From 598779089e67608ea8c592ef75697eb5c1ba37bf Mon Sep 17 00:00:00 2001
From: Dmytro Pukhkaiev <dmytro.pukhkaiev@tu-dresden.de>
Date: Fri, 7 Dec 2018 16:37:52 +0100
Subject: [PATCH] Linear normalizer with Java
---
.../clustering/AbstractNormalizer.java | 14 +++++
.../solving/clustering/HardwareComponent.java | 26 +++++++-
.../st/mquat/solving/clustering/KMeans.java | 62 ++++++++++++++++---
.../solving/clustering/LinearNormalizer.java | 25 ++++++++
.../mquat/solving/clustering/Normalizer.java | 7 +++
.../solving/clustering/StudentNormalizer.java | 12 ++++
6 files changed, 137 insertions(+), 9 deletions(-)
create mode 100644 jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/AbstractNormalizer.java
create mode 100644 jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/LinearNormalizer.java
create mode 100644 jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/Normalizer.java
create mode 100644 jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/StudentNormalizer.java
diff --git a/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/AbstractNormalizer.java b/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/AbstractNormalizer.java
new file mode 100644
index 0000000..2f91011
--- /dev/null
+++ b/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/AbstractNormalizer.java
@@ -0,0 +1,14 @@
+package de.tudresden.inf.st.mquat.solving.clustering;
+
+import java.util.Map;
+
+public abstract class AbstractNormalizer implements Normalizer {
+ Map<String, Double> minValue;
+ Map<String, Double> maxValue;
+
+ public AbstractNormalizer(Map<String, Double> minValue, Map<String, Double> maxValue){
+ this.minValue = minValue;
+ this.maxValue = maxValue;
+ }
+
+}
diff --git a/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/HardwareComponent.java b/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/HardwareComponent.java
index 5f334aa..aebe9cb 100644
--- a/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/HardwareComponent.java
+++ b/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/HardwareComponent.java
@@ -4,6 +4,9 @@ import de.tudresden.inf.st.mquat.jastadd.model.Resource;
import weka.core.DenseInstance;
import weka.core.Instance;
+import java.util.HashMap;
+import java.util.Map;
+
/***
* An entity unifying WEKA instances and Jastadd resources
*/
@@ -11,10 +14,15 @@ public class HardwareComponent {
private Resource resource;
private Instance instance;
+ //TODO: do it with Jastadd
+ private Map<String, Double> value;
+ private Map<String, Double> normalizedValue;
- public HardwareComponent(Resource resource, int attributes_number) {
+ HardwareComponent(Resource resource, int attributes_number) {
this.resource = resource;
this.instance = new DenseInstance(attributes_number);
+ value = new HashMap<>();
+ normalizedValue = new HashMap<>();
}
public Resource getResource() {
@@ -32,4 +40,20 @@ public class HardwareComponent {
public void setInstance(Instance instance) {
this.instance = instance;
}
+
+ public Map<String, Double> getValue() {
+ return value;
+ }
+
+ public void setValue(Map<String, Double> value) {
+ this.value = value;
+ }
+
+ public Map<String, Double> getNormalizedValue() {
+ return normalizedValue;
+ }
+
+ public void setNormalizedValue(Map<String, Double> normalizedValue) {
+ this.normalizedValue = normalizedValue;
+ }
}
diff --git a/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/KMeans.java b/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/KMeans.java
index 04ea64d..fd1746c 100644
--- a/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/KMeans.java
+++ b/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/KMeans.java
@@ -6,9 +6,7 @@ import weka.clusterers.*;
import weka.core.Attribute;
import weka.core.Instances;
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.Map;
+import java.util.*;
/***
* Wrapper for WEKA SimpleKMeans. Clustering based on:
@@ -28,6 +26,10 @@ public class KMeans{
// list of resources
private ArrayList<HardwareComponent> hardwareComponentList = new ArrayList<>();
+ /***
+ * Prepare clustering algorithm, extract WEKA instances from Jastadd model
+ * @param model Jastadd model
+ */
public KMeans(Root model) {
// create attributes for instances
Attribute cpu = new Attribute("cpu");
@@ -53,16 +55,20 @@ public class KMeans{
String typeName = sub.getType().getName().getName();
switch (typeName) {
case "CPU":
- hardwareComponent.getInstance().setValue(cpu, sub.getCurrentValueByPropertyName("frequency"));
+ hardwareComponent.getValue().put("CPU", sub.getCurrentValueByPropertyName("frequency"));
+ //hardwareComponent.getInstance().setValue(cpu, sub.getCurrentValueByPropertyName("frequency"));
break;
case "RAM":
- hardwareComponent.getInstance().setValue(ram, sub.getCurrentValueByPropertyName("total"));
