diff --git a/tests/benchmarks/evaluate_logs.ipynb b/tests/benchmarks/evaluate_logs.ipynb
index 7e6390723..c1c311a01 100644
--- a/tests/benchmarks/evaluate_logs.ipynb
+++ b/tests/benchmarks/evaluate_logs.ipynb
@@ -9,7 +9,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 155,
+   "execution_count": 69,
    "metadata": {
     "collapsed": true
    },
@@ -34,7 +34,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 156,
+   "execution_count": 70,
    "metadata": {
     "collapsed": false
    },
@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 157,
+   "execution_count": 71,
    "metadata": {
     "collapsed": false
    },
@@ -135,7 +135,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 161,
+   "execution_count": 72,
    "metadata": {
     "collapsed": false
    },
@@ -144,55 +144,92 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "540\n"
+      "Information for Test 0:\n",
+      "-------------------------------------------------------------------\n",
+      "Not written before connection established: 540\n",
+      "Total of missed steps at send side: 3960\n",
+      "4500 (0.45%) out of 1000000 samples samples were never sent\n",
+      "\n",
+      "\n",
+      "\n"
      ]
     }
    ],
    "source": [
-    "missing_send_arr = []\n",
+    "# Number of samples that were never written\n",
+    "not_written_send_arr = []\n",
     "\n",
-    "# This line indicates if we passed the \"node connected\" line. Only after this line\n",
-    "# the script will start counting missed steps\n",
+    "# Number of samples that were missed by signal node\n",
+    "missed_steps_send_arr = []\n",
+    "\n",
+    "# Total number of missed samples at send sides\n",
+    "total_missed_send_arr = []\n",
+    "\n",
+    "# Percentage of never sent samples samples\n",
+    "perc_miss_send_arr = []\n",
+    "\n",
+    "# This line indicates if we passed the \"node connected\" line. Count only the \"partial writes\" before this line\n",
     "connected = False\n",
     "\n",
     "for i, file in enumerate(log_paths):\n",
+    "    # Open the file\n",
     "    F = open(file, \"r\")\n",
     "    line = F.readline()\n",
-    "\n",
-    "    missing_send_arr.append(0)\n",
-    "\n",
+    "    \n",
+    "    not_written_send_arr.append(0)\n",
+    "    missed_steps_send_arr.append(0)\n",
+    "    \n",
     "    # Loop through file\n",
     "    while line:\n",
-    "        #if re.match(r'.*Connection established in node', line):\n",
-    "        connected = True\n",
+    "        # Check if node is connected\n",
+    "        if re.match(r'.*Connection established in node', line):\n",
+    "            connected = True\n",
     "    \n",
-    "        if connected:\n",
-    "            #matchObj = re.match(r'.*Missed steps: (\\d*)', line, re.M|re.I)\n",
-    "            matchObj = re.match(r'.*written=0, expected=(\\d*)', line, re.M|re.I)\n",
+    "        if not connected:\n",
+    "            # Check for samples that were not written\n",
+    "            matchObj = re.match(r'.*written=(\\d*), expected=(\\d*)', line, re.M|re.I)\n",
     "        \n",
     "            if matchObj:\n",
-    "                missing_send_arr[i] += int(matchObj.group(1))\n",
+    "                not_written_send_arr[i] += int(matchObj.group(2)) - int(matchObj.group(1))\n",
+    "                \n",
+    "        # Check for samples that were never generated\n",
+    "        matchObj = re.match(r'.*missed a total of (\\d*) steps', line, re.M|re.I)\n",
+    "        \n",
+    "        if matchObj:\n",
+    "                missed_steps_send_arr[i] += int(matchObj.group(1))\n",
+    "\n",
     "        \n",
     "        line = F.readline()\n",
     "    \n",
-    "    print(missing_send_arr[i])"
+    "                    \n",
+    "    # Take percentage\n",
+    "    perc_miss_send_arr.append(round((not_written_send_arr[i] + missed_steps_send_arr[i]) / int(settings_array[i][4]) * 100, 2))\n",
+    "    \n",
+    "    print(\"Information for Test {}:\".format(settings_array[i][0]))\n",
+    "    print(\"-------------------------------------------------------------------\")\n",
+    "    print(\"Not written before connection established: {}\".format(not_written_send_arr[i]))\n",
+    "    print(\"Total of missed steps at send side: {}\".format(missed_steps_send_arr[i]))\n",
+    "    \n",
+    "    total_missed_send_arr.append(not_written_send_arr[i] + missed_steps_send_arr[i])\n",
+    "    print(\"{} ({}%) out of {} samples samples were never sent\".format(total_missed_send_arr[i],\n",
+    "                                                                      perc_miss_send_arr[i],\n",
+    "                                                                      settings_array[i][4]))\n",
+    "    \n",
+    "    print(\"\\n\\n\")\n",
+    "    "
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Process data\n",
-    "\n",
-    "### Number of samples\n",
-    "* First number which appears in `result_array[*][3]` will be the first sample in the benchmark. Ignore all missing samples before that entry.\n",
-    "* After that, check how many samples are missing.\n",
-    "* Then, calculate the percentage of missing samples."
