Wireless Data Scheduling Using Threshold-Based Batch Allocation
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Solution Overview
Problem
Conventional service period scheduling in 60 GHz wireless data transmission systems inefficiently allocates timeslots, leading to unusable fragments and failures in data allocation, particularly for pseudo-static service periods.
Innovation Solution
A method and system that delays the allocation of data requests until a certain threshold is reached, using a connection admission control algorithm to optimize scheduling, and allocates pseudo-static service periods starting from the end of each beacon interval, and non-pseudo static service periods based on urgency, to minimize unusable time slots.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If service periods are allocated immediately upon admission, then data requests are quickly scheduled, but unusable time fragments are created and allocation fails occur
Solution Approach 1:
The system performs preliminary actions by collecting multiple data requests before allocating service periods. Instead of allocating immediately upon admission, the control device accumulates requests and then performs batch allocation, allowing for more efficient packing of service periods and elimination of unusable time fragments between allocations.
2Reliability
If maximum allocation time is assigned to each service period, then data transfer requirements are met, but time slot efficiency decreases
Solution Approach 1:
The system implements dynamic allocation where the actual service period duration is adjusted based on the specific data transfer requirements of each request rather than assigning fixed maximum allocation times. The control device determines appropriate service period lengths after collecting multiple requests, allowing for optimized time slot utilization that matches actual needs.
3Ease of operation
If pseudo-static service periods are allocated at the end of beacon intervals, then allocation is simple, but time utilization efficiency decreases
Solution Approach 1:
The system changes the allocation dimension by moving from end-of-interval allocation to a flexible positioning approach within the beacon interval. Pseudo-static service periods are allocated at optimal positions determined during batch scheduling, allowing them to be placed where they maximize time slot utilization rather than being constrained to fixed end positions.
Data Source
AI summary
According to one disclosed embodiment, a method for efficiently scheduling short-range wireless data transmissions is described. This method may include providing beacon intervals for timed data transmission, receiving a plurality of requests for data, delaying allocation of any of the plurality of requests for data into one of the beacon intervals until a number of admitted requests for data exceeds a threshold. The method may also include allocating timeslots for pseudo-static service periods before allocating timeslots for non-pseudo static service periods and allocating timeslots for non-pseudo static service periods in descending order of relative time urgency.


