Effective Low-Latency K-Nearest Neighbor Search Via Wireless Data Broadcast

Park, Kwangjin; Song, Mei; Kong, Ki-Sik; Kang, Shin-Gak; Hwang, Chong-Sun; Chung, Kwang-Sik; Jung, Soonyoung

doi:10.1007/11733836_67

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…In VST, the client uses exponential pointers from each data item for the purpose of reducing energy consumption. In [13][14], we proposed a generic framework for continuous range queries and k-NN queries via wireless data broadcast. The basic idea is to provide selective tuning with the minimal access time and tuning time for continuous range queries and k-NN queries on the air.…”

Section: Introductionmentioning

confidence: 99%

Location-Based Data Dissemination for Spatial Queries in Wireless Broadcast Environments

Park

Choo

2010

J. Comput. Sci. Technol.

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Most current research on Location-Based Services (LBSs, for short) assumes point-to-point wireless communication, where the server processes a query and returns the query result to the user via a point-to-point wireless channel. However, LBSs via point-to-point wireless channel suffer from a tremendous amount of traffic and service requests from the user and thereby result in poor performance. In this paper, we present broadcast-based spatial query processing algorithms designed to support k-NN (k-Nearest Neighbor) and range queries via a wireless network. The task of the query processor is to selectively monitor the wireless broadcast channel, when the data items are disseminated by the server, according to their locations. Experiments are conducted to evaluate the performance of the proposed algorithms. Comprehensive experiments illustrate that the presented algorithms are highly scalable and are more efficient than the previous techniques in terms of both access time and energy consumption.

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Section: Introductionmentioning

confidence: 99%

Location-Based Data Dissemination for Spatial Queries in Wireless Broadcast Environments

Park

Choo

2010

J. Comput. Sci. Technol.

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Spatial air index with neighbor information for processing k-nearest neighbor searches in IoT mobile computing

Shen

et al. 2019

J Supercomput

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Energy Efficient Data Access in Mobile P2P Networks

Park

Valduriez

2011

IEEE Trans. Knowl. Data Eng.

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A fundamental problem for peer-to-peer (P2P) applications in mobile-pervasive computing environment is to efficiently identify the node that stores particular data items and download them while preserving battery power. In this paper, we propose a P2P Minimum Boundary Rectangle (PMBR, for short) which is a new spatial index specifically designed for mobile P2P environments. A node that contains desirable data item (s) can be easily identified by reading the PMBR index. Then, we propose a selective tuning algorithm, called Distributed exponential Sequence Scheme (DSS, for short), that provides clients with the ability of selective tuning of data items, thus preserving the scarce power resource. The proposed algorithm is simple but efficient in supporting linear transmission of spatial data and processing of location-aware queries. The results from theoretical analysis and experiments show that the proposed algorithm with the PMBR index is scalable and energy efficient in both range queries and nearest neighbor queries.

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Effective Low-Latency K-Nearest Neighbor Search Via Wireless Data Broadcast

Cited by 3 publications

References 12 publications

Location-Based Data Dissemination for Spatial Queries in Wireless Broadcast Environments

Location-Based Data Dissemination for Spatial Queries in Wireless Broadcast Environments

Spatial air index with neighbor information for processing k-nearest neighbor searches in IoT mobile computing

Energy Efficient Data Access in Mobile P2P Networks

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