Abstract
Data aggregation techniques have emerged as promising solutions for extending Wireless Sensor Networks (WSNs) lifetime. However, this approach suffers from a design issue in delivering the strict requirements needed by some monitoring applications. Carefully balancing Energy, Delay and Accuracy is essential for achieving these requirements. In this work, we focus on distributed data aggregation, where a sensor estimates the network information by the exchange of readings with different priority levels. We then propose an optimal decision policy for scheduling the transmission of the aggregated data at the node level. To model the investigated problem, we first adopt Markov Decision Process (MDP) whereby we define the reward function. Then, we apply a Genetic Algorithm (GA) to find a set of optimal decisions that ensures the best trade-off between energy saving, delay and accuracy of the received data based on their priority level. The simulation results yield excellent performance and our optimization shows a significant enhancement up to 20% compared to the other policies.
Original language | English |
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Title of host publication | 2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2015 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 2066-2071 |
Number of pages | 6 |
ISBN (Electronic) | 9781467367820 |
ISBN (Print) | 9781467367813 |
DOIs | |
Publication status | Published - 3 Dec 2015 |
Externally published | Yes |
Event | 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications - Hong Kong, China Duration: 30 Aug 2015 → 2 Sept 2015 |
Conference
Conference | 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications |
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Abbreviated title | PIMRC 2015 |
Country/Territory | China |
City | Hong Kong |
Period | 30/08/15 → 2/09/15 |
Keywords
- WSNs
- Data aggregation
- Delay-Energy-Accuracy tradeoff
- Markov Decision Process (MDP)
- Genetic algorithm (GA)