Time slot resource adjusting method based on load evaluation

Abstract

The invention provides a time slot resource adjusting method based on load evaluation, which divides services into time sensitive services and time non-sensitive services, and respectively adjusts time slots required by the services according to different service types. Manual intervention is not needed, the number of time slots needing to be increased or released can be automatically calculated according to service loads, the oscillation phenomenon is avoided, and effective utilization of resources is achieved; and time slot resources are adjusted in time according to service types and queueload conditions, it is guaranteed that services are sent in time, and the method is already applied to practical engineering and can adjust the time slot resources for various services and load conditions in time in a complex network environment, and the service transmission characteristics are met.

Description

technical field [0001] The invention relates to the technical field of data link networks, in particular to a time slot resource adjustment method. Background technique [0002] The distributed network is a non-centered and distributed network architecture, which requires ensuring that the business is delivered to the destination node reliably and quickly. The choice of different access protocols in a distributed network directly affects the performance of the network. Competitive access protocols have the disadvantages of increased collisions and increased access delay as the network scale and business load increase. As the scale of the network increases, the multiple access protocol of the fixed allocation type will also increase the transmission delay, and the network expansion ability is poor. The dynamic TDMA protocol dynamically allocates time slots according to the node's service transmission requirements, which can provide greater network capacity, allocate resourc...

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Problems solved by technology

[0003] In response to the above problems, some scholars have proposed various load evaluation algorithms, but some methods fail to accurately evaluate the size of the load, resulting in multiple applications or waste of resources; some methods do not consider network dynamics and business characteristics in actual use, resulting in The non-convergence of the algorithm will cause frequent oscillations; some algorithms are based on queuing theory, and their evaluation indicators are based on statistical averages, which are not suitable for the transmission of time-sensitive services

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