protocols and linear regression approach, respectively. Copyright

Magnetic Optimization Algorithm for training Multi Layer Perceptron

Recently, feedforward neural network (FNN), especially Multi Layer Perceptron (MLP) has become one of the most widely-used computational tools, applied to many fields. Back Propagation is the most common method to learn MLP. This learning algorithm is a gradient-based algorithm, but it suffers some drawbacks such as trapping in local minima and slow convergence. These weaknesses make MLP unreliable in solving real-world problems. Using heuristic optimization algorithms is a popular approach to improve the drawbacks of BP. Magnetic Optimization Algorithm (MOA) is a novel heuristic optimization algorithm, inspired from the magnetic field theory. It has been proven that this algorithm is capable of solving optimization problems quickly and accurately. In this paper, MOA is employed as a new training method for MLP in order to improve the aforementioned shortcomings. The proposed learning method was compared with PSO and GA-based learning algorithms using 3-bit XOR and function approximation benchmark problems. The results prove the high performance of this new learning algorithm for large numbers of training samples.

Improved Geographical Routing in Vehicular Ad Hoc Networks

Vehicular Ad Hoc Networks (VANET) has emerged to establish communication between intelligent vehicles. The high mobility of vehicles and existing of obstacles in urban area make the communication link between vehicles to be unreliable. In this environment, most geographical routing protocols does not consider stable and reliable link during packet forwarding towards destination. Thus, the network performance will be degraded due to large number of packet losses and high packet delay. In this paper, we propose an improved geographical routing protocol named IG for VANET. The proposed IG incorporates relative direction between source vehicle and candidate vehicles, distance between candidate node and destination and beacon reception rate in order to improve geographical greedy forwarding between intersection. Simulation results show that the proposed routing protocols performs better as compared to the existing routing solution.

Advanced Mobility Handover for Mobile IPv6 Based Wireless Networks

We propose an Advanced Mobility Handover scheme (AMH) in this paper for seamless mobility in MIPv6-based wireless networks. In the proposed scheme, the mobile node utilizes a unique home IPv6 address developed to maintain communication with other corresponding nodes without a care-of-address during the roaming process. The IPv6 address for each MN during the first round of AMH process is uniquely identified by HA using the developed MN-ID field as a global permanent, which is identifying uniquely the IPv6 address of MN. Moreover, a temporary MN-ID is generated by access point each time an MN is associated with a particular AP and temporarily saved in a developed table inside the AP. When employing the AMH scheme, the handover process in the network layer is performed prior to its default time. That is, the mobility handover process in the network layer is tackled by a trigger developed AMH message to the next access point. Thus, a mobile node keeps communicating with the current access point while the network layer handover is executed by the next access point. The mathematical analyses and simulation results show that the proposed scheme performs better as compared with the existing approaches.

An Energy-Efficient Cross-Layer approach for cloud wireless green communications

In wireless sensor networks (WSN), energy consumption is one of the crucial issues. It is very important to conserve energy at each sensor node to prolong a network lifetime. The main challenge in WSN is to develop an energy efficient algorithm to minimize energy consumption during transmitting information from deployed sensors up to the cloud resources. Many researches have been studied the designing of energy efficient technique based on one-layer stack model approach. In this study, we propose Energy-Efficient Cross-Layer (EECL) approach by using the interaction of MAC layer and physical layer information to be exploited by a network layer to achieve energy efficient communication. More precisely, network layer could utilize the MAC layer and physical layer information to establish an energy efficient route path to be used in forwarding data. The proposed EECL approach uses X-MAC protocol in support of duty cycle which introduces short preambles that switches to wake-up/sensing mode only for nodes belonging to routing path while the other nodes set to be in sleep mode. The distance between nodes that influences energy consumption and Bit Error Rate (BER) are set to be the parameters which they are help in indicating the required power for each hop during route path selection in WSN and avoid the rely-hops that suffering from high average BER and with farther distance. We conduct the experiment using Matlab to evaluate the effectiveness of our proposed approach in terms of power consumption and obtained data rate. The results show that our proposed EECL approach outperforms its representatives in the ability of tuning the power utilized in respect with required data rate that could satisfy the desired Quality-of-Service (QoS).

Traceback model for identifying sources of distributed attacks in real time

Locating sources of distributed attack is time-consuming; attackers are identified long after the attack is completed. This paper proposes a trackback model for identifying attackers and locating their distributed sources in real time. Attackers are identified by monitoring violations of malicious end users on their bandwidth shares predefined in the service level agreement. Then, active connections of the malicious users are investigated to locate the host machines used as distributed sources of attack traffic. Mathematical model and simulation results demonstrate that the proposed model can reduce the required time for identifying malicious users and locating host machines used as the actual sources of attack packets. Copyright

What should be done to achieve greater use of cloud computing by higher education institutions

Cloud computing is a technology in which online service providers can store and host organizational data and information without the need for computer hard drives to be centered in organizations. The information is hosted on a network server where it can be accessed by enterprises and users when in need. Small and large companies, as well as institutions of higher learning, are embracing this technology due to economic advantage, improved manageability, less maintenance, high performance, accessibility/ availability thus bringing about a smooth facilitation of organizational operations [1]. The technology used in cloud computing is dependent on a reliable internet connection that may be unavailable in some countries and in certain business environments. There is a debate on the integrity, privacy, and ownership of the data hosted in a cloud computing scenario making it difficult for some organization to adopt this technology. Cloud computing poses privacy concerns because the security of data on this platform is available to a huge viewership making it susceptible to the ill-minded cyber criminals/hackers.