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18-03-2010, 12:38 PM
Post: #1
Flexible Rollback Recovery in Dynamic Heterogeneous Grid Computing full report

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Flexible Rollback Recovery in Dynamic Heterogeneous Grid Computing
SCOPE OF THE PROJECT
The Objective of the project is to provide recover the lost node or file when it is crashed. Path of the node till be vary according to the selection.
INTRODUCTION

Grid and cluster architectures have gained popularity for computationally intensive parallel applications. However, the complexity of the infrastructure, consisting of computational nodes, mass storage, and interconnection networks, poses great challenges with respect to overall system reliability. Simple tools of reliability analysis show that as the complexity of the system increases, its reliability, and thus, Mean Time to Failure (MTTF), decreases. The reliability of the entire system is computed as the product of the reliabilities of all system components. For applications executing on large clusters or a Grid, the long execution times may exceed the MTTF of the infrastructure and, thus, render the execution infeasible. As an example, let us consider an execution lasting 10 days in a system that does not consider fault tolerance. Under the optimistic assumption that the MTTF of a single node is 2,000 days, the probability of failure of this long execution using 100, 200, or 500 nodes is 0.39, 0.63, or 0.91, respectively, approaching fast certain failure. The high failure probabilities are due to the fact that, in the absence of fault-tolerance mechanisms, the failure of a single node will cause the entire execution to fail. Note that this simple example does not even consider network failures, which are typically more likely than computer failure. Fault tolerance is, thus, a necessity to avoid failure in large applications, such as found in scientific computing, executing on a Grid, or large cluster. The fault-tolerance mechanisms also have to be capable of dealing with the specific characteristics of a heterogeneous and dynamic environment. Even if individual clusters are homogeneous, heterogeneity in a Grid is mostly unavoidable, since different participating clusters often use diverse hardware or software architectures. One possible solution to address heterogeneity is to use platform independent abstractions such as the Java Virtual Machine. However, this does not solve the problem in general. There is a large base of existing applications that have been developed in other languages. Reengineering may not be feasible due to performance or cost reasons. Environments like Microsoft .Net address portability but only few scientific applications on Grids or clusters exist. Whereas Grids and clusters are dominated by unix operating systems, e.g., Linux or Solaris, Microsoft .Net is Windows-centric with only recent or partial unix support. Besides heterogeneity, one has to address the dynamic nature of the Grid. Volatility is not only an intracluster issue, i.e., configuration changes within a cluster, but also an intercluster reality. Intracluster volatility may be the result of node failures, whereas intercluster volatility is caused by network disruptions between clusters. From an administrative viewpoint, the reality of Grid operation, such as cluster/node reservations or maintenance, may restrict long executions on fixed topologies due to the fact that operation at different sites may be hard to coordinate. It is usually difficult to reserve a large cluster for long executions, let alone scheduling extensive uninterrupted time on multiple, perhaps geographically dispersed, sites. Lastly, configuration changes may be induced by the application as the result of changes of runtime observable quality-of-service (QOS) parameters. To overcome the aforementioned problems and challenges, we present mechanisms that tolerate faults and operation-induced disruption of parts or the entire execution of the application. We introduce flexible rollback recovery mechanisms that impose no artificial restrictions on the execution. They do not depend on the pre-failure configuration and consider 1) node and cluster failures as well as operation-induced unavailability of resources and 2) dynamic topology reconfiguration in heterogeneous systems.
MODULES
¢ Analysis of nodes
¢ Data security using Theft Induced Checkpoint
Crash
Checkpoint using Local
Checkpoint using Forced.
¢ Data transmission using Systematic Event Logging
¢ Evaluating Theft Induced Checkpoint
¢ Evaluating Systematic Event Logging
MODULES DESCRIPTION
¢ Analysis of nodes
The node are analyzed which are all the failure node and how to recover the data or node using different technique.
Data Security using Theft induced checkpoint
The process of detecting who are all the intruder by having specific anomaly detection. Those members are eliminated from the network.
Crash
When one of the client process failed it leads to crash and partly the current process are crashed and system fails which also can affect the other processors.
