Existing database drivers use blocking socket I/O to exchange data with relational database management systems (RDBMS). To concurrently send multiple requests to a RDBMS with blocking database drivers, a separate thread must be used for each request. This approach has been used successfully for many years. However, we propose that using non-blocking socket I/O is faster and scales better under load. In this paper we introduce the Asynchronous Database Connectivity in Java (ADBCJ) framework. ADBCJ provides a common API for asynchronous RDBMS interaction. Various implementations of the ADBCJ API are used to show how utilizing non-blocking socket I/O is faster and scales better than using conventional database drivers and multiple threads for concurrency. Our experiments show a significant performance increase when using non- blocking socket I/O for asynchronous RDBMS access while using a minimal number of OS threads. Non-blocking socket I/O enables the ability to pipeline RDBMS requests which can improve performance significantly, especially over high latency networks. We also show the benefits of asynchronous database drivers on different web server architectures.

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In this day and age, the Internet provides the biggest linkage of information, personal data and information, social contact facilities, entertainment and electronic repository for all things including software downloads and tools, online books and technical descriptions, music and movies - both legal and illegal [Clarke, 1994]. With the increasing bandwidth in the last few years worldwide, it is possible to access the so-called "Triple-Play-Solutions" - Voice over lP, High-Speed-Internet and Video on Demand. More than 100 million subscribers have signed on across Asia, Europe, and the Americas in 2007, and growth is likely to continue steadily in all three. As broadband moves into the mainstream, it is reshaping the telecommunications, cable and Internet access industrie [Beardsley, Scott and Doman, Andrew, and EdinMC Kinsey, Par, 2003]. Cisco [Cisco, 2012], one of the biggest network companies, will expect more than 966 exabytes (nearly 1 zettabyte) per year or 80.5 exabytes per month in 2015 and the "Global IP traffic has increased eightfold over the past 5 years, and will increase fourfold over the next 5 years. Overall, IP traffic will grow at a compound annual growth rate (CAGR) of 32 percent from 2010 to 2015" . More and more types of sensible data flow between different recipients. News from around the world are transferred within seconds from the one end to the other end of the world, and affect the financial market, stock exchange [Reuters, 2012] and also bring down whole governments. For instance, worldwide humoil might ensue if a hacker broke into the web-server of an international newspaper or news channel like N-TV in Germany or BBC in England and displayed messages of a political revolution in Dubai or the death of the CEO from Microsoft or IBM.

Este trabalho propõe políticas para servidores Web baseados em sessões, visando ao oferecimento de garantias de qualidade de serviço (Quality of Service - QoS) a seus usuários. Para o fornecimento de QoS, dois tipos de políticas são consideradas: as responsáveis pela diferenciação de serviços e as responsáveis pelo controle de admissão. Alguns algoritmos de escalonamento foram desenvolvidos com o objetivo de oferecer melhores serviços para as sessões prioritárias: o algoritmo de escalonamento baseado em sessão (SBSA) e o algoritmo de escalonamento baseado em sessão com diferenciação de serviços (SBSA-DS). Quanto ao controle de admissão, foram consideradas duas novas políticas, as quais utilizam diferentes parâmetros para a tomada de decisão e têm como objetivo garantir a finalização do maior número de sessões prioritárias. A partir dos resultados obtidos nos experimentos realizados por meio de simulação, constatou-se que o emprego dos algoritmos e das políticas desenvolvidos melhora o atendimento das sessões para as quais deve ser oferecido um serviço preferencial. Portanto, em servidores Web preocupados com a garantia de QoS para seus usuários, os quais interagem com o sistema por meio de sessões, o uso dessas novas técnicas se mostra adequado / This work considers policies for Web servers based on sessions, aiming at the guarantees of Quality of Service (QoS) to the systems users. Two types of policies are considered: the responsible for the differentiation of services and the responsible for the admission control. Some scheduling algorithms had been developed to offer better services for the priority sessions: the Session Based Scheduling Algorithm (SBSA) and the Session Based Scheduling Algorithm with Differentiation of Services (SBSA-DS). In relation to the admission control, two new policies had been considered, which use different parameters to help the decisions and have as objective guarantee the finalization of as many priority sessions as possible. From the obtained results of the experiments realized by mean of simulation, it is evidenced that the use of the developed algorithms and policies improves the attendance of the sessions that deserve preferential service. Therefore, in Web servers worried in the guarantee the QoS for their users, which interact with the system by sessions, the use of these new techniques reveals adequate

