Abstract
Up-to-date, research in WSN has found a stalemate due to issues, such as energy consumption, scalability and terrain adaptation. This has motivated recent studies about algorithms and protocols that can help solving them in a way that consumption is reduced and the device's life span is maximized, as well as a reduction of data loss caused by collisions. To overcome these obstacles, gossip-based transmission techniques have shown some advantages in routing and data distribution. This paper presents simulation results and implementation regarding the efficiency in message transmission for different gossip-based algorithms (flooding, RGA, DRG, RGAM) and how the results in different topologies shows the DRG algorithm supremacy over the rest, since this can reduce up to half the amount of messages transmitted in different networks to complete a certain task. Likewise, an implementation of a short-scale WSN has been made to verify the previous results and see the capabilities that these algorithms exhibit in WSN.
| Original language | English |
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| Title of host publication | 2013 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems, COMCAS 2013 |
| DOIs | |
| State | Published - 2013 |
| Event | 2013 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems, COMCAS 2013 - Tel Aviv, Israel Duration: 21 Oct 2013 → 23 Oct 2013 |
Publication series
| Name | 2013 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems, COMCAS 2013 |
|---|
Conference
| Conference | 2013 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems, COMCAS 2013 |
|---|---|
| Country/Territory | Israel |
| City | Tel Aviv |
| Period | 21/10/13 → 23/10/13 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Zigbee
- distributed algorithms
- energy consumption
- network topology
- routing protocols
- wireless sensor networks
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