Checkpoint using Local
The Local checkpoint is used to recover the processor from the crash. By giving local, with the help of Theft-Induced Protocol all the processes which are stored in a periodic time interval are recovered and send to client with the help of Systematic Event Logging protocol.
Checkpoint using Forced.
The Forced Checkpoint is also one of the recovery part in the theft induced Checkpoint protocol(TIC) during the system crash. By applying forced, with the help of TIC it recovers only the current events/processes and send to the client.
Data transmission using Systematic Event Logging
The process of transmitting the data with some particular protocols. Protocols have set of procedures to transmit the data
Evaluating Theft induced checkpoint
The process of evaluating how the intruders are detected in the TIC.
Evaluating Systematic Event Logging
The process of evaluating how the data rae transmitted using System Event Logging.
MODULES I/O:
Analysis of nodes
Input-n..nodes.
Output-Failure nodes.
Data Security using Theft induced checkpoint
Input-Intruders.
Output-Indentified intruders.
Crash
Input-nodes.
Output-Crashed nodes..
Checkpoint using Local
Input-Data& nodes.
Output-Recovered nodes& Data.
Checkpoint using Forced.
Input-Data& nodes.
Output-Recovered nodes &Data.
Data transmission using Systematic Event Logging
Input-Data.
Output-Transmitted Data.
Evaluating Theft induced checkpoint
Input-Existing results.
Output-Compared result.
Evaluating Systematic Event Logging
Input-Existing results.
Output-Compared result.
MODULE DIAGRAM
DATAFLOW DIAGRAM

ALGORITHMS/TECHNIQUES USED
THEFT-INDUCED CHECKPOINTING
The creation of checkpoints can be initiated by 1) work stealing or 2) at specific check pointing periods. We will first describe the protocol with respect to work-stealing, since it is the cause of the only communication (and thus, dependencies) between processes. Checkpoints resulting from work-stealing are called forced checkpoints. Then, we will consider the periodic checkpoints, called local checkpoints, which are stored periodically, after expiration of predefined periods.
SYSTEMATIC EVENT LOGGING
Systematic Event Logging which was derived from a log-based method . The motivation for SEL is to reduce the amount of computation that can be lost, which is bound by the execution time of a single failed task. In case of a fault, task duplication needs to be avoided during rollback. Specifically, in the implementation, one has to guarantee that only one instance of a any given task can exist. In the absence of such guarantee, it could happen that during rollback a task recreates other tasks or data objects that already exist from earlier failed executions. Note that, depending on the timing of the fault, this could result in a significant number of duplicated nodes, since each duplicated task itself may be the initiator of a significant portion of computation. In our implementation of SEL, duplication avoidance is achieved using a unique and reproducible identification method of all vertices in the graph.
ADVANTAGES
Efficient Theft detection.
Rollback recovery.
Time consumption.
APPLICATION
QUADRATIC ASSIGNMENT PROBLEM

The local experiments were conducted on the iCluster2,which consists of 104 nodes interconnected by a 100-Mbps Ethernet network, each node featuring two Itanium-2 processors (900 MHz) and 3 Gbytes of local memory. The intercluster experiments were conducted on Grid5000,which consists of clusters located at nine French institutions.

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25-03-2010, 06:21 PM
Post: #2
RE: Flexible Rollback Recovery in Dynamic Heterogeneous Grid Computing full report
i need the flexible rollback ppt, any body having ? u just send to me "natraj.raj2003[at]gmail.com" if you want to discuss with that u always welcome...

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09-04-2010, 08:35 PM
Post: #3
RE: Flexible Rollback Recovery in Dynamic Heterogeneous Grid Computing full report

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Flexible Rollback Recovery in Dynamic
Heterogeneous Grid Computing
Abstract:
Large applications executing on Grid or cluster architectures consisting of hundreds or thousands of computational nodes create problems with respect to reliability. The source of the problems is node failures and the need for dynamic configuration over extensive runtime.
By allowing recovery even under different numbers of processors, the approaches are especially suitable for applications with a need for adaptive or reactionary configuration control. The low-cost protocols offer the capability of controlling or bounding the overhead. A formal cost model is presented, followed by an experimental evaluation. It is shown that the overhead of the protocol is very small, and the maximum work lost by a crashed process is small and bounded.

