This paper presents a novel methodology to develop scheduling algorithms. The scheduling problem is phrased as a control problem, and control-theoretical techniques are used to design a scheduling algorithm that meets specific requirements. Unlike most approaches to feedback scheduling, where a controller integrates a "basic" scheduling algorithm and dynamically tunes its parameters and hence its performances, our methodology essentially reduces the design of a scheduling algorithm to the synthesis of a controller that closes the feedback loop. This approach allows the re-use of control-theoretical techniques to design efficient scheduling algorithms; it frames and solves the scheduling problem in a general setting; and it can naturally tackle certain peculiar requirements such as robustness and dynamic performance tuning. A few experiments demonstrate the feasibility of the approach on a real-time benchmark.
@cite_5 @cite_7 present contributions in this context, for the regulation of the service levels of a web server. The variable to be controlled is the delay between the arrival time of a request and the time it starts being processed. The goal is to keep this delay to within some desired range; the range depends on the class of each request. An interesting point of this works is the distinction between the transient and steady state performances, in the presence of variable traffic. This feature motivates a feedback-control approach to many computing-system performance problems.
@cite_5 @cite_7
2153466231 2135087359 2096441239 2136340918
How to effectively allocate system resource to meet the service level agreement (SLA) of Web servers is a challenging problem. In this paper, we propose an improved scheme for autonomous timing performance control in Web servers under highly dynamic traffic loads. We devise a novel delay regulation technique called queue length model based feedback control utilizing server internal state information to reduce response time variance in presence of bursty traffic. Both simulation and experimental studies using synthesized workloads and real-world Web traces demonstrate the effectiveness of the proposed approach Several works have established links between congestion control in communication networks and feedback control theory. In this paper, following this paradigm, the design of an AQM (active queue management) ensuring the stability of the congestion phenomenon at a router is proposed. To this end, a modified fluid flow model of TCP (transmission control protocol) that takes into account all delays of the topology is introduced. Then, appropriate tools from control theory are used to address the stability issue and to cope with the time-varying nature of the multiple delays. More precisely, the design of the AQM is formulated as a structured state feedback for multiple time delay systems through the quadratic separation framework. The objective of this mechanism is to ensure the regulation of the queue size of the congested router as well as flow rates to a prescribed level. Furthermore, the proposed methodology allows to set arbitrarily the QoS (quality of service) of the communications following through the controlled router. Finally, a numerical example and some simulations support the exposed theory. The paper presents the design, implementation, and evaluation of an adaptive architecture to provide relative delay guarantees for different service classes on Web servers under HTTP 1.1. The first contribution of the paper is the architecture based on a feedback control loop that enforces desired relative delays among classes via dynamic connection scheduling and process reallocation. The second contribution is our use of feedback control theory to design the feedback loop with proven performance guarantees. In contrast with ad hoc approaches that often rely on laborious tuning and design iterations, our control theory approach enables us to systematically design an adaptive Web server with established analytical methods. The design methodology includes using system identification to establish a dynamic model, and using the Root Locus method to design a feedback controller to satisfy performance specifications of a Web server. The adaptive architecture has been implemented by modifying an Apache Web server. Experimental results demonstrate that our adaptive server achieves robust relative delay guarantees even when workload varies significantly. Properties of our adaptive Web server include guaranteed stability, and satisfactory efficiency and accuracy in achieving the desired relative delay differentiation. We consider the problem of resource allocation in downlink OFDMA systems for multi service and unknown environment. Due to users' mobility and intercell interference, the base station cannot predict neither the Signal to Noise Ratio (SNR) of each user in future time slots nor their probability distribution functions. In addition, the traffic is bursty in general with unknown arrival. The probability distribution functions of the SNR, channel state and traffic arrival density are then unknown. Achieving a multi service Quality of Service (QoS) while optimizing the performance of the system (e.g. total throughput) is a hard and interesting task since it depends on the unknown future traffic and SNR values. In this paper we solve this problem by modeling the multiuser queuing system as a discrete time linear dynamic system. We develop a robust H∞ controller to regulate the queues of different users. The queues and Packet Drop Rates (PDR) are controlled by proposing a minimum data rate according to the demanded service type of each user. The data rate vector proposed by the controller is then fed as a constraint to an instantaneous resource allocation framework. This instantaneous problem is formulated as a convex optimization problem for instantaneous subcarrier and power allocation decisions. Simulation results show small delays and better fairness among users.