Читать книгу Dynamic Spectrum Access Decisions - George F. Elmasry - Страница 84

In this section, we apply the cloud services model to DSA services. Figure 5.6 shows the standard cloud services model applied to DSA with three distinct stages:

1 The pre‐run stage defines the service and the service agreement.

2 The runtime stage, represented by the gray rectangle, where the service is monitored and enforced to meet the service agreement.

3 Post processing, where service accountability is measured.

Figure 5.6 The DSA cloud services model.

The first step in the Figure 5.6 model application to DSA services is simple. One of the DSA cloud services, such as response time, is selected. In typical cloud services, customer response time can be defined in the service agreement and the customer can know the response time before purchasing the service. DSA also needs a service agreement. The definition of a service agreement with DSA can be driven from system requirements and analysis. Response time can be the time between an entity reporting suffering from interference above a certain threshold (that can render connectivity to be lost or bandwidth to be below a certain value) and the time a new frequency band is assigned to overcome interference.

The gray rectangle in Figure 5.6 shows the runtime aspects of a cloud service where the service is monitored and policies, rule sets, and configuration parameters are adapted in order to force the service to adhere to the defined agreement. With DSA as a cloud service, policies, rule sets, and configuration parameter updates can be triggered by the DSA cognitive engine resource monitor, as shown in Figure 5.2, or by the decision maker, as shown in Figure 5.3. These actions are made in order to enforce the service to adhere to the service agreement during runtime. With DSA as a service, the design can create log files that can be analyzed as post processed in order to evaluate the DSA service accountability over a long period of time.

With DSA as a set of cloud services, while service agreements can be driven from system requirements, the design of DSA cloud services has to create metrics to help force the services to conform to the agreement and use metrics for measuring services accountability. The cognitive engine‐based design would have to gain understanding of the properties of the metrics used to force the service to adhere to the service agreement and scripted scenarios must be used to assess service accountability before system deployment.