In challenging environment, sensory data must be stored inside the network in case of sink failures, we need to redistribute overflowing data items from the depleted storage source nodes to sensor nodes with available...In challenging environment, sensory data must be stored inside the network in case of sink failures, we need to redistribute overflowing data items from the depleted storage source nodes to sensor nodes with available storage space and residual energy. We design a distributed energy efficient data storage algorithm named distributed data preservation with priority （Dzp2）. This algorithm takes both data redistribution costs and data retrieval costs into account and combines these two problems into a single problem. DZP2 can effectively realize data redistribution by using cooperative communication among sensor nodes. In order to solve the redistribution contention problem, we introduce the concept of data priority, which can avoid contention consultations between source nodes and reduce energy consumption. Finally, we verify the performance of the proposed algorithm by both theory and simulations. We demonstrate that D2p2＇s performance is close to the optimal centralized algorithm in terms of energy consumption and shows superiority in terms of data preservation time.展开更多
基金supported by the National Natural Science Foundation of China (61401234,61271234)the Priority Academic Program Development Project of Jiangsu Higher Education InstitutionsJiangsu Government Scholarship for Overseas Studies
文摘In challenging environment, sensory data must be stored inside the network in case of sink failures, we need to redistribute overflowing data items from the depleted storage source nodes to sensor nodes with available storage space and residual energy. We design a distributed energy efficient data storage algorithm named distributed data preservation with priority （Dzp2）. This algorithm takes both data redistribution costs and data retrieval costs into account and combines these two problems into a single problem. DZP2 can effectively realize data redistribution by using cooperative communication among sensor nodes. In order to solve the redistribution contention problem, we introduce the concept of data priority, which can avoid contention consultations between source nodes and reduce energy consumption. Finally, we verify the performance of the proposed algorithm by both theory and simulations. We demonstrate that D2p2＇s performance is close to the optimal centralized algorithm in terms of energy consumption and shows superiority in terms of data preservation time.
