Time Aware Task Delegation in Agent Interactions for Video-Surveillance

Cameras are everywhere and the interest towards distributed surveillance systems is growing both in academic research and commercial applications. Multi-Agent Systems (MASs) are ideal to design and develop such applications: distributed by nature, the capability of software agents to communicate using messages and interaction protocols can be exploited to coordinate and control distributed surveillance system. However, there is also the need to optimize the use of available resources as the bandwidth to achieve on-line performances for automatic analysis algorithms. In this regard, this paper presents a multi-agent distributed video surveillance system to perform face recognition. The main goal of the system is to reduce the need to transmit the frames to be analyzed over the network. Each node of the system checks the available elaboration time to decide whether the face recognition should be performed locally (in the node which detected the faces) or remotely (in other nodes of the system), delegating the task. To achieve the delegation, the agents interact via a market-based protocol, the Extended Contract Net Protocol (ECNP). The test results show a two order of magnitude decrease in the size of data transmitted over the network to perform the face recognition. In addition, the proposed agent architecture is a first step towards more general real-time compliant multi-agent systems, by using the elaboration time to regulate the agents’ behaviours. Future steps include a deeper analysis of the interactions among agents to meet strict time constraints.