Deadline assignment in a distributed soft real-time system

In a distributed environment, tasks often have processing demands on multiple different sites. A distributed task is usually divided up into several subtasks, each one to be executed at some site in order. In a real-time system, an overall deadline is usually specified by an application designer indicating when a distributed task is to be finished. However, the problem of how a global deadline is automatically translated to the deadline of each individual subtask has not been well studied. This paper examines (through simulations) four strategies for subtask deadline assignment in a distributed soft real-time environment.published_or_final_versio

Synthesising robust schedules for minimum disruption repair using linear programming

An off-line scheduling algorithm considers resource, precedence, and synchronisation requirements of a task graph, and generates a schedule guaranteeing its timing requirements. This schedule must, however, be executed in a dynamic and unpredictable operating environment where resources may fail and tasks may execute longer than expected. To accommodate such execution uncertainties, this paper addresses the synthesis of robust task schedules using a slack-based approach and proposes a solution using integer linear programming (ILP). Earlier we formulated a time slot based ILP model whose solutions maximise the temporal flexibility of the overall task schedule. In this paper, we propose an improved, interval based model, compare it to the former, and evaluate both on a set of random scenarios using two public domain ILP solvers and a proprietary SAT/ILP mixed solver

Deadline Missing Prediction Through the Use of Milestones

Distributed Real-Time Thread is an important concept for distributed real-time systems. Distributed Threads are schedulable entities with an end-to-end deadline that transpose nodes, carrying their scheduling context. In each node, the thread will be locally scheduled according to a local deadline, which is defined by a deadline partitioning algorithm. Mechanisms for predicting the missing of deadlines are fundamental if corrective actions are incorporated for improving system quality of service. In this work, a mechanism for predicting missing deadlines is proposed and evaluated through simulation. In order to illustrate the main characteristics of the proposed mechanism, experiments will be presented taking into account different scenarios of normal load and overload. Simulations show that the deadline missing prediction mechanism proposed presents good results for improving the overall performance and availability of distributed systems

A Taxonomy of Workflow Management Systems for Grid Computing

With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. We also survey several representative Grid workflow systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure

Convex optimization framework for intermediate deadline assignment in soft and hard real-time distributed systems

It is generally challenging to determine end-to-end delays of applications for maximizing the aggregate system utility subject to timing constraints. Many practical approaches suggest the use of intermediate deadline of tasks in order to control and upper-bound their end-to-end delays. This paper proposes a unified framework for different time-sensitive, global optimization problems, and solves them in a distributed manner using Lagrangian duality. The framework uses global viewpoints to assign intermediate deadlines, taking resource contention among tasks into consideration. For soft real-time tasks, the proposed framework effectively addresses the deadline assignment problem while maximizing the aggregate quality of service. For hard real-time tasks, we show that existing heuristic solutions to the deadline assignment problem can be incorporated into the proposed framework, enriching their mathematical interpretation

사물인터넷 애플리케이션의 적응형 동적 스케줄링 기법

학위논문 (석사)-- 서울대학교 대학원 : 공과대학 컴퓨터공학부, 2019. 2. 하순회.IoT시스템은매우다른성능과기능을가진이기종스마트장치로구성된분산임베디드시스템이다. IoT시스템에서일반적으로리소스요구사항과실시간요구사항이서로 다른 많은 IoT 애플리케이션들이 동시에 실행된다. 또한, 전력 소비 및 장치 수명과 같은 비 기능적 특성이 중요하게 고려된다. IoT 애플리케이션은 언제든지 추가되거나 제거 될 수 있으며 런타임에 디바이스 상태가 변경 될 수 있다. 이 같이 시스템은 동적 특성을 갖기 때문에 IoT 애플리케이션을 스마트 디바이스에 매핑/스케줄링 하는 것은 매우까다로운문제이다.이문제를해결하기위해점진적매핑및글로벌재매핑의두 가지 스케줄링 기법으로 구성된 새로운 적응적 스케줄링 기법을 제안한다. 동적 환경 변화에 대한 빠른 응답을 제공하기 위해 점진적 매핑 방법을 제안하며, 정적 상태에서 비 기능적 특성에 기초하여 주어진 목적 함수를 최적화하기 위해 주기적으로 IoT 애플리케이션의 전체 태스크를 모두 다시 스케줄링 하는 유전 알고리즘 기반 글로벌 재 매핑 방법은 제안한다. 제안 된 스케줄링 방법의 두 가지 성능 지표로 애플리케이션 수용 비율 및 에너지 소비량을 사용하였으며, 성능 및 실용성은 무작위로 생성 된 시나리오를 사용한 시뮬레이션 환경을 통해 검증한다.An IoT system can be regarded as a distributed embedded system that is composed of heterogeneous smart devices with very different performance and functions. Also many IoT applications that have different resource requirements and real-time requirements will run concurrently in the IoT system. In addition, non-functional properties such as power consumption and device lifetime are considered important. Since an IoT application can be added or removed anytime and the device status may change at run-time, the system is unprecedentedly dynamic in its configuration, which brings up a challenging scheduling problem of IoT applications onto the smart devices. To tackle this problem, we propose a novel adaptive scheduling technique that consists of two scheduling techniques, incremental and global. An incremental heuristic method is proposed to provide fast responsiveness to dynamically changing configuration. During the steady-state operation, a GA-based method is applied to perform global rescheduling of IoT applications periodically to optimize a given objective function based on non-functional properties. We use the acceptance ratio of new applications and energy consumption as two performance metrics of the proposed scheduling method. The viability of the proposed approach is verified by extensive simulations with randomly generated scenarios.Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v List of Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2. Problem Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.1 Target IoT system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 Motivational Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.3 Problem Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3. Schedulability Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.1 Transformation of a Task Graphs to Independent Tasks . . . . . . . . . . 10 3.2 Schedulability Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 4. Proposed Mapping Technique . . . . . . . . . . . . . . . . . . . . . . . . . 14 4.1 Incremental Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 4.2 Global Re-mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 5. Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 5.1 Benchmarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 5.2 Experiment 1 (Incremental Mapping) . . . . . . . . . . . . . . . . . . . 23 5.3 Experiment 2 (Global Re-mapping) . . . . . . . . . . . . . . . . . . . . 25 5.4 Experiment 3 (Sensitivity Analysis) . . . . . . . . . . . . . . . . . . . . 27 6. RelatedWork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 7. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 요 약 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35Maste

