MIRRA™ Real-time Task Scheduling
Many reports predict that in the near future, a countless number of IoT devices will be used for different purposes. Moreover, most of them are real-time applications sampling statuses periodically, sending data to remote application servers. Since the number of deployed devices will be huge, and data processing demands may be massive, using a public, private, or hybrid cloud is not a viable option for ideal server deployment. In addition, managing and optimizing virtual machine infrastructure size is a serious matter to significantly reduce IT costs and increase productivity.
Amerra has designed and developed real-time task scheduling algorithms as part of a middleware (called MIRRA™) to resolve these issues in the form of a smart and dynamic virtual resource controller. MIRRA can operate inside virtual machines within most cloud infrastructures and independently from your application server running in the same virtual machine by providing the real-time task scheduler. Multiple peer-reviewed research papers about the technology and successful tests against existing cloud infrastructure have proven our approach.
The MIRRA™ Pilot Program
Engineers, entrepreneurs, and pioneers,
Amerra is seeking IoT companies within any industry to collaborate on pilot projects involving the development and release of a generic real-time deployment platform. As you know, many reports predict that in the near future, a countless number of IoT devices will be used for different purposes. Moreover, most of them will be real-time applications sampling statuses periodically and sending data to remote application servers. With the number of deployed devices increasing exponentially, the massive data sizes and coordination of types of data using public, private, or hybrid clouds will not be true viable options. Why? Due to a serious issue of managing & optimizing their virtual machine infrastructure size that now must be addressed in order to reduce heavy IT costs and increase productivity & profitability!
The implementation of the MIRRA™ commercial version from our research will enable additional external validation by deploying your device and/or program using our middleware to improve your company’s bottom line and IT resource allocation.
This opportunity is zero-risk, as Amerra will implement your application servers into a cloud infrastructure after assessing your business logic and current setup, as well as future potential needs . We invite all interested parties to please fill out the form below, or call 713-529-9776.
We look forward to empowering your company with our revolutionary cloud resource-optimization technology!
The Amerra Team
MIRRA™ Pilot Inquiry
Please fill out the following form
& a PDF of the Pilot Summary Overview will be in your confirmation email!
MIRRA: Rule-Based Resource Management for Heterogeneous Real-Time Applications Running in Cloud Computing Infrastructures
Feedback Computing 2015; April 14, 2015
Automatic Resource Scaling for Medical Cyber-Physical Systems Running in Private Cloud Computing Architecture
Medical Cyber Physical Systems Workshop, Cyber-Physical Systems Week, 2014
Autonomic Computing Architecture for Real-Time Medical Application Running on Virtual Private Cloud Infrastructures
IEEE Real-Time Systems Symposium – WIP session, 2012
An assortment of question & answers to help you understand how this will maximize your profitability by saving you money!
How does MIRRA™ work?
Is MIRRA a stand-alone solution or does it require prerequisites?
How is Amerra Connect used with MIRRA? Is this something else that needs to be purchased?
Is MIRRA compatible with any device?
What are MIRRA’s potential limitations?
Is MIRRA open source?
What language is MIRRA written in?
What is “System Reliability?
What is “Cloud Resource Optimization?
What is “Real-time Scheduling?
How much does MIRRA cost?
How is MIRRA purchased?
Does MIRRA require advanced software expertise to configure?
Has this technology been tested?
How do you ensure confidential information, such as patient data isn’t compromised?
How are system reliability and optimization measured?
The system optimization also can be measured by observing resource usages over time if the system reliability is kept as its minimum level.