Mobile Ad-hoc Network (MANET) characterized with high mobility and very limited resources. Such network requires a very high reliable routing protocol to be compatible with its limitations. In position-based routing protocols for MANET, each node chooses the next relay node for packet routing solely from neighbourhood stored in its neighbours’ matrix (NLM). The lifetime of neighbors’ entry in NLM matrix relates to beacon interval and timeout interval. Inaccurate information of NLM matrix may lead to a wrong selection decision, which can have devastating consequences on MANET resources. Thus, the freshness of the information in a node’s NLM matrix is in a high demand. This paper presents an intelligent dynamic fuzzy logic controller refreshment period of entries in neighbourhood matrices (IFPE) scheme. The IFPE algorithm utilizes neighbour’s Residual Lifetime of Links (RLT) in the fuzzy logic controller as an input, and the called neighbour expire entry life-time (ELT) as an output. Simulation results show that IFPE algorithm keeps neighbourhood matrices consistent, which achieve considerable improvement for position-based routing protocols performance.

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Journal: International Journal of Computer Science and Information Security (IJCSIS), Vol. 14, No. 1, January 2016

A Mobile Ad hoc network (MANET) is a dynamic selforganizing multi-hop wireless network. Owing the random and unpredictable movement of the mobile nodes, the topology is changing rapidly and frequently. In MANET, where is no routing infrastructure like fixed routers and routing backbones, all MNs participate in the routing process. Recently, position-aware routing protocols, and because of their simplicity, position awareness, and scalability, are the most routing protocols used with MANET. In recent years, a variety of position-aware routing protocols have been developed. The efficiency of such protocol affects by the used underlying mobility model. Thus, wrong selection of the Mobility model may has devastating consequences on the performance MANET. Research efforts haven't focused much in evaluating their performance when applied to different mobility models. In this paper, we have studied the effect of two different mobility models; Random Waypoint mobility model (RWP) and Boundless Mobility Model (BDM) on the performance of selected group of position-based routing protocols. The performance analysis was carried out by using the network simulator, Ns2. The simulation results clarify the performance of the selected routing protocols with three performance metrics

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Journal: Performance Evaluation

Journal: Editor: Csevcenco, Scholars' Press, ISBN: 978-3-659-83823-1.

Journal: International Journal of Computers, Communications and Control, 12(6): 1-15.

This study presents an investigation of enhancing the capability of the Scatter Search (SS) metaheuristic in guiding the search effectively toward elite solutions. Generally, SS generates a population of random initial solutions and systematically selects a set of diverse and elite solutions as a reference set for guiding the search. The work focuses on three strategies that may have an impact on the performance of SS. These are: explicit solutions combination, dynamic memory update, and systematic search re-initialization. First, the original SS is applied. Second, we propose two versions of the SS (V1 and V2) with different strategies. In contrast to the original SS, SSV1 and SSV2 use the quality and diversity of solutions to create and update the memory, to perform solutions combinations, and to update the search. The differences between SSV1 and SSV2 is that SSV1 employs the hill climbing routine twice whilst SSV2 employs hill climbing and iterated local search method. In addition, SSV1 combines all pairs (of quality and diverse solutions) from the RefSet whilst SSV2 combines only one pair. Both SSV1 and SSV2 update the RefSet dynamically rather than static (as in the original SS), where, whenever a better quality or more diverse solution is found, the worst solution in RefSet is replaced by the new solution. SSV1 and SSV2 employ diversification generation method twice to re-initialize the search. The performance of the SS is tested on three benchmark post-enrolment course timetabling problems. The results had shown that SSV2 performs better than the original SS and SSV1 (in terms of solution’s quality and computational time). It clearly demonstrates the effectiveness of using dynamic memory update, systematic search re-initialization, and combining only one pair of elite solutions. Apart from that, SSV1 and SSV2 can produce good quality solutions (comparable with other approaches), and outperforms some approaches reported in the literature (on some instances with regards to the tested datasets). Moreover, the study shows that by combining (simple crossover) only one pair of elite solutions in each RefSet update, and updating the memory dynamically, the computational time is reduced.

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Journal: Journal of Combinatorial Optimization 27(3)

This work investigates the effect of elite pool that has high-quality and diverse solutions in three hybrid population-based meta-heuristics with an elite pool of a hybrid Elitist-Ant System, a hybrid Big Bang-Big Crunch optimization, and a hybrid scatter search. The purpose ofincorporating an elite pool in populationbased meta-heuristics is to maintain the diversity of the search while exploiting the solution space as in the reference set of the scatter search. This may guarantee the effectiveness and efficiency of the search, which could enhance the performance of the algorithms and generalized well across different datasets. To test the generality of these meta-heuristics via their consistency and efficiency, we use three classes of well-known combinatorial optimization problems as follows: symmetric traveling salesman problem, 0–1 multidimensional knapsack problem, and capacitated vehicle routing problem. Experimental results showed that the performance of our hybrid population-based meta-heuristics, compared to the best known results, is competitive in many instances. This finding indicates the effectiveness of utilizing an elite pool in our hybrid meta-heuristics in diversifying the search and subsequently enhances their performance over different instances and problems.

