AMX Engine - Technical Specification

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apiVersion: amx.aimatrix.com/v1
kind: AgentPod
metadata:
  name: customer-service-agent
  namespace: production
  labels:
    app: customer-service
    version: v2.1.0
spec:
  agent:
    name: CustomerServiceAgent
    version: "2.1.0"
    runtime: kotlin
    image: aimatrix/agents:customer-service-v2.1.0
  
  resources:
    requests:
      cpu: "500m"
      memory: "1Gi"
      storage: "10Gi"
    limits:
      cpu: "2000m"
      memory: "4Gi"
      storage: "50Gi"
  
  scaling:
    minReplicas: 2
    maxReplicas: 20
    metrics:
      - type: CPU
        target: 70
      - type: Memory
        target: 80
      - type: Custom
        name: messages_per_second
        target: 1000
  
  networking:
    ports:
      - name: http
        port: 8080
        protocol: TCP
      - name: grpc
        port: 9090
        protocol: TCP
    
  persistence:
    volumes:
      - name: agent-state
        type: persistent
        size: 20Gi
        accessMode: ReadWriteOnce
      - name: temp-data
        type: ephemeral
        size: 5Gi
  
  security:
    isolation: strict
    capabilities:
      - NET_ADMIN
    securityContext:
      runAsUser: 1000
      runAsGroup: 1000
      fsGroup: 1000

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// Advanced process orchestration example
class ProcessOrchestrator {
    private val executor = ForkJoinPool.commonPool()
    private val scheduler = Executors.newScheduledThreadPool(4)
    private val rateLimiter = RateLimiter.create(1000.0) // 1000 ops/sec
    
    suspend fun executeAgent(
        agent: Agent,
        message: Message,
        priority: Priority = Priority.NORMAL
    ): ProcessingResult = withContext(Dispatchers.IO) {
        
        // Rate limiting
        rateLimiter.acquire()
        
        // Resource allocation
        val resources = allocateResources(agent, priority)
        
        try {
            // Set execution context
            val context = ExecutionContext(
                agentId = agent.id,
                resources = resources,
                isolation = IsolationLevel.STRICT,
                timeout = Duration.ofMinutes(5)
            )
            
            // Execute with monitoring
            val result = withTimeout(context.timeout.toMillis()) {
                executeInSandbox(agent, message, context)
            }
            
            // Update metrics
            updateMetrics(agent.id, result, resources.usedCpu, resources.usedMemory)
            
            result
            
        } catch (e: TimeoutCancellationException) {
            // Handle timeout
            killAgent(agent.id)
            ProcessingResult.error("Agent execution timed out")
        } catch (e: ResourceExhaustionException) {
            // Handle resource exhaustion
            throttleAgent(agent.id, Duration.ofMinutes(5))
            ProcessingResult.error("Agent resource limit exceeded")
        } finally {
            releaseResources(resources)
        }
    }
}

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// Digital twin execution model implementation
sealed class DigitalTwin(
    val id: TwinId,
    val type: TwinType,
    val version: String,
    val metadata: TwinMetadata
) {
    abstract suspend fun initialize(): TwinInitResult
    abstract suspend fun execute(context: ExecutionContext): ExecutionResult
    abstract suspend fun synchronize(physicalData: PhysicalData): SyncResult
    abstract suspend fun terminate(): TerminationResult
}

// Asset twin for physical equipment/devices
class AssetTwin(
    id: TwinId,
    val assetSpec: AssetSpecification,
    val sensors: List<SensorDefinition>,
    val actuators: List<ActuatorDefinition>
) : DigitalTwin(id, TwinType.ASSET, "1.0", assetSpec.metadata) {
    
    private val physicsModel = PhysicsModel(assetSpec.physicalProperties)
    private val behaviorModel = BehaviorModel(assetSpec.behaviors)
    private val synchronizer = AssetSynchronizer(sensors, actuators)
    
    override suspend fun initialize(): TwinInitResult {
        return try {
            // Initialize physics simulation
            physicsModel.initialize()
            
            // Setup sensor/actuator connections
            synchronizer.establishConnections()
            
            // Load behavior rules
            behaviorModel.compile(assetSpec.twinMLCode)
            
            TwinInitResult.Success(
                initialState = physicsModel.getCurrentState(),
                connectedSensors = synchronizer.getActiveSensors(),
                availableActuators = synchronizer.getActiveActuators()
            )
        } catch (e: Exception) {
            TwinInitResult.Failure(e.message ?: "Unknown initialization error")
        }
    }
    
    override suspend fun execute(context: ExecutionContext): ExecutionResult {
        val startTime = System.nanoTime()
        
        return try {
            // Update physics simulation
            val physicsState = physicsModel.step(context.timestep)
            
