Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Funneling-MAC: a localized, sink-oriented MAC for boosting fidelity in sensor networks
Proceedings of the 4th international conference on Embedded networked sensor systems
Tree-Clustered Data Gathering Protocol (TCDGP) for Wireless Sensor Networks
FGCN '07 Proceedings of the Future Generation Communication and Networking - Volume 02
TreeMAC: Localized TDMA MAC protocol for real-time high-data-rate sensor networks
PERCOM '09 Proceedings of the 2009 IEEE International Conference on Pervasive Computing and Communications
Real-time data gathering in sensor networks
Discrete Applied Mathematics
Lifetime maximisation algorithm in Wireless Sensor Network
International Journal of Ad Hoc and Ubiquitous Computing
Real-time quality of service with delay guarantee in sensor networks
International Journal of Sensor Networks
An energy efficient clustering protocol for routing in Wireless Sensor Network
International Journal of Ad Hoc and Ubiquitous Computing
An application-specific protocol architecture for wireless microsensor networks
IEEE Transactions on Wireless Communications
Hi-index | 0.00 |
Critical applications in real-time wireless sensor networks require bounded service latency and energy consumption optimisation. This motivates us to design a novel scheduling approach, which integrates communications with pipelining and data aggregation. The aim of our aggregation technique is to reduce the number of messages, which consequently reduces energy consumption. However, our pipelining technique is defined to minimise communication latency. Our approach is applied on tree wireless sensor networks and in a real-time context, which requires communications without interference. Thus, we use TDMA and a multi-frequency access method based on parent relationship clustering. In this context, we made the necessary mathematical formulation to determine communication response time and to predict the impact of real-time constraints, particularly deadlines, on communication delay. Our simulations outperform the efficiency of our approach to comprise between communication delay and energy consumption constraints.