Frequent-Pattern Based Broadcast Scheduling for Conflict Avoidance in Multi-Channel Data Dissemination Systems

TL;DR

This paper introduces FPBS, a novel broadcast scheduling method that uses frequent pattern trees to avoid data conflicts in multi-channel wireless data dissemination, significantly reducing access time.

Contribution

The paper proposes FPBS, a new scheduling algorithm utilizing FP*-trees to prevent data conflicts in multi-channel broadcasting, addressing the NP-complete DBCA problem.

Findings

FPBS reduces average access time by 30% compared to heuristics.

It effectively avoids data conflicts in multi-channel broadcast scheduling.

The approach is validated through simulations in online and offline modes.

Abstract

With the popularity of mobile devices, using the traditional client-server model to handle a large number of requests is very challenging. Wireless data broadcasting can be used to provide services to many users at the same time, so reducing the average access time has become a popular research topic. For example, some location-based services (LBS) consider using multiple channels to disseminate information to reduce access time. However, data conflicts may occur when multiple channels are used, where multiple data items associated with the request are broadcast at about the same time. In this article, we consider the channel switching time and identify the data conflict issue in an on-demand multi-channel dissemination system. We model the considered problem as a Data Broadcast with Conflict Avoidance (DBCA) problem and prove it is NP-complete. We hence propose the frequent-pattern based broadcast scheduling (FPBS), which provides a new variant of the frequent pattern tree, FP*-tree, to schedule the requested data. Using FPBS, the system can avoid data conflicts when assigning data items to time slots in the channels. In the simulation, we discussed two modes of FPBS: online and offline. The results show that, compared with the existing heuristic methods, FPBS can shorten the average access time by 30%.