We investigate the tail asymptotics of the response time distribution for the cancel-on-start (c.o.s.) and cancel-on-completion (c.o.c.) variants of redundancy- scheduling and the fork-join model with heavy-tailed job sizes. We present bounds, which only differ in the pre-factor, for the tail probability of the response time in the case of the first-come first-served (FCFS) discipline. For the c.o.s. variant we restrict ourselves to redundancy- scheduling, which is a special case of the fork-join model. In particular, for regularly varying job sizes with tail index the tail index of the response time for the c.o.s. variant of redundancy- equals , where $d_{} = \min{d,N-k}Nk$ is the integer part of the load. This result indicates that for the waiting time component is dominant, whereas for $d_{} > \frac{\nu}{\nu-1}d = \lceil \min{\frac{\nu}{\nu-1},N-k} \rceil$ replicas is sufficient to achieve the optimal asymptotic tail behavior of the response time. For the c.o.c. variant of the fork-join() model the tail index of the response time, under some assumptions on the load, equals and , for identical and i.i.d. replicas, respectively; here the waiting time component is always dominant.

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