Fault tolerant adaptive parallel and distributed simulation through functional replication

Abstract

This paper presents FT-GAIA, a software-based fault-tolerant parallel and distributed simulation middleware. FT-GAIA has being designed to reliably handle Parallel And Distributed Simulation (PADS) models, which are needed to properly simulate and analyze complex systems arising in any kind of scientific or engineering field. PADS takes advantage of multiple execution units run in multicore processors, cluster of workstations or HPC systems. However, large computing systems, such as HPC systems that include hundreds of thousands of computing nodes, have to handle frequent failures of some components. To cope with this issue, FT-GAIA transparently replicates simulation entities and distributes them on multiple execution nodes. This allows the simulation to tolerate crash-failures of computing nodes. Moreover, FT-GAIA offers some protection against Byzantine failures, since interaction messages among the simulated entities are replicated as well, so that the receiving entity can identify and discard corrupted messages. Results from an analytical model and from an experimental evaluation show that FT-GAIA provides a high degree of fault tolerance, at the cost of a moderate increase in the computational load of the execution units.

Minimum-Cost-Based Neighbour Node Discovery Scheme for Fault Tolerance under IoT-Fog Networks

“…To detect the fault, the cloud or Fog statuses are regularly monitored and various responses, such as replication, checkpoint, and resubmission, are recorded [8]. Gabriele et al [9] suggested the use of a Fault-Tolerance Generic Adaptive Interaction Architecture (FT-GAIA) software-based FT method for parallel and distributed environments. Mainly, this method deals with Byzantine faults and crash errors with the help of server restoration in the cloud layer, and this is achieved with the help of a replication mechanism.…”

“…E exe = T exe × p na (9) where p k and p na denote the power consumption of the IoT device and f na , respectively, during task execution.…”