2012
DOI: 10.1007/s11277-012-0725-0
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Hierarchical Distributed Source Coding Scheme and Optimal Transmission Scheduling for Wireless Sensor Networks

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Cited by 8 publications
(16 citation statements)
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“…Therefore, the recovered sensed data will be more accurate. Figures 5,6, and 7 show the SNR of reconstructed data, the number of transmitted data, and the number of computed data, respectively, in different surveillance scenarios. The number of uncorrelated two-dimensional Gaussian data sources ranges from 2 to 4.…”
Section: Experiments and Analysismentioning
confidence: 99%
See 1 more Smart Citation
“…Therefore, the recovered sensed data will be more accurate. Figures 5,6, and 7 show the SNR of reconstructed data, the number of transmitted data, and the number of computed data, respectively, in different surveillance scenarios. The number of uncorrelated two-dimensional Gaussian data sources ranges from 2 to 4.…”
Section: Experiments and Analysismentioning
confidence: 99%
“…Therefore, data collection schemes in wireless sensor network should be light weight and energy efficient. Two representative types of data collection schemes in wireless sensor networks are spatial-temporal correlation based data predication schemes [3][4][5] and distributed source coding schemes [6][7][8].…”
Section: Introductionmentioning
confidence: 99%
“…Output: the sums of each top-| | elements. The initial data set selection phase (1) If node is a member agent node Then (2) Sendsfirst positive and last negative elements in to administrator agent node; (3) Else (4) Computes partial sums for received elements according to (17); (5) ← {the largest positive sums and the smallest negative sums}; (6) Sends to all member agent nodes; The candidate data set selection phase (1) If node is a member agent node Then (2) Finds and in among all elements in the initial data set ; (3) Sends unsent elements in whose values ≥ or ≤ combined with and to the administrator agent node; (4) Else (5) Computes the partial sum for received elements according to (17); (6) ← the th highest positive element; (7) ← the th lowest negative element; (8) Computes upper bounds of whole sum for received elements according to (18); (9) Computes lower bounds of whole sum for received elements according to (19); (10) ← { | ( ) ≥ or ( ) ≤ }; (11) Sends to all member agent nodes; The top-|k| elements selection phase (1) If node is a member agent node Then (2) Sends unsent elements in to administrator agent node; (3) Else (4) Computes whole sums for received elements according to (16); (5) top-| | ← {the largest elements in magnitude};…”
Section: An Example Of the Three-phase Top-| | Query Algorithmmentioning
confidence: 99%
“…The outputs of this cooperative game are reduced data redundancy in the network and improved network lifetime. A hierarchical distributed source-coding algorithm combined with an optimal data-transmission strategy is presented in [171]. Two-tier network architecture is utilized to implement a hierarchical distributed source coding algorithm.…”
Section: Distributed Source Coding Based Data Compressionmentioning
confidence: 99%
“…A distributed lifting WT compression algorithm was suggested in [171] to achieve an energy-efficient data aggregation solution. Before compressing sensor node readings, the proposed solution employs spatial correlation among sensor nodes to build and organize sensor nodes into clusters.…”
Section: Karhunen-loève Transformmentioning
confidence: 99%