TY - GEN
T1 - Towards a self-healing multi-agent platform for distributed data management
AU - Rodríguez, Arles
AU - Gómez, Jonatan
AU - Diaconescu, Ada
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - We demonstrate a self-healing multi-agent simulation platform for distributed data-management tasks, including data collection and synchronisation. Collective tasks can be simulated within two types of environments: uncharted terrains with various obstacles, and computing networks with different complex topologies. Agents explore their environment, collect and update local data, and exchange data with agents that they encounter, until the collective task is completed. We have previously implemented several agent exploration algorithms and evaluated their performance in terms of completion speed (essential when agents may fail) and resource overheads (essential in constrained environments). Here, we focus on the agents’ ability to self-heal, via local replication, so as to ensure task completion. We focus on computing network environment, where software replication is more feasible. Envisaged applications include data management in computing clouds, distributed databases, sensor networks, robot swarms and the Internet of Things.
AB - We demonstrate a self-healing multi-agent simulation platform for distributed data-management tasks, including data collection and synchronisation. Collective tasks can be simulated within two types of environments: uncharted terrains with various obstacles, and computing networks with different complex topologies. Agents explore their environment, collect and update local data, and exchange data with agents that they encounter, until the collective task is completed. We have previously implemented several agent exploration algorithms and evaluated their performance in terms of completion speed (essential when agents may fail) and resource overheads (essential in constrained environments). Here, we focus on the agents’ ability to self-heal, via local replication, so as to ensure task completion. We focus on computing network environment, where software replication is more feasible. Envisaged applications include data management in computing clouds, distributed databases, sensor networks, robot swarms and the Internet of Things.
KW - Data-management tasks
KW - Multi-agent
KW - Self-healing
KW - Simulation
U2 - 10.1007/978-3-319-59930-4_36
DO - 10.1007/978-3-319-59930-4_36
M3 - Conference contribution
AN - SCOPUS:85021755729
SN - 9783319599298
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 350
EP - 354
BT - Advances in Practical Applications of Cyber-Physical Multi-Agent Systems
A2 - Demazeau, Yves
A2 - Davidsson, Paul
A2 - Vale, Zita
A2 - Bajo, Javier
PB - Springer Verlag
T2 - 15th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2017
Y2 - 21 June 2017 through 23 June 2017
ER -