n Self-Organization represents a kind of construction and organization mode from logical perspective of Cognitive Networks. It is more like a bridge connecting self- awareness and autonomy. There are two extended characteristics-self-learning self-reasoning, self-interacting, and self-sustaining-included to fully complete the functions of self-organization. Reference [55] indicates the meaning of self-organization from the perspective of biology. Actually, self-organization consists of a series of low-level components which are autonomous and operate independently following certain rules without unnecessary manual interventions. What is more important is that, these autono- mous components can pose a positive or negative influence by changing their behaviors. Thus, the whole system can act as a biological system with self-feedback, self-modification, and self-progress. Meanwhile, the stability as well as the reliabil- ity of system is significantly improved and guaranteed. Among those extended characteristics, self-interaction is one characteristic reflecting communication among components, while self-sustaining offers criteria for the stability of the system. Principles of self-learning and self-reasoning can be described by Figure 6.4. In Figure 6.4, learning is carried out in certain environment system, which can also enrich knowledge base. At the same time, knowledge in knowledge base can also benefit the process of learning. Besides, reasoning based on knowledge, can directly act on the performance of the system under the same environment. To put it in a nutshell, the operation of self-learning and self-reasoning is another feedback cycle and turns out to be the core part of self-organization. 6.3.2.3.3 Autonomy Autonomy is driven by business goals, service performance and efficiency, acting as an intelligent and automatic approach of guarantees of network performance and Overview of Cognitive NGSDP Model Performance Environment Knowledge Learning Figure 6.4 Functions cycle of self-learning and self-inductio