Energy-efficient shortest path query processing on air

Jing, Yinan; Chen, Chunan; Sun, Wei; Zheng, Baihua; Liu, Liang; Tu, Chuanchuan

doi:10.1145/2093973.2094031

Cited by 10 publications

(6 citation statements)

References 13 publications

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“…Most of the existing broadcast-based LBQ methods are aimed at Euclidean spaces and cannot be readily extended to road networks. Recently, many researchers have presented several methods to process spatial queries in road networks [2,[16][17][18][19][20][21][22][23][24]. Sun et al [2] present an air index called Network Partition Index (NPI) to support efficient spatial query processing in road networks via wireless broadcast.…”

Section: Index For Spatial Queries In Road Networkmentioning

confidence: 99%

DIM: a distributed air index based on MapReduce for spatial query processing in road networks

Jin

Chen

Tung

et al. 2018

J Wireless Com Network

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In this era of mobile application and socialization, location-based services (LBSs) have become unprecedentedly popular and emphasized. By submitting its location to the service provider, the mobile terminal can obtain useful service. As an important technology that can provide location-based services, spatial query processing has become a research hotspot. According to the problems existing in current road network partitioning, first of all, this paper proposes the partition density formula and the optimal road network partitioning method according to the partition density. Based on that, we propose the concepts of partition self-attraction, mutual attraction, and merger factor of partition to effectively merge the partitions with low densities, which can further reduce the number of unnecessary broadcast frames and optimize the index method. Then, we propose the real distributed air index method DIM and kNN spatial query processing algorithm based on the MapReduce platform. According to the DIM index method, the Name Node only stores the prime index, while not storing the data, and each frame consists of defined index and the data in a partition that need to be broadcasted. The mobile user can quickly localize the frame data that they need to obtain according to the main index or the index of current frame, in this way to reduce the tuning time and access latency, which can significantly optimize the query efficiency. Massive experiments have proved the stability and effectiveness of the proposed algorithm.

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Section: Index For Spatial Queries In Road Networkmentioning

confidence: 99%

DIM: a distributed air index based on MapReduce for spatial query processing in road networks

Jin

Chen

Tung

et al. 2018

J Wireless Com Network

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“…An energy-efficient air index, namely BagIndex, has also been proposed to support shortest path queries. Both [8] and [9] only support shortest path queries but not common spatial queries such as range query and kNN query. A more general index that can support multiple spatial queries is desired.…”

Section: Fig 2 Partitioning a Road Network Into 2×2 Gridsmentioning

confidence: 99%

“…Like many other existing works [4], [8], [9], we assume the clients are located at network nodes to simplify our discussion. However, our algorithms can be easily extended to support cases where clients' locations are located along the network edges.…”

Section: Client-site Query Processingmentioning

confidence: 99%

“…However, in most of real life applications, the objects' movement is constrained by road networks. Recently, [8], [9] propose air indexes to support shortest path queries in wireless broadcast environments. However, the issue of supporting spatial queries (e.g., range queries and kNN queries) on road networks via broadcasting • We propose a novel air index namely NPI to broadcast road network data to mobile clients to support spatial query processing at client side.…”

Section: Introductionmentioning

confidence: 99%

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An Air Index for Spatial Query Processing in Road Networks

Sun

Chen

Zheng

et al. 2015

IEEE Trans. Knowl. Data Eng.

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Spatial queries such as range query and kNN query in road networks have received a growing number of attention in real life. Considering the large population of the users and the high overhead of network distance computation, it is extremely important to guarantee the efficiency and scalability of query processing. Motivated by the scalable and secure properties of wireless broadcast model, this paper presents an air index called Network Partition Index (NPI) to support efficient spatial query processing in road networks via wireless broadcast. The main idea is to partition the road network into a number of regions and then to build an index to carry some pre-computation information of each region. We also propose multiple clientside algorithms to facilitate the processing of different spatial queries such as kNN query, range query and CNN query. A comprehensive experimental study has been conducted to demonstrate the efficiency of our scheme.Index Terms-wireless data broadcast, kNN query, air indexing, road network.

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“…Jing et al [5] propose the BagIndex for shortest path queries (and hence distance queries as well). Their method is based on a tree decomposition.…”

Section: Previous and Related Workmentioning

confidence: 99%

Energy-efficient air-indices for distance queries on road networks

Poon

Zhu

2012

Proceedings of the 20th International Conference on Advances in Geographic Information Systems

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We study the problem of distance queries on a road network under the wireless data broadcast environment. By exploiting special properties of road networks, we design an air-index (indexing scheme on the wireless broadcast model) called the CH Index. Experimental evaluation shows that our CH Index is more energy efficient than previous indices by an order of magnitude. We also extend the CH Index to the CHBN Index which provides a tradeoff between energy efficiency and response time via a user-tunable parameter. It has faster response time than CH while being more energyefficient than previous methods.

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Energy-efficient shortest path query processing on air

Cited by 10 publications

References 13 publications

DIM: a distributed air index based on MapReduce for spatial query processing in road networks

DIM: a distributed air index based on MapReduce for spatial query processing in road networks

An Air Index for Spatial Query Processing in Road Networks

Energy-efficient air-indices for distance queries on road networks

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