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The Promise of Grid Computing Technologies
for e-Learning Systems in Kenya
Data Engineering & Cloud Computing
Umma Khatuna Jannat
SRN:R16MDC06
Data Engineering & Cloud Computing Department
Outline
o Abstract
o E-learning grids
o Research Questions
o Research Methodology
o Current State of grid computing in Kenya
o Implementation Challenges
o E-learning Developments
o Grid Computing Benefits for E-Learning
o Conclusions
o References
Data Engineering & Cloud Computing
Abstract
o This paper presents an attempt of providing grid computing as an avenue
to heterogeneous e-learning platforms that can be accessed by different hardware
and software platforms.
o E-Learning involves using internet technologies to access learning resources
online such as school timetable, courseware, research material, and to run virtual
communities for sharing and creating knowledge.
o Grids can be used as a means to provide education and training through such
internet technologies.
o Literature review is used through examination of scientific research papers in
journals and conference proceedings.
o The objective of the paper is to contribute towards knowledge and lessons that can
be applied in Kenya towards effective approaches for development of an e-
learning grid infrastructure.
Data Engineering & Cloud Computing
E-learning
grids
o In recent years, there has been an increase in the number of institutions of higher
learning in Kenya as well as on the African continent. Many of these institutions
lack adequate information technology
o They also tend not to distribute computing power or storage, making data-
intensive fields, such as medicine, hard to teach. Elements of traditional
computing for purposes of providing e-learning, including software, hardware,
and the Internet, very often suffer from heavy workloads, leading to slower
computing speeds.
o In order to overcome these problems, it is necessary to upgrade or renew software
and hardware, which is often very difficult for many institutions because they
have limited budgets [9].
o E-learning based on grid computing models could offer a solution to these
problems. According to [10], the goal of grid computing is to provide
Data Engineering & Cloud Computing
Research
Questions
1.How can grid technologies be implemented in e-Learning platforms?
2. What challenges are Universities likely to encounter in implementation of e-
Learning grids?
3. What are the benefits of the grid computing for e-Learning?
Data Engineering & Cloud Computing
Research
Methodology
o In this study, data are collected from secondary sources.
Data Engineering & Cloud Computing
Current State
of grid
Computing in
Kenya
o Some organizations in Kenya were using grid computing technology over the
Local Area Network.
o There were expectations of more organizations switching to the technology and
deploying it over the Wide Area Network to provide faster communication on
larger areas.
o This development is based on the fact that the Internet network in Kenya has
evolved to a stage where it has many cables and routing equipment linked
together, connecting many organizations, institutions of higher learning and
mobile devices.
o Grid computing will enable organizations and individuals to leverage superior
computing resources online in a cost-effective and efficient manner.
Organizations’ and institutions of higher learning are capable of outsourcing their
excess and under-utilized computing power, which they can do for a fee.
o E- Learning systems in use by many Institutions of Higher Learning in Kenya
are diverse and are specific to different institutions meaning that permission must
be granted in order to access them.
o Most Personal Computers and mobile devices lack the computing power to
access these learning systems, and also network access speeds are slow.
Data Engineering & Cloud Computing
Implementation
Challenges
o One of the main challenges in implementation of e-learning grid systems is the
heterogeneity resulting from the vast range of technologies, both hardware and
software, encompassed by the grid [16].
o Some protocols and applications have been proposed and implemented in actual
works, such as the Globus Toolkit [9]. The Globus Toolkit is an open-architecture,
open-source suite of services and software libraries that support Grids and Grid
applications.
o In addition grid computing may require redefinition of ownership, copyrights, and
licensing all of which present cultural and legal issues which have to be resolved
before adjusting policies and expectations of these institutions to integrate with
what technology provides.
Data Engineering & Cloud Computing
E-learning
Developments
o Multimedia transmissions and related network application technologies have
helped fuel the development and popularization of e-learning techniques such as
Distance Education, Video Conferencing, and Video on Demand. An e-learning
Platform generally requires a high-capacity storage device, such as a Disk Array,
Network Attached Storage (NAS), or Storage Area Network (SAN), to store
teaching content [9]. Grid Computing can connect scattered computer resources
via Internet links. The resources that can be connected include computer
facilities, storage media, data and various input and output devices. Thus, Grid
computing can be used to build an e-learning platform that features expandability
and resource-sharing capability.
o The objective is to create virtual dynamic organizations or academic institutions
through secure, unlimited power, information access, synchronized resource-
sharing among users, institutions and resources.
