Create edge_computing.py

Author: KOSASIH

src/quantum_consensus/edge_computing.py

@@ -0,0 +1,96 @@
+# src/quantum_consensus/edge_computing.py
+
+import logging
+import random
+import time
+from concurrent.futures import ThreadPoolExecutor
+
+# Set up logging for the edge computing module
+logger = logging.getLogger(__name__)
+
+class EdgeComputing:
+    def __init__(self, node_id, num_nodes):
+        """
+        Initialize the Edge Computing integration.
+
+        Parameters:
+        - node_id (str): Unique identifier for the node.
+        - num_nodes (int): Total number of nodes participating in the consensus.
+        """
+        self.node_id = node_id
+        self.num_nodes = num_nodes
+        self.local_data = []  # Local data storage for processing
+        logger.info(f"Edge Computing initialized for node {self.node_id}.")
+
+    def collect_data(self, data):
+        """
+        Collect data for processing.
+
+        Parameters:
+        - data (any): The data to be collected and processed.
+        """
+        self.local_data.append(data)
+        logger.info(f"Node {self.node_id} collected data: {data}")
+
+    def process_data(self):
+        """
+        Process the collected data locally.
+
+        Returns:
+        - list: Processed results.
+        """
+        logger.info(f"Node {self.node_id} processing data...")
+        processed_results = [self._simulate_processing(d) for d in self.local_data]
+        logger.info(f"Node {self.node_id} processed data: {processed_results}")
+        return processed_results
+
+    def _simulate_processing(self, data):
+        """
+        Simulate data processing.
+
+        Parameters:
+        - data (any): The data to process.
+
+        Returns:
+        - any: Simulated processed result.
+        """
+        time.sleep(random.uniform(0.1, 0.5))  # Simulate processing time
+        return f"Processed({data})"
+
+    def reach_consensus(self, proposed_value):
+        """
+        Reach consensus using the processed data.
+
+        Parameters:
+        - proposed_value (any): The value proposed by the node for consensus.
+
+        Returns:
+        - bool: True if consensus is reached, False otherwise.
+        """
+        logger.info(f"Node {self.node_id} proposing value for consensus: {proposed_value}")
+        with ThreadPoolExecutor(max_workers=self.num_nodes) as executor:
+            futures = [executor.submit(self._vote, proposed_value) for _ in range(self.num_nodes - 1)]
+            votes = [future.result() for future in futures]
+
+        consensus_result = all(votes)
+        if consensus_result:
+            logger.info(f"Consensus reached on value: {proposed_value}")
+        else:
+            logger.warning(f"Consensus not reached for value: {proposed_value}")
+
+        return consensus_result
+
+    def _vote(self, proposed_value):
+        """
+        Simulate a vote based on local processing results.
+
+        Parameters:
+        - proposed_value (any): The value proposed by the node for consensus.
+
+        Returns:
+        - bool: Simulated vote result (True/False).
+        """
+        # Simulate a voting mechanism based on local processing results
+        vote = random.choice([True, False])
+        logger.info(f"Node {self.node_id} voted: {'Yes' if vote else 'No'} for value: {proposed_value}")
+        return vote