1. INTRODUCTION
Grid and cluster architectures have gained popularity for computationally intensive parallel applications. However, the complexity of the infrastructure, consisting of computational nodes, mass storage, and interconnection networks, poses great challenges with respect to overall system reliability. Simple tools of reliability analysis show that as the complexity of the system increases, its reliability, and thus, Mean Time to Failure (MTTF), decreases. If one models the system as a series reliability block diagram, the reliability of the entire system is computed as the product of the reliabilities of all system components. For applications executing on large clusters or a Grid, e.g., Grid5000, the long execution times may exceed the MTTF of the infrastructure and, thus, render the execution infeasible. As an example, let us consider an execution lasting 10 days in a system that does not consider fault tolerance. Under the optimistic assumption that the MTTF of a single node is 2,000 days, the probability of failure of this long execution using 100, 200, or 500 nodes is 0.39, 0.63, or 0.91, respectively, approaching fast certain failure. The high failure probabilities are due to the fact that, in the absence of fault-tolerance mechanisms, the failure of a single node will cause the entire execution to fail. Note that this simple example does not even consider network failures, which are typically more likely than computer failure. Fault tolerance is, thus, a necessity to avoid failure in large applications, such as found in scientific computing, executing on a Grid, or large cluster.
Algorithm / Technique used:
Logging Methods.
Algorithm Description:
Logging can be classified as pessimistic, optimistic, or causal. It is based on the fact that the execution of a process can be modeled as a sequence of state intervals. The execution during a state interval is deterministic. However,
each state interval is initiated by a nondeterministic event Now, assume that the system can capture and log sufficient information about the nondeterministic events that initiated the state interval. This is called the piecewise deterministic (PWD) assumption. Then, a crashed process can be recovered by 1) restoring it to the initial state and 2) replaying the logged events to it in the same order they appeared in the execution before the crash. To avoid a rollback to the initial state of a process and to limit the amount of nondeterministic events that need to be replayed, each process periodically saves its local state. Log based mechanisms in which the only nondeterministic events in a system are the reception of messages is usually referred to as message logging.
Existing System:
Communication Induced Check-pointing protocols usually make the assumption that any process can be check-pointed at any time. An alternative approach which releases the constraint of always check-pointable processes, without delaying any do not message reception nor did altering message ordering enforce by the communication layer or by the application. This protocol has been implemented within Pro-Active, an open source Java middleware for asynchronous and distributed objects implementing the ASP (Asynchronous Sequential Processes) model.
Proposed System:
This paper presents two fault-tolerance mechanisms called Theft-Induced Check pointing and Systematic Event Logging. These are transparent protocols capable of overcoming problems associated with both benign faults, i.e., crash faults, and node or subnet volatility. Specifically, the protocols base the state of the execution on a dataflow graph, allowing for efficient recovery in dynamic heterogeneous systems as well as multithreaded applications.
Hardware Requirements:
¢ System : Pentium IV 2.4 GHz.
¢ Hard Disk : 40 GB.
¢ Floppy Drive : 1.44 Mb.
¢ Monitor : 15 VGA Colour.
¢ Mouse : Logitech.
¢ Ram : 256 Mb.
Software Requirements:
¢ Operating system : - Windows XP Professional.
¢ Coding Language : - Java.
¢ Tool Used : - Eclipse.
Flexible Rollback Recovery in Dynamic
Heterogeneous Grid Computing
Modules:
1. Network Module
2. Logging Module
3. Check-pointing Module
4. Work Stealing Module
5. Fault and Fault Free Module
Module Description:
1. Network Module
Client-server computing or networking is a distributed application architecture that partitions tasks or workloads between service providers (servers) and service requesters, called clients. Often clients and servers operate over a computer network on separate hardware. A server machine is a high-performance host that is running one or more server programs which share its resources with clients. A client also shares any of its resources; Clients therefore initiate communication sessions with servers which await (listen to) incoming requests.
