Resource allocation in mobile edge cloud computing for data-intensive applications

Rapid advancement in the mobile telecommunications industry has motivated the development of mobile applications in a wide range of social and scientific domains. However, mobile computing (MC) platforms still have several constraints, such as limited computation resources, short battery life and high sensitivity to network capabilities. In order to overcome the limitations of mobile computing and benefit from the huge advancement in mobile telecommunications and the rapid revolution of distributed resources, mobile-aware computing models, such as mobile cloud computing (MCC) and mobile edge computing (MEC) have been proposed. The main problem is to decide on an application execution plan while satisfying quality of service (QoS) requirements and the current status of system networking and device energy. However, the role of application data in offloading optimisation has not been studied thoroughly, particularly with respect to how data size and distribution impact application offloading. This problem can be referred to as data-intensive mobile application offloading optimisation. To address this problem, this thesis presents novel optimisation frameworks, techniques and algorithms for mobile application resource allocation in mobile-aware computing environments. These frameworks and techniques are proposed to provide optimised solutions to schedule data intensive mobile applications. Experimental results show the ability of the proposed tools in optimising the scheduling and the execution of data intensive applications on various computing environments to meet application QoS requirements. Furthermore, the results clearly stated the significant contribution of the data size parameter on scheduling the execution of mobile applications. In addition, the thesis provides an analytical investigation of mobile-aware computing environments for a certain mobile application type. The investigation provides performance analysis to help users decide on target computation resources based on application structure, input data, and mobile network status

Exploring Media and Communication Students’ Perception of Egyptian Universities’ Use of Augmented Reality in Learning

The aim of this study was to investigate the perceptions of media students in Egypt universities about using augmented reality (AR) technology in learning. To achieve this, the study adopted Technology Acceptance Model (TAM) and utilized a survey questionnaire to collect data from students in seven universities across Egypt. The findings revealed that (i) the students had a positive perception about using AR in media and communication learning; (ii) many media students in Egypt were not fully aware of the various AR technology applications in media and communication education; (iii) the students identified several negative factors that may hinder their acceptance of AR technology as an instructional tool, such as poor connectivity, lack of free AR programs, and lack of training programs. Addressing these barriers could help promote the adoption of AR technology in media and communication learning among students in Egypt. The significance of the study lies in that it sheds light on the need for increased awareness and education of the potential benefits of using AR technology in media and communication learning

THE ROLE OF UNIVERSITIES IN PROMOTING DIGITAL ENTREPRENEURIAL INTENTION AMONG UNIVERSITY STUDENTS IN JORDAN

In today's world, technology has taken a place so drastically that everything is being digitalized. Universities play a critical role in promoting entrepreneurship, providing the right entrepreneurial education, and contributing to economic and social development. However, few studies have examined the role of business incubators in universities. Therefore, the study explores the status of entrepreneurship education and incubation services and the effect of entrepreneurial self-efficacy on supporting digital entrepreneurship intention among the students at public and private universities in Jordan. Eighty-one students’ responses were received from three universities through an online questionnaire. The result of multiple linear regression confirmed that there is a significant and positive relationship between digital entrepreneurship intention and each of the following factors: entrepreneurship education, business incubation, and entrepreneurial self-efficacy. The study findings contribute to the current literature of digital entrepreneurship, by representing the significance of universities supporting systems in stimulating the students to start their own online businesses

Central corneal thickness in a Jordanian population and its association with different types of Glaucoma: cross-sectional study

Abstract Background Central corneal thickness (CCT) has long been implicated to affect glaucoma predisposition. Several reports have identified that thinner CCT is a risk factor for open-angle glaucoma, and that CCT can be very variable between different ethnic groups. In this study, we aim to identify the relation between CCT and different glaucoma parameters in different types of glaucoma in an Arabian ethnicity. Methods We classified our participants into four main groups: primary open-angle glaucoma (POAG), primary angle-closure glaucoma (PACG), pseudoexfoliative glaucoma (PXFG), and a control group. We obtained demographics, intraocular pressure (IOP), cup to disc ratio (CDR), visual field mean deviation (MD) and pattern standard deviation (PSD), CCT, and retinal nerve fiber layer (RNFL) thickness for each participant. Results We included A total of 119 eyes with glaucoma, including POAG (54 eyes), PXFG (31 eyes) and PACG (34 eyes), we also included 57 control eyes. We found that PACG eyes have the thinnest CCT. Mean measurements of CCT for our groups were: 538.31 μm (SD = 36.30) in eyes with POAG, 544.45 μm (SD = 28.57) in eyes with PXFG, 506.91 μm (SD = 34.55) in eyes with PACG and 549.63 μm (SD = 42.9) in the control group. We found that CCT is significantly correlated with CDR (p = 0.012, r = − 0.231), MD (p < 0.001, r = 0.327),and RNFL thickness (p = .007, r = .283). Conclusion In Arabian ethnicity, PACG patients have the thinnest CCT compared to other types of glaucoma, namely POAG and PXFG. We demonstrated that glaucomatous eyes with thinner corneas will probably have more advanced glaucomatous optic neuropathy. Our results emphasize the importance of taking ethnicity into account upon glaucoma management

Data-intensive application scheduling on Mobile Edge Cloud Computing

Mobile cloud computing helps to overcome the challenges of mobile computing by allowing mobile devices to migrate computation-intensive and data-intensive tasks to high-performance and scalable computation resources. However, emerging data-intensive applications pose challenges for mobile cloud computing platforms because of high latency, cost and data location issues. To address the challenges of data-intensive applications on mobile cloud platforms, we propose an application offloading optimisation model that schedules application tasks on an integrated computation environment named Mobile Edge Cloud Computing. The optimisation model is formulated as a mixed integer linear programming model, which considers both monetary cost and device energy as optimisation objectives. Moreover, the allocation process considers parameters related to data size and location, data communication costs, context information and network status. To evaluate the performance of the proposed offloading algorithm, we conducted real experiments on the implemented system with a variety of scenarios, such as different deadline and multi-user parameters. Our results demonstrate the ability of the proposed algorithm to generate an optimised resource allocation plan in response to dramatic fluctuations in application data size and network bandwidth. The proposed technique reduced the execution cost of data-intensive applications by an average of 46% and 76% in comparison with particle swarm optimisation (PSO) and full execution on a mobile device only, respectively. In addition, our new technique reduced mobile energy consumption by 35% and 84%, compared to PSO and full execution on a mobile device only, respectively

Performance analysis of mobile, edge and cloud computing platforms for distributed applications

Mobile devices and their corresponding services have become ubiquitous and vital components of almost every aspect of social and business life. Mobile services enhance collaboration, communication, monitoring, tracking, streaming, and many other applications. This intense and continuous engagement presents significant challenges due to mobile devices’ limited computation power, dependence on batteries, and sensitivity to transmission network capacity and availability. A common technique for resolving mobile shortcomings is to migrate (offload) complex computations to more powerful resources such as edges, clouds, mobile clouds or integration. However, the huge variety in mobile applications complicates alignment of the unique characteristics and user quality of service (QoS) requirements for each application to a convenient offloading plan. The availability of powerful resources at different computing layers is another challenge for offloading techniques. This chapter was designed to generate insights into ways the mobile communications industry could realise cost savings and high-quality data-aware offloading solutions by adopting new technologies such as edge computing and region-based local networks. To demonstrate these insights, this chapter provides an experimental work on how to select the best mobile-aware computing environment based on parameters including application type, data size and network bandwidth quality. Moreover, this chapter provides a comprehensive analysis that highlights the experiment results and provides recommendations for scheduling the execution of data-intensive applications on mobile-aware computation systems