Data Engineering & Cloud Computing
E-learning
Developments
Data Engineering & Cloud Computing
Grid
Computing
Benefits for E-
Learning
o Academic institutions stand to reap significant benefits from grid computing by
creating environments that expose students to the real world data sets in a wide
range of disciplines.
o Instead of using mock or historical data, a grid could let students use grid
facilities to collect their own real data.
o By using the computing resources of the components of a grid, institutions can
save financial resources both in capital and operating costs [11].
o By increasing the processing power, applications run faster the computing tasks
and provide faster results [11]. Grid computing also encourages partnerships
among higher education institutions and research centers.
o Using a grid, researchers in Britain, for example, can conduct research that relies
on databases across Europe, instrumentation in Japan, and computational power
in the United States. Making resources available in this way exposes students to
the tools of the profession, facilitating new possibilities for research and
instruction [12].
Data Engineering & Cloud Computing
Conclusions
o The paper concludes that institutions of higher learning in the country can and
should take advantage of advances in the Internet and its technologies,
availability of powerful computers and high-speed networks to establish e-
learning grids.
o This paper concurs with [22] who asserted that while eLearning may never
replace face to face tuition; it will continue to grow in importance due to its role
in extending the educational experience in new and innovative directions.
Data Engineering & Cloud Computing
References
1. Nafukho, F. M., & Machuma, H. M. (2013). The World Bank’s Africa Virtual
University Project: a revisit. European Journal of Training and Development ,
37 (7), 646-661.
2. Beebe, M. A. ( September 2004). Impact of ICT Revolution on the African
Academic Landscape.Conference on Electronic Publishing and Dissemination.
Dakar, Senegal: CODESRIA.
3. European Commission. (2001). The eLearning Action Plan: Designing
tomorrow’s education. Retrieved october 15, 2015, from
http://www.elearningeuropa.info./
4. Arkorful, V., & Abaidoo, N. (2014). The role of e-learning, the advantages and
disadvantages of its adoption in Higher Education. International Journal of
Education and Research , 2 (12), 397-410.
5. Uzoka, F., Akinnuwesi, B., Olabiyisi, S., & Alabi, D. (2011). A Case Analysis
of Factors Affecting the Adoption of Grid Technology by Universities. IST-
Africa 2011 Conference Proceedings. IIMC International Information
Management Corporation.
Data Engineering & Cloud Computing
References
6. Lathia, M. (2005). Advantages of Grid Computing. Ieee Distributed Systems
Online 1541-.
7. Kemibaro, M. (2008). Grid computing: faster results at less cost. Retrieved
October 24, 2015, from https://www.moseskemibaro.com/2008/04/28/grid-
computing-faster-results-at- less-cost/
8. Yang, C.-T., & Ho, H.-C. (2005). An E-Learning Platform Based On Grid
Architecture. Journal Of Information Science And Engineering , 911-928.
Data Engineering & Cloud Computing
Thank you!
Data Engineering & Cloud Computing

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The Promise of Grid Computing Technologies for E-Learning Systems in Kenya

  • 1. The Promise of Grid Computing Technologies for e-Learning Systems in Kenya Data Engineering & Cloud Computing Umma Khatuna Jannat SRN:R16MDC06 Data Engineering & Cloud Computing Department
  • 2. Outline o Abstract o E-learning grids o Research Questions o Research Methodology o Current State of grid computing in Kenya o Implementation Challenges o E-learning Developments o Grid Computing Benefits for E-Learning o Conclusions o References Data Engineering & Cloud Computing
  • 3. Abstract o This paper presents an attempt of providing grid computing as an avenue to heterogeneous e-learning platforms that can be accessed by different hardware and software platforms. o E-Learning involves using internet technologies to access learning resources online such as school timetable, courseware, research material, and to run virtual communities for sharing and creating knowledge. o Grids can be used as a means to provide education and training through such internet technologies. o Literature review is used through examination of scientific research papers in journals and conference proceedings. o The objective of the paper is to contribute towards knowledge and lessons that can be applied in Kenya towards effective approaches for development of an e- learning grid infrastructure. Data Engineering & Cloud Computing
  • 4. E-learning grids o In recent years, there has been an increase in the number of institutions of higher learning in Kenya as well as on the African continent. Many of these institutions lack adequate information technology o They also tend not to distribute computing power or storage, making data- intensive fields, such as medicine, hard to teach. Elements of traditional computing for purposes of providing e-learning, including software, hardware, and the Internet, very often suffer from heavy workloads, leading to slower computing speeds. o In order to overcome these problems, it is necessary to upgrade or renew software and hardware, which is often very difficult for many institutions because they have limited budgets [9]. o E-learning based on grid computing models could offer a solution to these problems. According to [10], the goal of grid computing is to provide Data Engineering & Cloud Computing
  • 5. Research Questions 1.How can grid technologies be implemented in e-Learning platforms? 2. What challenges are Universities likely to encounter in implementation of e- Learning grids? 3. What are the benefits of the grid computing for e-Learning? Data Engineering & Cloud Computing
  • 6. Research Methodology o In this study, data are collected from secondary sources. Data Engineering & Cloud Computing
