PROJECT TITLE :

A Novel Scheduling Algorithm for Supporting Periodic Queries in Broadcast Environments

ABSTRACT:

Being a proven efficient approach to answering queries that have common data wants, knowledge broadcast has received much attention within the past decade, especially for dynamic and giant-scale data dissemination. An necessary class of rising information broadcast applications must monitor multiple knowledge items continuously so as to enable data-driven call making. For such applications, an vital problem that has got to be addressed is a way to disseminate information to periodic continuous queries therefore that all the requests will be happy while the bandwidth utilization is minimized. To our greatest knowledge, the only known work on this topic is that the RM-UO algorithm proposed in [27] . But, the RM-UO algorithm merely utilizes the algorithm introduced in [13] to remodel the original queries into -harmonic tasks, which would lead to a considerable waste of available bandwidth. During this paper, primarily based on the observation that some queries can be merged to avoid wasting bandwidth consumption, we propose 2 merging polices namely Multiple Question Merging ( ) and Redundant Question Merging ( ), and show that both will result in notable bandwidth savings. Additional, to disseminate data to periodic continuous queries, we tend to implement a unified scheduling algorithm known as , that combines each and . Intensive experiments are conducted to compare our algorithm with RM-UO, and also the results show that outperforms RM-UO considerably in terms of wireless bandwidth consumption and query service ratio.