CaaS project's results presented at the ASDENCA workshop preceeding CAiSE 2016

1. Design of Capability
Delivery Adjustments
Jānis Grabis, Jānis Kampars
Institute of Information Technology, Riga Technical University,
Kalku 1, Riga, Latvia

2. Outline
• Problem area
• Background
• Types of adjustments and their modeling
• Example
• Conclusion

3. Problem Area
• Development of adaptive applications
– Incl., context aware applications
• Complex, often computationally intensive
processing logics
• High volatility and variety of context and
other input data
• Adaptation criteria

4. Capability Delivery Application
• Companies provide business services
• Capability driven approach ensures service
delivery in different contextual situation
– With minimum context specific development
effort
• Capability delivery applications provide
capability enabled business services
– Context dependency processing is decoupled
from the core applications

5. Capability Delivery Application
Context
Capability
Delivery
Application
Goals
KPI
Patt-
erns Pattern RepositoryAdjustments

6. CDD Environment
CCP
Context data
retrieval
CPR
Pattern repository
CDA
Business service
CDT
Capability modeling
CNA
Monitoring
Adjust-
ment

7. Types of Adjustments
Adjustment
Calculation
Context
calculation
Performance
calculation
Adaptive
adjustment
Scheduled
adjustment
Event based
adjustment

8. Types of Adjustments
Calculations • Transforming raw context data into
meaningful interpretations for driving
service delivery
• Calculation of performance indicators
Scheduled
adjustments
• Adjustment is run according to a
specified schedule
• It alters behavior (e.g., parameters) of
the capability delivery applications
Event based
adjustment
• Capability delivery application invokes
scheduled adjustment whenever it
needs to make a context dependent
service delivery decision

9. Adjustment Modeling
• Event based
adjustment
• Scheduled
adjustment

10. Example
• A web service for processing images
– e.g. creating mosaics
• CDA is run on the cloud platform
• CNA changes parameters of the cloud
platform to ensure acceptable service
response time
• Adaptation algorithm is implemented as a
scheduled adjustment

11. Image Processing Service
CDA frontend
(image processing web site)
Msg Queue
Task
Container X
Container I
Mosaic
Request
Mosaic

12. Capability
Model

13. Scheduled Adjustment
public class ScaleScheduledAdjustment {
public String execute(int min_nodes,
int max_nodes, int max_wait_time,
int queue_size, int nodes_count,
int avg_time_in_queue,
int busy_nodes) {
try {
// Empty queues and surplus of
workers
if (min_nodes < 1)
return "";
this.debug("nodes cur-" +
nodes_count + " min-" + min_nodes
+ " max-" + max_nodes + "
busy-" + busy_nodes);
// Scale up if requests in queue,
average time exceeds constant and
// max nodes not reached
if ((queue_size > 0) &&
(avg_time_in_queue > max_wait_time)
&& (nodes_count <=
max_nodes)) {
this.scale("up");
return "CASE1: scaling up to "
+
Integer.toString(nodes_count + 1) + "
nodes (cur:"
+ nodes_count + " min:" +
min_nodes + " max:"
+ max_nodes + ")";
}
• Adjustment increases a number of containers if
waiting time increases
• Adjustment decreases a number of containers if
waiting time decreases
• Adjustment changes resolution of external
services respond slowly

14. Adjustment execution

16. Conclusion
• Adjustments allow for separation of
concerns
• Adjustments serve as containers for
implementing adaption algorithms of
varying complexity
• Adjustments are the key mechanisms for
enabling business service delivery in
changing circumstances