TY - GEN
T1 - Lensing
T2 - 3rd IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion, ACSOS-C 2022
AU - Diaconescu, Ada
AU - King, David
AU - Bellman, Kirstie
AU - Landauer, Christopher
AU - Nelson, Phyllis
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - Complex Adaptive Systems (CAS) are difficult to understand and predict. Certain CAS phenomena can only be observed at certain abstraction levels - e.g., swarm dynamics cannot be analysed by only tracking one individual. In most current systems the 'right' abstraction levels for each question asked, or each problem solved, are determined at design time. Yet, in adaptive self-integrating systems the abstraction level must be determined dynamically, depending on the questions encountered and the system context. This position paper aims to set-up the basis for a research initiative in this direction. It proposes the concept of 'lensing' to tune a system's observation granularity in terms of spatial and temporal scope, and information detail. It further introduces lens efficacy and efficiency to evaluate a lens' ability to answer specific questions-a critical process for self-aware systems performing lensing at runtime. Finally, the paper illustrates the criticality of lensing in answering different kinds of questions via several examples of collective movement systems, including a Game of Life (GoL) Glider simulation.
AB - Complex Adaptive Systems (CAS) are difficult to understand and predict. Certain CAS phenomena can only be observed at certain abstraction levels - e.g., swarm dynamics cannot be analysed by only tracking one individual. In most current systems the 'right' abstraction levels for each question asked, or each problem solved, are determined at design time. Yet, in adaptive self-integrating systems the abstraction level must be determined dynamically, depending on the questions encountered and the system context. This position paper aims to set-up the basis for a research initiative in this direction. It proposes the concept of 'lensing' to tune a system's observation granularity in terms of spatial and temporal scope, and information detail. It further introduces lens efficacy and efficiency to evaluate a lens' ability to answer specific questions-a critical process for self-aware systems performing lensing at runtime. Finally, the paper illustrates the criticality of lensing in answering different kinds of questions via several examples of collective movement systems, including a Game of Life (GoL) Glider simulation.
KW - abstraction
KW - collective movement
KW - complex adaptive systems
KW - game of life
KW - hierarchy
KW - lensing
UR - https://www.scopus.com/pages/publications/85143061888
U2 - 10.1109/ACSOSC56246.2022.00044
DO - 10.1109/ACSOSC56246.2022.00044
M3 - Conference contribution
AN - SCOPUS:85143061888
T3 - Proceedings - 2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion, ACSOS-C 2022
SP - 119
EP - 125
BT - Proceedings - 2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion, ACSOS-C 2022
A2 - Casadei, Roberto
A2 - Di Nitto, Elisabetta
A2 - Gerostathopoulos, Ilias
A2 - Pianini, Danilo
A2 - Dusparic, Ivana
A2 - Wood, Timothy
A2 - Nelson, Phyllis
A2 - Pournaras, Evangelos
A2 - Bencomo, Nelly
A2 - Gotz, Sebastian
A2 - Krupitzer, Christian
A2 - Raibulet, Claudia
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 19 September 2022 through 23 September 2022
ER -