Joint routing and scheduling for data collection with compressive sensing to achieve order-optimal latency

We consider a joint routing and scheduling scheme for data collection in wireless sensor networks leveraging compressive sensing under the protocol interference model. We propose the construction of a connected dominating set as a network backbone for efficient routing. A hybrid compressive sensing...

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Main Authors: Xiaohan Yu, Seung Jun Baek
Format: Article
Language:English
Published: SAGE Publishing 2017-10-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1177/1550147717737968
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spelling doaj-772a7c04e3784ddbb50db08264244ffa2020-11-25T03:46:27ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772017-10-011310.1177/1550147717737968Joint routing and scheduling for data collection with compressive sensing to achieve order-optimal latencyXiaohan Yu0Seung Jun Baek1Zhejiang Gongshang University, Hangzhou, ChinaKorea University, Seoul, KoreaWe consider a joint routing and scheduling scheme for data collection in wireless sensor networks leveraging compressive sensing under the protocol interference model. We propose the construction of a connected dominating set as a network backbone for efficient routing. A hybrid compressive sensing technique, which combines conventional and compressive data gathering schemes, is used to aggregate data over the backbone. Pipelined scheduling is developed for fast aggregation of compressed data over the backbone. We set the communication range of sensor nodes to an appropriate value to control the size of the backbone and demonstrate that the proposed scheme can achieve order-optimal latency for data gathering. We extend the proposed scheme to the physical interference model and show that comparable latency is achievable under physical interference model. In addition, the proposed scheme is shown to be energy-efficient, in that it can achieve order-optimal energy consumption given that the sensor data sparsity is of constant order. Simulation results show the effectiveness of the proposed scheme in terms of latency and energy consumption.https://doi.org/10.1177/1550147717737968
collection DOAJ
language English
format Article
sources DOAJ
author Xiaohan Yu
Seung Jun Baek
spellingShingle Xiaohan Yu
Seung Jun Baek
Joint routing and scheduling for data collection with compressive sensing to achieve order-optimal latency
International Journal of Distributed Sensor Networks
author_facet Xiaohan Yu
Seung Jun Baek
author_sort Xiaohan Yu
title Joint routing and scheduling for data collection with compressive sensing to achieve order-optimal latency
title_short Joint routing and scheduling for data collection with compressive sensing to achieve order-optimal latency
title_full Joint routing and scheduling for data collection with compressive sensing to achieve order-optimal latency
title_fullStr Joint routing and scheduling for data collection with compressive sensing to achieve order-optimal latency
title_full_unstemmed Joint routing and scheduling for data collection with compressive sensing to achieve order-optimal latency
title_sort joint routing and scheduling for data collection with compressive sensing to achieve order-optimal latency
publisher SAGE Publishing
series International Journal of Distributed Sensor Networks
issn 1550-1477
publishDate 2017-10-01
description We consider a joint routing and scheduling scheme for data collection in wireless sensor networks leveraging compressive sensing under the protocol interference model. We propose the construction of a connected dominating set as a network backbone for efficient routing. A hybrid compressive sensing technique, which combines conventional and compressive data gathering schemes, is used to aggregate data over the backbone. Pipelined scheduling is developed for fast aggregation of compressed data over the backbone. We set the communication range of sensor nodes to an appropriate value to control the size of the backbone and demonstrate that the proposed scheme can achieve order-optimal latency for data gathering. We extend the proposed scheme to the physical interference model and show that comparable latency is achievable under physical interference model. In addition, the proposed scheme is shown to be energy-efficient, in that it can achieve order-optimal energy consumption given that the sensor data sparsity is of constant order. Simulation results show the effectiveness of the proposed scheme in terms of latency and energy consumption.
url https://doi.org/10.1177/1550147717737968
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AT seungjunbaek jointroutingandschedulingfordatacollectionwithcompressivesensingtoachieveorderoptimallatency
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