Let U be the total payload arriving in one slot. Conditional on its Poisson packet count, use the exponential moment of each independent payload to get, for ,
For net work , its cumulant-generating function is
The mean net work is . Under the arrivals-before-service slot convention the Lindley recursion gives stationary queue workload . The positive root of the exponential-moment equation is . Thus is a nonnegative martingale. Stop it at the first crossing of r or a finite horizon; its value on the crossing event is at least . Increasing the horizon proves
This is an infinite-horizon bound, not a one-slot Chernoff estimate.
A useful refinement identifies both the exponential rate and the small-slot prefactor. Couple the random walk to the continuous compound Poisson input U(t), and write and . Their laws are the continuous and slot-boundary stationary queue workloads. Monotonicity of U implies the grid-sampled compound Poisson workload bound: , by rounding each t up to the next grid point.
The continuous queue workload law can be obtained directly from the stationary packet count. Conditional on Q=k, the k remaining payloads are independent unit-mean exponentials: unserved payloads have not affected earlier service completions, and the in-service residual uses the memoryless property. Hence
Thus W has mass at zero, and its positive part is exponential with rate . Combining this stationary workload of an exponential-payload queue with the grid bound gives the explicit estimate
In particular , and for small delta the estimate is . The exact continuous-time tail is that latter expression. Another slot convention may shift queue workload by the within-slot input/service timing; its convention must be specified before asserting a prefactor, while this exponential tail rate is unchanged.