Mobile learning applications utilise the advantages of mobile technologies to increase learning opportunities, mainly on an anytime, anywhere basis. The advancement of mobile technology has facilitated the development of numerous applications to improve students’ learning experience and performance. Successful implementation of m-learning is highly dependent on learning context and environment awareness. This work presents a multiphase exploration of early phases responsible for defining and validating the m-learning context, and later phases based on context validation results achieved from the previous phases, involving the development and evaluation of a new m-learning context prototype. This new prototype proved to provide context-aware and ubiquitous learning services fulfilling several diverse user interaction levels and requirements.

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Journal: , Int. J. Computer Applications in Technology, Vol. 58, No. 4, pp.296–307.

Mobile Ad-hoc network (MANET) is the guiding technology of ubiquitous era and a cornerstone in the 4G communication architecture. MANET has limited resources and characterized with high mobility and frequent topology change. Routing in MANET should follow these constrains, otherwise, it can severely degrade the performance of MANET. Owing to Greedy routing (GFS) nature in MANET, a certain part of the MANET becomes congested before other parts. In such area the nodes have failed to forward packets in a timely manner or drop them, thus such nodes called Network Holes. This paper presents a simple and efficient enhanced GFS routing algorithm called Intelligent Fuzzy logic Greedy forwarding Scheme (IFGFS). IFGFS consider the De-congestion level of each mobile node as another selective metric besides distance. In order to validate our algorithm, we rely on a wide simulation experiments. The evaluation results showed the correctness of our new proposed algorithm the adaptive- congestion IFGFS which maximize the performance of the network.

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Journal: ComputerandInformation Science; Vol. 11, No. 2; 2018 ISSN 1913-8989 E-ISSN 1913-8997

This paper delves into the capacity of enhanced Big Bang-Big Crunch (EBB-BC) metaheuristic to handle data clustering problems. BB-BC is a product of an evolution theory of the universe in physics and astronomy. Two main phases of BB-BC are big bang and big crunch. The big bang phase involves a creation of a population of random initial solutions, while in the big crunch phase these solutions are shrunk into one elite solution exhibited by a mass center. This study looks into enhancing the BB-BC’s effectiveness in clustering data. Where, the inclusion of an elite pool alongside implicit solution recombination and local search method, contribute to such enhancement. Such strategies resulted in a balanced search of good quality population that is also diverse. The proposed elite pool-based BB-BC was compared with the original BB-BC and other identical metaheuristics. Fourteen different clustering datasets were used to test BB-BC and the elite pool-based BB-BC showed better performance compared to the original BB-BC. BB-BC was impacted more by the incorporated strategies. The experiments outcomes demonstrate the high quality solutions generated by elite pool-based BB-BC. Its performance in fact supersedes that of identical metaheuristics such as swarm intelligence and evolutionary algorithms.

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Journal: Journal of Computer Science Volume 14, Issue 12

Mobile Ad hoc Networks (MANETs) are considered as a reunion of wireless mobile devices (nodes) that form a temporary wireless network. In order to facilitate communication in MANET, every node has to participate in the routing process. Reaching an optimal route is a fundamental task in MANET, because routes are multi-hoped and susceptible. Several routing protocols exist and can be categorized to; topology-based and position-based routing protocols. However, the efficiency of these protocols in highly dynamic and dense environments is a challenging task to be considered for increasing perceived Quality of Service (QoS) in MANET. This paper focuses on the presentation and basic operation of each category. A performance evaluation study was conducted comparing between both categories in terms of End-to End delay, packet- delivery ratio and routing overhead. Results analysis show that position-based protocols outperforms topology-based protocols in dense and high dynamic environments. Recommendations for implementing future efficient position-based protocols were presented.

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Journal: International Journal of Interactive Mobile Technologies (iJIM), 11(1), 84-97

Current greedy routing protocol (GFS) designed to find shortest path as a single routing objective. Considering only one routing objective is insufficient for the computation of a reliable rout, and can severely compromise network performance on the remaining overlooked objectives. This paper introduces the Dynamic and Reactive Reliability Estimation with Selective Metrics Mechanism (DRESM). The intended DRESM is constructed of two coherent techniques; the Fuzzy Logic Dynamic Nodes’ Reliability Estimation (FLDRE) and the Status Information Distribution and Outgoing Traffic Control Management (IDOTM). FLDRE introduce the notion of multi-criteria next relay node selection using fuzzy weighted logic multi-objectives. IDOTM provides the sender node with fresh information about its neighbour and control the outgoing traffic. The simulation results show that DRESM outperforms GFS in terms of packet delivery ratio, average end-to-end delay. Moreover, DRESM can find routs whose cost is close to the optimum.

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Journal: IJCSNS International Journal of Computer Science and Network Security, VOL.16 No.6, June 2016

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

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

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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)