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Md. Zakirul Alam Bhuiyan

Bio: Md. Zakirul Alam Bhuiyan is an academic researcher from Fordham University. The author has contributed to research in topics: Wireless sensor network & Key distribution in wireless sensor networks. The author has an hindex of 14, co-authored 32 publications receiving 565 citations. Previous affiliations of Md. Zakirul Alam Bhuiyan include Hong Kong Polytechnic University & Central South University.

Papers
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Journal ArticleDOI
TL;DR: A data-driven dynamic clustering framework for moderating the adverse economic impact of COVID-19 flare-up is proposed and the idea can be exploited for potentially the next waves of corona virus-related diseases and other upcoming viral life-threatening calamities.

111 citations

Journal ArticleDOI
TL;DR: An adaptive computation offloading method, named ACOM, is devised for edge computing in 5G-envisioned IoCV to optimize the task offloading delay and resource utilization of the edge system.
Abstract: Nowadays, the applications related to Internet of connected vehicles (IoCV) have been greatly promoted by the roadside units (RSUs). To improve the transmission efficiency by the RSUs, 5G is introduced to the IoCV scenario for offering sufficient communication bandwidth. Generally, the traditional offloading destinations of the computing tasks in IoCV are the distant cloud servers, which consequently increases the response time of the tasks. Edge servers, placed together with macro base stations (MABSs) in 5G and RSUs, offer alternatives to host the tasks. However, the complicated locations of MABSs and RSUs make it difficult to distinguish the offloading destinations of the computing tasks in IoCV. In view of this, an adaptive computation offloading method, named ACOM, is devised for edge computing in 5G-envisioned IoCV to optimize the task offloading delay and resource utilization of the edge system. More specifically, the multi-objective evolutionary algorithm based on decomposition (MOEA/D) is fully leveraged to generate the available solutions. Then, the optimal offloading solution is obtained by utility evaluation. Eventually, the experimental results demonstrate the effectiveness of ACOM.

102 citations

Journal ArticleDOI
TL;DR: A cognitive or intelligent model of bio-inspired approach is used to find the optimal solution of task scheduling for IoT applications in a heterogeneous multiprocessor cloud environment.

92 citations

Proceedings ArticleDOI
16 May 2012
TL;DR: This paper presents an approach, called FTSHM (fault tolerance in SHM), to repairing the network to guarantee a specified degree of fault tolerance and includes a SHM algorithm suitable for decentralized computing in energy-constrained WSNs, with the objective of prolonging the WSN lifetime under connectivity and data delivery constraints.
Abstract: Structural health monitoring (SHM) brings new challenges to wireless sensor networks (WSNs) : large volume of data, sophisticated computing, engineering-driven optimal deployment, and so forth. In this paper, we address two important challenges: sensor placement and decentralized computing. We propose a solution to place sensors at strategic locations to achieve the best estimates of geometric properties of a structure. To make the deployed network resilient to faults caused by communication errors, unstable network connectivity, and sensor faults, we present an approach, called FTSHM (fault tolerance in SHM), to repairing the network to guarantee a specified degree of fault tolerance. FTSHM searches the repairing points in clusters and places a set of backup sensors at those points by satisfying civil engineering requirements. FTSHM also includes a SHM algorithm suitable for decentralized computing in energy-constrained WSNs, with the objective to guarantee that the WSN for SHM remains connected in the event of a sensor fault thus prolonging the WSN lifetime under connectivity and data delivery constraints. We demonstrate the advantages of FTSHM through simulations and experiments on a real civil structure.

71 citations

Journal ArticleDOI
TL;DR: This article studies how mobile vehicles can be optimally selected in order to collect maximum data from the urban environment in a future period of tens of minutes and proposes a greedy online algorithm to recruit a subset of vehicles with a limited budget for the NP-Complete problem.
Abstract: Mobile crowdsensing is an emerging paradigm that selects users to complete sensing tasks. Recently, mobile vehicles are adopted to perform sensing data collection tasks in the urban city due to their ubiquity and mobility. In this article, we study how mobile vehicles can be optimally selected in order to collect maximum data from the urban environment in a future period of tens of minutes. We formulate the recruitment of vehicles as a maximum data limited budget problem. The application scenario is generalized to a realistic online setting where vehicles are continuously moving in real-time and the data center decides to recruit a set of vehicles immediately. A deep learning-based scheme through mobile vehicles (DLMV) is proposed to collect sensing data in the urban environment. We first propose a deep learning-based offline algorithm to predict vehicle mobility in a future time period. Furthermore, we propose a greedy online algorithm to recruit a subset of vehicles with a limited budget for the NP-Complete problem. Extensive experimental evaluations are conducted on the real mobility dataset in Rome. The results have not only verified the efficiency of our proposed solution but also validated that DLMV can improve the quantity of collected sensing data compared with other algorithms.

69 citations


Cited by
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Book ChapterDOI
01 Jan 1982
TL;DR: In this article, the authors discuss leading problems linked to energy that the world is now confronting and propose some ideas concerning possible solutions, and conclude that it is necessary to pursue actively the development of coal, natural gas, and nuclear power.
Abstract: This chapter discusses leading problems linked to energy that the world is now confronting and to propose some ideas concerning possible solutions. Oil deserves special attention among all energy sources. Since the beginning of 1981, it has merely been continuing and enhancing the downward movement in consumption and prices caused by excessive rises, especially for light crudes such as those from Africa, and the slowing down of worldwide economic growth. Densely-populated oil-producing countries need to produce to live, to pay for their food and their equipment. If the economic growth of the industrialized countries were to be 4%, even if investment in the rational use of energy were pushed to the limit and the development of nonpetroleum energy sources were also pursued actively, it would be extremely difficult to prevent a sharp rise in prices. It is evident that it is absolutely necessary to pursue actively the development of coal, natural gas, and nuclear power if a physical shortage of energy is not to block economic growth.

2,283 citations

Book
02 Jan 1991

1,377 citations

Journal ArticleDOI
TL;DR: A comprehensive survey on UAV communication towards 5G/B5G wireless networks is presented in this article, where UAVs are expected to be an important component of the upcoming wireless networks that can potentially facilitate wireless broadcast and support high rate transmissions.
Abstract: Providing ubiquitous connectivity to diverse device types is the key challenge for 5G and beyond 5G (B5G). Unmanned aerial vehicles (UAVs) are expected to be an important component of the upcoming wireless networks that can potentially facilitate wireless broadcast and support high rate transmissions. Compared to the communications with fixed infrastructure, UAV has salient attributes, such as flexible deployment, strong line-of-sight (LoS) connection links, and additional design degrees of freedom with the controlled mobility. In this paper, a comprehensive survey on UAV communication towards 5G/B5G wireless networks is presented. We first briefly introduce essential background and the space-air-ground integrated networks, as well as discuss related research challenges faced by the emerging integrated network architecture. We then provide an exhaustive review of various 5G techniques based on UAV platforms, which we categorize by different domains including physical layer, network layer, and joint communication, computing and caching. In addition, a great number of open research problems are outlined and identified as possible future research directions.

566 citations