The machine-to-machine (M2M) service network platform that accommodates and controls various types of Internet of Things devices has been presented. This paper investigates program file placement strategies for the M2M service network platform that achieve low blocking ratios of new task requests and accommodate as many tasks as possible in the dynamic scenario. We present four strategies for determining program file placement, which differ in the computation method and whether the relocation of program files being used by existing tasks is allowed or not. Simulation results show that a strategy based on solving a mixed-integer linear programming model achieves the lowest blocking ratio, but a heuristic algorithm-based strategy can be an attractive option by allowing recomputation of the placement when the placement cannot be obtained at the timing of new task request arrival.