Energy-Optimal and Energy-Balanced Sorting in a Single-Hop Wireless Sensor Network
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
Distributed Data Gathering Scheduling in Multihop Wireless Sensor Networks for Improved Lifetime
ICCTA '07 Proceedings of the International Conference on Computing: Theory and Applications
EBAT: Energy Balanced Adaptive Transmission Algorithm for Sensor Networks
NPC '08 Proceedings of the 2008 IFIP International Conference on Network and Parallel Computing
Modeling Data-Aggregation within Wireless Sensor Networks as Scheduling of Super Task-Flow-Graph
UKSIM '09 Proceedings of the UKSim 2009: 11th International Conference on Computer Modelling and Simulation
An application-specific protocol architecture for wireless microsensor networks
IEEE Transactions on Wireless Communications
Management Scheme for Data Collection within Wireless Sensor Networks
International Journal of Adaptive, Resilient and Autonomic Systems
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In this paper, we have proposed an energy constrained algorithm which selects direct transmission or multi-hop transmissions based on the residual energy level of the transmitting sensor node. The sensors with higher energy levels can directly transmit their collected data to the base stations, while the sensors with low energy level can employ a two-hop transmission to reach the base stations. Our proposed data management algorithm rules out the selection of hotspot sensors, which are located closer to the base stations, as the intermediate sensors to avoid the dying (battery run out) of these nodes. The proposed data management algorithm selects one of the neighborhood nodes having minimal Euclidean distance and maximum energy level as the intermediate node for transmission. We have also added constraints to avoid the repeatability in the selection of neighborhood sensors. We have utilized as soon as possible (ASAP) and as late as possible (ALAP) scheduling algorithms in combination with the proposed data management algorithm to manage the data collection from the sensors to the base station. The simulation results show that the proposed data management algorithm performs better in reducing the energy consumption and waiting time of the selected sensors compared to the direct transmission.