On calculating connected dominating set for efficient routing in ad hoc wireless networks
DIALM '99 Proceedings of the 3rd international workshop on Discrete algorithms and methods for mobile computing and communications
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
An Extended Localized Algorithm for Connected Dominating Set Formation in Ad Hoc Wireless Networks
IEEE Transactions on Parallel and Distributed Systems
A greedy approximation for minimum connected dominating sets
Theoretical Computer Science
On greedy construction of connected dominating sets in wireless networks: Research Articles
Wireless Communications & Mobile Computing - RRM for Next-Generation Wireless and Mobile Communication Systems
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
Data management within WSN through multi-hop transmissions
Proceedings of the 8th International Conference on Advances in Mobile Computing and Multimedia
An application-specific protocol architecture for wireless microsensor networks
IEEE Transactions on Wireless Communications
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This paper proposes a data management scheme which employs an energy constrained algorithm selecting between direct and multi-hop transmissions autonomously based on the residual energy level of the individual sensors. The proposed data management scheme rules out the selection of hotspot sensors, the sensors located closer to the base stations, as the intermediate sensors to avoid the dying of these sensors. In each data transmission, the scheme selects one of the neighborhood sensors having minimal Euclidean distance and maximum energy-level as the intermediate node from the neighboring set, without repeating the selection. The proposed data management scheme manages the data collection by utilizing two scheduling algorithms; as soon as possible (ASAP) and as late as possible (ALAP). As a measure of performance, the simulation results of the data management scheme have been compared with that of minimum connected dominating set algorithm (MCDS). The simulation results demonstrate that the data management scheme outperforms with respect to consume less energy; moreover, it can be observed that the scheme finishes an overall short waiting time of the selected sensors compared to the direct transmission in transmitting the data to the base station. The robustness of the proposed scheme is tested by varying the network sizes and varying the sensing radii.