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Sampling-based approximate skyline query in sensor equipped IoT networks

Ji Li, Akshita Maradapu Vera Venkata Sai, Xiuzhen Cheng, Wei Cheng, Zhi Tian, Yingshu Li

2020Tsinghua Science & Technology18 citationsDOIOpen Access PDF

Abstract

The ever increasing requirements of data sensing applications result in the usage of IoT networks. These networks are often used for efficient data transfer. Wireless sensors are incorporated in the IoT networks to reduce the deployment and maintenance costs. Designing an energy efficient data aggregation method for sensor equipped IoT to process skyline query, is one of the most critical problems. In this paper, we propose two approximation algorithms to process the skyline query in wireless sensor networks. These two algorithms are uniform sampling based approximate skyline query and Bernoulli sampling-based approximate skyline query. Solid theoretical proofs are provided to confirm that the proposed algorithms can yield the required query results. Experiments conducted on actual datasets show that the two proposed algorithms have high performance in terms of energy consumption compared to the simple distributed algorithm.

Topics & Concepts

SkylineComputer scienceWireless sensor networkProcess (computing)Data miningSampling (signal processing)Mathematical proofSoftware deploymentDistributed computingComputer networkDetectorMathematicsOperating systemTelecommunicationsGeometryData Management and AlgorithmsEnergy Efficient Wireless Sensor NetworksWater Quality Monitoring Technologies
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