1. Networking IEEE 2015 Projects
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List Link : http://kasanpro.com/projects-list/networking-ieee-2015-projects
Title :Medical Data Compression and Transmission in Wireless Ad Hoc Networks
Language : Java
Project Link : http://kasanpro.com/p/java/medical-data-compression-transmission-wireless-ad-hoc-networks
Abstract : A wireless ad hoc network (WANET) is a type of wireless network aimed to be deployed in a disaster area
in order to collect data of patients and improve medical facilities. The WANETs are composed of several small nodes
scattered in the disaster area. The nodes are capable of sending (wirelessly) the collected medical data to the base
stations. The limited battery power of nodes and the transmission of huge medical data require an energy efficient
approach to preserve the quality of service of WANETs. To address this issue, we propose an optimizationbased
medical data compression technique, which is robust to transmission errors. We propose a fuzzy-logic-based route
selection technique to deliver the compressed data that maximizes the lifetime of WANETs. The technique is fully
distributed and does not use any geographical/location information. We demonstrate the utility of the proposed work
with simulation results. The results show that the proposed work effectively maintains connectivity of WANETs and
prolongs network lifetime.
Title :Medical Data Compression and Transmission in Wireless Ad Hoc Networks
Language : C#
Project Link : http://kasanpro.com/p/c-sharp/medical-data-compression-transmission
Abstract : A wireless ad hoc network (WANET) is a type of wireless network aimed to be deployed in a disaster area
in order to collect data of patients and improve medical facilities. The WANETs are composed of several small nodes
scattered in the disaster area. The nodes are capable of sending (wirelessly) the collected medical data to the base
stations. The limited battery power of nodes and the transmission of huge medical data require an energy efficient
approach to preserve the quality of service of WANETs. To address this issue, we propose an optimizationbased
medical data compression technique, which is robust to transmission errors. We propose a fuzzy-logic-based route
selection technique to deliver the compressed data that maximizes the lifetime of WANETs. The technique is fully
distributed and does not use any geographical/location information. We demonstrate the utility of the proposed work
with simulation results. The results show that the proposed work effectively maintains connectivity of WANETs and
prolongs network lifetime.