            // Process behavior rules
            val behaviorEvents = behaviorModel.process(physicsState, context)
            
            // Handle actuator commands
            val actuatorCommands = behaviorEvents.filterIsInstance<ActuatorCommand>()
            synchronizer.sendActuatorCommands(actuatorCommands)
            
            // Generate telemetry
            val telemetry = generateTelemetry(physicsState, behaviorEvents)
            
            ExecutionResult.Success(
                newState = physicsState,
                events = behaviorEvents,
                telemetry = telemetry,
                executionTime = Duration.ofNanos(System.nanoTime() - startTime)
            )
        } catch (e: Exception) {
            ExecutionResult.Failure(
                error = e.message ?: "Execution failed",
                partialState = physicsModel.getCurrentState(),
                executionTime = Duration.ofNanos(System.nanoTime() - startTime)
            )
        }
    }
    
    override suspend fun synchronize(physicalData: PhysicalData): SyncResult {
        return synchronizer.synchronize(physicalData, physicsModel.getCurrentState())
    }
}

// Process twin for business/operational processes
class ProcessTwin(
    id: TwinId,
    val processSpec: ProcessSpecification,
    val workflowEngine: WorkflowEngine
) : DigitalTwin(id, TwinType.PROCESS, "1.0", processSpec.metadata) {
    
    private val stateChart = StateChart(processSpec.states, processSpec.transitions)
    private val kpiCalculator = KPICalculator(processSpec.kpis)
    private val optimizer = ProcessOptimizer(processSpec.objectives)
    
    override suspend fun initialize(): TwinInitResult {
        workflowEngine.initialize()
        stateChart.initialize(processSpec.initialState)
        return TwinInitResult.Success(
            initialState = stateChart.getCurrentState(),
            connectedSensors = emptyList(),
            availableActuators = emptyList()
        )
    }
    
    override suspend fun execute(context: ExecutionContext): ExecutionResult {
        // Execute process steps
        val workflowResult = workflowEngine.executeStep(context)
        
        // Update state chart
        stateChart.processEvent(workflowResult.event)
        
        // Calculate KPIs
        val kpis = kpiCalculator.calculate(stateChart.getCurrentState())
        
        // Apply optimizations
        val optimizations = optimizer.suggest(kpis, workflowResult)
        
        return ExecutionResult.Success(
            newState = stateChart.getCurrentState(),
            events = listOf(workflowResult.event),
            telemetry = mapOf("kpis" to kpis, "optimizations" to optimizations),
            executionTime = workflowResult.executionTime
        )
    }
    
    override suspend fun synchronize(physicalData: PhysicalData): SyncResult {
        // Process twins sync with business systems rather than physical sensors
        return SyncResult.NotApplicable("Process twins sync with business systems")
    }
}

// System twin for complex system-of-systems
class SystemTwin(
    id: TwinId,
    val systemSpec: SystemSpecification,
    val childTwins: List<DigitalTwin>,
    val interconnections: List<TwinInterconnection>
) : DigitalTwin(id, TwinType.SYSTEM, "1.0", systemSpec.metadata) {
    
    private val orchestrator = TwinOrchestrator(childTwins, interconnections)
    private val emergentBehaviorDetector = EmergentBehaviorDetector()
    
    override suspend fun initialize(): TwinInitResult {
        // Initialize all child twins
        val childResults = childTwins.map { it.initialize() }
        
        if (childResults.any { it is TwinInitResult.Failure }) {
            return TwinInitResult.Failure("One or more child twins failed to initialize")
        }
        
        // Setup interconnections
        orchestrator.establishConnections()
        
        return TwinInitResult.Success(
            initialState = orchestrator.getSystemState(),
            connectedSensors = childResults.flatMap { it.connectedSensors },
            availableActuators = childResults.flatMap { it.availableActuators }
        )
    }
    
    override suspend fun execute(context: ExecutionContext): ExecutionResult {
        // Execute child twins in parallel
        val childResults = childTwins.map { twin ->
            async { twin.execute(context) }
        }.awaitAll()
        
        // Process inter-twin communications
        val interactions = orchestrator.processInteractions(childResults)
        
        // Detect emergent behaviors
        val emergentBehaviors = emergentBehaviorDetector.analyze(childResults, interactions)
        
