Recent years have seen the deployments of wireless sensor networks (WSNs) in a variety of applications to gather the information about physical environments. A key requirement of many data-gathering WSNs is to deliver the information about dynamic physical phenomena to users at multiple temporal resolutions. In this paper, we propose a novel solution called theMinimumIncrementalDisseminationTree(MIDT) for dynamic multiresolution data dissemination in WSNs. MIDT includes an online tree construction algorithm with an analytical performance bound and two lightweight tree adaptation heuristics for handling data requests with dynamic temporal resolutions. Our simulations based on realistic settings of Mica2 motes show that MIDT outperforms several typical data dissemination schemes. The two tree adaptation heuristics can effectively maintain desirable energy efficiency of the dissemination tree while reducing the overhead of tree reconfigurations under representative traffic patterns in WSNs.

Recently, several storage-centric wireless sensor networks (WSNs) have been developed to store massive sensor data in the network. A crucial task of these networks is to disseminate useful information to the users at dynamic temporal resolutions. We formulate the problem of dynamic multi-resolution data dissemination in this paper. We propose a novel solution called the Minimum Incremental Dissemination Tree (MIDT) that includes an online tree construction algorithm with analytical performance bound and two lightweight tree adaptation heuristics for handling data requests with dynamic temporal resolutions. Our simulations show that MIDT outperforms several typical data dissemination schemes. The two tree adaptation heuristics can effectively maintain desirable energy efficiency of the dissemination tree while minimizing the tree adaption overhead under representative traffic patterns in WSNs.