A partition checkpoint strategy based on data segment priority is presented to meet the timing constraints of the data and the transaction in embedded real-time main memory database systems（ERTMMDBS） as well as to r...A partition checkpoint strategy based on data segment priority is presented to meet the timing constraints of the data and the transaction in embedded real-time main memory database systems（ERTMMDBS） as well as to reduce the number of the transactions missing their deadlines and the recovery time.The partition checkpoint strategy takes into account the characteristics of the data and the transactions associated with it;moreover,it partitions the database according to the data segment priority and sets the corresponding checkpoint frequency to each partition for independent checkpoint operation.The simulation results show that the partition checkpoint strategy decreases the ratio of trans-actions missing their deadlines.展开更多
In this paper, we propose multi-characteristics based data scheduling over smart grid. Three different pricing strategies are presented based on user priority and load rate. Then the corresponding novel scheduling alg...In this paper, we propose multi-characteristics based data scheduling over smart grid. Three different pricing strategies are presented based on user priority and load rate. Then the corresponding novel scheduling algorithms are introduced by the proposed data priority and pricing strategies. The simulation experiments are carried out to evaluate the proposed algorithms based on trace data. And the results show that our methods can outperform the conventional method.展开更多
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 (60673128)
文摘A partition checkpoint strategy based on data segment priority is presented to meet the timing constraints of the data and the transaction in embedded real-time main memory database systems（ERTMMDBS） as well as to reduce the number of the transactions missing their deadlines and the recovery time.The partition checkpoint strategy takes into account the characteristics of the data and the transactions associated with it;moreover,it partitions the database according to the data segment priority and sets the corresponding checkpoint frequency to each partition for independent checkpoint operation.The simulation results show that the partition checkpoint strategy decreases the ratio of trans-actions missing their deadlines.
基金supported in part by the Fundamental Key Research Project of Shanghai Municipal Science and Technology Commission(No.12JC1404201)
文摘In this paper, we propose multi-characteristics based data scheduling over smart grid. Three different pricing strategies are presented based on user priority and load rate. Then the corresponding novel scheduling algorithms are introduced by the proposed data priority and pricing strategies. The simulation experiments are carried out to evaluate the proposed algorithms based on trace data. And the results show that our methods can outperform the conventional method.
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.
