Pareto-based soft real-time task scheduling in multiprocessor systems

Static task scheduling in multiprocessor frameworks is one of the well-defined NP hard problem. Due to optimal utilization of processors and in addition investing less time, the scheduling of tasks in multiprocessor frameworks is of extraordinary significance. To solve NP hard problem using traditional strategies takes reasonable measures of time. Over the time, various heuristic procedures were presented for comprehending it. Therefore, heuristic methods such as genetic algorithms are appropriate methods for task scheduling in multiprocessor system. In this paper, a new GA for static task scheduling in multiprocessor systems has been presented whose priority of tasks’ execution is based on the height of task in graph and other mentioned parameters and then scheduling is performed. This proposed method is simulated and then compared with basic genetic algorithm.

A novel intelligent method for task scheduling in multiprocessor systems using genetic algorithm

Fault-tolerant LPT task scheduling in multiprocessor systems

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.

Real-time systems are those systems in which the correctness of the system depends not only on the logical results of computation but also on the time at which the results are produced [Stankovic 1988]. They span a broad spectrum of complexity from very simple microcontrollers in embedded systems (a microprocessor controlling an automobile engine) to highly sophisticated, complex, and distributed systems (air traffic control for the continental United States). Other real-time systems include command and control systems, process control systems, and multimedia and high-speed communication systems. Some real-time systems are beginning to add expert systems and other AI technology, creating additional requirements and complexities. At least three major trends in the real-time and embedded systems field have had a major impact on its technology: the increased growth and sophistication of embedded systems, the development of more scientific and technological results for hard real-time systems, and the advent of distributed multimedia. Most embedded systems consist of a small microcontroller and limited software situated within some product such as a microwave oven or automobile. However, with the increasing sophistication of such systems, powerful microcontrollers and digital signal processing (DSP) chips are commonly used, as are off-the-shelf real-time operating systems and design and debugging tools. Many people working with embedded systems deal on a daily basis with sensors and data acquisition technology and systems; others construct architectures based on single-board computers (many are still 68000-based, but RISC processors are being used more and more) and buses such as the VME bus. Many people are involved with the programming and debugging of embedded systems, largely using the C programming language and cross development and debugging platforms. Embedded systems may or may not have real-time constraints. Hard real-time systems are those in which missing an important deadline can cause severe consequences, even death. In this area, many fundamental results have been developed. For example, in real-time scheduling, rate monotonic analysis has enabled careful evaluation of many practical systems; the concept and analysis of competitive algorithms has provided important scheduling bounds and limits; and on-line planning has added flexible and dynamic capabilities to real-time systems. Operating systems research has produced predictable primitives, time-constrained synchronization techniques, and reservation and admission-control paradigms. Many other results exist in real-time architecture, fault tolerance, communication protocols, specification and design tools, formal verification, databases and object-oriented systems. Emphasis on all these areas is expected to increase in the foreseeable future. Many hard real-time systems are embedded systems. Distributed multimedia have produced a new set of soft real-time requirements. Real-time principles lie at the heart of distributed multimedia, but without the concomitant high reliability

We study the problem of scheduling periodic-time-critical tasks on a multiprocessor system. A periodic-time-critical task consists of a certain number of computations, each arising at a fixed interval of time, called the period of the task. The ratio of the computation time to the period is called the utilization factor of the task. Each computation has a prescribed deadline which must be guaranteed to be met, failing which there is likely to result an irrepairable loss. The scheduling problem is to specify the processor on which a computation is to be made and the order in which such computations will be made, such that every computation meets its deadline. The goal is to minimize the number of processors needed. The problem is NP-complete. As such, we devise a heuristic algorithm and analyze its performance. The algorithm assigns tasks based on the utilization factors of the tasks. We analyze the worst case performance of the algorithm by obtaining bounds on the ratio of the maximum number of processors needed by the algorithm to the minimum number of processors required. It is shown that this ratio is 2.

The number of processors is increasing, but the usefulness of parallel computation is not better leveraged due to the inflexibility of design and implementation for multiprocessor embedded system applications. A higher level abstraction (i.e., a parallel programming framework) can ease the programmers to define parallelism for tasks in an application but designers still face the complexity of mapping high-level requirements to the syntax and semantics of a parallel programming interface. Nevertheless, embedded system applications execute various periodic tasks that are carried out repeatedly within a certain time interval and these tasks may be able to run in parallel to utilize the system efficiently. Therefore, in this paper, we propose a parallel loop-based task construct approach to automate the design process of embedded system applications from AADL models for a parallel programming framework. To illustrate the applicability of our mechanism, we use a well-known parallel programming interface called OpenMP to demonstrate the automation process in mapping tasks over multiple processor cores. To ensure meeting high-level requirements of embedded system applications, we analyze the existing OpenMP scheduling mechanisms and propose a layer of adaptation. We show that our proposed adaptation layer facilitates a tighter execution time bound for time-sensitive tasks or a better throughput for tasks that require higher quality of service. Thus, the proposed design automation framework is applicable for a variety of applications with different quality of service (QoS) requirements preserved at the lower level.

