Approximate Aggregation for Tracking Quantiles in Wireless Sensor Networks

He, Zaobo; Cai, Zhipeng; Cheng, Siyao; Wang, Xiaoming

doi:10.1007/978-3-319-12691-3_13

Cited by 20 publications

(10 citation statements)

References 24 publications

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“…First, C is initialized to be empty, and target expression q is inserted into the queue (lines 1-2). Then, following operations are executed until FQueue becomes empty (lines [3][4][5][6][7][8][9][10][11][12] all possible relaxing operations (lines 5-11). The relaxations having no effects are ignored (lines 8-9).…”

Section: Naive Algorithmmentioning

confidence: 99%

Extracting entity-based information in cyber-physical systems

Yang

Yin

2017

International Journal of Distributed Sensor Networks

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This article proposes a framework P3E for evaluating entity extraction problem over cyber-physical system data. As known by us, this article is the first work focusing on this problem, which is an important step for identifying entities in cyber-physical system data. Directed by the initial entities, utilizing the relaxation and verification techniques, P3E provides a path expression-based solution for entity extraction problem, which has following characteristics. First, using path expressions, P3E provides a condensed presentation for entity locations whose size may get very large when scaling up the data size. Second, requiring only one entity example to indicate the interests, using relaxation technique, P3E can discover other similar entities automatically. Third, by adjusting the example given to P3E, users can specify their own interesting entities and control the entities discovered by P3E. Besides, utilizing the idea of sharing computations, by extending previous automaton techniques, an efficient implementation of P3E is provided. Experimental results are reported, which show that P3E can provide an effective and efficient solution to the entity extraction problem.

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Section: Naive Algorithmmentioning

confidence: 99%

Extracting entity-based information in cyber-physical systems

Yang

Yin

2017

International Journal of Distributed Sensor Networks

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“…Under such assumptions, a great number of query processing techniques on discrete sensory data have been proposed, including the curve query processing algorithms [13], aggregation query processing algorithms [14][15][16][17], top-k query processing algorithms [18][19][20], skyline [21,22], and quantilen [23,24] query processing algorithms. Although all the above algorithms are efficient for processing the discrete sensory data, they cannot meet the complicated query requirements given by users and do not support to retrieve the critical data points in current WSNs since only discrete data were considered.…”

Section: Introductionmentioning

confidence: 99%

Critical data points retrieving method for big sensory data in wireless sensor networks

Zhu

Cheng

Cai

et al. 2016

J Wireless Com Network

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With the development and widespread application of wireless sensor networks (WSNs), the amount of sensory data grows sharply and the volumes of some sensory data sets are larger than terabytes, petabytes, or exabytes, which have already exceeded the processing abilities of current WSNs. However, such big sensory data are not necessary for most applications of WSNs, and only a small subset containing critical data points may be enough for analysis, where the critical data points including the extremum and inflection data points of the monitored physical world during given period. Therefore, it is an efficient way to reduce the amount of the big sensory data set by only retrieving the critical data points during sensory data acquisition process. Since most of the traditional sensory data acquisition algorithms were only designed for discrete data and did not support to retrieve critical points from a continuously varying physical world, this paper will study such a problem. In order to solve it, we firstly provided the formal definition of the δ-approximate critical points. Then, a data acquisition algorithm based on numerical analysis and Lagrange interpolation is proposed to acquire the critical points. The extensive theoretical analysis and simulation results are provided, which show that the proposed algorithm can achieve high accuracy for retrieving the δ-approximate critical points from the monitored physical world.

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“…In recent years, wireless sensor networks (WSNs) have been used in monitoring and retrieving sensory data from the physical world [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 ], which are usually expected to last over several months or years. Therefore, it is very necessary to design an energy conservation mechanism for WSNs to extend the network lifetime [ 12 , 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Algorithm for Multicasting in Duty-Cycled Sensor Networks

Chen

Cheng

Gao

et al. 2015

Sensors

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Multicasting is a fundamental network service for one-to-many communications in wireless sensor networks. However, when the sensor nodes work in an asynchronous duty-cycled way, the sender may need to transmit the same message several times to one group of its neighboring nodes, which complicates the minimum energy multicasting problem. Thus, in this paper, we study the problem of minimum energy multicasting with adjusted power (the MEMAP problem) in the duty-cycled sensor networks, and we prove it to be NP-hard. To solve such a problem, the concept of an auxiliary graph is proposed to integrate the scheduling problem of the transmitting power and transmitting time slot and the constructing problem of the minimum multicast tree in MEMAP, and a greedy algorithm is proposed to construct such a graph. Based on the proposed auxiliary graph, an approximate scheduling and constructing algorithm with an approximation ratio of 4lnK is proposed, where K is the number of destination nodes. Finally, the theoretical analysis and experimental results verify the efficiency of the proposed algorithm in terms of the energy cost and transmission redundancy.

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Approximate Aggregation for Tracking Quantiles in Wireless Sensor Networks

Cited by 20 publications

References 24 publications

Extracting entity-based information in cyber-physical systems

Extracting entity-based information in cyber-physical systems

Critical data points retrieving method for big sensory data in wireless sensor networks

Energy-Efficient Algorithm for Multicasting in Duty-Cycled Sensor Networks

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