TY  - CONF
ID  - 10.1145/3583678.3603285
T1  - Agent-Based Orchestration on a Swarm of Edge Devices
A1  - Anuraj, Banani
TI  - Proceedings of the 17th ACM International Conference on Distributed and Event-Based Systems
T3  - DEBS '23
Y1  - 2023
SP  - 199–202
PB  - Association for Computing Machinery
CY  - Neuchatel, Switzerland
AD  - New York, NY, USA
SN  - 9798400701221
UR  - https://doi.org/10.1145/3583678.3603285
M2  - doi: 10.1145/3583678.3603285
KW  - actuators
KW  - agents
KW  - distributed architecture
KW  - Edge Computing
KW  - sensor networks
KW  - streaming data
KW  - swarms
N2  - The proliferation of smart devices, sensors, autonomous robots, drones, and other similar instruments have profoundly changed the way of implementing and deploying systems in industrial and home environments, for diverse scenarios such as smart agriculture, healthcare, or manufacturing. Devices in these settings are not limited to simply observe and acquire data for monitoring, but they are also equipped with actuation capabilities, as well as the possibility of autonomously processing the incoming data through various techniques. However, given their intrinsic limitations regarding the capacity to store and process computations, it is often necessary to delegate some of these processing tasks to intermediary edge nodes in the network. These nodes, given their unique position can act as orchestrators guiding the decentralized work of the interconnected autonomous devices. Beyond static and pre-defined organization structures, in this work we propose the usage of agent and multi-agent-based models for designing and implementing swarms of edge nodes, conceived to dynamically orchestrate other devices, while meeting quality of service conditions. Allowing the control of intelligent edge nodes as conveyors and orchestrators on swarms of devices, we aim at providing intelligence to the self-organization of edge nodes, which may interchange streaming data, and represent their own capabilities through semantic models. Swarm-inspired behavioral patterns would guide the collaborative distribution of their computational tasks. Finally, we will implement and demonstrate the proposed technologies in an elderly home environment powered with a host of edge computing, sensing, and actuating devices.
M1  - numpages={4}
ER  -