- •Introduction
- •Applications of Real-Time Systems
- •Voltage
- •Figure 7: Conversion of an Analog Signal to a 16 bit Binary Number
- •Figure 11: Schematic Representation of tmr
- •It is relatively simple to design a hardware equipment to be fault-tolerant. The following are two methods that are popularly used to achieve hardware fault-tolerance:
- •Software Fault-Tolerance Techniques
- •Types of Real-Time Tasks
- •Timing Constraints
- •Events in a Real-Time System
- •Figure 16: Delay Constraint Between Two Events el and e2
- •Examples of Different Types of Timing Constraints
- •Figure 19: Classification of Timing Constraints
- •Real-Time Task Scheduling
- •Figure 1: Relative and Absolute Deadlines of a Task
- •Figure 2: Precedence Relation Among Tasks
- •Types of Real-Time Tasks and Their Characteristics
- •Classification of Real-Time Task Scheduling Algorithms
- •Figure 5: An Example Schedule Table for a Cyclic Scheduler
- •Figure 6: Major and Minor Cycles in a Cyclic Scheduler
- •Comparison of Cyclic with Table-Driven Scheduling
- •Hybrid Schedulers
- •Event-driven Scheduling
- •Is edf Really a Dynamic Priority Scheduling Algorithm?
- •Implementation of edf
- •Figure 10: Priority Assignment to Tasks in rma
- •We now illustrate the applicability of the rma schodulability criteria through a few examples.
- •Deadline Monotonic Algorithm (dma)
- •Handling Aperiodic and Sporadic Tasks
- •Dealing With Task Jitter
- •W Good real-time task scheduling algorithms ensure fairness to real-time tasks while scheduling.
- •State whether the following assertions are True or False. Write one or two sentences to justify your choice in each case.
- •Figure 2: Unbounded Priority Inversion
- •Highest Locker Protocol(hlp)
- •Priority Ceiling Protocol (pcp)
- •Comparison of Resource Sharing Protocols
- •Handling Task Dependencies
- •Fault-Tolerant Scheduling of Tasks
- •Clocks in Distributed Real-Time Systems
- •Clock Synchronization
- •Figure 1: Centralized synchronization system
- •Cn Slave clocks
- •Commercial Real-Time Operating Systems
- •Time Services
- •Clock Interrupt Processing
- •Providing High Clock Resolution
- •Figure 2: Use of a Watchdog Tinier
- •Unix as a Real-Time Operating System
- •In Unix, dynamic priority computations cause I/o intensive tasks to migrate to higher and higher priority levels, whereas cpu-intensive tasks are made to seek lower priority levels.
- •Host-Target Approach
- •Preemption Point Approach
- •Self-Host Systems
- •Windows As a Real-Time Operating System
- •Figure 9: Task Priorities in Windows nt
- •Open Software
- •Genesis of posix
- •Overview of posix
- •Real-Time posix Standard
- •Rt Linux
- •7.8 Windows ce
- •Benchmarking Real-Time Systems
- •Figure 13: Task Switching Time Among Equal Priority Tasks
- •Real-Time Communication
- •Figure 2: a Bus Architecture
- •Figure 4: Logical Ring in a Token Bus
- •Soft Real-Time Communication in a lan
- •Figure 6: Priority Arbitration Example
- •Figure 8: Problem in Virtual Time Protocol
- •Figure 9: Structure of a Token in ieee 802.5
- •Figure 10: Frames in the Window-based Protocol
- •Performance Comparison
- •A Basic Service Model
- •Traffic Characterization
- •Figure 16: Constant Bit-Rato Traffic
- •Routing Algorithms
- •Resource Reservation
- •Resource Reservation Protocol (rsvp)
- •Traffic Shaping and Policing
- •Traffic Distortion
- •Traffic Scheduling Disciplines
- •Figure 20: Packet Service in Jittor-edd
- •Differentiated Services
- •Functional Elements of DiffServ Architecture
- •Real Time Databases
- •Isolation: Transactions are executed concurrently as long as they do not interfere in each other’s computations.
