An autonomic in network query processing for urban sensor networks
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AQPM is an autonomous and scalable in-network query processing model for urban sensor networks. It groups sensors with similar readings into clusters to improve scalability. Sensors within each cluster store their readings locally. Select sensors within each cluster are designated as repositories, which store readings for an entire cluster. This allows queries to be processed efficiently by only contacting the repository sensors instead of all sensors. Experimental results using an NS2 simulator show that AQPM is more effective than existing approaches for managing and querying data from large-scale sensor networks.
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みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
An autonomic in network query processing for urban sensor networks
- 1. 2020 – 2021 #13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, Vellore – 6. Off: 0416-2247353 Mo: +91 9500218218 / +91 8220150373 Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com An Autonomic in-Network Query Processing for Urban Sensor Networks Abstract The sensing ofurban environments usuallytakes into accountthe deploymentofa large number ofdevices to measure their environmental attributes,such as temperature,pressure,humidity,luminosityand pollution.In such applications, nearby sensors usually produce similar readings due to their spatial and temporal correlation. In the era of big data, managementofcollected data requires autonomous and scalable Wireless Sensor Network (WSN) structures.In this paper, we propose an in-network data storage model,called AQPM, that provides efficient processing ofboth spatial and value-based queries.AQPM is autonomous and scalable.Thatis, it does not rely on any central entity for neither managing data storage on sensor devices nor for processing queries.Scalabilityis achieved by grouping sensors with similar readings into clusters, while efficient query processing relies on the concept of repositories. Repositories are sensors thatstore readings ofa setof clusters,and are the only ones thathave to be contacted for answering queries. AQPM has been implemented on NS2 simulator and experimental results show that it is more effective than existing approaches.