+ hardwareComponent.getValue().put("RAM", sub.getCurrentValueByPropertyName("total"));
+ //hardwareComponent.getInstance().setValue(ram, sub.getCurrentValueByPropertyName("total"));
break;
case "DISK":
- hardwareComponent.getInstance().setValue(disk, sub.getCurrentValueByPropertyName("total"));
+ hardwareComponent.getValue().put("DISK", sub.getCurrentValueByPropertyName("total"));
+ //hardwareComponent.getInstance().setValue(disk, sub.getCurrentValueByPropertyName("total"));
break;
case "NETWORK":
- hardwareComponent.getInstance().setValue(network, sub.getCurrentValueByPropertyName("throughput"));
+ hardwareComponent.getValue().put("NETWORK", sub.getCurrentValueByPropertyName("throughput"));
+ //hardwareComponent.getInstance().setValue(network, sub.getCurrentValueByPropertyName("throughput"));
break;
default:
throw new RuntimeException("Unable to transform unknown resource of type" + typeName);
@@ -73,8 +79,48 @@ public class KMeans{
}
}
- for (HardwareComponent hwc : hardwareComponentList)
+ Map<String, Double> minValue = new HashMap<>();
+ Map<String, Double> maxValue = new HashMap<>();
+
+ for (HardwareComponent hwc :hardwareComponentList){
+ for (String key : hwc.getValue().keySet()){
+ if (! minValue.containsKey(key))
+ minValue.put(key, hwc.getValue().get(key));
+ else if (minValue.get(key) > hwc.getValue().get(key))
+ minValue.put(key, hwc.getValue().get(key));
+
+ if (! maxValue.containsKey(key))
+ maxValue.put(key, hwc.getValue().get(key));
+ else if (maxValue.get(key) < hwc.getValue().get(key))
+ maxValue.put(key, hwc.getValue().get(key));
+ }
+ }
+ LinearNormalizer linearNormalizer = new LinearNormalizer(minValue, maxValue);
+
+ for (HardwareComponent hwc : hardwareComponentList) {
+ hwc.setNormalizedValue(linearNormalizer.normalize(hwc));
+ for (String key : hwc.getNormalizedValue().keySet()){
+ switch (key){
+ case "CPU":
+ hwc.getInstance().setValue(cpu, hwc.getNormalizedValue().get(key));
+
+ break;
+ case "RAM":
+ hwc.getInstance().setValue(ram, hwc.getNormalizedValue().get(key));
+ break;
+ case "DISK":
+ hwc.getInstance().setValue(disk, hwc.getNormalizedValue().get(key));
+ break;
+ case "NETWORK":
+ hwc.getInstance().setValue(network, hwc.getNormalizedValue().get(key));
+
+ break;
+ default:
+ throw new RuntimeException("Unable to transform unknown resource of type" + key);
+ }
+ }
resources.add(hwc.getInstance());
+ }
k = (int) (0.2 * model.getHardwareModel().getResourceList().asJavaCollection().size());
diff --git a/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/LinearNormalizer.java b/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/LinearNormalizer.java
new file mode 100644
index 0000000..345a8e9
--- /dev/null
+++ b/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/LinearNormalizer.java
@@ -0,0 +1,25 @@
+package de.tudresden.inf.st.mquat.solving.clustering;
+
+import de.tudresden.inf.st.mquat.jastadd.model.Resource;
+
+import java.util.HashMap;
+import java.util.Map;
+
+public class LinearNormalizer extends AbstractNormalizer implements Normalizer {
+
+ public LinearNormalizer(Map<String, Double> minValue, Map<String, Double> maxValue)
+ {
+ super(minValue, maxValue);
+ }
+
+ @Override
+ public Map<String, Double> normalize(HardwareComponent hardwareComponent) {
+ Map<String, Double> normalizedHWC = new HashMap<>();
+ for (String key : hardwareComponent.getValue().keySet()){
+ double normalized =
+ (hardwareComponent.getValue().get(key) - minValue.get(key))/(maxValue.get(key) - minValue.get(key));
+ normalizedHWC.put(key, normalized);
+ }
+ return normalizedHWC;
+ }
+}
diff --git a/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/Normalizer.java b/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/Normalizer.java
new file mode 100644
index 0000000..5754695
--- /dev/null
+++ b/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/Normalizer.java
@@ -0,0 +1,7 @@
+package de.tudresden.inf.st.mquat.solving.clustering;
+
+import java.util.Map;
+
+public interface Normalizer {
+ Map<String, Double> normalize(HardwareComponent resource);
+}
diff --git a/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/StudentNormalizer.java b/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/StudentNormalizer.java
new file mode 100644
index 0000000..2ec9b3d
--- /dev/null
+++ b/jastadd-mquat-solver-ilp/src/main/java/de/tudresden/inf/st/mquat/solving/clustering/StudentNormalizer.java
@@ -0,0 +1,12 @@
+package de.tudresden.inf.st.mquat.solving.clustering;
+
+import java.util.HashMap;
+import java.util.Map;
+
+public class StudentNormalizer implements Normalizer {
+
+ @Override
+ public Map<String, Double> normalize(HardwareComponent hardwareComponent) {
+ return new HashMap<>();
+ }
+}
--
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