- •Real-Time Databases
- •Real-Time Database Application Design Issues
- •Temporal Consistency
- •Concurrency Control in Real-Time Databases
- •It can bo shown that pcp is doadlock froo and single blocking. Rocolloct that single blocking moans that once a transaction starts executing after being blocked, it may not block again.
- •Speculative Concurrency Control
- •Comparison of Concurrency Control Protocols
- •Commercial Real-Time Databases
- •Figure 16: Uniform Priority Assignment to Tasks of Example 15
- •Version 2 cse, iit Kharagpur
Temporal Consistency
Temporal consistency of data requires the actual state of the environment and the state represented by the database be very close and in any case within the limits required by the application. Temporal consistency of data has the following two main requirements:
Absolute Validity: This is the notion of consistency between the environment and its reflection in the database given by the data collected by the system about the environment.
Relative Consistency: This is the notion of consistency among the data that are used to derive new data.
Before we examine these notions in more detail, let us examine how data items can be represented in a real-time database and the notion of a relative consistency set.
How to Represent Data Items in a Real-Time Database?
A data item d can be represented as a triplet d:(value,avi,timestamp). The three components of a data item d are denoted as dvaiue,davi, and dtimestamp] where dtimestamp denotes the time when measurement of d took place; daVi is the absolute validity interval for the data item d and represents time interval following the dtimestamp during which the data item d is considered to have absolute validity; dvaiue represents the value recorded for d. For example, a data item d=(120, 5msec,100msec) represents the value of the data item to be 120, recorded at 100msec, with an absolute validity interval of 5msec.
Relative Consistency Set.
Consider a situation where a set of data items used to derive a new data. For the derived data items to be correct, the set of data items on which it is based must be relatively consistent with each other. For example, in an antimissile system, the current velocity and position of a missile can be used to predict its new position. In this case, it would be incorrect to use an earlier sampled position with the velocity value to determine the new position of the missile. In other words, relative consistency ensures that only contemporary data items are used to derive new data. The set of data items that are relatively consistent with each other, form a relative consistency set R. Each R is associated with a relative validity interval (rvi), denoted by Rrvi. The relative consistency of the data items in the relative consistency set can be determined by using Rrvi as explained below.
Based on the above discussions, we can now define the conditions for absolute and relative validity as follows:
Condition for Absolute Validity: A data item d is absolutely valid, iff (Current time — dtimestamp) < davi
Condition for Relative Consistency: A set R of data items is relatively consistent, iff Vd,Vd' G R \dtimestamp — ^timestampl — Rrvi
Example 7.1: Given a temporal data item d = (10,2500msec, lOOm.^c) and the value of current time as 2700msec. Is the given data item absolutely valid?
Solution: It has boon givon that daVi = MO. So, d is valid during tho interval botwoon 2500 and 2600. Hence, tho givon data itom d is not absolutely valid at tho time instant 2700 msec.
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Example 7.2: Let a relative consistency set R be {temperature, pressure} and lat Rrvi be 2. (a) Are tomporaturo={3470C,5 msec ,95 msec } and prossuro={50 bar,10 msec,97 msec} relatively consistent?
Are tomporaturo={3470C,5 msec ,95 msec } and prossuro={50bar, 10msec,92msoc} relatively consistent?
Solution: (a) tomporaturo={3470C,5 msec ,95 msec } and prossuro={50 bar,10 msec,97 msec} are relatively consistent.
tomporaturo={3470C,5 msec ,95 msec } and prossuro={50bar, 10msec,92msoc} are not relatively consistent. □
Example 7.3: Given that a relative consistency set R={position,velocity, acceleration} and Rrvi = lOOms^c and following data items: Position = (25m, 2500msec, 200msec), Velocity = (300m/s, 2550msec, 300msec), Acceleration = (20m/s2,2425msec, 200msec), Current time. = 2600тям. Are the given data items absolutely valid? Also, are they relatively consistent?
Solution: Position is absolutely valid as (2600 — 2500) < 200 Velocity is also absolutely valid as (2600 — 2550) < 300 Acceleration is also absolutely valid as (2600 — 2425) < 200
For relative consistency, we have to check whether the different data items are pair-wise consistent. It can be easily checked that the given set of data is not relatively consistent, since for velocity and acceleration: (2550 — 2425) -ft 100.
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