Processing Multiple Aggregation Queries in Geo-Sensor Networks Ken C.K. Lee 1 , Wang-Chien Lee 1 , Baihua Zheng 2 , and Julian Winter 1 1 Pennsylvania State University, USA {cklee, wlee, jwinter}@cse.psu.edu 2 Singapore Management University, Singapore bhzheng@smu.edu.sg Abstract. To process aggregation queries issued through different sen- sors as access points in sensor networks, existing algorithms handle queries independently and perform in-network aggregation only at the query time. As a result of ad-hoc and independent execution of queries, no partial result is sharable and reusable among the queries. Conse- quently, scarce sensor network resources can be easily overconsumed, particularly, those sensors commonly accessed by queries. In this paper, we address this issue by examining strategies to maintain Materialized In-Network Views (MINVs) that pre-compute and store commonly used aggregation results in the sensor network. With MINVs, aggregated sensed results for some spatial regions are available and sharable to queries. Thus, the number of sensor accesses is greatly reduced. Through simulations, we validate the effectiveness of proposed strategies. 1 Introduction Sensor network applications are often interested in the sensed data in ceratin geographical regions (typically in form of spatial windows) rather than on some specific sensors. Examples of such applications include pollution monitoring and city road traffic control. Through sensor networks, those environmental data (i.e., pollution and traffic) are tracked and made available for querying. Due to the expensive energy cost of communication in wireless sensor networks, a summary of readings (i.e., aggregated readings) is preferred over a collection of all individual sensor readings. This kind of queries that collect aggregated readings from sensors within a geographical area is called spatial aggregation query. In such queries, aggregate functions such as sum, count, average, max and min are frequently used. Example queries include: “What is the average pollution index value in the 10-meter space surrounding me?” and “How many available parking slots in the car park?”. In-network aggregation has been studied in sensor database projects (for ex- ample, Cougar [1] and TinyDB [2]). These works focus on the construction and optimization of a routing tree, an ad-hoc network topology over which query results are aggregated and routed toward the root where the result is collected. However, the design of these works focuses only on a single query. For a large- scale sensor network, multiple queries may be issued from different locations with M.L. Lee, K.L. Tan, and V. Wuwongse (Eds.): DASFAA 2006, LNCS 3882, pp. 20–34, 2006. c  Springer-Verlag Berlin Heidelberg 2006