Abstract
A common approach to improve the reliability of query results based on error-prone sensors is to introduce redundant sensors. However, using multiple sensors to generate the value for a data item can be expensive, especially in wireless environments where continuous queries are executed. Moreover, some sensors may not be working properly and their readings need to be discarded. In this paper, we propose a statistical approach to decide which sensor nodes to be used to answer a query. In particular, we propose to solve the problem with the aid of continuous probabilistic query (CPQ), which is originally used to manage uncertain data and is associated with a probabilistic guarantee on the query result. Based on the historical data values from the sensor nodes, the query type, and the requirement on the query, we present methods to select an appropriate set of sensors and provide reliable answers for several common aggregate queries. Our statistics-based sensor node selection algorithm is demonstrated in a number of simulation experiments, which shows that a small number of sensor nodes can provide accurate and robust query results.
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References
Cheng R, Kalashnikov D, Prabhakar S (2003) Evaluating probabilistic queries over imprecise data. In: Proc. of the ACM SIGMOD intl conf on management of data
Deshpande A, Guestrin C, Madden SR, Hellerstein JM, Hong W (2004) Model-driven data acquisition in sensor networks. In: Proc. of the 30thVLDB conference, Toronto, Canada
Dubois-Ferriere H, Estrin D (2004) Efficient and practical query scoping in sensor networks. CENS Technical Report #39
Elnahrawy E, Nath B (2003) Cleaning and querying noisy sensors. In: ACM WSNA’03, San Diego, California
Ertin E, Fisher J, Potter L (2003) Maximum mutual information principle for dynamic sensor query problems. In: Proc. IPSN’03, Palo Alto, CA
Kumar V (2003) Sensor: The atomic computing particle. In: SIGMOD Record 32(4)
Krishnamachari B, Iyengar S (2004) Distributed bayesian algorithms for fault-tolerant event region detection in wireless sensor networks. IEEE Trans Comput 53(3):241–250
Lam KY, Cheng R, Liang BY, Chau J (2004) Sensor node selection for execution of continuous probabilistic queries in wireless sensor networks. In: Proc. of ACM 2nd international workshop on video surveillance and sensor networks, New York, USA
Lam KY, Pang HCW (2004) Correct execution of continuous monitoring queries in wireless sensor systems. In: Proc. of the second international workshop on mobile distributed computing (MDC’2004), Tokyo, Japan
Liu J, Reich J, Zhao F (2003) Collaborative in-network processing for target tracking. EURASIP JASP: Spl Issue Sens Netw 2003(4):378–391
Madden S, Franklin MJ, Hellerstein J, Hong W (2002) Tiny aggregate queries in ad-hoc sensor networks. In: Proc. of the 5th symposium on operating systems design and implementation (OSDI), Boston, USA
Niculescu D, Nath B (2004) Error characteristics of ad hoc positioning systems. In: Proc. of the ACM Mobihoc 2004, Tokyo, Japan
Sharaf MA, Beaver J, Labrinidis A, Chrysanthis P (2003) TiNA: A scheme for temporal coherency-aware in-network aggregation. In: Proc. of 2003 international workshop in mobile data engineering
The national institute of standards and technology. Wireless ad hoc networks: smart sensor networks. URL: http://w3.antd.nist.gov/wahn_ssn.shtml
Wang H, Yao K, Pottie G, Estrin D (2004a) Entropy-based sensor selection heuristic for localization. In: Proc. 3rd international workshop on information processing in sensor networks (IPSN’04)
Wang H, Yip L, Yao K, Estrin D (2004b) Lower bounds of localization uncertainty in sensor networks. In: Proc. of IEEE international conference on acoustics, speech
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Song Han received the Bachelor of Science degree in Computer Science from Nanjing University, P.R. China in 2003. He is currently a M.Phil. student and research assistant in the Department of Computer Science at City University of Hong Kong. His research interests are real-time systems and wireless Sensor Networks. He is a student member of the IEEE.
Edward Chan received his BSc and MSc degrees in Electrical Engineering from Stanford University, and his Ph.D. in Computer Science from Sunderland University. He worked in the Silicon Valley for a number of years in the design and implementation of computer networks and real-time control systems before joining City University of Hong Kong where he is now an Associate Professor. His current research interests include performance evaluation of high speed networks, mobile data management, power-aware computing, and wireless sensor networks.
Reynold Cheng is an Assistant Professor of Computing in the Hong Kong Polytechnic University. Dr. Cheng received B.Eng in Computer Engineering in 1998 and M.Phil. in Computer Science in 2000 from the University of Hong Kong. He obtained his M.Sc. and Ph.D. degrees in Computer Science from Purdue University in 2003 and 2005, respectively. His main research area is database systems. He is currently working on uncertainty management efficient query execution of location databases and data streams, privacy and data mining. He has served as a program committee member in a number of intenrational journals and conferences. Dr. Cheng is a regular member of the IEEE, ACM and ACM SIGMOD.
Kam-Yiu Lam received the B.Sc. (Hons) degree on Computer Studies with distinction and Ph.D. degree from the City University of Hong Kong in 1990 and 1994, respectively. He is currently an Associate Professor in the Department of Computer Science, City University of Hong Kong. His current research interests are real-time database systems, real-time active database systems, mobile computing and distributed multimedia systems.
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Han, S., Chan, E., Cheng, R. et al. A statistics-based sensor selection scheme for continuous probabilistic queries in sensor networks. Real-Time Syst 35, 33–58 (2007). https://doi.org/10.1007/s11241-006-9000-3
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DOI: https://doi.org/10.1007/s11241-006-9000-3