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In an attempt to cope with time-varying workload, traditional adaptive Time Warp protocols are designed to react in response to performance changes by altering control parameter configurations, like the amount of available memory, the size of the checkpointing interval, the frequency of GVT computation, fossil collection invocations, etc.\ We call those schemes ``reactive'' because all control decisions are undertaken based on historical performance information collected at runtime, and come into effect in future system states. What must be considered a drawback of this class of approaches is that Time Warp logical processes (LPs) have most likely reached a state different from the one for which the control action was established - thus inducing performance control activities which are always outdated.This paper develops environment aware, self adaptive Time Warp LPs implementing a pro-active performance control scheme, addressing the timeliness of control decisions. Opposed to reactive TW schemes, our pro-active control mechanism based on a statistical analysis of the state history periodically collected in (real) time intervals of size d, forecasts a future LP state. A performance control decision is established, that is most appropriate for the expected future LP state, i.e. the state when the corresponding control activity would become effective. Depending on the forecast quality, a pro-active scheme will presumably exhibit performance superior to re-active schemes, at least for cases where state changes in the time frame $\Delta$ are very likely. In this paper we study the ability of pro-active TW LPs, to adapt to sudden load changes, especially to abruptly occurring background workloads injected by other applications executing concurrently with the TW simulation on a network of workstations. Experimental results show that the protocol is able to capture abrupt changes in both computational and communication resource availability, justifying the title: "shock resistant Time Warp".