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Journal: Journal of Applied Soft Computing, Vol. 44, pp. 45-56.

This work investigates the performance of a hybrid population-based meta-heuristic with an external memory structure of a hybrid elitist-ant system (elitist-AS). This memory is known as an elite pool, which contains high quality and diverse solutions to maintain a balance between diversity and quality of the search. This may guarantee the effectiveness and efficiency of the search, which could enhance the performance of the algorithm across different instances. A very well known and intensively studied NP-hard optimization problem has been selected to test the performance of the hybrid elitist-AS via its consistency, effectiveness and efficiency. This famous problem is the symmetric traveling salesman problem. The elitist-AS is a class of ant colony optimization techniques which are known to be outstanding for the traveling salesman problem where they have the ability to find the shortest tours guided by the heuristic and the pheromone trail information. An iterated local search is combined with elitist-AS to intensify the search around elite solution and maintains the solution’s exploitation mechanism. Experimental results showed that the performance, compared to the best known results, is optimal for many instances. This finding indicates the effectiveness, efficiency and consistency in diversifying the search while intensifying highquality solutions. This outstanding performance is due to the utilization of an elite pool along with diversification and intensification mechanisms. In addition, this work proposes two instances that consist of 26 Jordanian cities and 1094 Jordanian locations which have been generated based on coordinates and distances similar to the format of the selected symmetric traveling salesman problem. This step is meant to contribute to finding a solution for a realworld problem and further test the performance of the hybrid elitist-AS.

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Journal: Journal of Neural Computing and Applications, 27(2): 1-14.

- In various real-world face recognition applications such as forensics and surveillance, only partial face image is available. Hence, template matching and recognition are strongly needed. In this paper, a genetic algorithm to match a pattern of an image and then recognize this image by this pattern is proposed. This algorithm can use any pattern of an image such as eye, mouth or ear to recognize the image. The proposed genetic algorithm uses a small length chromosome to decrease the search space, and hence the results could be obtained in a short time. Two datasets were used to test the proposed method which are AR Face database and LFW database of face, the overall matching and recognition accuracy were calculated based on conducting sequences of experiments on random sub-datasets, where the overall matching and recognition accuracy was 91.7% and 90% respectively. The results of the proposed algorithm demonstrate the robustness and efficiency compared with other state-of-the-art algorithms.

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Journal: SUST Journal of Engineering and Computer Sciences, 18(1): 51-61.

The requirement of employability in the job market prompted universities to conduct internship training as part of their study plans. There is a need to train students on important academic and professional skills related to the workplace with an IT component. This article describes a statistical study that measures satisfaction levels among students in the faculty of Information Technology and Computer Science in Jordan. The objective of this study is to explore factors that influence student satisfaction with regards to enrolling in an internship training program. The study was conducted to gather student perceptions, opinions, preferences and satisfaction levels related to the program. Data were collected via a mixed method survey (surveys and interviews) from studentrespondents. The survey collects demographic and background information from students, including their perception of faculty performance in the training poised to prepare them for the job market. Findings from this study show that students expect internship training to improve their professional and personal skills as well as to increase their workplace-related satisfaction. It is concluded that improving the internship training is crucial among the students as it is expected to enrich their experiences, knowledge and skills in the personal and professional life. It is also expected to increase their level of confidence when it comes to exploring their future job opportunities in the Jordanian market.

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Journal: Journal of Evaluation and Program Planning, 63: 109-115.

In the first part of our research, a novel computer algorithm has been proposed to generate random path between two points in space. Random path consists of finite number of randomly generated adjacent points that satisfy the condition: L(pipn) < L(pi-1pn). Where L(p1pn) is the length of the path between the two adjacent points p1 and pn. The algorithm has been coded and evaluated. Experiments showed that the randomly generated points were converged to the target point. The main importance of this method is the ability to generate paths between two points in real time, which cannot be predicted in advance. Points are generated, one at a time, where each point brings us closer to the target point. This contribution is applicable to many fields such as economics, engineering, robotics, computer science, military, and other fields of applied sciences. In this part of our research work, we tackled the problem from different aspects. An ontology has been developed that describes the domain of discourse. The aim is two folds; firstly, to provide an optimized generation of best points that are closer to the target point. Secondly, to provide sharable, reusable ontological objects that can be deployed to other projects. The ontology is designed to guide the process of generating acceptable points based on some criteria described in the ontology. Adding intelligence to the process has provided us with a better solution, in comparison with our previous results. Ontologies have been engineered and reused in many research projects across the globe with success. Our contributed solution can attract many applications in the various fields of applied sciences. One implication of the utilization of ontologies is that it remains poorly exploited field, which may have an impact on the adoption of ontology-driven technologies outside the academic community. We underpinned our solution by the initiation of several case studies that have been designed using and extending our work, and progressing very well. Initial findings are very encouraging and leading to the applicability of the proposed solution to real life cases.

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Journal: Journal of Theoretical and Applied Information Technology 15th August 2018. Vol.96. No 15