Polynomial-Time Approximation Scheme for Data Broadcast

TL;DR

This paper introduces the first polynomial-time approximation scheme for data broadcast scheduling on multiple channels, significantly improving efficiency in asymmetric communication environments with probabilistic client requests.

Contribution

It presents a novel PTAS for data broadcast with constant channels and arbitrary message probabilities, surpassing previous approximation algorithms.

Findings

Achieves a PTAS with arbitrary message probabilities and bounded costs.

Improves the approximation ratio from 9/8 to near-optimal.

Applicable to satellite, cable, internet, and mobile broadcast environments.

Abstract

The data broadcast problem is to find a schedule for broadcasting a given set of messages over multiple channels. The goal is to minimize the cost of the broadcast plus the expected response time to clients who periodically and probabilistically tune in to wait for particular messages. The problem models disseminating data to clients in asymmetric communication environments, where there is a much larger capacity from the information source to the clients than in the reverse direction. Examples include satellites, cable TV, internet broadcast, and mobile phones. Such environments favor the ``push-based'' model where the server broadcasts (pushes) its information on the communication medium and multiple clients simultaneously retrieve the specific information of individual interest. This paper presents the first polynomial-time approximation scheme (PTAS) for data broadcast with O(1) channels and when each message has arbitrary probability, unit length and bounded cost. The best previous polynomial-time approximation algorithm for this case has a performance ratio of 9/8.