TY - GEN
T1 - Physics-inspired models for agile code and data in federated edges
AU - Ko, Bongjun
AU - Kraczek, Brent
AU - Salonidis, Theodoras
AU - Basu, Prithwish
AU - Chan, Kevin S.
AU - Porta, Thomas La
AU - Martens, Andreas
N1 - Funding Information:
These are all parts of our on-going efforts to find and apply fundamental models in agile composition of the computing tasks and data in distributed edge systems, and there are several interesting research directions from here. As discussed above, finite temperature simulations, especially Metropolis Monte Carlo (MMC), would aid in expanding the search space. Simulated annealing (SA), based on MMC, could be used to obtain the global optimum solution, while grand-canonical MMC could be used to vary the number of particles, simulating the replication of data and code resources. Alternatively, models from other, non-physics disciplines, such as evolutionary dynamics [7] may prove useful. Another interesting question is whether some “local” dynamics and interactions of the objects can help improve the performance in localized regions but do not impact long-term, global stability of the system. Also, more practical questions beyond the theoretical modeling concern the applicability of the models in real systems; e.g., how the force field information can get distributed to all objects in the system? How the “movement” of objects shall be realized, as the real, physical movement or only simulated ones? We plan to investigate these issues in the future. ACKNOWLEDGMENT This research was sponsored by the U.S. Army Research Laboratory and the U.K. Ministry of Defence under Agreement Number W911NF-16-3-0001. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Army Research Laboratory, the U.S. Government, the U.K. Ministry of Defence or the U.K. Government. The U.S. and U.K. Governments are authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon. This document does not contain technology or technical data controlled under either the U.S. International Traffic in Arms Regulations or the U.S. Export Administration Regulations. REFERENCES
Publisher Copyright:
© 2017 IEEE.
PY - 2018/6/26
Y1 - 2018/6/26
N2 - We study the problem of flexibly, dynamically, and adaptively moving, positioning, and instantiating computing tasks and data in federated, distributed edge systems. We call this process 'agile code and agile data' (ACAD). We explore the adaptation of physics-inspired models, used for atomistic simulations, to the ACAD problem, treating the code and data as particles on a graph, interacting through different potential energy models. We discuss the mapping between the different elements of ACAD problem and our particles-on-A-graph model, considering different frameworks for data analytics. We explore gravitational, elastic and Coulombic models, both with global and local energy minimization, finding that the Coulombic model obtains the most efficient solution.
AB - We study the problem of flexibly, dynamically, and adaptively moving, positioning, and instantiating computing tasks and data in federated, distributed edge systems. We call this process 'agile code and agile data' (ACAD). We explore the adaptation of physics-inspired models, used for atomistic simulations, to the ACAD problem, treating the code and data as particles on a graph, interacting through different potential energy models. We discuss the mapping between the different elements of ACAD problem and our particles-on-A-graph model, considering different frameworks for data analytics. We explore gravitational, elastic and Coulombic models, both with global and local energy minimization, finding that the Coulombic model obtains the most efficient solution.
UR - http://www.scopus.com/inward/record.url?scp=85050178851&partnerID=8YFLogxK
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U2 - 10.1109/UIC-ATC.2017.8397418
DO - 10.1109/UIC-ATC.2017.8397418
M3 - Conference contribution
AN - SCOPUS:85050178851
T3 - 2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017 - Conference Proceedings
SP - 1
EP - 6
BT - 2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017 - Conference Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017
Y2 - 4 April 2017 through 8 April 2017
ER -