A mobile agent-based system for dynamic task allocation in clusters of embedded smart cameras

This paper presents a dynamic task allocation method for smart cameras targeting traffic surveillance. Since our target platforms are distributed embedded systems with limited resources, the task allocation has to be light-weight, flexible as well as scalable and has to support real-time requirements. Therefore, surveillance tasks are not allocated to smart cameras directly, but to groups of smart cameras, so called surveillance clusters. We formulate the allocation problem as a distributed constraint satisfaction problem (DCSP) and present a distributed method for finding feasible allocations. Finally, a cost function is used to determine the optimal allocation of tasks. We have realized this dynamic task allocation using heterogeneous, mobile agents, which utilize their agencies and our embedded software framework to find the most appropriate mapping of tasks in a distributed manner. The dynamic task allocation has been implemented on our smart cameras (SmartCam), which are comprised of a network processor and several digital signal processors (DSPs) and provide a complex software framework.