A generalization result regarding the small and large scale behavior of infinitely divisible processes

General conditions for normalized, time-scaled stochastic integrals of independently scattered Levy random measures to converge to a limit are described. The idea is to provide general conditions to bypass the use of characteristic functions, which can sometimes have tedious calculations, to simplify and shorten the proofs of convergence of infinitely divisible processes, which have previously been done on a case by case basis. It is of particular interest to study both small and large scale asymptotics, since there are many applications, such as modeling internet traffic. The purpose of this paper is to generalize previous results to the greater class of all stochastically continuous (or, more generally, separable in probability) infinitely divisible processes with no Gaussian part and to expand the results to the multi-dimensional case.