EDF (Earliest Deadline First) has been proved to be optimal scheduling algorithm for single processor real-time system. It also performs well for multiprocessor system. Limitation of EDF is that its performance decreases exponentially when system becomes slightly overloaded. ACO (Ant Colony Optimization) based scheduling algorithm performs well in both underloaded and overloaded conditions. But its limitation is that it takes more time for execution compared to EDF. In this paper, an adaptive algorithm for multiprocessor real-time system is proposed, which is combination of both of these algorithms. The proposed algorithm along with EDF and ACO based algorithm is simulated for real-time multiprocessor system and the results are obtained. The performance is measured in terms of Success Ratio (SR) and Effective CPU Utilization (ECU). Execution Time taken by each scheduling algorithm is also measured. From analysis and experiments, it reveals that the proposed algorithm is fast as well as efficient in both underloaded and overloaded conditions for real-time multiprocessor systems.

Task scheduling in real-time systems is a concept by which we can schedule the tasks according to their priorities. In hard real-time systems, the task scheduling is more important due to the chance of system failure. We discuss EDF task scheduling which is an optimal technique for the uniprocessor systems. The existing result of the QPA algorithm was applied on the uniprocessor system to check the schedulability of the tasks in uniprocessor system. We have extended the QPA algorithm to check the schedulability of the task sets in multiprocessor systems. Our algorithm is based on QPA algorithm and the utilization balanced algorithm. The proposed algorithm checks the absolute deadlines much faster than the existing QPA algorithm for uniprocessor real-time systems.

Simulation and performance evaluation of parallel software on multiprocessor systems

The power consumption of modern high-performance processors is becoming a major concern because it leads to increased heat dissipation and decreased reliability. While many techniques have been proposed to reduce power consumption for uni-processors, there has been considerably less work on multi-processor systems. In this paper we focus on power-aware scheduling for multi-processor real-time systems. Based on the idea of slack sharing among processors, we propose two novel scheduling algorithms for task sets with and without precedence constraints. These scheduling techniques reclaim the time unused by a task to reduce the execution speed of future tasks, and thus reduce the total energy consumption of the system. Simulation results indicate that our algorithms achieve up to 60% energy savings on multi-processor systems with variable voltage processors.

We present a coordination language and its semantics for specification and implementation of object-oriented real-time systems. Real-time systems operate under real-time constraints, and our language supports expression thereof. In our language, a system is modeled by two separate but complementary descriptions: A collection of objects define the system's structure and functional behavior and a set of interaction constraints define how these objects may interact. Our language thereby supports development of real-time systems by enabling objects build in isolation or re-used from other systems to be composed via interaction constraints. We use the Actor model to describe objects and the concept of real-time synchronizers to describe interaction constraints. Our model is accompanied by a formal semantics that precisely defines what real-time constraints means, and what constitutes a program's correct real-time behaviors. The semantics defines how the system may evolve in the real-time domain, and what progress guarantees the language makes. We briefly discuss implementation problems and potential solutions.

Many real-time database systems are contained in environments that exhibit restricted access to information, such as government agencies, hospitals and military institutions, where mandatory access control for security is required. In addition to such security constraints, real-time database systems have real-time integrity constraints. These real-time constraints require deadlines to be met and data to be temporally consistent. Conventional multi-level secure database models are inadequate for time-critical applications and conventional real-time database models do not support security constraints. We propose a new concurrency control algorithm for secure real-time databases. We implement the algorithm and study the performance using a real-time database system simulation model. Results show that the algorithm performs fairly well in terms of security and timeliness compared to the non-secure algorithm. We argue and show that achieving more security does not necessarily mean a great deal of sacrifice in maintaining real-time constraints.

Embedded multiprocessor systems are often used in the domain of real-time stream processing applications to keep up with increasing power and performance requirements. Examples of such real-time stream processing applications are digital radio baseband processing and WLAN transceivers. These stream processing applications often have a dynamic character. For example the execution times and execution rates of the tasks of the stream processing applications vary and can even be data dependent. To cope with this dynamic behavior, the tasks are executed on the multiprocessor system in a data-driven fashion on run-time scheduled resources. Another important aspect of real-time stream processing applications are their strict performance constraints. A periodic source or sink imposes a throughput constraint and also latency constraints are common. For stream processing applications, violating these constraints typically leads to a major reduction of the quality of service of the applications. To prevent such violations of the temporal constraints, analysis methods are used. These analysis methods ease the processes of dimensioning, programming and optimizing the multiprocessor systems within these temporal constraints. Analysis methods rely on accurate abstractions of the analyzed applications. However, current abstractions have a limited accuracy and applicability and do therefore not always suffice. In this thesis we will present abstractions for multiprocessor systems in which the tasks are executed in a data-driven fashion and in which they have aperiodic schedules. These aperiodic schedules can capture the dynamic behavior of the real-time stream processing applications. We present accurate abstractions based on dataflow analysis techniques which can be used for a large class of multiprocessor systems. Compared to state of the art, we broaden the scope of dataflow analysis techniques, improve their accuracy and provide a new higher level of abstraction.

This paper proposes an off-line dynamic voltage scaling (DVS) scheme that can be integrated with EDF$$^{(k)}$$(k), which is a global real-time scheduling algorithm for symmetric multiprocessor systems. The scheme computes the static execution speed for each individual task assuming the task's worst-case execution. Based on the individual speed, it determines static dual speeds off-line for each task to make use of the gap between actual execution demand and the worst-case execution demand. The simulation results show that the proposed scheme combined with an existing online DVS technique can reduce energy consumption by up to 37 % compared with a uniform speed technique when the number of processors is 32.