Title
Physics-inspired models for agile code and data in federated edges
Abstract
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.
Year
DOI
Venue
2017
10.1109/UIC-ATC.2017.8397418
2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
Keywords
Field
DocType
agile code,physical models
Data modeling,Data analysis,Computer science,Agile software development,Potential energy,Minification,Distributed database,Gravitation,Energy minimization,Distributed computing
Conference
ISBN
Citations 
PageRank 
978-1-5386-1591-1
0
0.34
References 
Authors
2
7
Name
Order
Citations
PageRank
Bongjun Ko126821.18
Brent Kraczek200.34
Theodoros Salonidis3124793.31
P. Basu417417.10
kevin chan528422.53
T. F. La Porta622256.86
Andreas Martens700.34