Feedback Control-based Database Connection Management for Proportional Delay Differentiation-enabled Web Application Servers

Abstract. As an important differentiated service model, proportional delay differentiation (PDD) aims to maintain the queuing delay ratio between different classes of requests or packets according to pre-specified parameters. This paper considers providing PDD service in web application servers through feedback control-based database connection management. To achieve this goal, an approximate linear time-invariant model of the database connection pool (DBCP) is identified experimentally and used to design a proportional-integral (PI) controller. Periodically the controller is invoked to calculate and adjust the probabilities for different classes of dynamic requests to use database connections, according to the error between the measured delay ratio and the reference value. Three kinds of workloads, which follow deterministic, uniform and heavy-tailed distributions respectively, are designed to evaluate the performance of the closed-loop system. Experiment results indicate that, the controller is effective in handling varying workloads, and PDD can be achieved in the DBCP even if the number of concurrent dynamic requests changes abruptly under different kinds of workloads

High-performance packet scheduling to provide relative delay differentiation in future high-speed networks

Due to significant advances in interconnection networks and optical technologies, line rate for future high-speed networks call upgrade to terabits per second (Tb/s). Reduction of computational overhead and decrease of packet queueing delay are two critical issues in the design of a packet scheduler for efficiently delivering relative differentiated services over such high-speed networks. In this paper, we propose a new packet scheduler called multi-level dynamic deficit round-robin (MLDDRR). MLDDRR considers packet size and priority at the same time in making scheduling decision. Thus, MLDDRR can deliver relatively small delays not only for traffic of high priority but also for short packets of each class. Because MLDDRR acts like the shortest job first scheduler, MLDDRR call reduce average queueing delay for each class and also provide a better service for real-time applications with a large amount of short packets. MLDDRR also exploits concurrency and pipelining approach to speedup scheduling decision. Furthermore, MLDDRR call protect the traffic of the highest priority from serious performance degradation due to bursts of low priority traffic or high link utilization, and simultaneously prevent the traffic of the lowest priority from starvation. MLDDRR allows network operators to simply change the level of delay differentiation by adjusting parameters. Complexity analysis and extensive simulation results are presented and illustrate that MLDDRR is a high-performance packet scheduler and suitable for being deployed in future high-speed networks to provide relative delay differentiated service. (C) 2007 Elsevier B.V. All rights reserved