Network Device Task Distribution via Cloud Virtual Machines
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Solution Overview
Problem
Large computer networks face limitations in computing resources due to the constraints of a single chassis, leading to increased heat and power consumption, which hampers network throughput and administrative tasks, and existing solutions complicate resource management by requiring additional separate devices.
Innovation Solution
Offloading tasks to virtual machines in a computing cloud, allowing network devices to utilize computing resources beyond the limitations of their operating system, by establishing network sockets and distributing tasks such as routing information updates and path calculations to virtual machines, thereby optimizing resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If additional computing resources are added within a single chassis, then computing capacity increases, but heat production and power consumption increase, overwhelming cooling and power capabilities
Solution Approach 1:
The patent segments computing resources across multiple physical devices (chassis) rather than concentrating them in a single chassis. By distributing the computing load across a network of devices, the system achieves high computing capacity while preventing any single device from overheating, thus resolving the contradiction between power and temperature.
2Power
If additional computing resources are added within a single chassis, then computing capacity increases, but the number of processors and computing resources is limited by physical constraints
Solution Approach 1:
The patent transitions from a single-chassis physical constraint to a distributed network architecture, adding the network dimension to resource allocation. This allows computing capacity to scale beyond physical limits of any single device by utilizing available network connectivity and remote computing resources.
3Power
If separate chassis are used to provide additional computing power, then computing capacity increases, but management complexity increases as each chassis must be managed as a separate device
Solution Approach 1:
The patent merges multiple separate chassis into a unified managed system through a centralized management platform. This allows the system to achieve high computing capacity across distributed devices while simplifying management by providing a single point of control for all devices, thus resolving the contradiction between power and ease of operation.
4Power
If the operating system supports a maximum number of computing resources, then system stability is maintained, but total computing capacity is limited
Solution Approach 1:
The patent segments the operating system instance across multiple devices, with each device running a lightweight OS instance while a centralized management system coordinates resources. This allows the system to exceed the computing capacity limits of a single OS while maintaining stability through distributed architecture and centralized control.
Data Source
AI summary
Techniques are described for distributing network device tasks across virtual machines executing in a computing cloud. A network device includes a network interface to send and receive messages, a routing unit comprising one or more processors configured to execute a version of a network operating system, and a virtual machine agent. The virtual machine agent is configured to identify a virtual machine executing at a computing cloud communicatively coupled to the network device, wherein the identified virtual machine executes an instance of the version of the network operating system, to send, using the at least one network interface and to the virtual machine, a request to perform a task, and to receive, using the at least one network interface and from the virtual machine, a task response that includes a result of performing the task. The routing unit is configured to update the network device based on the result.