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The last couple of years have seen a growing momentum toward using the Internet for conducting business. Web-based electronic commerce applications are one of the fastest growing segments of the Internet today. A key enabler for e-commerce applications is the ability to setup secure private channels over a public network. The Secure Sockets Layer protocol provides this capability and is the most widely used security protocol in the Internet. We take a close look at the working principles behind SSL with an eye on performance. We benchmark two of the popular Web servers in wide use in a number of large e-commerce sites. Our results show that the overheads due to SSL can make Web servers slower by a couple of orders of magnitude. We investigate the reason for this deficiency by instrumenting the SSL protocol stack with a detailed profiling of the protocol processing components. In light of our observations, we outline architectural guidelines for large e-commerce sites.

As more business applications have become web enabled, the web server architecture has evolved to provide performance isolation, service differentiation, and QoS guarantees. Various server mechanisms that provide QoS extensions, however, rely on external administrators to set the right parameter values for their desirable performance. Due to the complexity of handling varying workloads and bursty traffic, configuring such parameters optimally becomes a challenge. In this paper, we describe an observation-based approach for self-managing web servers that can adapt to changing workloads while maintaining the QoS requirements of different classes. In this approach, the system state is monitored continuously and parameter values of various system resources-primarily the accept queue and the CPU-are adjusted to maintain the system-wide QoS goals. We implement our techniques using the Apache web server and the Linux operating system. We first demonstrate the need to manage different resources in the system depending on the workload characteristics. We then experimentally demonstrate that our observation-based system monitors such as workload changes and adjusts the resource parameters of the accept queue and CPU schedulers in order to maintain the QoS requirements of the different classes.

The exponential growth in Internet traffic has motivated the development of a new breed of microprocessors called network processors, which are designed to address the performance problems resulting from the explosion in Internet traffic. The development efforts of these network processors concentrate almost exclusively on streamlining their data paths to speed up network packet processing, which mainly consists of routing and data movement. Rather than blindly pushing the performance of packet processing hardware, an alternative approach is to avoid repeated computation by applying the time-tested architecture idea of caching to network packet processing. Because the data streams presented to network processors and general-purpose CPUs exhibit different characteristics, detailed cache design tradeoffs for the two also differ considerably. This research focuses on cache memory design specifically for network processors. Using a trace-drive simulation methodology, we evaluate a series of three progressively more aggressive routing-table cache designs. Our simulation results demonstrate that the incorporation of hardware caches into network processors, when combined with efficient caching algorithms, can significantly improve the overall packet forwarding performance due to a sufficiently high degree of temporal locality in the network packet streams. Moreover, different cache designs can result in up to a factor of 5 difference in the average routing table lookup time, and thus in the packet forwarding rate.

Suez is a high-performance real-time packet router that supports fast best-effort packet routing and scalable QoS-guaranteed packet scheduling, and is built on a hardware platform consisting of a cluster of commodity PCs connected by a gigabit/sec system area network. The major goal of the Suez project is to demonstrate that the PC cluster architecture can be as cost-effective a platform for high-performance network packet routing as for parallel computing. Suez features a cache-conscious routing-table search algorithm that exploits CPU caching hardware for fast lookup by treating IP addresses directly as virtual addresses. To scale the number of real-time connections supportable with the link speed, Suez implements a fixed-granularity fluid fair queuing (FGFFQ) algorithm that completely eliminates the per-packet sorting overhead associated with conventional weighted fair queuing algorithms. This paper presents the architectural features of Suez, and reports the performance measurements of the Linux-based Suez prototype, which is built on four Pentium-II 400 MHz machines and Myrinet.

Server providers that support e-commerce applications as a service for multiple e-commerce Web sites traditionally use a tiered server architecture. This architecture includes an application tier to process requests for dynamically generated content. How this tier is provisioned can significantly impact a provider's profit margin. In this article we study methods to provision servers in the application serving tier that increase a server provider's profits. First, we examine actual traces of request arrivals to the application tier of an e-commerce site, and show that the arrival process is effectively Poisson. Next, we construct an optimization problem in the context of a set of application servers modeled as M / G /1/ PS queueing systems, and derive three simple methods that approximate the allocation that maximizes profits. Simulation results demonstrate that our approximation methods achieve profits that are close to optimal, and are significantly higher than those achieved via simple heuristics.