240 likes | 351 Views
Query Aggregation for Providing Efficient Data Services in Sensor Networks. Wei Yu * , Thang Nam Le + , Dong Xuan + and Wei Zhao * * Computer Science Department Texas A&M University + Department of Computer Science and Engineering The Ohio State University
E N D
Query Aggregation for Providing Efficient Data Services in Sensor Networks Wei Yu*, Thang Nam Le+, Dong Xuan+ and Wei Zhao* *Computer Science Department Texas A&M University +Department of Computer Science and Engineering The Ohio State University IEEE Mobile Ad-hoc and Sensor Systems (MASS), 2004 Shin_wei Ho
Outline • Introduction • Query Aggregation-Based Data Service Frameworks • Weighted Zone-based Query Aggregation Algorithm • Performance Evaluation • Conclusion
Introduction • The wireless sensor networks are required to provide efficient data services as a distributed database. • The application can submit its requests as queries.
Introduction (cont’d) • Sensor networks are deployed for monitoring the environment consisting of • Temperature sensors • Humidity sensors • Wind sensors • Such networks typically need to support a large number of users.
Introduction (cont’d) • There are salient features that all of the above application share: • query rate can be high • the energy consumption spent on sending and routing queries may far exceed • For these class of applications, optimizing query dissemination is critical to improve performance of the sensor network.
Introduction (cont’d) • In the traditional query dissemination model, applications forward queries to the base station of the sensor networks. • processes the queries one by one • This simple approach suffers from shortcomings: • Applications may pose duplicate queries • Overlapping queries
Query Aggregation-Based Data Service Frameworks • Two major problems • aggregating the queries • routing queries efficiently to proper regions • We discuss three frameworks to solve these problems: • Purely Sensor Network-based Framework (PSNF) • Purely Base Station-Oriented Framework (PBSOF) • Integrated Query Aggregation Framework (IQAF)
Query Query Query Query Aggregation-Based Data Service Frameworks-- Purely sensor network-based framework (PSNF) send the same data multiple times to reply for different queries Without conducting query aggregation decision Base Station
Query Query Query Query Query New Query Query Aggregation-Based Data Service Frameworks-- Purely base station-oriented framework (PBSOF) makes the query aggregation decision based on the input query information. Base Station
Query Aggregation-Based Data Service Frameworks-- Integrated query aggregation framework (IQAF) • We consider the fact • base station has a global picture of all input queries • sensor network can take certain roles to execute the aggregated query plan • Thus, a number of sensor nodes as access nodes are selected as the query proxy.
Query Aggregation-Based Data Service Frameworks-- Integrated query aggregation framework (IQAF) (cont’d)
Weighted Zone-based Query Aggregation Algorithm-- Problem Definition
Weighted Zone-based Query Aggregation Algorithm Process the input queries in set Q by filtering queries with full cover property. Q4(v4) Q1(v1) Q6 Q3(v3) Q5(v5) Q2(v2) Q: Input query V: Attribute information : Query region
Weighted Zone-based Query Aggregation Algorithm (cont’d) Calculate the overlapping zone and assign the weight Q4(v4) Q1(v1) Q3(v3) O3 O4 Q5(v5) O5 Q2(v2) O1 O2 Q: Input query V: Attribute information : Query region
Weighted Zone-based Query Aggregation Algorithm (cont’d) Consolidate overlapping zones in O Q4(v4) Q1(v1) Q3(v3) O3 O1 O4 Q5(v5) O5 Q2(v2) O1 O2 Q: Input query V: Attribute information : Query region
Weighted Zone-based Query Aggregation Algorithm (cont’d) Sort the weights and assign queries to corresponding zone Q4(v4) Q1(v1) Q3(v3) O3 O1 O4 Q5(v5) O5 Q2(v2) O1 O2 Q: Input query V: Attribute information : Query region
Weighted Zone-based Query Aggregation Algorithm (cont’d) New aggregated queries Query 1:{Q1, Q2, Q3} Query 2:{Q4 ,Q5} Q4(v4) Q1(v1) Q6 Q3(v3) O3 O1 O4 Q5(v5) O5 Calculate the access point Q2(v2) O1 O2 Q: Input query V: Attribute information : access point : Query region
Performance Evaluation-- Experimental Model • A grid-topology network • 1500m x 1500m • Grid size is 5m x 5m • N queries, each of which is m-bit long • Each query uniformly request the data from area of S (=200). • Query messages are combined with compression ratio(0.7).
Performance Evaluation-- Experimental Model (cont’d) • The energy consumption of sending message is calculated by • The energy consumption of receiving a message is calculated by
Conclusion • Query Aggregation • A multi-layer overlay-based framework for efficient sensor data service • can support other routing protocols • An effective query aggregation mechanism • do not consider the existing topology and distribution of sensors • query buffer