18150397. Distributed Computing Topology with Energy Savings simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)
Contents
- 1 Distributed Computing Topology with Energy Savings
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 Distributed Computing Topology with Energy Savings - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Questions about Topology Management in Network Computing Systems
- 1.11 Original Abstract Submitted
Distributed Computing Topology with Energy Savings
Organization Name
INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor(s)
Peng Hui Jiang of Beijing (CN)
Cheng Fang Wang of Beijing (CN)
Distributed Computing Topology with Energy Savings - A simplified explanation of the abstract
This abstract first appeared for US patent application 18150397 titled 'Distributed Computing Topology with Energy Savings
Simplified Explanation
The patent application describes a method for managing a network computing system's topology by determining tasks for a workload to be performed by computing devices. The topology is created based on the number of processor units and includes nodes representing tasks connected in an execution order with alternative paths for task performance based on energy consumption.
- Tasks for a workload are determined by a number of processor units in a network computing system.
- The number of processor units creates a topology with nodes representing tasks assigned to computing devices.
- Nodes are connected based on an execution order for tasks, with alternative paths available for task performance.
- Energy consumption for alternative paths is determined by the number of processor units.
- A particular path is selected for task performance based on energy consumption for the alternative paths.
Key Features and Innovation
- Management of network computing system topology based on tasks and processor units.
- Creation of a topology with nodes representing tasks and alternative paths for task performance.
- Selection of task performance path based on energy consumption for alternative paths.
Potential Applications
This technology can be applied in various industries such as telecommunications, cloud computing, and data centers for optimizing task performance and energy efficiency.
Problems Solved
This technology addresses the challenges of managing complex network computing systems efficiently by optimizing task performance paths based on energy consumption.
Benefits
- Improved efficiency in task performance in network computing systems.
- Enhanced energy optimization for task execution.
- Streamlined management of workload tasks in a network computing environment.
Commercial Applications
Optimizing energy consumption and task performance in telecommunications networks, cloud computing services, and data centers can lead to cost savings and improved operational efficiency.
Questions about Topology Management in Network Computing Systems
How does the number of processor units impact the creation of the network computing system's topology?
The number of processor units determines the tasks assigned to computing devices and the energy consumption for alternative paths in the topology.
What factors are considered when selecting a particular path for task performance in the network computing system?
The energy consumption for the alternative paths is a key factor in selecting a specific path for task execution.
Original Abstract Submitted
A computer implemented method manages a topology for a network computing system. A number of processor units determines tasks for a workload to be performed by computing devices in the network computing system. The number of processor units creates the topology for performing the tasks in the workload. The topology comprises nodes representing the tasks assigned to the computing devices. The nodes are connected to each other based on an execution order for the tasks, and the topology has alternative paths for performing the tasks for the workload. The number of processor units determines energy consumption for the alternative paths in the topology. The number of processor units selects a particular path from the alternative paths for performing the tasks for the workload based on the energy consumption for the alternative paths.
