Mahmoud M. Fahmy

An enhanced differential evolution optimization algorithm

The Differential Evolution (DE) algorithm, introduced by Storn and Price in 1995, has become one of the most efficacious population-based optimization approaches. In this algorithm, use is made of the significant concepts of mutation, crossover, and selection. The tuning control parameters are population size, mutation scaling factor, and crossover rate. Over the last decade, several variants of DE have been presented to improve its performance aspects. In the present paper, we further enhance DE. The population size and mutation scaling factor are taken alone in the tuning process; the crossover rate is treated implicitly in the crossover stage. Five forms for crossover are suggested for the first 100 iterations of the computational algorithm. After this learning period, we pick the form which yields the best value of the objective function in the greatest number of iterations (among the 100). Our algorithm is tested on a total of 47 benchmark functions: 27 traditional functions and 20 special functions chosen from CEC2005 and CEC2013. The results are assessed in terms of the mean and standard deviation of the error, success rate, and average number of function evaluations over successful runs. Convergence characteristics are also investigated. Comparison is made with the original DE and Success-History based Adaptive DE (SHADE) as a state-of-the-art DE algorithm, and the results demonstrate the superiority of the proposed approach for the majority of the functions considered.

A dynamic uplink scheduling scheme for WiMAX networks

Over the past few years, there has been a rapid growth of new services such as online video games, video conferences, and multimedia services to end users. WiMAX is an emerging technology for next generation wireless networks which supports a large number of users. To achieve Quality of Service (QoS) requirements, an efficient and reliable scheduling algorithm is urgently needed. Among a large number of the proposed approaches in the literature, a variably weighted round robin scheduling algorithm (VWRR) has been proven to provide the best performance in an IP backbone network with no attempts on WiMAX networks. This paper proposes a dynamic uplink scheduling algorithm for WiMAX networks based on VWRR to allocate the bandwidth to users to maximize the throughput and ensure the constraints of delay, jitter, and load. A comparative study between the proposed scheduling algorithm and the two most famous scheduling algorithms: weighted round robin algorithm (WRR) and modified deficit round robin algorithm (MDRR) over WiMAX networks, is presented. Simulation results obtained using OPNET reveal that the proposed algorithm has a superior performance compared with WRR with respect to throughput, delay, jitter, and load. Additionally, the proposed scheduling algorithm is shown to provide an excellent level of reliability and scalability when increasing the number of served subscriber stations.

A proposed generalized mean single multiplicative neuron model

This paper presents a single multiplicative neuron model based on a polynomial architecture. The proposed neuron model consists of a non-linear aggregation function based on the concept of generalized mean of all multiplicative inputs. This neuron model has the same number of parameters as the single multiplicative neuron model (SMN). The SMN model is a special case of the proposed generalized mean single multiplicative neuron (GMSMN) model. The structure of this model is simpler than higher-order neuron model. The simulation results show that the performance of the proposed neuron model is better than SMN model.

Performance Comparison of CBT and PIM Multicast Routing Protocols over MPLS Networks

Multi-protocol label switching (MPLS) is a promising cutting-edge technology for advanced forwarding of IP packets. Better performance of multicast routing in large-scale networks is expected when it is implemented over MPLS. In this paper, we simulate core-based tree (CBT) multicast routing protocol over MPLS-based networks using NS2, and compare its performance with protocol-independent multicast-sparse mode (PIM-SM). Simulations are performed for different network topologies with various group sizes using a modified version of the MPLS Network Simulator (MNS). Results reveal that as the number of source nodes increases CBT gives better performance than PIM-SM in terms of routing table size, join time, and total hop count. On the other hand, PIM-SM has less end-to-end delay than CBT

Modelling of CVBF algorithm using Coloured Petri Nets

Modelling is a general method used throughout the development of systems. Numerous modelling languages were proposed for analyzing and building systems. Petri Nets language is considered as one of the formal modelling and analysis techniques. These techniques allow users to do both the performance evaluation and model checking. Coloured Petri Nets (CPN) is one of the modelling languages especially for discrete-event systems. In this paper, we use Coloured Petri Nets to model and analyze the behavior of the Clustering Vector-Based Forwarding (CVBF) routing protocol in Underwater Wireless Sensor Networks (UWSNs). Our proposed model is tested and verified by the state space statistics analysis which results that the proposed CPN model is liveness, responsiveness and free from deadlocks. The results of the performance evaluation of the proposed model demonstrate the proposed model capability to increase both the packet delivery ratio and the average end-to-end delay.

