M
Mahmoud Daneshmand
Researcher at Stevens Institute of Technology
Publications - 119
Citations - 3437
Mahmoud Daneshmand is an academic researcher from Stevens Institute of Technology. The author has contributed to research in topics: Computer science & Wireless network. The author has an hindex of 21, co-authored 101 publications receiving 2149 citations. Previous affiliations of Mahmoud Daneshmand include AT&T Labs & AT&T.
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Journal ArticleDOI
A survey of transport protocols for wireless sensor networks
TL;DR: This article highlights several unique aspects of WSNs, and describes the basic design criteria and challenges of transport protocols, including energy-efficiency, quality of service, reliability, and congestion control.
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Upstream congestion control in wireless sensor networks through cross-layer optimization
TL;DR: It is demonstrated that PCCP achieves efficient congestion control and flexible weighted fairness for both single-path and multi-path routing, as a result this leads to higher energy efficiency and better QoS in terms of both packet loss rate and delay.
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Residual Energy-Based Cluster-Head Selection in WSNs for IoT Application
Trupti Mayee Behera,Sushanta Kumar Mohapatra,Umesh Chandra Samal,Mohammad S. Khan,Mahmoud Daneshmand,Amir H. Gandomi +5 more
TL;DR: A efficient CH election scheme that rotates the CH position among the nodes with higher energy level as compared to other to elect the next group of CHs for the network that suits for IoT applications, such as environmental monitoring, smart cities, and systems is proposed.
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Internet of Things Mobile–Air Pollution Monitoring System (IoT-Mobair)
TL;DR: A three-phase air pollution monitoring system analogous to Google traffic or the navigation application of Google Maps is proposed, and air quality data can be used to predict future air quality index (AQI) levels.
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Human Memory Update Strategy: A Multi-Layer Template Update Mechanism for Remote Visual Monitoring
Shuai Liu,Shuai Wang,Xinyu Liu,Amir H. Gandomi,Mahmoud Daneshmand,Khan Muhammad,Victor Hugo C. de Albuquerque +6 more
TL;DR: A multi-layer template update mechanism to achieve effective monitoring in a multimedia environment by considering the strategy of updating human memory and shows that this strategy does not affect the speed and improves the robustness in the multimedia background.