The week's pick
Random Articles
Reseach Article
Stochastic Heuristic Optimization based Multi-Query Processing in Wireless Sensor Network using Genetic Algorithm
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 97 - Number 5 |
| Year of Publication: 2014 |
| Authors: S. Antony Alice Jeya Bharathi, K. Alagarsamy |
10.5120/17002-7147
|
S. Antony Alice Jeya Bharathi, K. Alagarsamy . Stochastic Heuristic Optimization based Multi-Query Processing in Wireless Sensor Network using Genetic Algorithm. International Journal of Computer Applications. 97, 5 ( July 2014), 9-15. DOI=10.5120/17002-7147
Abstract
Wireless Sensor Network is an infrastructure comprising of sensing, and computing. The communication elements in sensor network give capability to instrument, watch, and respond to events and phenomenon in a particular situation. Query processing in sensor network first transfers the query generated position to the node where the result obtained is similar to this query. Collaborative Query-Centric Framework (COSE) heterogeneous sensor networks are effectual and well-organized for processing of queries. Query processing with respect to energy efficiency attain single pipeline of query processing but fails to address the issues related to multiple pipeline of query processing. COSE major drawback is that it is unable to attain an optimal solution for multiple pipelines. Next, Pocket Driven Trajectories (PDT) algorithm monitors the query processing based on spatial layout of the selected nodes. PDT algorithm efficiently adapts to different types of data collection paths but not effective for multicast query phase. To develop a multiple query processing strategy in wireless sensor network, Stochastic Heuristic Optimization using Genetic Algorithm (SHO-GA) is introduced. The SHO-GA framework process the multiple query plans based on the closeness of nodes required to answer the user query. The multi-query processing using Genetic Algorithm (GA) takes the associations with FROM clause and other multiple query operators. The SHO-GA framework carries the probability of crossover, mutation and the pre-specified number of generations as input, and produces the top 'n' multi-query processing as output. The stochastic heuristic optimization fitness value provides the best fit chromosome to find the improvement in its query processing parameters. The stochastic heuristic for multi-query called base station optimization (BSO) eliminates the redundancy from the original set. The multi-query plans processed involve minimum processing time for answering the user query leading to efficient query processing sensor network system. Experimental evaluation is performed on factors such as average processing cost, cumulative distribution, multi-query processing time, query answer transmitted speed, query processing delay and user accessibility level.
References
- Yue-Hsun Lin. , Shih-Ying Chang. , and Hung-Min Sun. , "CDAMA: Concealed Data Aggregation Scheme for Multiple Applications in WSNs," IEEE TRANSMOVEMENTS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 25, NO. 7, JULY 2013
- Chi Lin. , Guowei Wu. , Feng Xia, Mingchu Li. , Lin Yao, Zhongyi Pei. , "Energy efficient ant colony algorithms for data aggregation in wireless sensor networks," Journal of Computer and System Sciences. , Elsevier Journal. , 2012
- Suat Ozdemir and Hasan Çam,"Integration of False Data Detection with Data Aggregation and Confidential Transmission in WSNs," IEEE/ACM TRANSMOVEMENTS ON NETWORKING, VOL. 18, NO. 3, JUNE 2010
- Liu Xiang. , Jun Luo. , and Catherine Rosenberg. , "Compressed Data Aggregation: Energy Efficient and High Fidelity Data Collection," IEEESECON, 2011
- Liang He. , Jianping Pan. , and Jingdong Xu. , "A Progressive Approach to Reducing Data Collection Latency in Wireless Sensor Networks with Mobile Elements," IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 12, NO. 7, JULY 2013
- Leandro Aparecido Villas. , Azzedine Boukerche, Heitor Soares Ramos. ,Horacio A. B. Fernandes de Oliveira. , Regina Borges de Araujo. , and Antonio Alfredo Ferreira Lour. , "DRINA: A Lightweight and Reliable Routing Approach for In-Network Aggregation in WSNs," IEEE TRANSACTIONS ON COMPUTERS, VOL. 62, NO. 4, APRIL 2013
- Cunqing Hua. , and Tak-Shing Peter Yum. , Senior Member, IEEE. , "Optimal Routing and Data Aggregation for Maximizing Lifetime of WSNs," IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 16, NO. 4, AUGUST 2008
- Ungjin Jang. , Sunggu Lee. , Sungjoo Yoo. , "Optimal wake-up scheduling of data gathering trees for WSNs," Journal Parallel Distributed Computing, Elsevier Journal. , 2012
- Rui Zhang. ,Yanchao Zhang. , and Kui Ren. , "Distributed Privacy-Preserving Access Control in Sensor Networks," IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 23, NO. 8, AUGUST 2012
- Jiguo Yua. , Yingying Qia. , Guanghui Wangb. , Xin Gua. , "A cluster-based routing protocol for WSNs with non uniform node distribution," International Journal of Electronics and Communications (AEÜ). , 2012
- Selcuk Okdem. , and Dervis Karaboga. , "Routing in WSNs Using an Ant Colony Optimization (ACO) Router Chip," Sensors 2009, 9, 909-921; doi:10. 3390/s90200909
- Yun Wang. , Weihuang Fu. , and Dharma P. Agrawal. , "Gaussian versus Uniform Distribution for Intrusion Detection in Wireless Sensor Networks," IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 24, NO. 2, FEBRUARY 2013.
Index Terms
Keywords