TY - CPAPER 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 -