This paper presents a feedback control real-time scheduling (FCS) framework for adaptive real-time systems. An advantage of the FCS framework is its use of feedback control theory (rather than ad hoc solutions) as a scientific underpinning. We apply a control theory based methodology to systematically design FCS algorithms to satisfy the transient and steady state performance specifications of real-time systems. In particular, we establish dynamic models of real-time systems and develop performance analyses of FCS algorithms, which are major challenges and key steps for the design of control theory based adaptive real-time systems. We also present a FCS architecture that allows plug-ins of different real-time scheduling policies and QoS optimization algorithms. Based on our framework, we identify different categories of real-time applications where different FCS algorithms should be applied. Performance evaluation results demonstrate that our analytically tuned FCS algorithms provide robust transient and steady state performance guarantees for periodic and aperiodic tasks even when the task execution times vary by as much as 100% from the initial estimate.

The Internet is undergoing substantial changes from a communication and browsing infrastructure to a medium for conducting business and marketing a myriad of services. The World Wide Web provides a uniform and widely-accepted application interface used by these services to reach multitudes of clients. These changes place the web server at the center of a gradually emerging eservice infrastructure with increasing requirements for service quality and reliability guarantees in an unpredictable and highly-dynamic environment.

We develop Feedback Control real-time Scheduling (FCS) as a unified framework to provide Quality of Service (QoS) guarantees in unpredictable environments (such as ebusiness servers on the Internet). FCS includes four major components. First, novel scheduling architectures provide performance control to a new category of QoS critical systems that cannot be addressed by traditional open loop scheduling paradigms. Second, we derive dynamic models for computing systems for the purpose of performance control. These models provide a theoretical foundation for adaptive performance control. Third, we apply established control methodology to design scheduling algorithms with proven performance guarantees, which is in contrast with existing heuristics-based solutions relying on laborious design/tuning/testing iterations. Fourth, a set of controlbased performance specifications characterizes the efficiency, accuracy, and robustness of QoS guarantees. The

With increasing costs of energy consumption and cooling, power management in server clusters has become an increasingly important design issue. Current clusters for real-time applications are designed to handle peak loads, where all servers are fully utilized. In practice, peak load conditions rarely happen and clusters are most of the time underutilized. This creates the opportunity for using slower frequencies, and thus smaller energy consumption, with little or no impact on the Quality of Service (QoS), for example, performance and timeliness. In this work we present a cluster-wide QoS-aware technique that dynamically reconfigures the cluster to reduce energy consumption during periods of reduced load. Moreover, we also investigate the effects of local QoS-aware power management using Dynamic Voltage Scaling (DVS). Since most real-world clusters consist of machines of different kind (in terms of both performance and energy consumption) we focus on heterogeneous clusters. For validation, we describe and evaluate an implementation of the proposed scheme using the Apache Webserver in a small realistic cluster. Our experimental results show that using our scheme it is possible to save up to 45 % of the total energy consumed by the servers, maintaining average response times within the specified deadlines and number of dropped requests within the required amount. 1

Abstract—Real-time scheduling theory offers constant-time schedulability tests for periodic and sporadic tasks based on utilization bounds. Unfortunately, the periodicity or the minimal interarrival-time assumptions underlying these bounds make them inapplicable to a vast range of aperiodic workloads such as those seen by network routers, Web servers, and event-driven systems. This paper makes several important contributions toward real-time scheduling theory and schedulability analysis. We derive the first known bound for schedulability of aperiodic tasks. The bound is based on a utilization-like metric we call synthetic utilization, which allows implementing constant-time schedulability tests at admission control time. We prove that the synthetic utilization bound for deadline-1 monotonic scheduling of aperiodic tasks is 1þ ffiffiffiffiffi p. We also show that no other time-independent scheduling policy can have a higher 1=2 schedulability bound. Similarly, we show that EDF has a bound of 1 and that no dynamic-priority policy has a higher bound. We assess the performance of the derived bound and conclude that it is very efficient in hit-ratio maximization. Index Terms—Real-time scheduling, schedulability analysis, utilization bounds, aperiodic tasks. 1

This paper generalizes the notion of utilization bounds for schedulability of aperiodic tasks to the case of distributed resource systems. In the basic model, aperiodically arriving tasks are processed by multiple stages of a resource pipeline within end-to-end deadlines. The authors consider a multi-dimensional space in which each dimension represents the instantaneous utilization of a single stage. A feasible region is derived in this space such that all tasks meet their deadlines as long as pipeline resource consumption remains within the feasible region. The feasible region is a multi-dimensional extension of the single-resource utilization bound giving rise to a bounding surface in the utilization space rather than a scalar bound. Extensions of the analysis are provided to non-independent tasks and arbitrary task graphs. We evaluate the performance of admission control using simulation, as well as demonstrate the applicability of these results to task schedulability analysis in the total ship computing environment envisioned by the US navy. Keywords: Real-time scheduling, schedulability analysis, utilization bounds, aperiodic tasks, total ship computing environment. 1

Multihop wireless sensor networks have recently emerged as an important embedded computing platform. This paper defines a quantitative notion of real-time capacity of a wireless network. Real-time capacity describes how much real-time data the network can transfer by their deadlines. A capacity bound is derived that can be used as a sufficient schedulability condition for a class of fixedpriority packet scheduling algorithms. Using this bound, a designer can perform capacity planning prior to network deployment to ensure satisfaction of applications ’ real-time requirements. 1

Utilization bounds for schedulability of aperiodic tasks are new in real-time scheduling literature. All aperiodic bounds known to date apply only to independent tasks. They either assume a liquid task model (one with infinitely many infinitesimal tasks) or are limited to deadline-monotonic and earliest-deadline first scheduling. In this paper, the authors make two important contributions. First, they derive the first aperiodic utilization bound that considers a task model with resource requirements. Second, the new bound is a function of a parameter called preemptable deadline ratio that depends on the scheduling policy. We show that many scheduling policies can be classified by this parameter allowing per-policy bounds to be derived. Simulation results demonstrating the applicability of aperiodic utilization bounds are presented.

Real-time scheduling theory has developed powerful tools for translating conditions on aggregate system utilization into per-task schedulability guarantees. The main breakthrough has been Liu and Layland's utilization bound for schedulability of periodic tasks. In 2001 this bound was generalized by Abdelzaher and Lu to the aperiodic task case. In this paper, we further generalize the aperiodic bound to the case of multiprocessors, and present key new insights into schedulability analysis of aperiodic tasks.

While utilization bound based schedulability test is simple and effective, it is often difficult to derive the bound itself. For its analytical complexity, utilization bound results are usually obtained on a case-by-case basis. In this paper, we develop a general framework that allows one to effectively derive schedulability bounds for a wide range of real-time systems with different workload patterns and schedulers. Our analytical model is capable of describing a wide range of tasks and schedulers ’ behaviors. We propose a new definition of utilization, called workload rate. While similar to utilization, workload rate enables flexible representation of different scheduling and workload scenarios and leads to uniform derivation of schedulability bounds. We derive a parameterized schedulability bound for static priority schedulers with arbitrary priority assignment. Existing utilization bounds for different priority assignments and task releasing patterns can be derived from our closed-form formula by simple assignments of proper parameters. 1.