Adaptive Packet Scheduling in Cloud-RAN via Dynamic Priority
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Solution Overview
Problem
Traditional cellular systems face scalability issues, fault tolerance challenges, and resource utilization inefficiencies due to dynamic load conditions in mobile data transmission, particularly in Cloud-RAN architectures, where packet scheduling is ineffective as it relies on predefined priorities.
Innovation Solution
An adaptive packet scheduling system utilizing an intelligent packet classifier and advanced dynamic packet scheduler within the Cloud-RAN's centralized baseband unit, which computes a Dynamic-Packet-Level-Priority (DPLP) value based on packet parameters like cell priority, load, interface, and Quality Class Identifier, and schedules packets accordingly to optimize resource utilization and scalability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional predefined priority scheduling is used in Cloud-RAN, then implementation is simple, but resource utilization is inefficient and scalability is poor
Solution Approach 1:
The patent implements dynamic packet scheduling by computing DPLP values that change based on real-time network conditions, cell load, and packet characteristics. The scheduler continuously adapts priorities rather than using static predefined priorities, allowing the system to respond to dynamic load conditions and improve resource utilization efficiently.
Solution Approach 2:
The patent changes the scheduling parameter from fixed predefined priorities to dynamic DPLP values that are computed based on multiple variables including cell priority, cell load, interface type, and QCI. This parameter transformation enables flexible resource allocation that adapts to changing network conditions without requiring complex manual configuration.
2Reliability
If maximum load capability is built into each BBU to ensure fault tolerance, then reliability is improved, but cost increases due to redundant resources
Solution Approach 1:
The patent merges multiple BBU instances into a shared Cloud-RAN platform where computing resources are pooled and dynamically allocated. Instead of each BBU having dedicated backup capacity, the system combines resources and uses dynamic scheduling to distribute load across available capacity, reducing total resource requirements while maintaining reliability through load balancing and failover capabilities.
Solution Approach 2:
The patent creates a universal Cloud-RAN platform where a single pool of computing resources can serve multiple cells and handle various traffic types dynamically. The virtualized BBU instances can be allocated to different cells based on current load conditions, allowing the same physical resources to perform multiple functions and serve multiple purposes simultaneously.
3Reliability
If dynamic load conditions are handled by over-provisioning each BBU, then service continuity is ensured, but resource waste increases during idle periods
Solution Approach 1:
The patent implements dynamic resource allocation where BBU computing capacity is adjusted in real-time based on actual traffic load. During high load periods, more computing resources are activated to maintain service continuity. During idle periods, resources are scaled down or put into low-power states, reducing energy consumption while ensuring service continuity when needed.
Solution Approach 2:
The patent enables the Cloud-RAN system to automatically manage its own resource allocation and load balancing without manual intervention. The dynamic scheduling algorithm continuously monitors network conditions and automatically distributes traffic across available BBU instances, allowing the system to self-adjust resource usage and energy consumption based on actual service requirements.
Data Source
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AI summary
Method and systems for adapative scheduling of packets in a wireless broadband network are disclosed. In one embodiment, the method comprises receiving the packets from applications. The method further comprises analyzing the packets to obtain one or more packet parameters. The method further comprises determining a Dynamic-Packet-Level-Priority (DPLP) value for each of the packets based on the one or more packet parameters. The method further comprises placing each of the packets in priority queues based on the DPLP value. The method further comprises scheduling the packets present in the priority queues based on scheduling parameters and the DPLP value. The method further comprises performing dynamic configuration adaptation for the packet parameters, scheduling parameters and the DPLP value.