BADANIA REDUKCJI OPÓŹNIEŃ SERWERA WWW

This paper investigates the characteristics of web server response delay in order to understand and analyze the optimization techniques of reducing latency. The analysis of the latency behavior for multi-process Apache HTTP server with different thread count and various workloads, was made. It was indicated, that the insufficient number of threads used by the server handling the concurrent requests of clients, is responsible for increasing latency under various loads. The problem can be solved by using a modified web server configuration allowing to reduce the response time.W artykule opisano badania charakterystyk czasowych serwera WWW w celu zrozumienia i analizy technik optymalizacyjnych powodujących redukcję opóźnienia. Dokonano analizy czasów opóźnień dla wieloprocesowego serwera Apache dla różnej liczby wątków i obciążeń. Wskazano, że niewystarczająca liczba wątków wykorzystywanych przez serwer, obsługujących jednoczesne żądania klientów, wpływa znacząco na zwiększenie opóźnień dla różnych obciążeń. Problem może być rozwiązany za pomocą modyfikacji ustawień serwera WWW, pozwalających na skrócenie czasu reakcji

TCP Connection Management Mechanisms for Improving Internet Server Performance

This thesis investigates TCP connection management mechanisms in order to understand the behaviour and improve the performance of Internet servers during overload conditions such as flash crowds. We study several alternatives for implementing TCP connection establishment, reviewing approaches taken by existing TCP stacks as well as proposing new mechanisms to improve server throughput and reduce client response times under overload. We implement some of these connection establishment mechanisms in the Linux TCP stack and evaluate their performance in a variety of environments. We also evaluate the cost of supporting half-closed connections at the server and assess the impact of an abortive release of connections by clients on the throughput of an overloaded server. Our evaluation demonstrates that connection establishment mechanisms that eliminate the TCP-level retransmission of connection attempts by clients increase server throughput by up to 40% and reduce client response times by two orders of magnitude. Connection termination mechanisms that preclude support for half-closed connections additionally improve server throughput by up to 18%

Understanding and Efficiently Servicing HTTP Streaming Video Workloads

Live and on-demand video streaming has emerged as the most popular application for the Internet. One reason for this success is the pragmatic decision to use HTTP to deliver video content. However, while all web servers are capable of servicing HTTP streaming video workloads, web servers were not originally designed or optimized for video workloads. Web server research has concentrated on requests for small items that exhibit high locality, while video files are much larger and have a popularity distribution with a long tail of less popular content. Given the large number of servers needed to service millions of streaming video clients, there are large potential benefits from even small improvements in servicing HTTP streaming video workloads. To investigate how web server implementations can be improved, we require a benchmark to analyze existing web servers and test alternate implementations, but no such HTTP streaming video benchmark exists. One reason for the lack of a benchmark is that video delivery is undergoing rapid evolution, so we devise a flexible methodology and tools for creating benchmarks that can be readily adapted to changes in HTTP video streaming methods. Using our methodology, we characterize YouTube traffic from early 2011 using several published studies and implement a benchmark to replicate this workload. We then demonstrate that three different widely-used web servers (Apache, nginx and the userver) are all poorly suited to servicing streaming video workloads. We modify the userver to use asynchronous serialized aggressive prefetching (ASAP). Aggressive prefetching uses a single large disk access to service multiple small sequential requests, and serialization prevents the kernel from interleaving disk accesses, which together greatly increase throughput. Using the modified userver, we show that characteristics of the workload and server affect the best prefetch size to use and we provide an algorithm that automatically finds a good prefetch size for a variety of workloads and server configurations. We conduct our own characterization of an HTTP streaming video workload, using server logs obtained from Netflix. We study this workload because, in 2015, Netflix alone accounted for 37% of peak period North American Internet traffic. Netflix clients employ DASH (Dynamic Adaptive Streaming over HTTP) to switch between different bit rates based on changes in network and server conditions. We introduce the notion of chains of sequential requests to represent the spatial locality of workloads and find that even with DASH clients, the majority of bytes are requested sequentially. We characterize rate adaptation by separating sessions into transient, stable and inactive phases, each with distinct patterns of requests. We find that playback sessions are surprisingly stable; in aggregate, 5% of total session duration is spent in transient phases, 79% in stable and 16% in inactive phases. Finally we evaluate prefetch algorithms that exploit knowledge about workload characteristics by simulating the servicing of the Netflix workload. We show that the workload can be serviced with either 13% lower hard drive utilization or 48% less system memory than a prefetch algorithm that makes no use of workload characteristics