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AbstractÐThe 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 e-service infrastructure with increasing requirements for service quality and reliability guarantees in an unpredictable and highly-dynamic environment. This paper describes performance control of a Web server using classical feedback control theory. We use feedback control theory to achieve overload protection, performance guarantees, and service differentiation in the presence of load unpredictability. We show that feedback control theory offers a promising analytic foundation for providing service differentiation and performance guarantees. We demonstrate how a general Web server may be modeled for purposes of performance control, present the equivalents of sensors and actuators, formulate a simple feedback loop, describe how it can leverage on real-time scheduling and feedback-control theories to achieve per-class response-time and throughput guarantees, and evaluate the efficacy of the scheme on an experimental testbed using the most popular Web server, Apache. Experimental results indicate that controltheoretic techniques offer a sound way of achieving desired performance in performance-critical Internet applications. Our QoS (Quality-of-Service) management solutions can be implemented either in middleware that is transparent to the server, or as a library called by server code.

Virtualized data centers enable sharing of resources among hosted applications. However, it is difficult to satisfy servicelevel objectives (SLOs) of applications on shared infrastructure, as application workloads and resource consumption patterns change over time. In this paper, we present AutoControl, a resource control system that automatically adapts to dynamic workload changes to achieve application SLOs. AutoControl is a combination of an online model estimator and a novel multi-input, multi-output (MIMO) resource controller. The model estimator captures the complex relationship between application performance and resource allocations, while the MIMO controller allocates the right amount of multiple virtualized resources to achieve application SLOs. Our experimental evaluation with RUBiS and TPC-W benchmarks along with production-trace-driven workloads indicates that AutoControl can detect and mitigate CPU and disk I/O bottlenecks that occur over time and across multiple nodes by allocating each resource accordingly. We also show that AutoControl can be used to provide service differentiation according to the application priorities during resource contention.

Absrrucr-The congestion control mechanisms used in TCP have been the focus of numerous studies and have undergone a number of enhancements. However, even with these enhancements, TCP connections still experience alarmingly high loss rates, especially during times of congestion. To alleviate this problem, the IETF is considering active queue management mechanisms, such as RED, for deployment in the network. In this paper, we first show that the effectiveness of RED depends, to a large extent, on the appropriate parameterization of the RED queue. We then show that there is no single set of RED parameters that work well under different congestion scenarios. In light of this observation, we propose and experiment with more a d a p tive RED gateways which self-parameterize themselves based on the traffic mix. Our results show that traffic cognizant parameterization of RED gateways can effectively reduce packet loss while maintaining high link utilizations under a range of network loads.KqwordsCongestion control, Internet, TCP, RED, queue management.

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How to control hand-off drops is a very importantQualityof-Service (QoS) issue in cellular networks. In order to keep the hand-off dropping probability below a pre-specified target value (thus providing a probabilistic QoS guarantee), we design and evaluate predictive and adaptive schemes for the bandwidth reservation for the existing connections' handoffs and the admission control of new connections. We first develop a method to estimate user mobility based on an aggregate history of hand-offs observed in each cell. This method is then used to predict (probabilistically) mobiles' directions and hand-off times in a cell. For each cell, the bandwidth to be reserved for hand-offs is calculated by estimating the total sum of fractional bandwidths of the expected hand-offs within a mobility-estimation time window. We also develop an algorithm that controls this window for efficient use of bandwidth and effective response to (1) time-varying traffic/mobility and (2) inaccuracy of mobility estimation.Three different admission-control schemes for new connection requests using this bandwidth reservation are proposed.Finally, we evaluate the performance of the proposed schemes to show that they meet our design goal and outperform the static reservation scheme under various scenarios.

In recent years, there has been a rapid and wide spread of nontraditional computing platforms, especially mobile and portable computing devices. As applications become increasingly sophisticated and processing power increases, the most serious limitation on these devices is the available battery life. Dynamic Voltage Scaling (DVS) has been a key technique in exploiting the hardware characteristics of processors to reduce energy dissipation by lowering the supply voltage and operating frequency. The DVS algorithms are shown to be able to make dramatic energy savings while providing the necessary peak computation power in general-purpose systems. However, for a large class of applications in embedded real-time systems like cellular phones and camcorders, the variable operating frequency interferes with their deadline guarantee mechanisms, and DVS in this context, despite its growing importance, is largely overlooked/under-developed. To provide real-time guarantees, DVS must consider deadlines and periodicity of real-time tasks, requiring integration with the real-time scheduler. In this paper, we present a class of novel algorithms called real-time DVS (RT-DVS) that modify the OS's real-time scheduler and task management service to provide significant energy savings while maintaining real-time deadline guarantees. We show through simulations and a working prototype implementation that these RT-DVS algorithms closely approach the theoretical lower bound on energy consumption, and can easily reduce energy consumption 20% to 40% in an embedded real-time system. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies boar this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. SOSP01 Banff, Canada ful microprocessors running sophisticated, intelligent control software in a vast array of devices including digital camcorders, cellular phones, and portable medical devices.