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Title: Enhancing an Application Server to Support Available Components

Abstract:

INTRODUCTION

1.1. Data mining

Recent client-server distributed computing systems may be seen as implementations of N-tier architectures. Typically, the first tier consists of client applications containing browsers, with the remaining tiers deployed within an enterprise representing the server side; the second tier (Web tier) consists of web servers that receive requests from clients and pass on the requests to specific applications residing in the third tier (middle tier) consisting of application servers where the computations implementing the business logic are performed; and the fourth tier (database/back-end tier) contains databases that maintain persistent data for applications.

Existing application server that are capable to handle entire architecture Web logic , JBOSS ,Web sphere .A specification model should be develop that aloes approach to build N-tire architecture application.

The performance of the existing application server is proportional to N-tier application developer’s expose and skills in technology this are the limitations of the existing application. Is Enhancement of application server that would generate an N-tier architecture template based on the given requirements so, develops enhance their template to fulfill there business requirements.

The focus of this project work has been to combine existing techniques to provide a complete working solution on a real platform. Our techniques for replicating the database tier and that for replicating the middle tier are not dependent on each other and can be used together or separately without any difficulties.

Modern client-server distributed computing systems may be seen as implementations of N-tier architectures. Typically, the first tier consists of client applications containing browsers, with the remaining tiers deployed within an enterprise representing the server side; the second tier (Web tier) consists of web servers that receive requests from clients and pass on the requests to specific applications residing in the third tier (middle tier) consisting of application servers where the computations implementing the business logic are performed; and the fourth tier (database/back-end tier) contains databases that maintain persistent data for applications. Applications in this architecture are typically structured as a set of interrelated components hosted by containers within an application server.

Various services required by applications, such as transaction, persistence, security, and concurrency control, are provided via the containers, and a developer can simply specify the services required by components in a declarative manner. This architecture also allows flexible configuration using clustering for improved performance and scalability. Availability measures, such as replication, can be introduced in each tier in an application-specific manner. In a typical n-tier system, the interactions between clients and the web tier are performed across the Internet. The infrastructures supporting these interactions are generally beyond the direct control of an application service provider.

The middle and the database tiers are the most important, as it is on these tiers that the computations are performed and persistency provided. These two tiers are considered in this paper. Data as well as object replication techniques have been studied extensively in the literature, so our task is not to invent new replication techniques for components, but to investigate how existing techniques can be migrated to components. Component-oriented middleware infrastructure provides clear separation between components that have persistent state and those that do not. Therefore, it is natural to divide the replication support for these components into two categories: state replication and computation replication. State replication deals with masking data store failures to make persistent data highly available to components, while computation replication deals with masking application server failures where the computations are performed. We examine how an application server can be enhanced to support replication for availability so that components that are transparently using persistence and transactions can also be made highly available, enabling a transaction involving EJBs to commit despite a finite number of failures involving application servers and databases.

1Clustering and transparent failover

A common practice is to use application servers in a clustered configuration primarily for improving the performance (through load balancing) and scalability (deal with a large number of clients). Such a cluster system should provide transparent failover while preserving exactly once execution semantics allowing client requests to a failed server to be redirected automatically to another available server

Exactly once execution

One important concept related to availability measures is that of exactly once transaction or exactly once execution . The concept is particularly relevant in web-based e-services where the system must guarantee exactly once execution of user requests despite intervening failures. Problems arise as the clients in such systems are usually not transactional, thus they are not part of the recovery guarantee provided by the underlying transaction processing systems that support the web-based e-services. When failures occur, clients often do not know if their requests have been processed or not. Resubmitting the requests may result in duplication. Replication should hide such problems from clients, masking failures such that for each request submitted, a client receives exactly one response (safety) in a prompt manner.

Nonblocking multidatabase transaction processing:

Multi-database transactions need to use the well-known two-phase commit protocol to maintain ACID properties (ACID: Atomicity, Consistency, Isolation, and Durability). In a nonreplicated system, a crash of the application server that happens in the middle of the two-phase commitment (2PC) protocol can cause one or more participating back-end databases to become blocked, waiting for the transaction coordinator (which may be located at the crashed application server) to be available again, so that they can find out the outcome of the transaction. A replicated system should prevent such blocking.

Modular design:

Application server enhancements for replication should support 1) persistent state replication (database replication) and 2) computation replication (application server replication) in a modular fashion. By this, we mean that it should be possible to deploy replication in any configuration, namely, just 1 or just 2. or both 1 and 2 with independently controlled replication levels within each tier.

Open, transparent solution:

A solution should be open (nonpropriety) and implementable using commodity hard-ware and software components. Furthermore, a solution should be transparent to the component middleware. The transparency requirement imposes the following constraints: 1) no modifications to the Application Programming Interface (API) between a client and a component, 2) no modifications to the API between an EJB and the container hosting it, and 3) no modification to databases.

