Cmkrishna Real Time Systems PDF: A Review and Comparison with Other Tools
What is Cmkrishna Real Time Systems PDF and Why You Need It
If you are an engineer or a developer working on real-time applications, you might have heard of Cmkrishna Real Time Systems PDF. This is a book written by C. Mani Krishna and Kang G. Shin, two experts in the field of real-time systems. The book covers the major issues involved in designing, implementing, and evaluating real-time systems, such as performance measures, scheduling, architectures, algorithms, fault-tolerance, and reliability.
But what exactly are real-time systems and why are they important? Real-time systems are systems that have to respond to events or stimuli within a specified time limit. For example, a flight control system has to react to the pilot's commands and the environmental conditions within milliseconds to ensure the safety of the passengers and the aircraft. A video game has to render graphics and sound within fractions of a second to provide a smooth and immersive experience for the players. A factory automation system has to coordinate the actions of multiple machines and sensors within microseconds to optimize the production process and avoid errors.
As you can see, real-time systems are ubiquitous and critical in many domains, such as aerospace, automotive, industrial, medical, entertainment, and military. However, developing real-time systems is not an easy task. It requires a deep understanding of the system requirements, the hardware and software components, the timing constraints, the possible failures, and the trade-offs between different design choices. Moreover, it requires rigorous testing and verification methods to ensure that the system meets its specifications and behaves correctly under all circumstances.
This is where Cmkrishna Real Time Systems PDF comes in handy. This book provides a comprehensive and systematic treatment of the theory and practice of real-time systems. It covers topics such as:
Real-time system characteristics and classifications
Real-time system performance measures and analysis techniques
Real-time task allocation and scheduling algorithms
Real-time synchronization mechanisms and protocols
Real-time system architectures and design methodologies
Real-time fault-tolerance techniques and reliability models
Real-time system testing and verification methods
The book also includes numerous exercises and examples to help you apply the concepts and techniques to real-world problems. For instance, you can learn how to design a real-time alarm clock or a real-time traffic light controller using simple examples found in Chapter 2. You can also learn how to compare different real-time scheduling algorithms using analytical models or simulation tools. You can also learn how to use redundancy in real-time architectures to maintain high reliability.
Cmkrishna Real Time Systems PDF is a valuable resource for anyone who wants to learn more about real-time systems or improve their skills in developing real-time applications. Whether you are a student, a researcher, or a practitioner, you will find this book useful and informative. You can download the PDF version of the book from various online sources or buy the hardcopy from your favorite bookstore.
Real-Time System Characteristics and Classifications
One of the first steps in designing a real-time system is to identify its characteristics and classify it according to its requirements. Some of the common characteristics of real-time systems are:
Timeliness: The system has to meet certain deadlines or timing constraints for its outputs or actions. For example, a real-time system may have to respond within a hard deadline (a fixed and non-negotiable time limit), a soft deadline (a flexible time limit that can be missed occasionally without serious consequences), or a firm deadline (a time limit that can be missed but with some penalty or degradation in performance).
Predictability: The system has to behave in a consistent and deterministic manner under all conditions. For example, a real-time system may have to guarantee that its worst-case execution time (WCET) or response time does not exceed a certain bound.
Dependability: The system has to provide correct and reliable services despite the presence of faults or errors. For example, a real-time system may have to tolerate hardware failures, software bugs, communication errors, or environmental disturbances.
Adaptability: The system has to adjust its behavior or parameters according to the changes in the system state or the environment. For example, a real-time system may have to adapt its scheduling policy, resource allocation, or fault-tolerance strategy based on the current workload, resource availability, or fault occurrence.
Based on these characteristics, real-time systems can be classified into different categories, such as:
Hard real-time systems: These are systems that have to meet hard deadlines for all their tasks. A single deadline miss can result in catastrophic consequences, such as loss of life or property. Examples of hard real-time systems are flight control systems, nuclear reactor control systems, and pacemakers.
Soft real-time systems: These are systems that have to meet soft deadlines for most of their tasks. A few deadline misses can be tolerated without serious consequences, but they may affect the quality of service (QoS) or user satisfaction. Examples of soft real-time systems are multimedia applications, video games, and online auctions.
Firm real-time systems: These are systems that have to meet firm deadlines for some of their tasks. A deadline miss can result in some penalty or degradation in performance, but not in catastrophic consequences. Examples of firm real-time systems are stock market trading systems, robot navigation systems, and industrial control systems.
Real-Time System Performance Measures and Analysis Techniques
Another important step in designing a real-time system is to define and evaluate its performance measures and analysis techniques. Some of the common performance measures of real-time systems are:
Utilization: This is the ratio of the total execution time of all tasks to the total available time. It indicates how efficiently the system uses its resources.
Throughput: This is the number of tasks completed per unit time. It indicates how productive the system is.
Response time: This is the time elapsed from the arrival of a task to its completion. It indicates how fast the system responds to requests.
Jitter: This is the variation in the response time of tasks. It indicates how stable the system is.
Deadline miss ratio: This is the fraction of tasks that miss their deadlines. It indicates how reliable the system is.
Some of the common analysis techniques for real-time systems are:
Analytical methods: These are mathematical methods that use formulas or equations to compute the performance measures of real-time systems. They are based on certain assumptions and simplifications about the system behavior and parameters. They provide exact or approximate results that can be used for design optimization or verification.
Simulation methods: These are computational methods that use software tools or models to mimic the behavior and parameters of real-time systems. They are based on actual or synthetic data and scenarios about the system inputs and outputs. They provide empirical results that can be used for design evaluation or validation.
Experimental methods: These are empirical methods that use hardware devices or prototypes to measure the performance of real-time systems. They are based on actual or simulated data and scenarios about the system inputs and outputs. They provide realistic results that can be used for design testing or debugging.
Real-Time Task Allocation and Scheduling Algorithms
One of the core challenges in designing a real-time system is to allocate and schedule the tasks to the available resources, such as processors, memory, or communication channels. The goal is to ensure that all tasks meet their deadlines while maximizing the system performance and minimizing the resource consumption. There are many factors that affect the task allocation and scheduling problem, such as:
Task characteristics: These include the task arrival pattern (periodic, sporadic, or aperiodic), the task execution time (constant, variable, or unknown), the task deadline (hard, soft, or firm), the task priority (static or dynamic), and the task dependency (independent or interdependent).
Resource characteristics: These include the resource type (single or multiple), the resource capacity (homogeneous or heterogeneous), the resource availability (static or dynamic), and the resource contention (shared or exclusive).
System characteristics: These include the system mode (offline or online), the system objective (optimization or feasibility), and the system constraints (resource, timing, or power).
Based on these factors, there are many types of task allocation and scheduling algorithms for real-time systems, such as:
Static algorithms: These are algorithms that allocate and schedule tasks before the system starts running. They are based on prior knowledge of the task and resource characteristics. They provide predictable and optimal results, but they are not flexible or adaptable to changes.
Dynamic algorithms: These are algorithms that allocate and schedule tasks during the system execution. They are based on current information of the task and resource characteristics. They provide flexible and adaptab