Research issues in real-time database systems

Cataloged from PDF version of article.Today's real-time systems are characterized by managing large volumes of data. Efficient database management algorithms for accessing and manipulating data are required to satisfy timing constraints of supported applications. Real-time database systems involve a new research area investigating possible ways of applying database systems technology to real-time systems. Management of real-time information through a database system requires the integration of concepts from both real-time systems and database systems. Some new criteria need to be developed to involve timing constraints of real-time applications in many database systems design issues, such as transaction/query processing, data buffering, CPU, and IO scheduling. In this paper, a basic understanding of the issues in real-time database systems is provided and the research efforts in this area are introduced. Different approaches to various problems of real-time database systems are briefly described, and possible future research directions are discussed

Real-time transaction processing for autonomic grid application

The advances in computing and communication technologies and software have resulted in an explosive growth in computing systems and applications that impact all aspects of our life. Computing systems are expected to be effective and serve useful purpose when they are first introduced and continue to be useful as condition changes. With increase in complexity of systems and applications, their development, configuration, and management challenges are beyond the capabilities of existing tools and methodologies. So the system becomes unmanageable and insecure. So in order to make the systems selfmanageable and secure the concept of Autonomic computing is evolved. Autonomic computing offers a potential solution to these challenging research problems. It is inspired by nature and biological systems (such as the autonomic nervous system) that have evolved to cope with the challenges of scale, complexity, heterogeneity and unpredictability by being decentralized, context aware, adaptive and resilient. This new era of computing is driven by the convergence of biological and digital computing systems and is characterized by being self-defining, self-configuring, self-optimizing, self-protecting, self-healing, context aware and anticipatory. Autonomic computing is a new computing model to self manages computing systems with a minimal human interference. It provides an unprecedented level of self-regulation and hides complexity from Users. The Autonomic computing initiative is inspired by the human body’s autonomic nervous system. The autonomic nervous system monitors the heart- beats, checks blood sugar levels and maintains normal body temperature with out any conscious effort from the human. There is an important distinction between autonomic activity in the human body and autonomic responses in computer systems. Many of the decision made autonomic elements in computer systems make decisions based on tasks, which are chosen to be delegated to the technology. The influences of the autonomic nervous systems may imply that the autonomic computing initiative is concerned only with lowlevel self-managing capability such as reflex reaction. The basic application area of autonomic computing is grid computing. Both autonomic computing and grid computing are proposed as innovations of IT. Autonomic computing aims to present a solution to the rapidly increasing complexity crises in IT industry, as grid computing tries to share and integrate distributed computational resources and data resources. Basic aim is to implement the autonomic computing in grid related study like autonomic task distribution and handling in grids, and autonomic resource allocation. In this thesis paper we presents methods of calculating deadlines of global and local transaction And sub transaction by taking EDF algorithm and measure the performance by taking miss ratio in Different workload. We implement this work in an existing grid. The basic aim is to know autonomic computing better. It is a model to self manage computing Systems with minimal human interference. Self manage has properties like self-configuration, self-optimization, self-healing, self-protection. Autonomic grid computing combines autonomic computing with grid technologies to help companies to reduce the complexity associated with the grid system and hides the complexity from their grid user. Autonomic real-time transaction services incorporate fault tolerance into autonomic grid technology by automatically recovering systems from various failures. Here in this paper Deadlines of global transaction, sub transaction and local transaction are calculated by taking parameters arrival time, execution time, relative deadline, and slack time. We are taking a periodic transaction having λ (transaction arrival rate per second) Tasks are generated at different nodes with Poisson ratio with λ as workload. Miss ratio is the performance metrics. With increase in workload miss ratio first decreased and then rose. The reason was each sub transaction acted as a unit to compete for resources so that more workload the more system resource they consumed. So more transaction missed their deadlines, as they could not get enough resource in time. EDF algorithm has both less global and local miss ratios then other scheduling algorithm. If EDF is compare with FCFS or SJF or HPF it is apparent that both algorithms perform almost identically until no of transaction is low, then EDF misses fewer dead lines than other. Real-time transaction can handled by the grid in autonomic environment and satisfy properties of autonomic computing