Cloud-Network Integrated MEC Architecture with SDN Control
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Solution Overview
Problem
Existing multi-access edge computing (MEC) architectures face challenges due to coarse-grained resource allocation policies, which lack fine-grained control over resources, hindering the implementation of latency-sensitive services.
Innovation Solution
A software-defined fine-grained MEC architecture with physical layer/MAC layer slicing and a two-stage resource allocation strategy based on deep reinforcement learning Q-learning, enabling flexible and adaptive resource management and offloading.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If coarse-grained resource allocation policies are used in MEC, then device complexity is reduced and ease of operation is improved, but manufacturing precision (resource allocation precision) deteriorates, making fine-grained control impossible
Solution Approach 1:
The patent segments the physical channel into multiple subchannels, each supporting independent MAC access modes. This segmentation enables fine-grained resource allocation by allowing different users or services to be assigned to specific subchannels with dedicated MAC protocols, thereby achieving precise control over transmission resources without overwhelming system complexity
Solution Approach 2:
The SDN controller is introduced as an intermediary component that centralizes the intelligence for resource allocation. It receives allocation requests, determines optimal subchannel and MAC protocol assignments, and enforces these decisions at the edge computing nodes. This intermediary approach enables fine-grained control while keeping individual node complexity manageable
2Productivity
If fine-grained resource allocation is implemented, then resource utilization efficiency is improved and latency is reduced, but device complexity increases due to the need for sophisticated control mechanisms
Solution Approach 1:
The SDN controller serves as a centralized intermediary that handles the complexity of fine-grained resource allocation. It performs intelligent decision-making for subchannel assignment and MAC protocol selection based on real-time network conditions and service requirements, while edge nodes simply execute the controller's decisions. This separation of control and execution enables high resource utilization without burdening individual nodes with complex control logic
Solution Approach 2:
The system dynamically adapts resource allocation based on real-time conditions. The SDN controller continuously monitors network state and adjusts subchannel assignments and MAC protocol configurations to match changing traffic patterns and service demands. This dynamic approach maximizes resource utilization efficiency while maintaining manageable complexity through automated adaptation rather than static complex configurations
3Adaptability or versatility
If physical layer and MAC layer slicing are implemented, then adaptability to different services is improved, but device complexity increases due to multi-layer control requirements
Solution Approach 1:
The patent implements slicing at both the physical layer (subchannel division) and MAC layer (protocol selection). This multi-layer segmentation creates isolated resource pools that can be independently configured for different service types (e.g., ultra-reliable low-latency services, enhanced mobile broadband). Each slice can be optimized for its specific requirements without affecting other slices, achieving high service adaptability while keeping individual slice management simple through the SDN controller's centralized orchestration
Data Source
AI summary
The present application discloses a cloud-network integration (CNI) oriented multi-access edge computing (MEC) architecture. An access network (AN) side of the architecture is provided with a plurality of edge computing nodes, a physical channel of the AN side is split into a plurality of subchannels with each of the subchannels supporting a media access control (MAC) access mode, and a software defined network (SDN) controller is arranged in the architecture and is configured to allocate resources of the subchannels at a physical layer and protocols at an MAC layer and control offloading at the edge computing nodes or a cloud center by a terminal user. The present application can carry out fine-grained control and cooperative management on network resources and computing resources, and achieve more effective computation offloading and service enhancement.