This book is organized around the notions of scaling phenomena and scale invariance. The various stochastic models commonly used to describe scaling are introduced: self-similarity, long-range dependence and multi-fractals. These models are compared and related one to the other. Second, they introduce fractional integration, a mathematical tool closely related to the notion of scale invariance. Also, they define stochastic processes with prescribed scaling properties (self-similar processes, locally self-similar processes, fractionally filtered processes, iterated function systems). A number of applications where the scaling paradigm proved fruitful are detailed: image processing, financial and stock market fluctuations, geophysics, scale relativity and fractal time-space.