A scalable and elastic cloud-assisted publish/subscribe model for IPTV video surveillance system

In this paper, we present a scalable and elastic content-based publish/subscribe model over cloud computing platform to support a smart, flexible and ubiquitous IPTV video surveillance system. Through this system, users of a surveillance system can subscribe to many surveillance events and receive video streams as a notification of new event occurring. This has direct impact on the way surveillance activities are carried out in different application domains including public safety and security, healthcare surveillance, etc. In the publish/subscribe model, it is challenging to match the events with the subscriptions efficiently that contains a large number of live contents. Existing algorithms on event matching are not very effective in the case of range predicates in subscriptions that are commonly used in IPTV video surveillance-based healthcare system and other areas. This paper addresses the aforementioned issue and propose an elastic and scalable algorithm for event matching in IPTV video surveillance over cloud platform. We also show the performance assessment of the proposed event matching algorithm in cloud-based IPTV video surveillance scenario and compare with various state-of-the-art approaches.