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Design of Capability
Delivery Adjustments
Jānis Grabis, Jānis Kampars
Institute of Information Technology, Riga Technical University,
Kalku 1, Riga, Latvia
Outline
• Problem area
• Background
• Types of adjustments and their modeling
• Example
• Conclusion
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
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
Capability Delivery Application
Context
Capability
Delivery
Application
Goals
KPI
Patt-
erns Pattern RepositoryAdjustments
CDD Environment
CCP
Context data
retrieval
CPR
Pattern repository
CDA
Business service
CDT
Capability modeling
CNA
Monitoring
Adjust-
ment
Types of Adjustments
Adjustment
Calculation
Context
calculation
Performance
calculation
Adaptive
adjustment
Scheduled
adjustment
Event based
adjustment
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
Adjustment Modeling
• Event based
adjustment
• Scheduled
adjustment
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
Image Processing Service
CDA frontend
(image processing web site)
Msg Queue
Task
Container X
Container I
Mosaic
Request
Mosaic
Capability
Model
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
Adjustment execution
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

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Design of Capability Delivery Adjustments @ASDENCA

  • 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
  • 6. CDD Environment CCP Context data retrieval CPR Pattern repository CDA Business service CDT Capability modeling CNA Monitoring Adjust- ment
  • 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
  • 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
  • 15.
  • 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