What Shape is Your Real-Time System? Lonnie R. Welch Intelligent, Real-Time, Secure Systems Lab. School of EECS Ohio University Michael W. Masters Naval Surface Warfare Center Dahlgren Division mil
Overview Patterns in real-time mission-critical systems Basis for a taxonomy of RTMCSs Useful for –technology selection –identifying research needs
Ship Computational Resource Pool
OpticalCrosslink PassiveOptical Ka Crosslink In-situ User PC Based GS In-situ User PC Based GS Comm Gateway MetadataWarehouseMetadataWarehouse NASA GSFC Earth Science Vision- Distributed Information-System-in-the-Sky CommercialCommunicationNetwork ActiveOptical DigitalLibraryDigitalLibrary Ka Optical Crosslink Ka Ka Interoperating Measurement Systems (Air / Spacecraft / In- situ) Interoperating Measurement Systems (Air / Spacecraft / In- situ) Flexible Measurement Network Architecture Flexible Measurement Network Architecture Direct Distribution of Derived Products Direct Distribution of Derived Products Network Computing-in- the-Sky Network Computing-in- the-Sky
System Agility is Needed § unpredictable environments (e.g., war-fighting situations) § system intrusions § harsh conditions (resulting in damage)
Most Previous Work § “worst-case” execution time (WCET) known a priori for each job [Liu73, Ram89, Xu90, Sha91, Bak91] § static resource allocation and guarantees; low agility § poor resource utilization when WCET normal execution time [Ram89, Leh96, Hab90] § accurately measuring WCET is often difficult, and sometimes impossible [Ste97, Abe98]
Adaptive QoS Management Diagnose Monitor QoS violation(s) Causes and possible actions for recovery 1 2 Analyze 3 Allocate 4 “Best” recovery actions
Critical Use Cases
Analysis Packages
Inter-Class Collaborations “Maintain a Feasible Allocation” use case
Air traffic control Satellite C 2 Air defense Squads of mobile robots, UAVs, satellites environment sensors actuators assessment control initiation event
Data Source Data Handler Data Stream Situation Assessment Use Case sensor periodically produces a stream of data elements decide if actions should be performed variable data set size heterogeneous elements λ obs < λ req
Event Source Event Handler Event Stream Action Initiation Use Case λ obs < λ req plan and initiate an action to handle event environment-dependent event arrival rate heterogeneous events timely performance is mandatory
Control Use Case Data Source Event- Driven Periodic Data Handler Data Stream Event Source Event Stream
activated by an event guides actions to success deactivated by an event – the completion of the action period deadline and action completion deadline completion deadline is dynamic control initiationassessment >
Characterizing Design Patterns Larger granularity than task or object Cannot characterized accurately by worst case Fixed set of applications, with varying loads How to characterize the problem space?
Taxonomy Categories Properties of a real-time system Properties of the environment (which effect the real-time system) The set of properties defines a “shape”
Properties of a Real-Time System Pattern Behavior Timing Requirement Task Relations Forms of Adaptation
Timing Requirement Granularity Strictness Abstraction level Complexity
Properties of the Environment Dynamics Characteristics Workload
Properties of Workload event arrival rate data stream size period stream elements
Uses of the Taxonomy Characterizing applications Categorizing real-time technology Selecting appropriate techniques for engineering of a particular system Identifying open research areas
Characterizing RT (sub)Systems The situation assessment path in an air defense system Periodically reviews all radar tracks If a threat track is detected, notifies the missile engagement path
Situation Assessment Design Pattern Behavior Timing Requirement Task Relations Forms of Adaptation assessment initiation guidance Periodic Transient Transient- periodic Independent Dependent Rrsc. alloc. Precision Concurrency Slack
Situation Assessment Granularity Strictness Abstraction level Complexity Soft Importance Utility Hybrid Hard Firm Multiple Single msec sec minutes hours task object method instr task group
Situation Assessment Dynamics Characteristics Workload static time invariant stochastic dynamic time variant stochastic hybrid burtsy constant gradually changing
Situation Assessment event arrival rate data stream size period stream elements constant set interval distribution dynamic constant set interval distribution dynamic homogeneous set interval distribution unknown fixed set interval unconstrained
Categorizing Technology RMA - the rate monotonic technique for schedulability analysis Determines if a set of periodic, independent tasks is schedulable The worst case execution time is known for each task
Rate Monotonic Analysis Design Pattern Behavior Timing Requirement Task Relations Forms of Adaptation assessment initiation guidance Periodic Transient Transient- periodic Independent Dependent Rrsc. alloc. Precision Concurrency Slack
Rate Monotonic Analysis Granularity Strictness Abstraction level Complexity Soft Importance Utility Hybrid Hard Firm Multiple Single msec sec minutes hours task object method instr task group
Rate Monotonic Analysis Dynamics Characteristics Workload static time invariant stochastic dynamic time variant stochastic hybrid burtsy constant gradually changing
Rate Monotonic Analysis event arrival rate data stream size period stream elements constant set interval distribution dynamic constant set interval distribution dynamic homogeneous set interval distribution unknown fixed set interval unconstrained
Technology Selection Is the application region contained within the space covered by the technology? Inefficiencies may result if the technology space is larger than the application region Errors may result if the technology space does not contain the application region
Identifying Research Needs Define the shapes of existing technology Which shapes are missing? Who cares? Engineers of applications not having corresponding technologies