Name
Abstract | ||
|---|---|---|
Sensor networks can be viewed as large distributed databases, and SQL-like high-level declarative languages can be used for data and information retrieval. Energy constraints make optimizing query processing particularly important. This paper addresses for the first time, multi-root, multi-query optimization for long duration aggregation queries. The paper formulates three algorithms - naive algorithm (NMQ), which does not exploit any query result sharing, and two proposed new algorithms: an optimal algorithm (OMQ) and a heuristic (zone-based) algorithm (ZMQ). The heuristic algorithm is based on sharing the partially aggregated results of pre-configured geographic regions and exploits the novel idea of applying a grouping technique by using the location attribute of sensor nodes as the grouping criterion. Extensive simulations indicate that the proposed algorithms provide significant energy savings under a wide range of sensor network deployments and query region options. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-69170-9_29 | DCOSS |
Keywords | Field | DocType |
naive algorithm,sensor networks,optimal algorithm,query region option,multi-query processing,sensor network,query result sharing,heuristic algorithm,proposed new algorithm,query processing,proposed algorithm,long duration aggregation query,query optimization,distributed database,information retrieval | Sensor node,Query optimization,Data mining,Heuristic,Query expansion,Heuristic (computer science),Computer science,Brooks–Iyengar algorithm,Distributed database,Wireless sensor network,Distributed computing | Conference |
Volume | ISSN | Citations |
5067 | 0302-9743 | 1 |
PageRank | References | Authors |
0.38 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhiguo Zhang | 1 | 1 | 0.38 |
| Ajay Kshemkalyani | 2 | 142 | 13.04 |
| Sol M. Shatz | 3 | 469 | 55.25 |