Rights statement: © 2015 IEEE. This is an author produced version of a paper published in IEEE Transactions on Services Computing. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Uploaded in accordance with the publisher's self-archiving policy.
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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - SEED
T2 - a scalable approach for cyber-physical system simulation
AU - Garraghan, Peter
AU - McKee, David
AU - Ouyang, Xue
AU - Webster, David
AU - Xu, Jie
N1 - © 2015 IEEE. This is an author produced version of a paper published in IEEE Transactions on Services Computing. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Uploaded in accordance with the publisher's self-archiving policy.
PY - 2015/10/14
Y1 - 2015/10/14
N2 - Simulation is critical when studying real operational behavior of increasingly complex Cyber-Physical Systems, forecasting future behavior, and experimenting with hypothetical scenarios. A critical aspect of simulation is the ability to evaluate large-scale systems within a reasonable time frame while modeling complex interactions between millions of components. However, modern simulations face limitations in provisioning this functionality for CPSs in terms of balancing simulation complexity with performance, resulting in substantial operational costs required for completing simulation execution. Moreover, users are required to have expertise in modeling and configuring simulations to infrastructure which is time consuming. In this paper we present Simulation EnvironmEnt Distributor (SEED), a novel approach for simulating large-scale CPSs across a loosely-coupled distributed system requiring minimal user configuration. This is achieved through automated simulation partitioning and instantiation while enforcing tight event messaging across the system. SEED operates efficiently within both small and large-scale OTS hardware, agnostic of cluster heterogeneity and OS running, and is capable of simulating the full system and network stack of a CPS. Our approach is validated through experiments conducted in a cluster to simulate CPS operation. Results demonstrate that SEED is capable of simulating CPSs containing 2,000,000 tasks across 2,000 nodes with only 6.89 times; slow down relative to real time, and executes effectively across distributed infrastructure.
AB - Simulation is critical when studying real operational behavior of increasingly complex Cyber-Physical Systems, forecasting future behavior, and experimenting with hypothetical scenarios. A critical aspect of simulation is the ability to evaluate large-scale systems within a reasonable time frame while modeling complex interactions between millions of components. However, modern simulations face limitations in provisioning this functionality for CPSs in terms of balancing simulation complexity with performance, resulting in substantial operational costs required for completing simulation execution. Moreover, users are required to have expertise in modeling and configuring simulations to infrastructure which is time consuming. In this paper we present Simulation EnvironmEnt Distributor (SEED), a novel approach for simulating large-scale CPSs across a loosely-coupled distributed system requiring minimal user configuration. This is achieved through automated simulation partitioning and instantiation while enforcing tight event messaging across the system. SEED operates efficiently within both small and large-scale OTS hardware, agnostic of cluster heterogeneity and OS running, and is capable of simulating the full system and network stack of a CPS. Our approach is validated through experiments conducted in a cluster to simulate CPS operation. Results demonstrate that SEED is capable of simulating CPSs containing 2,000,000 tasks across 2,000 nodes with only 6.89 times; slow down relative to real time, and executes effectively across distributed infrastructure.
KW - Computational modeling
KW - Synchronization
KW - Network topology
KW - Hardware
KW - Cyber-physical systems
KW - Scalability
KW - Accuracy
U2 - 10.1109/TSC.2015.2491287
DO - 10.1109/TSC.2015.2491287
M3 - Journal article
VL - 9
SP - 199
EP - 212
JO - IEEE Transactions on Services Computing
JF - IEEE Transactions on Services Computing
SN - 1939-1374
IS - 2
ER -