2. Logging Module
Logging can be classified as pessimistic, optimistic, or causal. It is based on the fact that the execution of a process can be modeled as a sequence of state intervals. The execution during a state interval is deterministic. However, each state interval is initiated by a nondeterministic event. Now, assume that the system can capture and log sufficient information about the nondeterministic events that initiated the state interval. This is called the piecewise deterministic (PWD) assumption .Then, a crashed process can be recovered by 1) restoring it to the initial state and 2) replaying the logged events to it in the same order they appeared in the execution before the crash. To avoid a rollback to the initial state of a process and to limit the amount of nondeterministic events that need to be replayed, each process periodically saves its local state. Log-based mechanisms in which the only nondeterministic events in a system are the reception of messages is usually referred to as message logging.
3. Check-pointing Module
Rather than logging events, checkpointing relies on periodically saving the state of the computation to stable storage. If a fault occurs, the computation is restarted from one of the previously saved states. Since the computation is distributed, one has to consider the tradeoff space of local and global checkpointing strategies and their resulting recovery cost. Thus, checkpointing based methods differ in the way processes are coordinated and in the derivation of a consistent global state. The consistent global state can be achieved either at the time of checkpointing or at the time of rollback recovery. The two approaches are called coordinated and uncoordinated checkpointing, respectively
4. Work Stealing Module
The runtime environment and primary mechanism for load distribution is based on a scheduling algorithm called work-stealing .The principle is simple: when a process becomes idle it tries to steal work from another process called victim. The initiating process is called thief. Work-stealing is the only mechanism for distributing the workload constituting the application, i.e., an idle process seeks to steal work from another process. From a practical point of view, the application starts with the process executing main (), which creates tasks. Typically, some of these tasks are then stolen by idle processes, which are either local or on other processors. Thus, the principal mechanism for dispatching tasks in the distributed environment is task stealing
5. Fault and Fault Free Module
We add a checkpointing mechanism; it is of special interest to analyze its overhead associated with fault-free execution, since the occurrence of faults is considered to be the rare exception rather than the norm.
Software Environment
Java Technology
Java technology is both a programming language and a platform.
The Java Programming Language
The Java programming language is a high-level language that can be characterized by all of the following buzzwords:
Simple
Architecture neutral
Object oriented
Portable
Distributed
High performance
Interpreted
Multithreaded
Robust
Dynamic
Secure
With most programming languages, you either compile or interpret a program so that you can run it on your computer. The Java programming language is unusual in that a program is both compiled and interpreted. With the compiler, first you translate a program into an intermediate language called Java byte codes ”the platform-independent codes interpreted by the interpreter on the Java platform. The interpreter parses and runs each Java byte code instruction on the computer. Compilation happens just once; interpretation occurs each time the program is executed. The following figure illustrates how this works.

You can think of Java byte codes as the machine code instructions for the Java Virtual Machine (Java VM). Every Java interpreter, whether itâ„¢s a development tool or a Web browser that can run applets, is an implementation of the Java VM. Java byte codes help make write once, run anywhere possible. You can compile your program into byte codes on any platform that has a Java compiler. The byte codes can then be run on any implementation of the Java VM. That means that as long as a computer has a Java VM, the same program written in the Java programming language can run on Windows 2000, a Solaris workstation, or on an iMac.
The Java Platform
A platform is the hardware or software environment in which a program runs. Weâ„¢ve already mentioned some of the most popular platforms like Windows 2000, Linux, Solaris, and MacOS. Most platforms can be described as a combination of the operating system and hardware. The Java platform differs from most other platforms in that itâ„¢s a software-only platform that runs on top of other hardware-based platforms.
The Java platform has two components:
¢ The Java Virtual Machine (Java VM)
¢ The Java Application Programming Interface (Java API)
Youâ„¢ve already been introduced to the Java VM. Itâ„¢s the base for the Java platform and is ported onto various hardware-based platforms.
The Java API is a large collection of ready-made software components that provide many useful capabilities, such as graphical user interface (GUI) widgets. The Java API is grouped into libraries of related classes and interfaces; these libraries are known as packages. The next section, What Can Java Technology Do Highlights what functionality some of the packages in the Java API provide.
The following figure depicts a program thatâ„¢s running on the Java platform. As the figure shows, the Java API and the virtual machine insulate the program from the hardware.