Esta dissertação de mestrado apresenta o projeto, implementação e teste de um gerador de carga de trabalho para servidores Web que permite a caracterização de sessões e que representa uma carga real. O gerador desenvolvido gera carga visando à alimentar programas que simulam o comportamento de servidores Web. Para a definição dos parâmetros utilizados no gerador de carga sintética desenvolvido, diversos estudos sobre a carga em servidores Web encontrados na literatura, logs de servidores Web reais e benchmarks para servidores Web, foram utilizados. Vários algoritmos de controle de admissão e de escalonamento de requisições descritos na literatura foram implementados para teste e validação do gerador desenvolvido. Visando a utilização de sessões, é proposto nesta dissertação um algoritmo de controle de admissão, RED-SB (Random Early Detection - Session Based) que se baseia em um algoritmo (RED) que não considera sessão. Esses algoritmos foram executados utilizando-se um modelo de simulação de servidor Web com suporte a diferenciação de serviços, chamado SWDS (Servidor Web com Diferenciação de Serviços) / This MSc dissertation presents the design, implementation and tests of a workload generator for Web servers that allows the characterization of sessions and represents a real workload. The generator developed generates a workload to be used as an input to programs that simulate the behavior of Web servers. For the definition of the parameters used in the synthetic workload generator developed, several studies about the web server load described in the literature, actual web server logs and benchmarks for Web servers were used. Several algorithms for admission control and scheduling of requests described in the literature were implemented for testing and validation of the generator developed. Aiming at the utilization of sessions, this dissertation proposes an admission control algorithm RED-SB (Random Early Detection - Session based) which is based on an algorithm (RED) that does not consider session. These algorithms were implemented using a simulation model ofWeb server that supports service differentiation, called SWDS (Web Server with Service Differentiation)

The main objective of this thesis focuses on the design of an adaptive algorithm for admission control and content-aware load balancing for Web traffic. In order to set the context of this work, several reviews are included to introduce the reader in the background concepts of Web load balancing, admission control and the Internet traffic characteristics that may affect the good performance of a Web site. The admission control and load balancing algorithm described in this thesis manages the distribution of traffic to a Web cluster based on QoS requirements. The goal of the proposed scheduling algorithm is to avoid situations in which the system provides a lower performance than desired due to servers' congestion. This is achieved through the implementation of forecasting calculations. Obviously, the increase of the computational cost of the algorithm results in some overhead. This is the reason for designing an adaptive time slot scheduling that sets the execution times of the algorithm depending on the burstiness that is arriving to the system. Therefore, the predictive scheduling algorithm proposed includes an adaptive overhead control.Once defined the scheduling of the algorithm, we design the admission control module based on throughput predictions. The results obtained by several throughput predictors are compared and one of them is selected to be included in our algorithm. The utilisation level that the Web servers will have in the near future is also forecasted and reserved for each service depending on the Service Level Agreement (SLA). Our load balancing strategy is based on a classical policy. Hence, a comparison of several classical load balancing policies is also included in order to know which of them better fits our algorithm. A simulation model has been designed to obtain the results presented in this thesis.

This is a embedded system that designed to achieve the goal of remote control andwireless communication with web page. The embedded web server using uIP whichis TCP/IP stack. Web page are designed using HTML5, JavaScript and CSS languageto format the layout. On the home page, you can see the index of different items.

A Web-server farm is a specialized facility designed specifically for housing Web servers catering to one or more Internet facing Web sites. In this dissertation, stochastic dynamic programming technique is used to obtain the optimal admission control policy with different classes of customers, and stochastic uid- ow models are used to compute the performance measures in the network. The two types of network traffic considered in this research are streaming (guaranteed bandwidth per connection) and elastic (shares available bandwidth equally among connections). We first obtain the optimal admission control policy using stochastic dynamic programming, in which, based on the number of requests of each type being served, a decision is made whether to allow or deny service to an incoming request. In this subproblem, we consider a xed bandwidth capacity server, which allocates the requested bandwidth to the streaming requests and divides all of the remaining bandwidth equally among all of the elastic requests. The performance metric of interest in this case will be the blocking probability of streaming traffic, which will be computed in order to be able to provide Quality of Service (QoS) guarantees. Next, we obtain bounds on the expected waiting time in the system for elastic requests that enter the system. This will be done at the server level in such a way that the total available bandwidth for the requests is constant. Trace data will be converted to an ON-OFF source and fluid- flow models will be used for this analysis. The results are compared with both the mean waiting time obtained by simulating real data, and the expected waiting time obtained using traditional queueing models. Finally, we consider the network of servers and routers within the Web farm where data from servers flows and merges before getting transmitted to the requesting users via the Internet. We compute the waiting time of the elastic requests at intermediate and edge nodes by obtaining the distribution of the out ow of the upstream node. This out ow distribution is obtained by using a methodology based on minimizing the deviations from the constituent in flows. This analysis also helps us to compute waiting times at different bandwidth capacities, and hence obtain a suitable bandwidth to promise or satisfy the QoS guarantees. This research helps in obtaining performance measures for different traffic classes at a Web-server farm so as to be able to promise or provide QoS guarantees; while at the same time helping in utilizing the resources of the server farms efficiently, thereby reducing the operational costs and increasing energy savings.

