ViCo: An adaptive distributed video correlation system

Abstract

Many emerging applications such as video sensor monitoring can benefit from an on-line video correlation system, which can be used to discover linkages between different video streams in realtime. However, on-line video correlations are often resource-intensive where a single host can be easily overloaded. We present a novel adaptive distributed on-line video correlation system called ViCo. Unlike single stream processing, correlations between different video streams require a distributed execution system to observe a new correlation constraint that any two correlated data must be distributed to the same host. ViCo achieves three unique features: (1) correlation-awareness that ViCo can guarantee the correlation accuracy while spreading excessive workload on multiple hosts; (2) adaptability that the system can adjust algorithm behaviors and switch between different algorithms to adapt to dynamic stream environments; and (3) fine-granularity that the workload of one resource-intensive correlation request can be divided and distributed among multiple hosts. We have implemented and deployed a prototype of ViCo on a commercial cluster system. Our experiment results using both real videos and synthetic workloads show that ViCo outperforms existing techniques for scaling-up the performance of video correlations. Copyright 2006 ACM.