Shrinivas R. Managalwede

Work place: Department of Computer Science and Engineering, Gogte Institute of Technology, Belagavi, India

E-mail: mangalwede@git.edu

Website:

Research Interests: E-learning, Wireless Networks

Biography

Shrinivas R. Mangalwede received the B.E. degree in Computer Science and Engineering from Karnataka University, Dharwad, India, in 1994, the M. Tech. degree in Computer Network Engineering, from Visvesvaraya Technological University, Belagavi, India, in 2004 and the Ph.D. degree from Visvesvaraya Technological University, Belgaum, India, in 2012. Since 2012, he has been with the Gogte Institute of Technology, Belagavi, India and he is currently working as Professor in the Department of Computer Science and Engineering. His research interests include E-Learning, M-Learning, Agent Technology and Wireless Networks.

Author Articles
Delay-sensitive Quality of Service Routing with Integrated Admission Control for Wireless Mesh Network

By Satish S. Bhojannawar Shrinivas R. Managalwede Carlos F. Cruzado

DOI: https://doi.org/10.5815/ijcnis.2024.06.02, Pub. Date: 8 Dec. 2024

Wireless mesh networks (WMNs) extend and improve broadband Internet connectivity for the end-users roaming around the edges of the wired network. Amid the explosive escalation of users sharing multimedia content over the Internet, the WMNs need to support the effective implementation of various multimedia applications. The multimedia applications require assured quality of service (QoS) to fulfill the user requirements. The QoS routing in WMNs needs to guarantee the QoS requirements of multimedia applications. Admission control (AC) is the primary traffic control mechanism used to provide QoS provisioning. AC admits a new flow only if the QoS requirements of already admitted flows are not violated, even after the admission of a new flow. We propose a new QoS routing protocol integrated with AC called Delay-Sensitive QoS Routing with integrated Admission Control (DSQRAC) to control the admission of delay-sensitive flows. A delay-aware cross-layer routing metric is used to find the feasible path. DSQRAC is implemented using ad-hoc on-demand distance vector (AODV) routing protocol, where a delay-sensitive controlled flooding mechanism is used to forward the route request packets. In the proposed work, we adjust/reassign the channels to aid the QoS routing to increase the likelihood of accepting a new flow. The simulation results show that the performance of the proposed QoS routing protocol is better than the existing schemes.

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Distributed and Dynamic Channel Assignment Schemes for Wireless Mesh Network

By Satish S. Bhojannawar Shrinivas R. Managalwede

DOI: https://doi.org/10.5815/ijcnis.2022.02.04, Pub. Date: 8 Apr. 2022

Wireless mesh network (WMN) with wireless backhaul technology provides last-mile Internet connectivity to the end-users. In multi-radio multi-channel WMN (MRMC-WMN), routers provide multiple concurrent transmissions among end-users. The existence of interference among concurrent transmissions severely degrades the network performance. A well-organized channel assignment (CA) scheme significantly alleviates the interference effect. But in trying to minimize interference, the CA scheme may affect the network connectivity. So, the CA scheme has to consider both these two conflicting issues. In this paper, as part of the initial configuration of WMNs, we propose a game theory-based load-unaware CA scheme to minimize the co-channel interference and to maximize the network connectivity. To adapt to the varying network traffic, we propose a dynamic channel assignment scheme. This scheme measures the traffic-load condition of the working channels of each node. Whenever a node finds an overloaded channel, it initiates a channel switch. Channel switching based on the fixed threshold may result in a channel over/underutilization. For optimal channel utilization, we propose a fuzzy logic-based approach to compute the channel switch threshold. The contending nodes and their densities and loads dominantly affect the network capacity and hence the performance. In the context of network capacity enhancement, we have addressed these factors and focused on increasing the network capacity. The simulation results indicate that our proposed load-unaware and load-aware CA schemes outperform the other related load-unaware and load-aware CA approaches.

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