Continuous answering-holistic-queries-over sensor networks
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This document discusses the challenges and solutions for continuous holistic queries in sensor networks, particularly focusing on median calculations as opposed to average. It proposes a hybrid approach that utilizes correlation between data and adapts to changing data speeds, offering both exact and approximate results while reducing traffic costs. Additionally, it outlines the hardware and software requirements for implementing the proposed system.
Continuous answering-holistic-queries-over sensor networks
- 1. #13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, Vellore – 6. Off: 0416-2247353 / 6066663 Mo: +91 9500218218 Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com CONTINUOUS ANSWERING HOLISTIC QUERIES OVER SENSOR NETWORKS ABSTRACT: Sensor networks are widely used in various domains like the intelligent transportation systems. Users issue queries to sensors and collect sensing data. Due to the low quality sensing devices or random link failures, sensor data are often noisy. In order to increase the reliability of the query results, continuous queries are often employed. In this work we focus on continuous holistic queries like Median. Existing approaches are mainly designed for non-holistic queries like Average. However, it is not trivial to answer holistic ones due to their non-decomposable property. We first propose two schemes based on the data correlation between different rounds, with one for getting the exact answers and the other one for deriving the approximate results. We then combine the two proposed schemes into a hybrid approach, which is adaptive to the data changing speed. We evaluate this design through extensive simulations. The results show that our approach significantly reduces the traffic cost compared with previous works while maintaining the same accuracy. EXISTING SYSTEM: L-PEDAPs focused on routing tree construction and maintenance for query processing. Uncertainties may exist in both sensing data and queries. For example, Zhang et al. studied the problem of calculating the aggregate while the query location is uncertain. Ye et al. proposed to determine possible query results among all imprecise sensing data. Yu et al. presented a method which aiming at secure continuous aggregation querying. DISADVANTAGES OF EXISTING SYSTEM: It makes more sense to get a median result of the monitoring area than to derive an average result, since the noise may affect the average result largely Due to the limitation of message size, the merging process may lose some information.
- 2. #13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, Vellore – 6. Off: 0416-2247353 / 6066663 Mo: +91 9500218218 Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com Generally, these methods can only achieve approximate results with some error guarantee by introducing different restricts and pruning algorithms on the data structure PROPOSED SYSTEM: In this paper, we explore the correlation between data of different rounds and present two approaches to monitor continuous holistic queries, one for getting the exact answers and the other one for deriving the approximate results. Then, we propose an effective hybrid approach that adaptively selects appropriate one based on data changing speed and improves the performance of continuous queries. We propose a hybrid approach, combining F-Bucket and wavelet-like approaches, to handle the continuous holistic queries. If the sensor values in network are relatively stable, we apply an exact algorithm to calculate the exact median. When the data changes quickly, our approach can adaptively switch to the approximate algorithm. We propose a histogram-based approach to get exact answers for continuous queries. Specifically, we use the histogram summary structure to store the value distribution of the network. Each bucket in the histogram counts the number of values in a certain range. We propose two algorithms for refining the range assignment, Slip refining and Hierarchical refining. ADVANTAGES OF PROPOSED SYSTEM: This merging process reduces transmissions at the cost of losing some information. Finally, the sink aggregates all received AF-Buckets to an integrated one and calculates the query results. We propose an effective hybrid approach that adaptively selects appropriate one based on data changing speed and improves the performance of continuous queries
- 3. #13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, Vellore – 6. Off: 0416-2247353 / 6066663 Mo: +91 9500218218 Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com We propose a histogram-based approach to get exact answers for continuous queries. Specifically, we use the histogram summary structure to store the value distribution of the network. The metric number of transmissions to evaluate the traffic cost of all these approaches which is defined as the total size of transmitted data packets in one round. SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS: System : Pentium Dual Core. Hard Disk : 120 GB. Monitor : 15’’ LED Input Devices : Keyboard, Mouse Ram : 1GB. SOFTWARE REQUIREMENTS: Operating system : Windows 7. Coding Language : JAVA/J2EE Tool : Netbeans 7.2.1 Database : MYSQL