        // Aggregate system state
        val systemState = orchestrator.aggregateState(childResults)
        
        return ExecutionResult.Success(
            newState = systemState,
            events = interactions + emergentBehaviors,
            telemetry = aggregateTelemetry(childResults),
            executionTime = childResults.maxOf { it.executionTime }
        )
    }
}

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// Real-time simulation engine implementation
class RealTimeSimulationEngine {
    private val solverRegistry = SolverRegistry()
    private val timestepManager = AdaptiveTimestepManager()
    private val parallelExecutor = ParallelExecutor()
    private val performanceMonitor = SimulationPerformanceMonitor()
    
    init {
        // Register available numerical solvers
        solverRegistry.register("euler", EulerSolver())
        solverRegistry.register("runge_kutta_4", RungeKutta4Solver())
        solverRegistry.register("adams_bashforth", AdamsBashforthSolver())
        solverRegistry.register("implicit_euler", ImplicitEulerSolver())
        solverRegistry.register("bdf", BackwardDifferentiationSolver())
        solverRegistry.register("cvode", CVODESolver()) // SUNDIALS integration
    }
    
    suspend fun runSimulation(
        twins: List<DigitalTwin>,
        simulationConfig: SimulationConfiguration
    ): SimulationResult = withContext(Dispatchers.Default) {
        
        val session = SimulationSession(
            id = UUID.randomUUID(),
            twins = twins,
            config = simulationConfig,
            startTime = Instant.now()
        )
        
        performanceMonitor.startSession(session)
        
        try {
            when (simulationConfig.mode) {
                SimulationMode.REAL_TIME -> runRealTimeSimulation(session)
                SimulationMode.BATCH -> runBatchSimulation(session)
                SimulationMode.MONTE_CARLO -> runMonteCarloSimulation(session)
                SimulationMode.SENSITIVITY_ANALYSIS -> runSensitivityAnalysis(session)
            }
        } finally {
            performanceMonitor.endSession(session)
        }
    }
    
    private suspend fun runRealTimeSimulation(
        session: SimulationSession
    ): SimulationResult {
        val results = mutableListOf<SimulationFrame>()
        val wallClockStart = System.nanoTime()
        var simulationTime = session.config.startTime
        val endTime = session.config.endTime
        
        // Real-time synchronization
        val realTimeSync = RealTimeSync(session.config.timeScale)
        
        while (simulationTime.isBefore(endTime)) {
            val frameStart = System.nanoTime()
            
            // Adaptive timestep calculation
            val timestep = timestepManager.calculateTimestep(
                currentTime = simulationTime,
                twins = session.twins,
                targetAccuracy = session.config.targetAccuracy,
                maxTimestep = session.config.maxTimestep
            )
            
            // Execute simulation step
            val frame = executeSimulationStep(
                session = session,
                currentTime = simulationTime,
                timestep = timestep
            )
            
            results.add(frame)
            simulationTime = simulationTime.plus(timestep)
            
            // Real-time synchronization
            realTimeSync.synchronize(frameStart, timestep)
            
            // Performance monitoring
            performanceMonitor.recordFrame(frame, System.nanoTime() - frameStart)
            
            // Check for early termination conditions
            if (shouldTerminateEarly(frame, session.config)) {
                break
            }
            
            // Yield control periodically
            if (results.size % 1000 == 0) {
                yield()
            }
        }
        
        return SimulationResult(
            sessionId = session.id,
            frames = results,
            totalDuration = Duration.ofNanos(System.nanoTime() - wallClockStart),
            simulatedDuration = Duration.between(session.config.startTime, simulationTime),
            performance = performanceMonitor.getSessionMetrics(session.id),
            status = SimulationStatus.COMPLETED
        )
    }
    
    private suspend fun executeSimulationStep(
        session: SimulationSession,
        currentTime: Instant,
        timestep: Duration
    ): SimulationFrame {
        
        val context = ExecutionContext(
            currentTime = currentTime,
            timestep = timestep,
            sessionId = session.id,
            configuration = session.config
        )
        
        // Execute twins in parallel where possible
        val twinResults = if (session.config.allowParallelExecution) {
            parallelExecutor.executeInParallel(session.twins, context)
        } else {
            session.twins.map { twin ->
                twin.execute(context)
            }
        }
        
        // Process inter-twin communications
        val communications = processInterTwinCommunications(twinResults)
        
