Numerical Implementation of Random Workload Device and Network Reliability Models


design software for implementation of random workload reliability model

conduct numerical studies on different types of stress metrics in order to facilitate implementation and integration into products


We have a comprehensive groundbreaking perspective and mathematical model for device/server reliability that allows the user to input his desired metrics for the workload, along with estimation of parameters such as the service rate and arrival rate and arrive at an exact equation for the failure probability under workload. This model doesn't require standard simplifications, so the application covers a broad area of situations. Full background can be found in our publications Stochastic Reliability of a Server under a Random Workload, On Server Efficiency, and this PhD dissertation


Efficiency and capacity planning for individual devices and systems

Having a full understanding of your device's reliability under the stochastic conditions so common across all industries allows for dynamic and more accurate planning to fully take advantage of your devices and cut costs.

Risk Analysis and Monitoring

Break free of oversimplified assumptions that don't give you an accurate picture of your devices and their interactions in a system. The development of this work would allow for better risk analysis, maintenance and warranty policy design, and cost-effective system design. No more excessive over provisioning. 

Ideal Candidates

Manufacturing Engineering, Tooling, and Quality Control

Network Engineering

Mechanical/Aerospace Engineering

Industrial Engineering

Operations and Logistics