+    "## Get missed steps from destination node\n",
+    "..."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 162,
+   "execution_count": 60,
    "metadata": {
     "collapsed": false
    },
@@ -201,37 +238,27 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Test 0 missed 68 (0.011%) of 995605 (1000000 before correction) samples\n"
+      "Test 0 missed 4500 (0.45%) of 1000000 that were intended to send samples\n"
      ]
     }
    ],
    "source": [
-    "# Sequence number of first sample that occurs are receive side\n",
-    "start_sequence = []\n",
-    "# Real total number of sent messages, after subtraction of first sequence\n",
-    "real_total_arr = []\n",
-    "# Number of missing samples after first sample\n",
-    "missing_recv_arr = []\n",
+    "# Number of missing samples at receive side\n",
+    "total_missed_recv_arr = []\n",
     "# Percentage of missed samples\n",
-    "perc_miss_arr = []\n",
+    "perc_miss_recv_arr = []\n",
     "\n",
     "# Generate real total and number of missing samples.\n",
     "# Print percentage of missed samples\n",
     "for (i, csv_vec) in enumerate(result_array):\n",
-    "    start_sequence.append(csv_vec[0][3])\n",
+    "    # Get number of missing samples\n",
+    "    total_missed_recv_arr.append(int(settings_array[i][4]) - len(csv_vec))\n",
     "    \n",
-    "    # Real total number = total number - start_seqquence\n",
-    "    # Number missing = real total number - length of data arary\n",
-    "    real_total = int(settings_array[i][4]) - int(start_sequence[i])\n",
-    "    missing_recv = real_total - len(csv_vec)\n",
-    "    perc_miss = round(missing_recv / real_total * 100, 3)\n",
+    "    # Take percentage\n",
+    "    perc_miss_recv_arr.append(round(total_missed_recv_arr[i] / int(settings_array[i][4]) * 100, 2))\n",
     "    \n",
-    "    print(\"Test {} missed {} ({}%) of {} ({} before correction) samples\"\n",
-    "          .format(i, number_miss, perc_miss, real_total, settings_array[i][4]))\n",
-    "    \n",
-    "    real_total_arr.append(real_total)\n",
-    "    missing_recv_arr.append(number_miss)\n",
-    "    perc_miss_arr.append(perc_miss)"
+    "    print(\"Test {} missed {} ({}%) of {} that were intended to send samples\"\n",
+    "          .format(settings_array[i][0], total_missed_recv_arr[i], perc_miss_recv_arr[i], settings_array[i][4]))"
    ]
   },
   {
@@ -246,11 +273,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 107,
+   "execution_count": 68,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "import matplotlib.pyplot as plt\n",
     "from matplotlib.font_manager import FontProperties\n",
@@ -310,8 +348,12 @@
     "    \n",
     "    # Create text for missed steps\n",
     "    #ToDo: Add percentage\n",
-    "    missed_text  = 'missed by villas-pipe:  {0: <23}\\n'.format(missing_recv_arr[i])\n",
-    "    missed_text += 'missed by villas-node: {0: <23}'.format(0)\n",
+    "    missed_text  = '{0: <22} {1: <8} ({2: <5}%)\\n'.format(\"missing at send side:\",\n",
+    "                                                           total_missed_send_arr[i],\n",
+    "                                                           perc_miss_send_arr[i])\n",
+    "    missed_text += '{0: <23} {1: <8} ({2: <5}%)'.format(\"missing at recv side:\",\n",
+    "                                                         total_missed_recv_arr[i],\n",
+    "                                                         perc_miss_recv_arr[i])\n",
     "           \n",
     "    # bbox accepts FancyBboxPatch prop dict\n",
     "    font_header = FontProperties()\n",