        // Aggregate frame data
        return SimulationFrame(
            timestamp = currentTime,
            timestep = timestep,
            twinResults = twinResults,
            communications = communications,
            systemMetrics = collectSystemMetrics(),
            validationErrors = validateFrameConsistency(twinResults)
        )
    }
    
    private suspend fun runMonteCarloSimulation(
        session: SimulationSession
    ): SimulationResult {
        val monteCarloConfig = session.config.monteCarloConfig 
            ?: throw IllegalArgumentException("Monte Carlo configuration required")
        
        val allResults = ConcurrentLinkedQueue<SimulationResult>()
        val random = SecureRandom()
        
        // Run multiple simulation iterations with parameter variations
        (1..monteCarloConfig.iterations).toList().chunked(
            session.config.maxParallelRuns
        ).forEach { batch ->
            
            val batchResults = batch.map { iteration ->
                async {
                    val perturbedConfig = perturbParameters(
                        session.config, 
                        monteCarloConfig.parameterDistributions,
                        random
                    )
                    
                    val perturbedSession = session.copy(config = perturbedConfig)
                    runBatchSimulation(perturbedSession)
                }
            }.awaitAll()
            
            allResults.addAll(batchResults)
        }
        
        // Aggregate Monte Carlo results
        return aggregateMonteCarloResults(allResults.toList(), monteCarloConfig)
    }
}

// Advanced solver framework
abstract class NumericalSolver {
    abstract fun solve(
        state: SimulationState,
        derivatives: (SimulationState, Instant) -> SimulationState,
        timestep: Duration,
        currentTime: Instant
    ): SolverResult
    
    abstract val order: Int
    abstract val stability: StabilityCharacteristics
    abstract val computationalComplexity: ComplexityClass
}

class RungeKutta4Solver : NumericalSolver() {
    override val order = 4
    override val stability = StabilityCharacteristics.EXPLICIT
    override val computationalComplexity = ComplexityClass.O_N
    
    override fun solve(
        state: SimulationState,
        derivatives: (SimulationState, Instant) -> SimulationState,
        timestep: Duration,
        currentTime: Instant
    ): SolverResult {
        
        val dt = timestep.toNanos() / 1_000_000_000.0
        val k1 = derivatives(state, currentTime)
        val k2 = derivatives(state + k1 * (dt/2.0), currentTime.plusNanos((dt/2.0 * 1e9).toLong()))
        val k3 = derivatives(state + k2 * (dt/2.0), currentTime.plusNanos((dt/2.0 * 1e9).toLong()))
        val k4 = derivatives(state + k3 * dt, currentTime.plusNanos((dt * 1e9).toLong()))
        
        val newState = state + (k1 + k2*2.0 + k3*2.0 + k4) * (dt/6.0)
        
        return SolverResult(
            newState = newState,
            error = estimateLocalTruncationError(k1, k2, k3, k4, dt),
            iterations = 1,
            converged = true
        )
    }
    
    private fun estimateLocalTruncationError(
        k1: SimulationState, k2: SimulationState, 
        k3: SimulationState, k4: SimulationState, 
        dt: Double
    ): Double {
        // Local truncation error estimation for RK4
        val errorState = (k1 - k2*2.0 + k3) * (dt.pow(5) / 90.0)
        return errorState.magnitude()
    }
}

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// TwinML runtime integration
class TwinMLRuntime {
    private val interpreter = TwinMLInterpreter()
    private val jitCompiler = TwinMLJITCompiler()
    private val typeSystem = TwinMLTypeSystem()
    private val memoryManager = TwinMLMemoryManager()
    
    suspend fun loadTwinDefinition(
        twinMLCode: String,
        optimizationLevel: OptimizationLevel = OptimizationLevel.O2
    ): CompiledTwin {
        
        // Parse TwinML source
        val ast = interpreter.parse(twinMLCode)
        
        // Type checking and semantic analysis
        val typedAst = typeSystem.analyze(ast)
        
        // Optimization passes
        val optimizedAst = when (optimizationLevel) {
            OptimizationLevel.O0 -> typedAst // No optimization
            OptimizationLevel.O1 -> applyBasicOptimizations(typedAst)
            OptimizationLevel.O2 -> applyAdvancedOptimizations(typedAst)
            OptimizationLevel.O3 -> applyAggressiveOptimizations(typedAst)
        }
        
