Enhanced Backoff Selection Algorithm (EBSA)

Description

Wireless Sensor Networks (WSNs) have gained wide-scale popularity for real-time events monitoring and detection due to their high accuracy and ease of deployment. Therefore, they have become increasingly prevalent solutions in several application domains such as health-care, transportation, etc. Many studies in the literature have focused on optimizing the energy consumption of the wireless sensors in order to ensure their autonomous operation for longer periods. Some applications of WSNs, however, have strict delay requirements due to the nature of the information being transmitted. This delay should be kept as short as possible to ensure timely and efficient reaction of the system, such as a Traffic Management System (TMS) dealing with an incident on the road. In this context, we propose in this work, two novel schemes to reduce the transmission delay of prioritized messages in WSNs deployed in road networks to report regular traffic as well as event-driven (i.e. incidents) information. These schemes improve the backoff computation mechanism at the MAC layer of IEEE 802.15.4 standard protocol, by providing an original dual mode operation mechanism which speeds up the transmission of event-driven messages, while keeping the transmission delay of periodic messages reasonably low. Simulation results show that our schemes succeed in reducing the transmission delay of event-driven messages and achieve a very high packets delivery ratio.

Source code

EBSA source code for ns-2.35

License

EBSA source code is released under the same BSD license as ns-2.

Reference

If you use EBSA source code for your research work, please cite:

pdf Messages Prioritization in IEEE 802.15.4 based WSNs for Roadside Infrastructure.
Imane Horiya Brahmi, Soufiene Djahel, Damien Magoni, John Murphy.
ICCVE'14 - International Conference on Connected Vehicles and Expo,
pp. 1106-1113, November 3-7, 2014, Vienna, Austria.


Spatio-temporal Correlation for Data Aggregation (SCDA)

Description

One of the most popular and efficient methods for conserving energy in Wireless Sensor Networks (WSNs) is data aggregation. This technique usually introduces an additional delay in the transmission of data packets. The inherent trade-off between energy consumption and end-to-end delay imposes an important decision to be made by the nodes, mainly to determine the most appropriate time for aggregating local/transiting packets and forwarding the resulting packet(s) to the next hop towards the sink. Most of the solutions proposed so far are either unable to significantly reduce the overhead caused by the redundant transmissions, or require a long waiting time before aggregating the received packets. To overcome the above limitations, we propose a novel scheme that ensures efficient and fast packets aggregation in WSNs. This scheme defines optimal decision making policies at the cluster head level (i.e. in a cluster based topology) to determine the appropriate waiting time before aggregating the local data sampling, as well as data sampling received from other neighbor cluster heads. The obtained evaluation results confirm the efficiency of our scheme in terms of the achieved end-to-end transmission delay for periodic packets and the reduced overhead. These results reveal also that our scheme outperforms other three literature schemes (no aggregation, randomized waiting and full aggregation) as it ensures the best compromise for aggregation saving and delay reduction.

Source code

SCDA source code for ns-2.35

License

SCDA source code is released under the same BSD license as ns-2.

Reference

If you use SCDA source code for your research work, please cite:

pdf A Spatial Correlation Aware Scheme for Efficient Data Aggregation in Wireless Sensor Networks.
Imane Horiya Brahmi, Soufiene Djahel, Damien Magoni, John Murphy.
P2MNET'15 - IEEE International Workshop on Performance and Management of Wireless and Mobile Networks,
pp. 847-854, October 26-29, 2015, Clearwater Beach, FL, USA.


Last updated: March 5, 2016.