Gathering data in an energy efficient manner in wireless sensor networks isan important design challenge. In wireless sensor networks, the readings ofsensors always exhibit intra-temporal and inter-spatial correlations.Therefore, in this letter, we use low rank matrix completion theory to explorethe inter-spatial correlation and use compressive sensing theory to takeadvantage of intra-temporal correlation. Our method, dubbed MCCS, cansignificantly reduce the amount of data that each sensor must send throughnetwork and to the sink, thus prolong the lifetime of the whole networks.Experiments using real datasets demonstrate the feasibility and efficacy of ourMCCS method.
展开▼
