17806857. ATTRIBUTES FOR WORKLOADS, INFRASTRUCTURE, AND DATA FOR AUTOMATED EDGE DEPLOYMENT simplified abstract (Dell Products L.P.)

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ATTRIBUTES FOR WORKLOADS, INFRASTRUCTURE, AND DATA FOR AUTOMATED EDGE DEPLOYMENT

Organization Name

Dell Products L.P.

Inventor(s)

Eric Bruno of Shirley NY (US)

Victor Fong of Medford MA (US)

Amy N. Seibel of Newton MA (US)

ATTRIBUTES FOR WORKLOADS, INFRASTRUCTURE, AND DATA FOR AUTOMATED EDGE DEPLOYMENT - A simplified explanation of the abstract

This abstract first appeared for US patent application 17806857 titled 'ATTRIBUTES FOR WORKLOADS, INFRASTRUCTURE, AND DATA FOR AUTOMATED EDGE DEPLOYMENT

Simplified Explanation

The patent application describes a method for placing workloads in a computing environment based on their attributes and the attributes of the nodes and data. Here are the key points:

  • Workloads in a computing environment are given a workload score based on their attributes.
  • The workload attributes are compared with the attributes of the nodes and/or data.
  • Based on this comparison and the node score, the workload is placed with one of the nodes.
  • This attribute-based workload placement helps optimize resource allocation in the computing environment.

Potential applications of this technology:

  • Cloud computing platforms can use this method to efficiently allocate workloads to different nodes based on their attributes.
  • Data centers can benefit from this technology by optimizing workload placement and improving overall performance.
  • Distributed computing systems can use this method to balance the workload across different nodes based on their capabilities.

Problems solved by this technology:

  • Efficient workload placement: The method helps in placing workloads in the most suitable nodes based on their attributes, leading to better resource utilization.
  • Resource optimization: By considering both workload and node attributes, the method ensures that workloads are placed in nodes that can handle them effectively, reducing resource wastage.
  • Scalability: The attribute-based approach allows for easy scalability as new nodes can be added to the computing environment and workloads can be dynamically placed based on their attributes.

Benefits of this technology:

  • Improved performance: By placing workloads in nodes that are best suited for them, overall system performance is enhanced.
  • Resource efficiency: The attribute-based placement ensures that resources are utilized optimally, reducing costs and improving energy efficiency.
  • Flexibility and scalability: The method allows for dynamic workload placement, making it adaptable to changing computing environments and workload demands.


Original Abstract Submitted

Attribute-based workload placement and orchestration in a computing environment including nodes is disclosed. A workload, when received at a scheduling engine, is given a workload score determined from the workload's attributes. Using the workload attributes, along with node attributes and/or data attributes, the workload is placed with one of the nodes. The node is selected based on how the workload attributes compare with the node attributes and/or the data attributes and based on the node score.

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