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Trade off Between Accuracy and Message Complexity for Approximate Data Aggregation

  • We consider large scale Peer-to-Peer Sensor Networks, which try to calculate and distribute the mean value of all sensor inputs. For this we design, simulate and evaluate distributed approximation algorithms which reduce the number of messages. The main difference of these algorithms is the underlying communication protocol which all use the random call model, where in discrete round model eachWe consider large scale Peer-to-Peer Sensor Networks, which try to calculate and distribute the mean value of all sensor inputs. For this we design, simulate and evaluate distributed approximation algorithms which reduce the number of messages. The main difference of these algorithms is the underlying communication protocol which all use the random call model, where in discrete round model each node can call a random sensor node with uniform probability.The amount of data exchanged between sensor nodes and used in the calculation process affects the accuracy of the aggregation results leading to a trade-off situation. The key idea of our algorithms is to limit the sample size using the Finite Population Correction (FPC) method and collect the data using a distribution aggregation using Push-Pull Sampling, Pull Sampling, and Push Sampling communication protocols. It turns out that all methods show exponential improvement of Mean Squared Error (MSE) with the number of messages and rounds.show moreshow less

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Metadaten
Document Type:Conference Proceeding
Conference Type:Konferenzartikel
Zitierlink: https://opus.hs-offenburg.de/6647
Bibliografische Angaben
Title (English):Trade off Between Accuracy and Message Complexity for Approximate Data Aggregation
Conference:DCOSS: International Conference on Distributed Computing in Sensor Systems (18. : 30 May 2022-01 June 2022 : Marina del Rey, Los Angeles, CA, USA)
Author:Saptadi NugrohoStaff MemberORCiD, Alexander Weinmann, Christian Schindelhauer
Year of Publication:2022
Publisher:IEEE
First Page:61
Last Page:64
Parent Title (English):Proceedings : 18th Annual International Conference on Distributed Computing in Sensor Systems (DCOSS 2022)
ISBN:978-1-6654-9512-7 (Elektronisch)
ISBN:978-1-6654-9513-4 (Print on Demand)
ISSN:2325-2944 (Elektronisch)
ISSN:2325-2936 (Print on Demand)
DOI:https://doi.org/10.1109/DCOSS54816.2022.00021
URL:https://ieeexplore.ieee.org/document/9881662
Language:English
Inhaltliche Informationen
Institutes:Fakultät Medien (M) (ab 22.04.2021)
Institutes:Bibliografie
Tag:approximation; data aggregation; message complexity; random call model; sensor network
Formale Angaben
Relevance:Konferenzbeitrag: h5-Index < 30
Open Access: Closed 
Licence (German):License LogoUrheberrechtlich geschützt