Mobility Management via Computation Forecasting
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Solution Overview
Problem
Existing handover techniques in wireless communication networks primarily focus on signal measurements, which can lead to decreased or disrupted computation performance due to insufficient computation resources at the target network node.
Innovation Solution
The proposed solution involves configuring one or more processors to execute instructions that cause a user equipment (UE) to offload tasks to a network node, determine a computation requirement forecast, transmit this forecast, and perform a handover procedure to a second network node that satisfies the computation requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If handover is based only on signal measurements, then handover speed is fast, but computation reliability deteriorates due to insufficient computation resources at target node
Solution Approach 1:
The system performs preliminary actions by forecasting computation requirements before handover occurs. The UE determines computation requirement forecasts for upcoming times and transmits them to the source network node, enabling proactive assessment of whether the target node will have sufficient resources, thus preventing computation interruptions before they happen.
Solution Approach 2:
The handover decision mechanism becomes dynamic by integrating both signal measurements and computation requirement forecasts. The source network node dynamically evaluates multiple parameters including signal quality, computation capacity, and task requirements to make adaptive handover decisions that balance communication reliability and computation reliability.
2Reliability
If handover considers computation requirements, then computation reliability improves, but handover decision complexity increases
Solution Approach 1:
Computation requirement forecasts are determined in advance for upcoming time periods, allowing the system to assess future resource availability before handover is triggered. This preliminary assessment prevents the need for complex real-time calculations during the handover execution phase, reducing actual handover decision time.
Solution Approach 2:
The system uses configured granularity for computation requirement forecasts (e.g., specific time intervals or event triggers) rather than continuous monitoring. This partial sampling approach provides sufficient information for handover decisions without requiring exhaustive real-time computation requirement tracking, thus limiting the time overhead to acceptable levels.
3Reliability
If computation requirement forecast is transmitted frequently, then computation reliability improves, but signaling overhead increases
Solution Approach 1:
The UE transmits computation requirement forecasts periodically according to configured granularity (e.g., every T milliseconds or at specific event triggers) rather than continuously. This periodic transmission maintains adequate awareness of computation requirements for reliable handover decisions while significantly reducing the quantity of signaling messages compared to continuous reporting.
Solution Approach 2:
The system changes the parameter of reporting frequency based on network conditions and task characteristics. The configured granularity allows flexible adjustment of how often computation requirement forecasts are transmitted, optimizing the balance between maintaining computation reliability and minimizing signaling overhead for different operational scenarios.
Data Source
AI summary
One or more processors are configured to execute instructions that cause a UE to perform operations. The operations include offloading a task to a first network node. The operations include determining a computation requirement forecast, wherein the computation requirement forecast indicates a computation requirement of the task at an upcoming time. The operations include transmitting the computation requirement forecast to the first network node. The operations include performing a handover procedure from the first network node to a second network node.