A New Novel Fidelity Digital Watermarking Adaptively Pixel Based on Medial Pyramid of Embedding Error in Spatial Domain and Robust

Digital watermarking refers to techniques that are used to protect digital data by imperceptibly embedding watermark into the original data in such a way that always remains present. In particular, digital watermarking techniques in frequency domain have been widely recognized to be more prevalent than others, but in recent years the techniques in spatial domain they are becoming generally abandoned. One of the problems in digital watermarking is that the three requirements of robustness capacity and imperceptibility, that are must be satisfied but they almost conflict with each other, accordingly there are trade-off between fidelity and robustness. In this paper, we proposed a new novel fidelity and robust watermark embedding method that satisfies the requirements and statement problem, called adaptively pixel adjustment process based on medial pyramid of embedding error, applying in the falling-off-boundary in corners board of the cover image set of the Most Significant Bit ‘6’ blind in spatial domain. In addition, the paper provides a theoretical analysis and modified algorithms of previous works. Theoretically, the proposed technique proves the effectiveness of the technique in the average of worst case and minimizing the number of embedding error to the half. Experimental results of the proposed technique was applied on the different benchmark of six gray scale images and two quantum of watermark bit embedded are compared with previous works and was found better. Moreover in all different benchmark of six test images the watermarks were extracted from watermark degrading, removal and geometric transformations attacks to an acceptable degree.

Single multiplicative neuron model based on generalized mean

This paper presents a single multiplicative neuron model based on a polynomial architecture. The proposed neuron model consists of a non-linear aggregation function based on the concept of generalized mean of all multiplicative inputs. This neuron model has the same number of parameters as the single multiplicative neuron model (SMN). The SMN model is a special case of the proposed generalized mean single multiplicative neuron (GMSMN) model. The structure of this model is simpler than higher-order neuron model. The simulation results show that the performance of the proposed neuron model is better than SMN model.

Securing JPEG architecture based on enhanced chaotic hill cipher algorithm

In the last two decades, Chaos theory has received a great deal of attention from the cryptographic community. This paper presents two ideas. First idea is using chaotic functions to overcome the weaknesses of the classical Hill cipher. The second idea is proposing a new encoder-decoder architecture, called ChaoEncoDeco, for securing JPEG images. An extra stage of encryption is embedded within the traditional JPEG codec to improve security level of such system. This security stage uses one of the chaotic functions called Logistic Map. This map is used to enhance the Hill cipher and achieve more secure encryption key. The properties of both chaotic system and of the Hill cipher encryption key are all utilized to obtain ultimate secure systems. The proposed encryption algorithm is crypto-analyzed and compared to the standard Hill cipher algorithm. Complete evaluation for the proposed architecture is also performed which indicates the effectiveness of the proposed system.

Development of secure encoder-decoder for JPEG images

Digital image copyrights and image authentication draw a great attention specially in critical image communications. This paper presents a proposal for a new encoder-decoder, which we call SecEncoDeco, for securing JPEG images. An extra stage of security is embedded in the traditional JPEG codec. This security stage uses the Secure Hill cipher technique. This encryption technique has many advantages over the traditional Hill cipher. The Safe Time of the Secure Hill cipher is deduced and presented in detail. Implementation of the proposed method is built based on MATLAB. Complete evaluation for the proposed codec is performed which indicates the effectiveness of the proposed secure codec for image copyright protection.