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In recent times, there has been a significant growth in the number of smartphone users and number and types of mobile applications (apps). Such a trend has resulted in increased Internet data consumption, particularly for users of “data hungry” apps. Thus, smartphone apps should be allocated to their required budget to minimize resource wastage without compromising on user’s quality of experience. In this paper, we develop a prioritized and dynamic budget allocation policy framework for ensuring an optimal budget allocation to each app as well as improving system performance. We formulate the optimal Internet data budget management (O-IDM) problem as a mixed-integer nonlinear programming (MINLP) problem, which maximizes the resource utilization and minimizes user penalties. We also employ runtime monitoring technique to estimate future bandwidth utilization so as to ensure budget reservation as close as to the required amount. A heuristic Internet data budget management algorithm (H-IDM) is also presented, which is designed to reduce time complexity and computational overhead of the O-IDM system. The experimental results from test-bed implementation demonstrate the effectiveness of the proposed IDM systems, in comparison to state-of-the-art approaches.
Modern webpages become complex and richer to provide full-feature contents. However, it decreases the site responsiveness due to the growing number of DNS lookups. As users and service providers want faster responsive websites, developers proposed several web performance metrics such as First Meaningful Paint, Page Load Time, and Speed Index to analyze the performance of websites. In this paper, we investigate the performance of different webpages using web performance metrics and provide a novel mechanism MR-DNS to reduce DNS lookups and improve web performance. MR-DNS provides multi-resolution service to reduce DNS lookups in the local DNS and reduces incoming traffic to Authoritative DNS. We also investigate memory and network traffic conditions for MR-DNS system.
The popularity of Augmented Reality applications is increasing. People want real-time service, up-to-date and personalized information in Augmented Reality (AR). The communication in AR is a challenge due to the high latency between the device to cloud communication, especially in vehicular applications. Vehicular applications need real-time services and data abstraction with minimal latency. In this survey paper, we comprehensively investigate augmented reality communication and compare how other technologies handle the problems of serving the data in real-time and what are the challenges to implementing similar solutions in AR systems.
Recommended citation: Saidur Rahman, Anika Anzum Prima, Md. Abdur Razzaque IEEE Conference on Networking Systems and Security. NSysS 2016.
Recommended citation: Saidur Rahman, Anika Anzum Prima, Md. Abdur Razzaque, Mohammad Mehedi Hassan, Abdulhameed Alelaiwi, Majed Alrubaian, Kim-Kwang Raymond Choo Springer Journal on JWCN 2016. JWCN 2016.
Recommended citation: Saidur Rahman, Mike P Wittie The 12th International Conference on Internet and Distributed Computing Systems IDCS 2019.
CSCI-232: Data Structure and Algorithm, CSCI-246: Discrete Structures
CSCI-132: Basic Data Structure and Algorithm
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