Maximizing Service Reward for Queues with Deadlines

TL;DR

This paper introduces a new scheduling policy for real-time queues with rewards and deadlines, improving performance over traditional methods by maximizing packet processing and reward collection.

Contribution

It proposes an optimal scheduling policy for known processing times and demonstrates its effectiveness through theoretical proofs and simulations.

Findings

Policy is optimal under deterministic service times and binomial rewards.

Policy maximizes packet processing and reward collection in general cases.

Simulation results show high performance compared to existing policies.

Abstract

In this paper we consider a real time queuing system with rewards and deadlines. We assume that packet processing time is known upon arrival, as is the case in communication networks. This assumption allows us to demonstrate that the well known Earliest-Deadline-First policy performance can be improved. We then propose a scheduling policy that provides excellent results for packets with rewards and deadlines. We prove that the policy is optimal under deterministic service time and binomial reward distribution. In the more general case we prove that the policy processes the maximal number of packets while collecting rewards higher than the expected reward. We present simulation results that show its high performance in more generic cases compared to the most commonly used scheduling policies.