TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Nugroho, Saptadi
A1  - Schindelhauer, Christian
A1  - Christ, Andreas
ED  - González-Briones, Alfonso
ED  - Almeida, Ana
ED  - Fernandez, Alberto
ED  - El Bolock, Alia
ED  - Durães, Dalila
ED  - Jordán, Jaume
ED  - Lopes, Fernando
T1  - Approximate Time-Series Data Aggregation Using Grouping Nodes in Peer to Peer Network
T2  - Highlights in Practical Applications of Agents, Multi-Agent Systems, and Complex Systems Simulation. The PAAMS Collection
N2  - We consider the local group of agents for exchanging the time-series data value and computing the approximation of the mean value of all agents. An agent represented by a node knows all local neighbor nodes in the same group. The node has the contact information of other nodes in other groups. The nodes interact with each other in synchronous rounds to exchange the updated time-series data value using the random call communication model. The amount of data exchanged between agent-based sensors in the local group network affects the accuracy of the aggregation function results. At each time step, the agent-based sensor can update the input data value and send the updated data value to the group head node. The group head node sends the updated data value to all group members in the same group. Grouping nodes in peer-to-peer networks show an improvement in Mean Squared Error (MSE).
KW  - Agent based sensor
KW  - Time series data
KW  - Approximation
KW  - Random call model
KW  - Peer to peer network
Y1  - 2022
UR  - https://link.springer.com/chapter/10.1007/978-3-031-18697-4_25
SN  - 978-3-031-18697-4 (eBook)
SS  - 978-3-031-18697-4 (eBook)
SN  - 1865-0929 (Print)
SS  - 1865-0929 (Print)
SN  - 1865-0937 (eBook)
SS  - 1865-0937 (eBook)
SN  - 978-3-031-18696-7 (Print)
SB  - 978-3-031-18696-7 (Print)
U6  - https://doi.org/10.1007/978-3-031-18697-4_25
DO  - https://doi.org/10.1007/978-3-031-18697-4_25
VL  - CCIS 1678
SP  - 306
EP  - 312
PB  - Springer
CY  - Cham
ET  - 1.
ER  -