Native code is code that after you compile it, the compiled code runs on a specific hardware platform. As a platform-independent environment, the Java platform can be a bit slower than native code. However, smart compilers, well-tuned interpreters, and just-in-time byte code compilers can bring performance close to that of native code without threatening portability.
What Can Java Technology Do
The most common types of programs written in the Java programming language are applets and applications. If youâ„¢ve surfed the Web, youâ„¢re probably already familiar with applets. An applet is a program that adheres to certain conventions that allow it to run within a Java-enabled browser.
However, the Java programming language is not just for writing cute, entertaining applets for the Web. The general-purpose, high-level Java programming language is also a powerful software platform. Using the generous API, you can write many types of programs.
An application is a standalone program that runs directly on the Java platform. A special kind of application known as a server serves and supports clients on a network. Examples of servers are Web servers, proxy servers, mail servers, and print servers. Another specialized program is a servlet. A servlet can almost be thought of as an applet that runs on the server side. Java Servlets are a popular choice for building interactive web applications, replacing the use of CGI scripts. Servlets are similar to applets in that they are runtime extensions of applications. Instead of working in browsers, though, servlets run within Java Web servers, configuring or tailoring the server.
How does the API support all these kinds of programs It does so with packages of software components that provides a wide range of functionality. Every full implementation of the Java platform gives you the following features:
¢ The essentials: Objects, strings, threads, numbers, input and output, data structures, system properties, date and time, and so on.
¢ Applets: The set of conventions used by applets.
¢ Networking: URLs, TCP (Transmission Control Protocol), UDP (User Data gram Protocol) sockets, and IP (Internet Protocol) addresses.
¢ Internationalization: Help for writing programs that can be localized for users worldwide. Programs can automatically adapt to specific locales and be displayed in the appropriate language.
¢ Security: Both low level and high level, including electronic signatures, public and private key management, access control, and certificates.
¢ Software components: Known as JavaBeansTM, can plug into existing component architectures.
¢ Object serialization: Allows lightweight persistence and communication via Remote Method Invocation (RMI).
¢ Java Database Connectivity (JDBCTM): Provides uniform access to a wide range of relational databases.
The Java platform also has APIs for 2D and 3D graphics, accessibility, servers, collaboration, telephony, speech, animation, and more. The following figure depicts what is included in the Java 2 SDK.
How Will Java Technology Change My Life
We canâ„¢t promise you fame, fortune, or even a job if you learn the Java programming language. Still, it is likely to make your programs better and requires less effort than other languages. We believe that Java technology will help you do the following:
¢ Get started quickly: Although the Java programming language is a powerful object-oriented language, it™s easy to learn, especially for programmers already familiar with C or C++.
¢ Write less code: Comparisons of program metrics (class counts, method counts, and so on) suggest that a program written in the Java programming language can be four times smaller than the same program in C++.
¢ Write better code: The Java programming language encourages good coding practices, and its garbage collection helps you avoid memory leaks. Its object orientation, its JavaBeans component architecture, and its wide-ranging, easily extendible API let you reuse other people™s tested code and introduce fewer bugs.
¢ Develop programs more quickly: Your development time may be as much as twice as fast versus writing the same program in C++. Why You write fewer lines of code and it is a simpler programming language than C++.
¢ Avoid platform dependencies with 100% Pure Java: You can keep your program portable by avoiding the use of libraries written in other languages. The 100% Pure JavaTM Product Certification Program has a repository of historical process manuals, white papers, brochures, and similar materials online.
¢ Write once, run anywhere: Because 100% Pure Java programs are compiled into machine-independent byte codes, they run consistently on any Java platform.
¢ Distribute software more easily: You can upgrade applets easily from a central server. Applets take advantage of the feature of allowing new classes to be loaded on the fly, without recompiling the entire program.
ODBC
Microsoft Open Database Connectivity (ODBC) is a standard programming interface for application developers and database systems providers. Before ODBC became a de facto standard for Windows programs to interface with database systems, programmers had to use proprietary languages for each database they wanted to connect to. Now, ODBC has made the choice of the database system almost irrelevant from a coding perspective, which is as it should be. Application developers have much more important things to worry about than the syntax that is needed to port their program from one database to another when business needs suddenly change.
