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National Center for Big Data & Cloud Computing

Project funded by Heigher Education Commission Pakistan, inline with long term Vision 2025 of Government of Pakistan

"that knowledge has become the key driver for socio-economic development in the globalized world, “People First: Developing social and human capital” has been identified as very first of the seven Pillars of the Vision 2025. In order to enhance collective competitiveness in the longer run and channelize and streamline energies and potential of Pakistani youth. One of the most important pillars is to create Knowledge Economy through higher education and research.


Due to increased use of mobile devices such as laptops, tablets and cellphones, more than 90% of the network traffic generated is comprised of multimedia data – such as the data generated through multimedia applications, remote sensing, sensor networks and digital services applications. Although high compression efficient algorithms have been developed for representation of such multimedia data, but owing to the amount of information the size of the generated multimedia data is immense. Furthermore, the utility of the stored data is directly related to its size, due to the extent of analytical information that can be extracted from the big size of the data. Therefore, a rich multimedia data and its allied applications requires huge storage and computational requirement. Keeping in view the rapid advancements in the computing hardware, increased trend in the use of mobile devices, their limited memory, low computational capability and less battery life the use of cloud computing is a valuable resource.

Our focus is to effectively utilize cloud computing for Big Data applications for solution to problems of national importance. With support of cloud computing resource limited resource devices can perform heavy data services to store, edit, generate, process and communicate media files such as audio, video, images, graphics and so on, even without large storage and computation power. Therefore, keeping in view the advantages of cloud computing in provisioning and processing of big data and its suitability for the emerging trend in mobile devices and Pakistani R&D environment having limited hardware resources, the utility of the cloud computing is plausible. In the proposed Lab, our focus is on the following key sub-domains, which are R&D problems of National importance.

The advancements in the above listed fields is limited due to its demanding storage and computation requirements. However, this limitation can be overcome through Cloud Computing resource with high storage and computation capability with additional advantage of Big Data analytic resource.

Furthermore, all the proposed sub-domains have focus on scientific solution to problems of National importance. Currently, none of the proposed subdomains have been investigated in the perspective of cloud computing in Pakistan.

This opportunity to work on the utility of cloud computing in the proposed domains will surely advance the field and its impact in Pakistan.

Scientific Objectives

The emerging cloud technology has removed the barrier in the way of storage and computation resource dependent Research and Development activities within Pakistan and rest of the world. Now, the organizations can only focus on their core R&D activity as the required resources can be outsourced through cloud model. The cloud’s benefits such as resource availability, scalability, rapid elasticity, efficiency, availability and dynamic resource allocation are very attractive for big data dependent and computationally demanding services and applications. Therefore, keeping in view the pros of the cloud computing model and the expertise of our R&D team, our research activities will focus on the following key domains, which are of National importance.

We will like to mention that Pakistan is a developing country, and its research and development community is facing various challenges in their way towards successful implementation and deployment of big data dependent and computationally intensive solutions. More specifically, the most critical resources which have direct impact on the Pakistani scientific R&D activities is availability of electricity, appropriate computational power and sufficient data storage facility. Proper maintenance of computational and storage facility itself has very high financial demands and keeping in view the current scenario of shortage of electricity in Pakistan, provisioning of secondary resources to provide electricity for the computational and storage facilities is outside the budget scope of majority of the R&D organizations. In such a scenario, facilitation of the R&D community in the use of cloud resource and to focus on the utility of cloud resources can remove the limitation of resource barrier in the way of national R&D advancements and is of very high scientific importance. This will act as a source to motivate and educate our community in the use of cloud computing and the utility of data analytics from stored big data. Through the use of cloud computing the Pakistani community can utilize geographically distributed remote servers for their storage and computational requirements, without the worry of arrangement of resources for its power, maintenance and upgrades. Furthermore, keeping in view the suitability of the cloud computing for the community oriented technological applications our R&D organization can compete with the rest of the world as of the same level in terms of storage and computational resources because in cloud model everyone has a fair and equal access to resources with no geographic bounds.

The proposed Lab will act as role model to educate national R&D community and to conduct applied research in the field of Data Analytics and Cloud Computing and to target national and international challenges in the relevant scope of work. It will provide a shared platform for the R&D organizations of the country to collaborate with each other and to participate in interdisciplinary research. This Lab has a vision to collaborate with various national and international research centers in various funded projects. This Lab will provide an opportunity to the national and international collaborators to offer conferences, seminars, workshops, courses and lectures in the field of Data Analytics and Cloud Computing.

Summary of Application Domains

The established research Lab will focus on applied research in the field of Data Analytics and Cloud Computing. Keeping in view the research interests and expertise of our team members and the potential of cloud computing in developing beneficial application systems for the Pakistani community. Our research and development activities are broadly categorized in the following sub-domains.

1. Multimedia streaming and analytics

The objective of this R&D activity is to develop a cloud computing based P2P live and on-demand multimedia streaming application to assist media houses, educational institutes, individuals and organizations, to stream live multimedia contents, with support of scalability feature to work effectively in diverse networking conditions and provision of high users quality of experience with increase in number of users. An open source P2P multimedia streaming system will be developed, that will effective utilization cloud computing, storage and analytics resource for multimedia streaming.

2. Remote sensing big data analytics

The objective of this R&D activity is to develop a cloud computing based land-use and change detection system using remote sensing to assist Planning Agencies, Government organizations, environment monitoring agencies, individuals and organizations, to effectively obtain land-use and change detection statistics for planning and monitoring of the land surface and environment. A Remote Sensing system will be developed that will effective utilization cloud’s storage, computing and analytics resource for land-cover use and change detection.

3. Traffic characterization and analytics

Vehicular traffic flow being a dynamic system, experiences perturbation because of new entrant vehicles at ingress. Causing shock waves which travels back in the traffic flow system causing congestions. Congestion, excessive acceleration and deceleration increases fuel consumption, emissions (CO2, CO, dust particles etc.) and accident's vulnerability. Traffic flow models will be devised using Wave propagation, Fluid Flow dynamics, Constraint/linear programming, Queuing theory and regression techniques for forecasting, congestion mitigation and ameliorating traffic flow. A working simulator for traffic flow characterization and analytics will be developed that will support of real time route choice to the drivers by integrating real time data (congestion, pollution, and traffic flow) and make decisions for real time traffic.

4. Cloud Integration and analytics for mass data platform

Gathering of digital data and computing analytics to ensure governmental regularization of revenue and citizens welfare from digital apps and IoT ecosystem. Map-based digital portal will be developed that provides citizens and governing bodies with visual analytics to understand complex municipal data e.g. a citizen can see the analytics of pollution, crimes, road conditions, load shedding timing, street light conditions of any postal code. Governing bodies can use data for policy making, and monitoring. The digital portal will have support of search engine, analytics and heat maps support.

A pictorial representation of our model and sub-domains is given below.

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Pictorial representation of our sub-domains


Dr.Nasru Minallah
Associate Professor
Chairman, Department of Computer Science & IT
University of Engineering and Technology Peshawar
Contact: +92-3452757576 / +92 091 9222276

Co Principal Investigators

CoPI-1 Dr. Iftikhar Ahmad
Assistant Professor, Department of Computer Science and IT, UET Peshawar
CoPI-2 Dr. Zawar Hussain Khan
Assistant Professor, Department of Electrical Engineering, UET Peshawar, Jalozai Campus
CoPI-3 Dr. Aamir Saeed
Assistant Professor, Department of Computer Science and IT, UET Peshawar, Jalozai Campus