<p><p>Context represents any information regarding the situation of entities, being these a person, place or object that is considered relevant to the interaction between a user and an application.</p><p><p>The results obtained permits an user to save context information attached to a picture in a database, as well as retrieve pictures from that database and show it in a web interface with its context information associated. The web interface also allows the user to perform searches by using different criteria, so only the pictures that matches with that criteria will be shown.</p></p></p> / Final Degree Project - Thesis

Background. High-availability (HA) is a cloud’s ability to keep functioning after one or more hardware or software components fail. Its purpose is to minimize the system downtime and data loss. Many service providers guarantee a Service Level Agreement including uptime percentage of the computing service, which is calculated based on the available time and system downtime excluding the planned outage time. The aim of the thesis is to perform the update of the virtual machines running in the cloud without causing any interruptions to the user by redirecting the resources/services running on them to an alternative virtual machine before the original VM is updated. Objectives. The objectives for the above aim include. • The first objective is to investigate existing solutions for high-availability and, if possible, adapt them to our aim. The alternative is to design our own solution. • The second objective is to implement the solution in an Open Stack environment. As an alternative, we can try a smaller scale implementation under a virtualization platform such as Virtual Box. • The final objective is to run experiments to quantify the effectiveness of our solution in terms of overhead and degree of seamlessness to the users. Methods. An environment with multiple virtual machines may be created to represent multiple virtual servers in the cloud. The state of service provided by the primary virtual machine is saved to persistent storage and the client is redirected to an alternate virtual machine. At that point the primary virtual machine may reboot for an update or any other issues. Results. In the case of CPU Utilization, the mean CPU utilization on Server and Host in scenario 1 are 0.34% and 3.2% respectively. The mean CPU utilization on Primary server and Host in scenario 2 during the failover cycle are 2.0% and 9.7% respectively. The mean CPU utilization on Secondary server and Host in scenario 2 during failover cycle are 0.99% and 8.0% respectively. For the Memory Utilization, the mean Memory usage on server in scenario 1 is 16%. The mean Memory usage on primary server and secondary server in scenario 2 during failover cycle are 37% and 48% respectively. The Time for failover of the high availability environment remains for 6.8 seconds and the time for the off-line node to rejoin the cluster as on-line when told would take 1.5 seconds. The network traffic is measured in Kilobits per second, it is 1.2 Kilobits per second on port 80 in scenario 2 and is 1.4 Kilobits per second between the client and the server in scenario 1. In addition, data traffic on ports 5405, 2224 and 7788 are captured where port 5405 (Pacemaker/Corosync) contains UDP traffic, port 2224 (Pcsd) contains TCP traffic and port 7788 (DRBD) contains TCP traffic. The traffic captured on these ports represent network overhead due to HA. During failover cycle an additional traffic of 45Kb/s, 1.2Kb/s. 7.0Kb/s flow on 5405, 2224 and 7788 ports respectively. Conclusions. From our experiment results we can say that the overhead to handle live updates on high availability environment is approximately 1.1 - 1.7 % of CPU higher in HA mode than when a stand-alone server is used. The overhead is around 21 - 32 % higher in terms of memory utilization for the live updates on the HA system than for the standard server. The network traffic overhead induced by the ports used by high availability environment (5405, 2224, 7788) is approximately 53 Kilobits /Second while the minimum overhead is approximately 16 Kilobits / Second. The Final and the important metric is the Failover time which tells the seamlessness of the service as the environment needs to provide the services uninterrupted to the users. The failover time of the HA model is about just 6.8 seconds leaving the environment highly available. However, the user may notice slight interruption for the requests made during this span.