A Study of Scheduling Algorithms to Maintain Small Overflow Probability in Cellular Networks with a Single Cell

Nagarajan B,Venkatesan G,Santhosh Kumar C

doi:10.23953/cloud.ijacsit.234

Abstract

Wireless scheduling algorithms for the download of a single cell that can maximize the asymptotic decay rate of the queue-overflow probability as the overflow threshold approaches infinity. We first derive an upper bound on the decay rate of the queue-overflow probability over all scheduling policies. Specifically, we focus on the class of “α - algorithms,” the base station picks the user for service at each time that has the largest product of the transmission rate multiplied by the backlog raised to the power α. The α-algorithms arbitrarily achieve the highest decay rate of the queue-overflow probability. We design a scheduling algorithm that is both close to optimal in terms of the asymptotic decay rate of the overflow probability and to maintain small queue-overflow probabilities over queue-length ranges of practical interest.

Highlights

Link scheduling is an important functionality in wireless networks due to both the shared nature of the wireless medium and the variations of the wireless channel over time
Most of the scheduling algorithms focus on stable throughput to the users
We show that there exists an optimal decay rate Iopt such that for any scheduling algorithm

Summary

Introduction

Link scheduling is an important functionality in wireless networks due to both the shared nature of the wireless medium and the variations of the wireless channel over time. At any given time, the base-station can only serve the queue of one user (refer Figure 1 and Figure 2) This system can be modeled as a single server serving N queues. While stability is an important first-order metric of success, for many We use large-deviation theory and reformulate the QoS constraint in terms of the asymptotic decay rate of the queue-overflow probability as B approaches infinity. For many queue-length-based scheduling algorithms of interest, this multidimensional calculus-of-variations problem is very difficult to solve. Using the insight of our main result, we design a scheduling algorithm that is both close to optimal in terms of the asymptotic decay rate of the overflow probability and empirically shown to maintain small queue-overflow probabilities over queue-length ranges of practical interest

An Upper Bound on the Decay Rate of the Overflow Probability

Probability for the α-Algorithms

Asymptotical Optimality of α-Algorithms

Conclusion