E3S Web Conf.
Volume 125, 2019The 4th International Conference on Energy, Environment, Epidemiology and Information System (ICENIS 2019)
|Number of page(s)||5|
|Section||Decision Support Systems|
|Published online||28 October 2019|
Gaussian Prediction Method to Enhance Energy Efficient in Energy Aware AODV
1 Department of Electrical and Electronics Engineering Diponegoro University, Semarang - Indonesia
2 Department of Computer Engineering Diponegoro University, Semarang – Indonesia
* Corresponding author: email@example.com
One of the concerns in the development routing protocol in Mobile Ad Hoc Network is energy consumption which is very influential on package delivery. Energy Delay Aware Ad hoc Demand on Distance Vector (EA-AODV) is one of the routing protocols for the development of Ad hoc Demand on Vector (AODV) that considers energy when receiving packets stored in the routing table. The routing protocol applies the Dijkstra algorithm to determine the shortest route by considering the sequence number and hop count. In the development carried out on EA-AODV is a modification of the Dijkstra algorithm by adding a gaussian prediction method in consideration of the energy level that is expected to be more efficient in terms of energy consumption. Gaussian prediction method was executed in receive request (RREQ) when the packet saved in the routing table. The Application of the network protocol was conducted by comparing the performance of AODV with EA-AODV. The consumption energy of EA-AODV is more efficient at 12.07% compared to AODV.
Key words: EA-AODV / Dijkstra Algorithm / Gaussian prediction method / NS2.35
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.