Dynamic Network Resource Assignment for Efficient Pod Allocation
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Solution Overview
Problem
In wireless communication systems, network resources are often wasted due to pods having more resources than needed for specific services, leading to inefficiencies and increased processing times.
Innovation Solution
Systems and methods dynamically assign and redistribute network resources to pods, resource pools, and slices, utilizing machine learning algorithms to optimize resource utilization and reduce waste, enabling efficient access to services during maintenance windows and peak times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pods are allocated fixed network resources, then resource availability is guaranteed, but resource utilization efficiency deteriorates due to over-provisioning
Solution Approach 1:
The patent implements dynamic resource allocation where network resources are not fixed to pods but are continuously adjusted based on real-time monitoring of resource usage metrics. The system monitors pod performance and dynamically assigns or reassigns network resources (such as spectrum, power, memory) to match actual demand, transforming the static allocation model into a dynamic one that adapts to changing conditions.
Solution Approach 2:
The system changes the allocation parameters of network resources based on monitored performance metrics. When pods exhibit under-utilization of assigned resources, the system modifies the resource allocation parameters by reducing the assigned amounts. Conversely, when resource demand increases, the parameters are adjusted upward. This parameter-based control enables flexible adaptation without rigid fixed allocations.
2Loss of energy
If network resources are reassigned dynamically, then resource utilization efficiency is improved, but system complexity increases
Solution Approach 1:
The patent implements a self-service mechanism where the system automatically monitors its own resource usage and performs reassignment without external intervention. The monitoring component detects when pods are under-utilizing resources, and the control system automatically reassigns these resources to other pods that need them. This automation reduces the need for complex manual management while achieving efficient resource utilization.
Solution Approach 2:
The system employs feedback loops where resource usage metrics from pods are continuously monitored and fed back to the control system. Based on this feedback, the system determines whether reassignment is needed and executes the appropriate actions. This feedback mechanism simplifies the control logic by relying on observed performance data rather than complex predictive models, making the system more manageable despite the dynamic nature of resource allocation.
3Reliability
If resource reassignment occurs during maintenance windows, then service disruption is minimized, but reassignment flexibility is reduced
Solution Approach 1:
The system performs resource reassignment during pre-scheduled maintenance windows, which are planned in advance. By conducting reassignment operations during these predetermined intervals, the system ensures that resource reallocation happens when service disruption is already expected and acceptable. This preliminary scheduling of maintenance activities allows the system to maintain service continuity while still providing opportunities for flexible reassignment when needed.
Data Source
AI summary
An apparatus comprises a memory and a processor communicatively coupled to one another. The memory may comprise information on one or more network resources. The processor may be configured to determine that one or more network resources are available for allocation to a first resource pool and a second resource pool in response to determining that the one or more network resources are unassigned, determine first network resources of the one or more network resources configured to enable first layer operations, and determine second network resources of the one or more network resources configured to enable second layer operations. Further, the processor may be configured to assign the first network resources to the first resource pool, assign the second network resources to the second resource pool, generate a first pod comprising the first resource pool, and generate a second pod comprising the second resource pool.


