# C2 Concepts: Summary ## C2 Functions 1. Establishing intent. 2. Determining roles, responsibilities and relationships. 3. Establishing rules and constraints. 4. Monitoring and assessing the situation and progress. 5. Inspiring, motivating and engendering trust. 6. Training and education. 7. Provisioning. ## Approaches to Information Sharing 1. Push - Broadcast. 2. Post. 3. Pull - Incl. Smart Pull. 4. Subscribe. ## C2 Networks 1. **Fully connected networks:** 1. Every node is connected to every other node. 2. **Random networks:** 1. Develops when each node has an equal probability of interacting with any other node. 2. Forms relatively few clusters. 3. Follows a normal or Poisson distribution - or bell curve. 4. Not very efficient - takes a very large number of steps to get from one node to another. 5. Lack resilience. 6. Removing a modest number of nodes or linkages will splinter it into a number of unconnected structures. 7. Sometimes referred to as egalitarian networks. 3. **Scale-free networks:** 1. Extreme distribution of interactions amongst nodes. 2. A few nodes have a very large number of interactions, most nodes have few interactions. 3. Has a power law distribution. 4. Distribution sharply skewed towards origin with long flat tale. 5. Found throughout nature - wherever complex adaptive systems develop. 6. Most stable, naturally evolved complex adaptive systems operate as scale-free networks. 7. Examples include - Branches of a river system and Distribution of nodes in the internet. 8. Contains sets of naturally occurring clusters (aka; Hubs). 9. Strong and capable social network. 10. Sometimes referred to as aristocratic networks. 4. **Small world networks:** 1. Richest, most efficient class of network. 2. Moving information from any one node in the network to another requires only a very small number of steps. 3. Very large clustering coefficient. 4. Actual structure of most effective groups of experts. 5. Link clusters together that can be thought of as communities of interest - each community forms its own "small world". 6. Can evolve from or evolve into scale-free networks. 7. The networks required for self-synchronization or Edge organizations are small world networks in which those with the relevant knowledge and capabilities form richly linked and frequently interacting clusters that permit them to exchange information, develop shared situation awareness, and collaborate in order to synchronize their plans (explicit or implicit) and undertake synergistic actions. 5. **Richest Network Structure:** 1. Most resilient, richest network structure is a hybrid of the above structures. 2. Looks like a scale-free network at the global level; 3. A small world network at the intermediate level; and 4. A fully-connected network at the local level. 5. These patterns of interaction are capable of becoming complex adaptive systems. ## Information Flow 1. Data becomes information when uncertainty is reduced. 2. Information becomes awareness when it passes from information systems into the cognitive domain (the human brain). 3. Humans, as individuals, hold awareness of situational information and combine it with prior knowledge and mental models (which include perceptual filters that may prevent awareness of some information) to generate situation understanding - which includes some perceptions of cause and effect relationships at work and their temporal dynamics. 4. These elements of the sensemaking process also drive decision making.