        // JIT compilation
        val compiledCode = jitCompiler.compile(optimizedAst)
        
        return CompiledTwin(
            ast = optimizedAst,
            bytecode = compiledCode,
            metadata = extractMetadata(optimizedAst),
            dependencies = resolveDependencies(optimizedAst)
        )
    }
    
    suspend fun executeTwinBehavior(
        twin: CompiledTwin,
        event: TwinEvent,
        context: ExecutionContext
    ): BehaviorExecutionResult {
        
        // Create execution environment
        val environment = ExecutionEnvironment(
            twin = twin,
            context = context,
            memoryManager = memoryManager,
            eventQueue = EventQueue()
        )
        
        try {
            // Find matching behavior handler
            val handler = twin.findBehaviorHandler(event)
                ?: return BehaviorExecutionResult.NoHandler(event.type)
            
            // Execute compiled behavior
            val result = jitCompiler.execute(handler.bytecode, environment)
            
            return BehaviorExecutionResult.Success(
                result = result,
                sideEffects = environment.collectSideEffects(),
                memoryUsage = memoryManager.getCurrentUsage(),
                executionTime = result.executionTime
            )
            
        } catch (e: TwinMLRuntimeException) {
            return BehaviorExecutionResult.Error(
                error = e,
                stackTrace = e.twinMLStackTrace,
                context = environment.captureContext()
            )
        }
    }
}

// Advanced TwinML type system
class TwinMLTypeSystem {
    private val primitiveTypes = setOf(
        "integer", "float", "boolean", "string", "timestamp", 
        "duration", "vector", "matrix", "complex"
    )
    
    private val collectionTypes = setOf("list", "map", "set", "queue")
    private val specializationTypes = mutableMapOf<String, TypeDefinition>()
    
    fun analyze(ast: TwinMLAST): TypedTwinMLAST {
        val typeChecker = TypeChecker(
            primitiveTypes = primitiveTypes,
            collectionTypes = collectionTypes,
            userDefinedTypes = specializationTypes
        )
        
        return typeChecker.check(ast)
    }
    
    fun defineCustomType(
        name: String,
        definition: TypeDefinition
    ) {
        specializationTypes[name] = definition
    }
    
    // Support for complex types in engineering applications
    fun registerEngineeringTypes() {
        defineCustomType("Temperature", TypeDefinition(
            baseType = "float",
            unit = "celsius",
            constraints = listOf(
                Constraint.Range(-273.15, Double.MAX_VALUE),
                Constraint.Precision(2)
            )
        ))
        
        defineCustomType("Pressure", TypeDefinition(
            baseType = "float",
            unit = "pascal",
            constraints = listOf(
                Constraint.NonNegative,
                Constraint.Precision(1)
            )
        ))
        
        defineCustomType("Position3D", TypeDefinition(
            baseType = "vector",
            dimensions = 3,
            unit = "meter",
            constraints = listOf(
                Constraint.FiniteValues
            )
        ))
    }
}

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// Advanced synchronization protocols
class TwinSynchronizationManager {
    private val protocolRegistry = ProtocolRegistry()
    private val conflictResolver = ConflictResolver()
    private val timeSync = TimeSynchronizer()
    private val dataValidator = DataValidator()
    
    init {
        registerStandardProtocols()
    }
    
    private fun registerStandardProtocols() {
        protocolRegistry.register("mqtt", MQTTSyncProtocol())
        protocolRegistry.register("opcua", OPCUASyncProtocol())
        protocolRegistry.register("modbus", ModbusSyncProtocol())
        protocolRegistry.register("coap", CoAPSyncProtocol())
        protocolRegistry.register("websocket", WebSocketSyncProtocol())
        protocolRegistry.register("grpc", GRPCSyncProtocol())
    }
    
    suspend fun synchronizeTwin(
        twin: DigitalTwin,
        physicalSystem: PhysicalSystem,
        syncConfig: SynchronizationConfiguration
    ): SynchronizationResult {
        
        val protocol = protocolRegistry.get(syncConfig.protocol)
            ?: return SynchronizationResult.ProtocolNotFound(syncConfig.protocol)
        
        return try {
            // Establish connection to physical system
            val connection = protocol.connect(physicalSystem.connectionInfo)
            
            // Time synchronization
            val timeOffset = timeSync.calculateOffset(connection)
            
            // Bidirectional data synchronization
            val syncResult = performBidirectionalSync(
                twin, connection, syncConfig, timeOffset
            )
            
            SynchronizationResult.Success(syncResult)
            