  • 7. Current State of grid Computing in Kenya o Some organizations in Kenya were using grid computing technology over the Local Area Network. o There were expectations of more organizations switching to the technology and deploying it over the Wide Area Network to provide faster communication on larger areas. o This development is based on the fact that the Internet network in Kenya has evolved to a stage where it has many cables and routing equipment linked together, connecting many organizations, institutions of higher learning and mobile devices. o Grid computing will enable organizations and individuals to leverage superior computing resources online in a cost-effective and efficient manner. Organizations’ and institutions of higher learning are capable of outsourcing their excess and under-utilized computing power, which they can do for a fee. o E- Learning systems in use by many Institutions of Higher Learning in Kenya are diverse and are specific to different institutions meaning that permission must be granted in order to access them. o Most Personal Computers and mobile devices lack the computing power to access these learning systems, and also network access speeds are slow. Data Engineering & Cloud Computing
  • 8. Implementation Challenges o One of the main challenges in implementation of e-learning grid systems is the heterogeneity resulting from the vast range of technologies, both hardware and software, encompassed by the grid [16]. o Some protocols and applications have been proposed and implemented in actual works, such as the Globus Toolkit [9]. The Globus Toolkit is an open-architecture, open-source suite of services and software libraries that support Grids and Grid applications. o In addition grid computing may require redefinition of ownership, copyrights, and licensing all of which present cultural and legal issues which have to be resolved before adjusting policies and expectations of these institutions to integrate with what technology provides. Data Engineering & Cloud Computing
  • 9. E-learning Developments o Multimedia transmissions and related network application technologies have helped fuel the development and popularization of e-learning techniques such as Distance Education, Video Conferencing, and Video on Demand. An e-learning Platform generally requires a high-capacity storage device, such as a Disk Array, Network Attached Storage (NAS), or Storage Area Network (SAN), to store teaching content [9]. Grid Computing can connect scattered computer resources via Internet links. The resources that can be connected include computer facilities, storage media, data and various input and output devices. Thus, Grid computing can be used to build an e-learning platform that features expandability and resource-sharing capability. o The objective is to create virtual dynamic organizations or academic institutions through secure, unlimited power, information access, synchronized resource- sharing among users, institutions and resources. Data Engineering & Cloud Computing
  • 11. Grid Computing Benefits for E- Learning o Academic institutions stand to reap significant benefits from grid computing by creating environments that expose students to the real world data sets in a wide range of disciplines. o Instead of using mock or historical data, a grid could let students use grid facilities to collect their own real data. o By using the computing resources of the components of a grid, institutions can save financial resources both in capital and operating costs [11]. o By increasing the processing power, applications run faster the computing tasks and provide faster results [11]. Grid computing also encourages partnerships among higher education institutions and research centers. o Using a grid, researchers in Britain, for example, can conduct research that relies on databases across Europe, instrumentation in Japan, and computational power in the United States. Making resources available in this way exposes students to the tools of the profession, facilitating new possibilities for research and instruction [12]. Data Engineering & Cloud Computing
  • 12. Conclusions o The paper concludes that institutions of higher learning in the country can and should take advantage of advances in the Internet and its technologies, availability of powerful computers and high-speed networks to establish e- learning grids. o This paper concurs with [22] who asserted that while eLearning may never replace face to face tuition; it will continue to grow in importance due to its role in extending the educational experience in new and innovative directions. Data Engineering & Cloud Computing
  • 13. References 1. Nafukho, F. M., & Machuma, H. M. (2013). The World Bank’s Africa Virtual University Project: a revisit. European Journal of Training and Development , 37 (7), 646-661. 2. Beebe, M. A. ( September 2004). Impact of ICT Revolution on the African Academic Landscape.Conference on Electronic Publishing and Dissemination. Dakar, Senegal: CODESRIA. 3. European Commission. (2001). The eLearning Action Plan: Designing tomorrow’s education. Retrieved october 15, 2015, from http://www.elearningeuropa.info./ 4. Arkorful, V., & Abaidoo, N. (2014). The role of e-learning, the advantages and disadvantages of its adoption in Higher Education. International Journal of Education and Research , 2 (12), 397-410. 5. Uzoka, F., Akinnuwesi, B., Olabiyisi, S., & Alabi, D. (2011). A Case Analysis of Factors Affecting the Adoption of Grid Technology by Universities. IST- Africa 2011 Conference Proceedings. IIMC International Information Management Corporation. Data Engineering & Cloud Computing
  • 14. References 6. Lathia, M. (2005). Advantages of Grid Computing. Ieee Distributed Systems Online 1541-. 7. Kemibaro, M. (2008). Grid computing: faster results at less cost. Retrieved October 24, 2015, from https://www.moseskemibaro.com/2008/04/28/grid- computing-faster-results-at- less-cost/ 8. Yang, C.-T., & Ho, H.-C. (2005). An E-Learning Platform Based On Grid Architecture. Journal Of Information Science And Engineering , 911-928. Data Engineering & Cloud Computing
  • 15. Thank you! Data Engineering & Cloud Computing