We, thus, see that the introduction of availability measures in a multitier system poses challenging system design problems of integrating open, nonproprietary solutions to transparent failover, exactly once execution of client requests, nonblocking transaction processing, and the ability to work with clusters. As we discuss later, availability mechanisms of existing application servers fall short of meeting these requirements .

For this reason, there has been much recent research on increasing availability of components hosted by commonly used application servers. However, we know of no research as of yet that meets all the stated requirements. In particular, experimental work reported so far for EJB components has dealt with transactions that update a single database only (as against multidatabase transactions).

JBoss can be enhanced to support replication for availability that satisfy all the requirements stated here. Our approach requires enhancements to the middle tier only for supporting replication of both the tiers. This paper discusses the technical issues involved and presents design, implementation, and performance evaluation.

Availability in Current Application Servers

Commercial approaches make use of multiple application servers deployed over a cluster of machines with some specialist router hardware that acts as a load balancer. If any server were to fail for any reason, the system is expected to continue to operate with the remaining servers, with the load balancer ensuring that the client load is redistributed to the remaining servers, each of which will henceforth process a proportionately slightly higher percentage of the total load. Load balancing at the database tier is commonly achieved in a similar manner, using proprietary solutions offered by database vendors. This allows an individual application server cluster member’s requests to be distributed across databases.

Transparent failover (failures are masked from a client, who minimally might need to retransmit the current request) is an ideal, but is rarely achievable with current technology for the reasons to be outline below. However, forward progress is possible and in less time than would be the case if only a single machine was used.

Transparent failover is easy to achieve for stateless sessions: Any server in the cluster can service any request and, if a client makes multiple requests in succession, each may well be serviced by a different server. If a failure of the server occurs while it is doing work for the client, then the client will get an exceptional response and will have to retransmit the request. The situation is more complicated for a stateful session, where the same server instance must be used for requests from the client, so the server failure will lead to loss of state. The approach adopted in commercial systems to avoid loss of state is to use the stateless session approach with a twist: The stateful session component is required to serialize its state to a database at the end of each client request and for the subsequent component instance in the other server to deserialize the state before servicing the new request (obviously, the servers must have access to the same database). The replication of the database is assumed to be the domain of the database itself. This way, some of the functionality available for stateless sessions can be regained. However, a failure during serialization (which could result in the state being corrupted) is not addressed.

IBM’s WebSphere coupled with Oracle’s propriety load balancing and failover exemplifies the difficulties in allowing developers to make use of transactions across multiple databases in current state-of-the art commercial products . Oracle can successfully load balance data-base connection requests by directing application servers to specific database nodes using its Real Application Cluster (RAC) technology. This approach can result in a transaction operating over multiple RAC nodes and may result in indeterminate state during two-phase commit if one or more RAC nodes fail. The following example, taken from , highlights such a scenario. Assume a single Web-Sphere node requests two database connections during a single transaction, say T1, that are satisfied by two different RAC nodes, say RAC1 and RAC2, resulting in two transaction branches TB1 and TB2. If RAC1 fails after prepare has been issued but before the issuing of commit by the WebSphere transaction manager, the WebSphere transaction manager will receive notice that RAC1 is unavailable.

The WebSphere transaction manager will then attempt to get a new RAC connection, and as failover is provided by Oracle, will gain another connection and attempt to finish TB1 by issuing commit. However, Oracle may throw an exception indicating that the transaction does not exist as RAC2 may be unaware of TB1. In this scenario, T1 will be unresolved, requiring manual intervention to release any locks held. To avoid this, WebSphere encourages developers to avoid multiple databases, in reality, this means not using Oracle’s load balancing and failover in such circumstances and thus restricts a devel-oper to a single RAC node. In fact, this problem is common and is frequently referred to as the unresolved transaction problem in commercial products (such as SAP J2EE and WebLogic), which all advocate manual intervention to resolve such issues

In commercial systems, the fact remains that failure of database alone may lead to inconsistencies requiring manual intervention to alleviate unresolved transactions. Turning off failover alleviates this problem, but only provides hot failover of transaction manager if database failover is not present.

Worth mentioning is JBoss’s attempt to achieve failover within the application server cluster tier by advocating session replication to enable failover of a component processing on one node to another. This approach load balances across replicas, allowing each replica to handle different client sessions. The state of a session is propagated to a backup after the computation finishes. When a server crashes, all sessions hosted on the crashed server can be migrated and continued on another server, regardless of the outcome of formerly active transactions on the crashed server, which may lead to inconsistencies.

1.2 Database Availability

In transactional systems, strict consistency is also characterized as one-copy serializability (the replicated system must appear to the client as a single copy). Many algorithms satisfy this property by employing an eager replication scheme, i.e., by propagating state updates to all replicas eagerly before transactions commit. In contrast, propagating state update to replicas can also be done lazily, i.e., after transactions commit (however, one-copy serializability is typically not guaranteed in this approach).

Traditionally, for performance reasons, lazy replication schemes have been favored by commercial products.

Recent research results of employing group communication for database replication identify eager schemes as a viable choice. A drawback of these approaches is the need to integrate a group communication subsystem into the database architecture, a difficult task with existing commercial databases.