        } catch (e: SynchronizationException) {
            SynchronizationResult.Failure(e.message ?: "Synchronization failed", e)
        }
    }
    
    private suspend fun performBidirectionalSync(
        twin: DigitalTwin,
        connection: ProtocolConnection,
        config: SynchronizationConfiguration,
        timeOffset: Duration
    ): DetailedSyncResult {
        
        val startTime = Instant.now()
        val telemetryData = mutableListOf<TelemetryPoint>()
        val commandsSent = mutableListOf<Command>()
        val conflicts = mutableListOf<DataConflict>()
        
        // Phase 1: Read from physical system
        val physicalData = connection.readSensorData(config.sensorMappings)
        
        // Validate and transform incoming data
        val validatedData = dataValidator.validate(physicalData, config.validationRules)
        val transformedData = applyDataTransformations(validatedData, config.transformations)
        
        // Apply time correction
        val timeCorrectedData = transformedData.map { dataPoint ->
            dataPoint.copy(timestamp = dataPoint.timestamp.plus(timeOffset))
        }
        
        // Detect conflicts between twin state and physical data
        val detectedConflicts = conflictResolver.detectConflicts(
            twinState = twin.getCurrentState(),
            physicalData = timeCorrectedData
        )
        
        conflicts.addAll(detectedConflicts)
        
        // Resolve conflicts using configured strategy
        val resolvedData = if (detectedConflicts.isNotEmpty()) {
            conflictResolver.resolve(detectedConflicts, config.conflictResolutionStrategy)
        } else {
            timeCorrectedData
        }
        
        // Update twin with resolved data
        val syncResult = twin.synchronize(PhysicalData(resolvedData))
        
        // Phase 2: Send commands to physical system
        if (config.enableActuatorControl) {
            val pendingCommands = twin.getPendingActuatorCommands()
            
            for (command in pendingCommands) {
                try {
                    connection.sendActuatorCommand(command)
                    commandsSent.add(command)
                    twin.markCommandAsSent(command.id)
                } catch (e: CommandExecutionException) {
                    twin.markCommandAsFailed(command.id, e.message)
                }
            }
        }
        
        return DetailedSyncResult(
            duration = Duration.between(startTime, Instant.now()),
            dataPointsReceived = resolvedData.size,
            commandsSent = commandsSent.size,
            conflicts = conflicts,
            telemetry = telemetryData,
            success = syncResult.isSuccess,
            errors = if (syncResult.isFailure) listOf(syncResult.error) else emptyList()
        )
    }
}

// OPC UA synchronization protocol implementation
class OPCUASyncProtocol : SynchronizationProtocol {
    private val client = OpcUaClient.create("urn:amx:twin-runtime")
    
    override suspend fun connect(connectionInfo: ConnectionInfo): ProtocolConnection {
        val endpointUrl = connectionInfo.url
        val securityPolicy = SecurityPolicy.valueOf(
            connectionInfo.parameters["securityPolicy"] ?: "None"
        )
        
        client.connect(endpointUrl, securityPolicy).get()
        
        return OPCUAConnection(client)
    }
}

class OPCUAConnection(private val client: OpcUaClient) : ProtocolConnection {
    
    override suspend fun readSensorData(
        mappings: List<SensorMapping>
    ): List<DataPoint> = withContext(Dispatchers.IO) {
        
        val nodeIds = mappings.map { NodeId.parse(it.address) }
        val readRequest = ReadRequest(
            requestHeader = RequestHeader.NULL_REQUEST_HEADER,
            nodesToRead = nodeIds.map { nodeId ->
                ReadValueId(nodeId, AttributeId.Value.uid(), null, QualifiedName.NULL_VALUE)
            }.toTypedArray(),
            maxAge = 0.0,
            timestampsToReturn = TimestampsToReturn.Both
        )
        
        val response = client.read(readRequest).get()
        
        response.results.mapIndexedNotNull { index, dataValue ->
            if (dataValue.statusCode.isGood) {
                DataPoint(
                    sensor = mappings[index].sensorId,
                    value = dataValue.value.value,
                    timestamp = dataValue.serverTimestamp?.javaInstant ?: Instant.now(),
                    quality = dataValue.statusCode.value.toDouble(),
                    metadata = mapOf("nodeId" to nodeIds[index].toParseableString())
                )
            } else {
                null
            }
        }
    }
    
    override suspend fun sendActuatorCommand(command: Command): CommandResult {
        return try {
            val nodeId = NodeId.parse(command.targetAddress)
            val variant = Variant(command.value)
            
            val writeRequest = WriteRequest(
                requestHeader = RequestHeader.NULL_REQUEST_HEADER,
                nodesToWrite = arrayOf(
                    WriteValue(nodeId, AttributeId.Value.uid(), null, DataValue(variant))
                )
            )
            
            val response = client.write(writeRequest).get()
            val statusCode = response.results[0]
            
            if (statusCode.isGood) {
                CommandResult.Success(command.id, Instant.now())
            } else {
                CommandResult.Failure(command.id, statusCode.toString())
            }
            
