Hesham A. Ali

Toward SWSs Discovery: Mapping from WSDL to OWL-S Based on Ontology Search and Standardization Engine

Semantic Web Services (SWSs) represent the most recent and revolutionary technology developed for machine-to-machine interaction on the web 3.0. As for the conventional web services, the problem of discovering and selecting the most suitable web service represents a challenge for SWSs to be widely used. In this paper, we propose a mapping algorithm that facilitates the redefinition of the conventional web services annotations (i.e., WSDL) using semantic annotations (i.e., OWL-S). This algorithm will be a part of a new discovery mechanism that relies on the semantic annotations of the web services to perform its task. The “local ontology repository” and “ontology search and standardization engine” are the backbone of this algorithm. Both of them target to define any data type in the system using a standard ontology-based concept. The originality of the proposed mapping algorithm is its applicability and consideration of the standardization problem. The proposed algorithm is implemented and its components are validated using some test collections and real examples. An experimental test of the proposed techniques is reported, showing the impact of the proposed algorithm in decreasing the time and the effort of the mapping process. Moreover, the experimental results promises that the proposed algorithm will have a positive impact on the discovery process as a whole.

Design of optimal PID controller using hybrid differential evolution and particle swarm optimization with an aging leader and challengers

Propose a modified PSO-DV algorithm using aging mechanism.The algorithm is tested on 12 benchmark functions.The algorithm is used for determining the optimal parameters of PID controller.Comparisons with different evolutionary algorithms show that the algorithm is efficient and robust. This paper presents a new algorithm designed to find the optimal parameters of PID controller. The proposed algorithm is based on hybridizing between differential evolution (DE) and Particle Swarm Optimization with an aging leader and challengers (ALC-PSO) algorithms. The proposed algorithm (ALC-PSODE) is tested on twelve benchmark functions to confirm its performance. It is found that it can get better solution quality, higher success rate in finding the solution and yields in avoiding unstable convergence. Also, ALC-PSODE is used to tune PID controller in three tanks liquid level system which is a typical nonlinear control system. Compared to different PSO variants, genetic algorithm (GA), differential evolution (DE) and Ziegler-Nichols method; the proposed algorithm achieve the best results with least standard deviation for different swarm size. These results show that ALC-PSODE is more robust and efficient while keeping fast convergence.

Multimodal biometric authentication algorithm using ear and finger knuckle images

Biometrics that use physiological traits such as face, iris, fingerprints, ear, and finger knuckle (FK) for authentication face the problems of noisy sensors data, non-universality, and unacceptable error rates. Multimodal biometric methods use different fusion techniques to avoid such problems. Fusion methods have been proposed in different levels such as feature and classification level. This paper proposes two multimodal biometric authentication methods using ear and FK images. We propose a method based on fusion of images of ear and FK before the feature level, thus there is no information lost. We also propose a multi-level fusion method at image and classification levels. The features are extracted from the fused images using different classifiers and then combine the outputs of the classifiers in the abstract, rank, and score levels of fusion. Experimental results show that the proposed authentication methods increase the recognition rate compared to the state-of-the-art methods.

Semantic web services matchmaking: Semantic distance-based approach

The semantic web services (SWSs) discovery is the process of finding a service that can possibly satisfy the user requirements, choosing between several services, and composing services to form a single service. The matchmaking between the user request and SWSs is the main task of any SWSs discovery mechanism. In this paper, a semantic distance-based matchmaking algorithm (SDMA) is introduced. The idea behind SDMA is to use the measurement of the semantic distance between the user request and the tested service as an indicator of the degree of relevance between them. In addition to many proposals, a new concepts tree is proposed to perform the process of computing the semantic distance between two concepts. SDMA bases on many concept-to-concept semantic distance measures that are modified and adapted. A deep evaluation process is performed to validate the great impact of using semantic distance measures in the field of SWSs matchmaking.

Internet connectivity for mobile ad hoc network: a survey based study

AbstractMobile ad hoc network (MANET) is a collection of wireless mobile nodes forming a temporary network without the aid of any established infrastructure or centralized administration. MANETs have become increasingly significant in recent years due to their potential applications. From a technological point of view, the realization of this vision still requires a large number of challenges to be solved related to devices, protocols, applications and services. The drawbacks of MANETs are the limited number of services and applications, limited wireless coverage, limited bandwidth and battery power, and dynamic network topology. The growth of the Internet services and applications and the trend in the fourth generation (4G) wireless networks to all-IP networks have led to an increasing demand for enabling MANET nodes to connect to the Internet and use its services and applications. These kinds of networks are named as hybrid MANETs which can be deployed quickly and easily. The main objective of this paper is to introduce an overview of the different challenges and solutions for MANET–Internet integration. It will also introduce a solid analysis of the most significant proposals by describing their functionality, characteristics, and drawbacks. Summary of features of existing hybrid integration approaches for integration is presented. This survey concludes with further points for investigation.

