lytics and collector MSs. 8.3.4 CONTROL-LOOP AUTOMATION An intelligent service collects information about resources (users, devices, networks, and applica- tions) used to deliver the service and about the environment in which it operates. It then makes deci- sions based on this information and domain knowledge, which includes adapting and personalizing Building the Network of the Future Data Collection Data Analytics Control Policy FIGURE 8.12 Basic components of a control-loop automation system. the service for the users consuming it. An intelligent service receives feedback on its performance and learns. There are primarily three attributes that characterize an intelligent service, known as personalized, adaptive, and dynamic (PAD). A predictive personalized service is one that antici- pates a user's need and proactively takes intelligent actions and recommends valuable and timely personalized information. An adaptive service learns from its past actions of all users and adjusts its behavior to provide superior service quality. A service that is dynamic is one that is robust and can survive and self-repair or self-organize itself from possible service interruptions. In this section, we describe how intelligent services can be described essentially in the form of control-loop systems. These systems have been widely used in system design. The basic concept is to compute an error signal between an actual target and measurements computed from sensors and through a feedback control loop to attain a desired state where the error is zero. One example is a home thermostat that is continuously controlling the heating/cooling system to maintain a desired room temperature. The basic components of such a system, as shown in Figure 8.12, includes data collection for measuring the current temperature, data analytics to compute the variation between the desired and actual readings, policy for recommending the next best action, and a controller for per- forming the action. The action may include turning the heating on/off, coo