        } catch (e: Exception) {
            CommandResult.Failure(command.id, e.message ?: "Unknown error")
        }
    }
}

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// Advanced event processing system
class TwinEventProcessor {
    private val eventQueue = PriorityBlockingQueue<TwinEvent>(1000) { e1, e2 ->
        e1.priority.compareTo(e2.priority)
    }
    private val patternMatcher = ComplexEventPatternMatcher()
    private val stateManager = DistributedStateManager()
    private val eventHandlers = ConcurrentHashMap<EventType, List<EventHandler>>()
    
    suspend fun processEvent(event: TwinEvent): EventProcessingResult {
        return try {
            // Validate event
            val validationResult = validateEvent(event)
            if (!validationResult.isValid) {
                return EventProcessingResult.ValidationFailed(validationResult.errors)
            }
            
            // Pattern matching for complex events
            val matchedPatterns = patternMatcher.match(event)
            
            // State transition processing
            val stateChanges = processStateTransitions(event, matchedPatterns)
            
            // Execute event handlers
            val handlerResults = executeEventHandlers(event, matchedPatterns)
            
            // Update distributed state
            stateManager.applyChanges(stateChanges)
            
            EventProcessingResult.Success(
                event = event,
                stateChanges = stateChanges,
                handlerResults = handlerResults,
                matchedPatterns = matchedPatterns
            )
            
        } catch (e: Exception) {
            EventProcessingResult.Error(event, e.message ?: "Processing failed")
        }
    }
    
    // Complex event pattern matching
    private suspend fun processStateTransitions(
        event: TwinEvent,
        matchedPatterns: List<EventPattern>
    ): List<StateChange> {
        
        val transitions = mutableListOf<StateChange>()
        
        for (pattern in matchedPatterns) {
            when (pattern.type) {
                EventPatternType.SEQUENCE -> {
                    // Handle sequential event patterns
                    val sequenceState = stateManager.getSequenceState(pattern.id)
                    val newState = sequenceState.advance(event)
                    
                    if (newState.isComplete) {
                        transitions.add(StateChange.SequenceCompleted(pattern.id, newState))
                    } else {
                        transitions.add(StateChange.SequenceAdvanced(pattern.id, newState))
                    }
                }
                
                EventPatternType.TEMPORAL -> {
                    // Handle time-based patterns
                    val temporalWindow = stateManager.getTemporalWindow(pattern.id)
                    if (temporalWindow.contains(event.timestamp)) {
                        val aggregateState = temporalWindow.aggregate(event)
                        transitions.add(StateChange.TemporalAggregated(pattern.id, aggregateState))
                    }
                }
                
                EventPatternType.SPATIAL -> {
                    // Handle location-based patterns
                    val spatialRegion = stateManager.getSpatialRegion(pattern.id)
                    if (spatialRegion.contains(event.location)) {
                        val spatialState = spatialRegion.updateWithEvent(event)
                        transitions.add(StateChange.SpatialUpdated(pattern.id, spatialState))
                    }
                }
                
                EventPatternType.CAUSAL -> {
                    // Handle cause-effect patterns
                    val causalChain = stateManager.getCausalChain(pattern.id)
                    val chainState = causalChain.processEvent(event)
                    transitions.add(StateChange.CausalChainUpdated(pattern.id, chainState))
                }
            }
        }
        
        return transitions
    }
}

// Distributed state management with ACID properties
class DistributedStateManager {
    private val statePartitions = ConcurrentHashMap<PartitionKey, StatePartition>()
    private val transactionManager = TransactionManager()
    private val replicationManager = ReplicationManager()
    private val consistencyChecker = ConsistencyChecker()
    
    suspend fun applyChanges(changes: List<StateChange>): StateTransactionResult {
        val transaction = transactionManager.beginTransaction()
        
        return try {
            // Group changes by partition for efficient processing
            val changesByPartition = changes.groupBy { it.partitionKey }
            
            // Apply changes within transaction
            val results = changesByPartition.map { (partitionKey, partitionChanges) ->
                async {
                    applyPartitionChanges(partitionKey, partitionChanges, transaction)
                }
            }.awaitAll()
            
