Distributed Multi-Representative Re-Fusion Approach for Heterogeneous Sensing Data Collection-Reference-Cited by-同舟云学术

Distributed Multi-Representative Re-Fusion Approach for Heterogeneous Sensing Data Collection

Published:2017-07-07 Issue:3 Volume:16 Page:1-25
ISSN:1539-9087
Container-title:ACM Transactions on Embedded Computing Systems
language:en
Short-container-title:ACM Trans. Embed. Comput. Syst.

Author:

Liu Anfeng¹,Liu Xiao¹,Wei Tianyi¹,Yang Laurence T.²,Rho Seungmin (Charlie)³,Paul Anand⁴

Affiliation:

1. Central South University, ChangSha, China

2. St. Francis Xavier University, Antigonish, NS, Canada

3. Sungkyul University, Anyang-si, Korea

4. Kyungpook National University, Korea

Abstract

A multi-representative re-fusion (MRRF) approximate data collection approach is proposed in which multiple nodes with similar readings form a data coverage set (DCS). The reading value of the DCS is represented by an R-node. The set near the Sink is smaller, while the set far from the Sink is larger, which can reduce the energy consumption in hotspot areas. Then, a distributed data-aggregation strategy is proposed that can re-fuse the value of R-nodes that are far from each other but have similar readings. Both comprehensive theoretical and experimental results indicate that the MRRF approach increases lifetime and energy efficiency.

Funder

The National Basic Research Program of China

National Natural Science Foundation of China

GDUPS

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Software

Link

https://dl.acm.org/doi/pdf/10.1145/2974021

Reference33 articles.

1. Cooperative network-coding system for wireless sensor networks