Through the ODBC Administrator in Control Panel, you can specify the particular database that is associated with a data source that an ODBC application program is written to use. Think of an ODBC data source as a door with a name on it. Each door will lead you to a particular database. For example, the data source named Sales Figures might be a SQL Server database, whereas the Accounts Payable data source could refer to an Access database. The physical database referred to by a data source can reside anywhere on the LAN.
The ODBC system files are not installed on your system by Windows 95. Rather, they are installed when you setup a separate database application, such as SQL Server Client or Visual Basic 4.0. When the ODBC icon is installed in Control Panel, it uses a file called ODBCINST.DLL. It is also possible to administer your ODBC data sources through a stand-alone program called ODBCADM.EXE. There is a 16-bit and a 32-bit version of this program and each maintains a separate list of ODBC data sources.
From a programming perspective, the beauty of ODBC is that the application can be written to use the same set of function calls to interface with any data source, regardless of the database vendor. The source code of the application doesnâ„¢t change whether it talks to Oracle or SQL Server. We only mention these two as an example. There are ODBC drivers available for several dozen popular database systems. Even Excel spreadsheets and plain text files can be turned into data sources. The operating system uses the Registry information written by ODBC Administrator to determine which low-level ODBC drivers are needed to talk to the data source (such as the interface to Oracle or SQL Server). The loading of the ODBC drivers is transparent to the ODBC application program. In a client/server environment, the ODBC API even handles many of the network issues for the application programmer.
The advantages of this scheme are so numerous that you are probably thinking there must be some catch. The only disadvantage of ODBC is that it isnâ„¢t as efficient as talking directly to the native database interface. ODBC has had many detractors make the charge that it is too slow. Microsoft has always claimed that the critical factor in performance is the quality of the driver software that is used. In our humble opinion, this is true. The availability of good ODBC drivers has improved a great deal recently. And anyway, the criticism about performance is somewhat analogous to those who said that compilers would never match the speed of pure assembly language. Maybe not, but the compiler (or ODBC) gives you the opportunity to write cleaner programs, which means you finish sooner. Meanwhile, computers get faster every year.
JDBC
In an effort to set an independent database standard API for Java; Sun Microsystems developed Java Database Connectivity, or JDBC. JDBC offers a generic SQL database access mechanism that provides a consistent interface to a variety of RDBMSs. This consistent interface is achieved through the use of plug-in database connectivity modules, or drivers. If a database vendor wishes to have JDBC support, he or she must provide the driver for each platform that the database and Java run on.
To gain a wider acceptance of JDBC, Sun based JDBCâ„¢s framework on ODBC. As you discovered earlier in this chapter, ODBC has widespread support on a variety of platforms. Basing JDBC on ODBC will allow vendors to bring JDBC drivers to market much faster than developing a completely new connectivity solution.
JDBC was announced in March of 1996. It was released for a 90 day public review that ended June 8, 1996. Because of user input, the final JDBC v1.0 specification was released soon after.
The remainder of this section will cover enough information about JDBC for you to know what it is about and how to use it effectively. This is by no means a complete overview of JDBC. That would fill an entire book.
JDBC Goals
Few software packages are designed without goals in mind. JDBC is one that, because of its many goals, drove the development of the API. These goals, in conjunction with early reviewer feedback, have finalized the JDBC class library into a solid framework for building database applications in Java.
The goals that were set for JDBC are important. They will give you some insight as to why certain classes and functionalities behave the way they do. The eight design goals for JDBC are as follows:
1. SQL Level API
The designers felt that their main goal was to define a SQL interface for Java. Although not the lowest database interface level possible, it is at a low enough level for higher-level tools and APIs to be created. Conversely, it is at a high enough level for application programmers to use it confidently. Attaining this goal allows for future tool vendors to generate JDBC code and to hide many of JDBCâ„¢s complexities from the end user.
2. SQL Conformance
SQL syntax varies as you move from database vendor to database vendor. In an effort to support a wide variety of vendors, JDBC will allow any query statement to be passed through it to the underlying database driver. This allows the connectivity module to handle non-standard functionality in a manner that is suitable for its users.