            // Consistency validation
            val consistencyResult = consistencyChecker.validate(results)
            if (!consistencyResult.isConsistent) {
                transaction.rollback()
                return StateTransactionResult.ConsistencyViolation(consistencyResult.violations)
            }
            
            // Replicate changes
            replicationManager.replicate(changes, transaction.id)
            
            // Commit transaction
            transaction.commit()
            
            StateTransactionResult.Success(
                transactionId = transaction.id,
                appliedChanges = changes,
                partitionResults = results
            )
            
        } catch (e: Exception) {
            transaction.rollback()
            StateTransactionResult.Failure(transaction.id, e.message ?: "State update failed")
        }
    }
    
    private suspend fun applyPartitionChanges(
        partitionKey: PartitionKey,
        changes: List<StateChange>,
        transaction: StateTransaction
    ): PartitionUpdateResult {
        
        val partition = statePartitions.computeIfAbsent(partitionKey) { 
            StatePartition(partitionKey)
        }
        
        return partition.applyChanges(changes, transaction)
    }
    
    // State querying with consistency guarantees
    suspend fun queryState(
        query: StateQuery,
        consistencyLevel: ConsistencyLevel = ConsistencyLevel.STRONG
    ): StateQueryResult {
        
        return when (consistencyLevel) {
            ConsistencyLevel.STRONG -> queryWithStrongConsistency(query)
            ConsistencyLevel.EVENTUAL -> queryWithEventualConsistency(query)
            ConsistencyLevel.WEAK -> queryWithWeakConsistency(query)
        }
    }
    
    private suspend fun queryWithStrongConsistency(query: StateQuery): StateQueryResult {
        // Ensure all replicas are synchronized before query
        replicationManager.waitForSynchronization()
        
        val relevantPartitions = findPartitionsForQuery(query)
        val partitionResults = relevantPartitions.map { partition ->
            async { partition.executeQuery(query) }
        }.awaitAll()
        
        return aggregateQueryResults(partitionResults, query)
    }
}

// Advanced state partition implementation
class StatePartition(val key: PartitionKey) {
    private val stateStore = ConcurrentHashMap<StateKey, StateValue>()
    private val versionVector = VersionVector()
    private val lockManager = PartitionLockManager()
    private val changeLog = PartitionChangeLog()
    
    suspend fun applyChanges(
        changes: List<StateChange>,
        transaction: StateTransaction
    ): PartitionUpdateResult = lockManager.withWriteLock {
        
        val appliedChanges = mutableListOf<StateChange>()
        val failedChanges = mutableListOf<StateChangeError>()
        
        for (change in changes) {
            try {
                when (change) {
                    is StateChange.ValueUpdate -> {
                        val oldValue = stateStore[change.key]
                        val newValue = applyValueChange(change, oldValue)
                        stateStore[change.key] = newValue
                        versionVector.increment(key)
                        appliedChanges.add(change)
                    }
                    
                    is StateChange.StructuralChange -> {
                        applyStructuralChange(change)
                        versionVector.increment(key)
                        appliedChanges.add(change)
                    }
                    
                    is StateChange.RelationshipChange -> {
                        applyRelationshipChange(change)
                        versionVector.increment(key)
                        appliedChanges.add(change)
                    }
                }
                
                // Log change for replication
                changeLog.append(change, transaction.id, versionVector.current)
                
            } catch (e: StateChangeException) {
                failedChanges.add(StateChangeError(change, e.message))
            }
        }
        
        PartitionUpdateResult(
            partitionKey = key,
            appliedChanges = appliedChanges,
            failedChanges = failedChanges,
            newVersion = versionVector.current
        )
    }
    
    private fun applyValueChange(
        change: StateChange.ValueUpdate,
        oldValue: StateValue?
    ): StateValue {
        
        return when (change.updateType) {
            UpdateType.SET -> change.newValue
            UpdateType.INCREMENT -> {
                val currentNum = oldValue?.asNumber() ?: 0.0
                StateValue.Number(currentNum + change.newValue.asNumber())
            }
            UpdateType.APPEND -> {
                val currentList = oldValue?.asList() ?: emptyList()
                StateValue.List(currentList + change.newValue.asList())
            }
            UpdateType.MERGE -> {
                val currentMap = oldValue?.asMap() ?: emptyMap()
                StateValue.Map(currentMap + change.newValue.asMap())
            }
        }
    }
}