An Administrative Cluster-based Cooperative Caching (ACCC) strategy for Mobile Ad Hoc Networks

Recent explosive growth in computing and wireless communication technologies has led to an increasing interest in mobile ad hoc networks (MANET). Among the many challenges for MANET designers and users, data availability is a critical issue. Caching is considered as an effective solution for the availability problem. Although cooperative caching improves the data access by reducing access latency and bandwidth usage in MANETs, it still suffers from several hurdles and technical problems. This paper introduces a new cooperative caching strategy for MANETs, which is called Administrative Cluster-Based Cooperative Caching (ACCC). ACCC keeps at most two copies of the cached data items in each cluster. Moreover, it develops a new administrative module, which perfectly controls the caching process. ACCC is a cluster-based caching strategy, hence, it divides the network into a set of overlapping clusters. Each cluster is managed by a Cluster Manager (CM) as well as a Cluster Backup (CB). ACCC has several salient features that other techniques do not have such as: (i) the integration between CM and CB besides the integration among all the caching modules improves the data availability within the cluster, (ii) ACCC; maximizes the caching hit ratio, reduces access delay, and saves the battery power of network nodes. ACCC is simulated using Java Caching System JCS2 with the efficient platform Java Enterprise Edition EE8 using a client/server model. Experimental results have shown that ACCC outperforms recent cluster-based caching strategies as it introduces higher cache hit ratio as well as better data availability.

A context-aware dispatcher for the Internet of Things

Graphical abstractDisplay Omitted Detailed explanation of an automatic dispatcher, its components and functions.Framework structure is based on context-awareness integration. with IOT middlewareFramework tested in electrical distribution systems as a case study.High progress in the system performance in terms of cost, time and effort.Acceleration in faults repairing and increased user satisfaction. Automating actions based on collected context from Internet of Things (IOT)-controlled systems is one of the most important requirements of IOT systems; this paper seeks to satisfy this requirement by offering a context-aware service framework on top of IOT controlled systems. The fault management process in electric power distribution networks is taken here as a case study and used for implementing our proposed framework. We discuss the different aspects that need to be covered in such a framework and its components. The obtained results from simulating and testing the framework show a significant improvement in the task management process compared to the traditional approach.

A risk evaluation approach for authorization decisions in social pervasive applications

A new risk indicator model to evaluate security risks associated with information sharing on social pervasive applications.A risk indicator value can be predicted by assessing a number of risk attributes using a neurofuzzy technique.The proposed model was implemented successfully in a case study at a university campus.An effective approach in predicting security risks and in deciding up on them about disclosure decisions in social pervasive applications. Most research in social networks has focused on the assumption that unknown entities are malicious and thus the traditional approach was to detect them and deny their access to sensitive data. In this paper, we propose a new computational model that helps users predict security risks associated with their information sharing on social networks. The model is based on the assumption that a risk indicator value can be predicted by assessing a number of risk attributes using a neuro-fuzzy technique. A disclosure decision is made based on this risk indicator value. The approach was tested in a real prototype of a social mobile service at a university campus. Further, we show how the model can be implemented in a popular social rating site. Results obtained show the relevance and effectiveness of the proposed approach in predicting risks and in deciding up on it about disclosure decisions in social pervasive applications. Display Omitted

Database Security Protection based on a New Mechanism

The database security is one of the important issues that should take a complete attention from researchers. Although applying the traditional security mechanisms, the database still violate from both of external and internal users. So, the researchers develop a Database Intrusion Detection System (DBIDS) to detect intrusion as soon as it occurs and override its malicious affects. The previous work developed a DBIDS as a third party product which is isolated from the DBMS security functions especially access controls. The lack of coordination and inter-operation between these two components prevent detecting and responding to ongoing attacks in real time, and, it causes high false alarm rate. On the other hand, one of the directions that are followed to build a profile is the data dependency model. Although this model is sufficient and related to the natural of database, it suffers from high false alarm rate. This means that it needs an enhancement to get its benefits and eliminate its drawbacks. This Paper aims to strengthen the database security via applying a DBID. To achieve this goal it develops an efficient IDS for DB and integrates it with DBMS for cooperation and completeness between the different parts in the security system. The experiments declare that the proposed model is an efficient DBIDS with a minimum false positive rate (nearly zero %) and maximum true positive rate (nearly 100%). Moreover, it is based on a novel method to build an accurate normal user profile and integrate it with access control.

HPRDG: A scalable framework hypercube-P2P-based for resource discovery in computational Grid

As Grids try to achieve optimal and balanced utilization of unused resources in a distributed system, efficient resource discovery mechanism is one of the fundamental requirement for Grid computing systems, as it aids in resource management and scheduling of applications. Resource discovery in Grid is a challenging issue because characteristics of its resources are heterogeneous, dynamic, various and autonomous. Supporting Range queries, preserving autonomous administrative and preserving locality in this environment is a hot topic in recent researches. This paper propose HPRDG a scalable and reliable framework that present essential characteristic for efficient range queries, performs explicit load balancing and preserving autonomous administrative and locality. Also this scheme is self-organized with capability of handling dynamic attributes such as CPU and memory load. Our proposal architecture eliminates centralized control by using a hybrid P2P structure with hypercube overlays. In addition, HPRDG takes the accounting and authorization concerns into the consideration.