Decentralized Throughput Maximizing Policies for Deadline-Constrained Wireless Networks

TL;DR

This paper introduces a decentralized scheduling policy for multi-hop wireless networks that maximizes throughput of packets meeting strict deadlines, using local deadline information and average transmission constraints.

Contribution

It proposes a novel decentralized policy that achieves maximum throughput for deadline-constrained wireless networks, simplifying implementation by using local information and average constraints.

Findings

Significant throughput improvement over existing deadline-based policies.

Policy is easy to implement and extend to time-varying channels.

Theoretical guarantees of maximum throughput are provided.

Abstract

We consider multi-hop wireless networks serving multiple flows in which only packets that meet hard end-to-end deadline constraints are useful, i.e., if a packet is not delivered to its destination node by its deadline, it is dropped from the network. We design decentralized scheduling policies for such multi-hop networks that attain the maximum throughput of useful packets. The resulting policy is decentralized in the sense that in order to make a transmission decision, a node only needs to know the "time-till-deadline" of the packets that are currently present at that node, and not the state of the entire network. The key to obtaining an easy-to-implement and highly decentralized policy is to replace the hard constraint on the number of simultaneous packet transmissions that can take place on the outgoing links of a node, by a time-average constraint on the number of transmissions. The policy thus obtained is guaranteed to provide maximum throughput. Analysis can be extended to the case of time-varying channel conditions in a straightforward manner. Simulations showing significant improvement over existing policies for deadline based scheduling, such as Earliest Deadline First, and supporting the theory, are presented.