To overcome this drawback, a middleware layer Middle-R has been proposed that provides a way of integrating group communication-based eager replication schemes into existing commercial databases . However, there are two limitations: The approach as it stands cannot be used for applications that require multidatabase transactions, as 2PC is not supported; furthermore, it still requires some database modifications to support the protocol (the database needs to be modified to provide support for obtaining the write-set of a transaction and for applying the write-set into the database). The distributed versioning approach overcomes the need for database modifications by requiring the middleware layer to perform its own concurrency control, but the approach has not been investigated within multidatabase settings. Furthermore, nonmodification of database comes at a scalability cost: Middle-R can implement optimizations in the database layer.

Clustered JDBC (C-JDBC) is middleware for database clustering . It provides transparency for clients to access a set of replicated and partitioned databases via a standard Java DataBase Connectivity (JDBC) driver. The architecture consists of C-JDBC drivers that run as part of a client’s process, a C-JDBC controller and back-end databases. The C-JDBC controller, via C-JDBC drivers, provides a virtual database to clients by relaying requests to appropriate databases transparently. C-JDBC schedules all requests from clients by sending read operations to any single database and sending update, commit, or abort operations to all databases. Worth mentioning is phoenix/ODBC that provides a similar approach to C-JDBC but for ODBC drivers and their associated databases. Our approach requires minimal modifications to an application server and requires implementing a database proxy that can be plugged into the application server as a JDBC driver. This proxy intercepts all interaction between an application server and an external database; hence, it can introduce state replication into the application server smoothly, without any modification to other parts of the application server.

LITERATURE SURVEY With the increasing need for the maintainability and extensibility of web applications, it is very important to select a robust, efficient and suitable framework to standardize and bring structure to web application development. Among numerous technologies now existing, many web developers show great preference for the Java web frameworks because of the outstanding design concepts and the popularity of Java programming language. Java web framework is a platform based on Model-View-Control (MVC) design pattern which dictates structure and separates web application into different components to help safeguard it from a potential mess of tangled code. Currently as almost every Java web application adopts Java web frameworks as the implementation of the web presentation tier, the Java web framework has already became an indispensable part of the Java web development.

In the early days of building Java web applications, developers often used JSP scriptlets and printed out content they wanted to display directly within their scriptlets—the same place where critical business logic was located. Although to some degree this could greatly reduce the time spending and increase the efficiency of development, it soon becomes clear that this technique too tightly coupled the core business code with the presentation, which greatly limits the readability, maintainability and extensibility of a web application. As the elicitation of the concept: “Web MVC”, it is now possible to divide web applications easily into “Model-View-Controller" three tier structure with each tier capable of being developed and tested independently without affecting each other. Although extra integration work for the different tiers is needed, the benefit we could procure from the separation is incontestable. The first mature Java Web MVC implementation is the “JSP Model 2” structure defined by Sun Microsystem, which has been proved as the foundation of building Java web applications .

The success of the Web MVC has triggered a proliferation of the Java web presentation frameworks. During the last few years, there are a glut of Java web frameworks invented, each of which has its special design concept, advantage and disadvantage, it has thus becomes increasingly difficult for Java web developers to choose the right framework to use.

Moreover, because of the complexity and distinctness of design concepts between different frameworks, it often takes months for developers to learn a new framework. Considering the time and effort needed to spend for choosing and learning java web frameworks, the term “framework” has actually turned into a “burden” for project teams. To solve this problem, a few researches related to this field have been preformed such as “Architectural models of J2EE Web tier frameworks” and “Art of Java Web development”. However, the purpose of these researches is to help readers to understand java web presentation tier development, and although they listed and introduced several popular java web frameworks, not enough feature comparison of web frameworks is provided. In addition, Java open source expert Matt Raible has given several conference presentations for comparing java web frameworks, for instance, “Java web framework sweet sport” and “Comparing Java web frameworks”,although in these presentations pros and cons of different framework features have been pointed out, measurements were restricted to concept discussion, there were no detailed examples and practical issues presented, Indeed developers with little experience of a specific framework can barely comprehend the points referring to that framework.

The goal of this thesis is to help web developers or technique managers gain deep insight of these frameworks through a comparison and therefore are able to choose the right framework for their web application. This work investigates four popular Java web frameworks: Struts, WebWork, Tapestry, and JSF. It focuses on comparing various web features of these frameworks such as “Type conversion”, “Internationalization”, “Post and Redirect” and “Navigation rules”. In addition to the theoretical analysis, a case study web application is also presented to provide practical support for feature comparison.

After the introduction chapter, the background technology information is presented in chapter two which includes a basic introduction of technologies used in Java web, MVC design pattern information and the concept of Java web frameworks. In the chapter three the infrastructure of the four chosen frameworks is introduced, the content includes framework overview, framework lifecycle and core components of the framework, we also give a general summarization of different frameworks at the end.

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Title: Enhancing an Application Server to Support Available Components

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