Sherif Abdelwahed

Self-optimization in computer systems via on-line control: application to power management

Computer systems hosting critical e-commerce applications must typically satisfy stringent quality-of-service (QoS) requirements under dynamic operating conditions and workloads. Also, as such systems increase in size and complexity, maintaining the desired QoS by manually tuning the numerous performance-related parameters will become very difficult. This paper addresses the design of self-optimizing computer systems using a generic online control framework in which the control actions governing the operation of the system are obtained by optimizing its behavior, as forecast by a mathematical model, over a limited time horizon. As a specific application of this control technique, we show how to minimize the power consumed by a single computer processing a time-varying workload. Assuming a processor capable of operating at multiple frequencies, we design an online controller to satisfy the QoS requirements of the workload while operating the processor at the lowest possible frequency. We describe the processor model, formulate the power management problem, and derive the online control algorithm. The performance of the controller is evaluated using representative e-commerce workloads. Finally, we discuss how the proposed technique can be applied to other resource management problems in computer systems.

Online control for self-management in computing systems

Dependable computer systems hosting critical commerce, transportation, and military applications, among others, must satisfy stringent quality-of-service (QoS) requirements. However, as these systems become increasingly complex, maintaining the desired QoS by manually tuning the numerous performance-related parameters are very difficult. This paper develops a generic online control framework to design self-managing computer systems. The proposed approach explores a limited region of the system state-space at each time step and decides the best control action accordingly. We present two case studies to demonstrate the practicality of the proposed control framework.

A control-based framework for self-managing distributed computing systems

This paper describes an online control framework to design self-managing distributed computing systems that continually optimize their performance in response to changing computing demands and environmental conditions. An online control technique is used in conjunction with predictive filters to tune the performance of individual system components based on their forecast behavior. In a distributed setting, a global controller is used to manage the interaction between components such that overall system requirements are satisfied.

Enabling Self-Managing Applications using Model-based Online Control Strategies

The increasing heterogeneity, dynamism and uncertainty of emerging DCE (Distributed Computing Environment) systems imply that an application must be able to detect and adapt to changes in its state, its requirements and the state of the system to meet its desired QoS constraints. As system and application scales increase, ad hoc heuristic-based approaches to application adaptation and self-management quickly become insufficient. This paper builds on the Accord programming system for rule-based self-management and extends it with model-based control and optimization strategies. This paper also presents the development of a self-managing data streaming service based on online control using Accord. This service is part of a Grid-based fusion simulation workflow consisting of long-running simulations, executing on remote supercomputing sites and generating several terabytes of data, which must then be streamed over a wide-area network for live analysis and visualization. The self-managing data streaming service minimize data streaming overheads on the simulations, adapt to dynamic network bandwidth and prevent data loss. An evaluation of the service demonstrating its feasibility is presented.

Engineering future cyber-physical energy systems: Challenges, research needs, and roadmap

Cyber-physical energy systems require the integration of a heterogeneous physical layers and decision control networks, mediated by decentralized and distributed local sensing/actuation structures backed by an information layer. With the North American Electric Reliability Corporation (NERC) Critical Infrastructure Protection (CIP) [1] requirements and presidents visions of more secure, reliable and controllable cyber-physical system, a new paradigm for modeling and research investigation is needed. In this paper, we present common challenges and our vision of solutions to design advanced Cyber-physical energy systems with embedded security and distributed control. Finally, we present a survey of our research results in this domain.

Verifying distributed real-time properties of embedded systems via graph transformations and model checking

Component middleware provides dependable and efficient platforms that support key functional, and quality of service (QoS) needs of distributed real-time embedded (DRE) systems. Component middleware, however, also introduces challenges for DRE system developers, such as evaluating the predictability of DRE system behavior, and choosing the right design alternatives before committing to a specific platform or platform configuration. Model-based technologies help address these issues by enabling design-time analysis, and providing the means to automate the development, deployment, configuration, and integration of component-based DRE systems. To this end, this paper applies model checking techniques to DRE design models using model transformations to verify key QoS properties of component-based DRE systems developed using Real-time CORBA. We introduce a formal semantic domain for a general class of DRE systems that enables the verification of distributed non-preemptive real-time scheduling. Our results show that model-based techniques enable design-time analysis of timed properties and can be applied to effectively predict, simulate, and verify the event-driven behavior of component-based DRE systems.

On the application of predictive control techniques for adaptive performance management of computing systems

This paper addresses adaptive performance management of real-time computing systems. We consider a generic model-based predictive control approach that can be applied to a variety of computing applications in which the system performance must be tuned using a finite set of control inputs. The paper focuses on several key aspects affecting the application of this control technique to practical systems. In particular, we present techniques to enhance the speed of the control algorithm for real-time systems. Next we study the feasibility of the predictive control policy for a given system model and performance specification under uncertain operating conditions. The paper then introduces several measures to characterize the performance of the controller, and presents a generic tool for system modeling and automatic control synthesis. Finally, we present a case study involving a real-time computing system to demonstrate the applicability of the predictive control framework.

Practical Implementation of Diagnosis Systems Using Timed Failure Propagation Graph Models

Timed failure propagation graphs (TFPGs) are causal models that capture the temporal aspects of failure propagation in typical engineering systems. In this paper, we present several practical modeling and reasoning considerations that have been addressed based on experience with complex real-time vehicle subsystems. These include handling intermittent faults, reasoning over dynamically commanded test sequences, dealing with the constraints of limited computational resources, and providing automated model verification. We finally present a vehicle subsystem case study.

Performance estimation of distributed real-time embedded systems by discrete event simulations

Key challenges in the performance estimation of distributed real-time embedded (DRE) systems include the systematic measurement of coverage by simulations, and the automated generation of directed test vectors. This paper investigates how DRE systems can be represented as discrete event systems (DES) in continuous time, and proposes an automated method for the performance evaluation of such systems. The proposed method also provides a way for the verification of dense time properties for a large class of DRE systems. This approach provides a formal executable model allowing to bridge the gap between simulations and formal verification. Our results show that the proposed DES-based evaluation method can achieve better coverage in large-scale DRE systems than alternative methods.

Model-based analysis of distributed real-time embedded system composition

Key challenges in distributed real-time embedded (DRE) system developments include safe composition of system components and mapping the functional specifications onto the target platform. Model-based verification techniques provide a way for the design-time analysis of DRE systems enabling rapid evaluation of design alternatives with respect to given performance measures before committing to a specific platform. This paper introduces a semantic domain for model-based analysis of a general class of DRE systems capturing their key time-based performance measures. We then utilize this semantic domain to develop a verification strategy for preemptive schedulability using available model checking tools. The proposed framework and verification strategy is demonstrated on a mission-critical avionics DRE system case study.