3. JDBC must be implemental on top of common database interfaces
The JDBC SQL API must sit on top of other common SQL level APIs. This goal allows JDBC to use existing ODBC level drivers by the use of a software interface. This interface would translate JDBC calls to ODBC and vice versa.
4. Provide a Java interface that is consistent with the rest of the Java system
Because of Javaâ„¢s acceptance in the user community thus far, the designers feel that they should not stray from the current design of the core Java system.
5. Keep it simple
This goal probably appears in all software design goal listings. JDBC is no exception. Sun felt that the design of JDBC should be very simple, allowing for only one method of completing a task per mechanism. Allowing duplicate functionality only serves to confuse the users of the API.
6. Use strong, static typing wherever possible
Strong typing allows for more error checking to be done at compile time; also, less error appear at runtime.
7. Keep the common cases simple
Because more often than not, the usual SQL calls used by the programmer are simple SELECTâ„¢s, INSERTâ„¢s, DELETEâ„¢s and UPDATEâ„¢s, these queries should be simple to perform with JDBC. However, more complex SQL statements should also be possible.
Finally we decided to proceed the implementation using Java Networking.
And for dynamically updating the cache table we go for MS Access database.
Java ha two things: a programming language and a platform.
Java is a high-level programming language that is all of the following
Simple Architecture-neutral
Object-oriented Portable
Distributed High-performance
Interpreted multithreaded
Robust Dynamic
Secure

Java is also unusual in that each Java program is both compiled and interpreted. With a compile you translate a Java program into an intermediate language called Java byte codes the platform-independent code instruction is passed and run on the computer.
Compilation happens just once; interpretation occurs each time the program is executed. The figure illustrates how this works.
You can think of Java byte codes as the machine code instructions for the Java Virtual Machine (Java VM). Every Java interpreter, whether itâ„¢s a Java development tool or a Web browser that can run Java applets, is an implementation of the Java VM. The Java VM can also be implemented in hardware.
Java byte codes help make write once, run anywhere possible. You can compile your Java program into byte codes on my platform that has a Java compiler. The byte codes can then be run any implementation of the Java VM. For example, the same Java program can run Windows NT, Solaris, and Macintosh.
Networking
TCP/IP stack
The TCP/IP stack is shorter than the OSI one:
TCP is a connection-oriented protocol; UDP (User Datagram Protocol) is a connectionless protocol.
IP datagramâ„¢s
The IP layer provides a connectionless and unreliable delivery system. It considers each datagram independently of the others. Any association between datagram must be supplied by the higher layers. The IP layer supplies a checksum that includes its own header. The header includes the source and destination addresses. The IP layer handles routing through an Internet. It is also responsible for breaking up large datagram into smaller ones for transmission and reassembling them at the other end.
UDP
UDP is also connectionless and unreliable. What it adds to IP is a checksum for the contents of the datagram and port numbers. These are used to give a client/server model - see later.
TCP
TCP supplies logic to give a reliable connection-oriented protocol above IP. It provides a virtual circuit that two processes can use to communicate.
Internet addresses
In order to use a service, you must be able to find it. The Internet uses an address scheme for machines so that they can be located. The address is a 32 bit integer which gives the IP address. This encodes a network ID and more addressing. The network ID falls into various classes according to the size of the network address.
Network address
Class A uses 8 bits for the network address with 24 bits left over for other addressing. Class B uses 16 bit network addressing. Class C uses 24 bit network addressing and class D uses all 32.
Subnet address
Internally, the UNIX network is divided into sub networks. Building 11 is currently on one sub network and uses 10-bit addressing, allowing 1024 different hosts.
Host address
8 bits are finally used for host addresses within our subnet. This places a limit of 256 machines that can be on the subnet.
Total address
The 32 bit address is usually written as 4 integers separated by dots.
Port addresses
A service exists on a host, and is identified by its port. This is a 16 bit number. To send a message to a server, you send it to the port for that service of the host that it is running on. This is not location transparency! Certain of these ports are "well known".
Sockets
A socket is a data structure maintained by the system to handle network connections. A socket is created using the call socket. It returns an integer that is like a file descriptor. In fact, under Windows, this handle can be used with Read File and Write File functions.
#include <sys/types.h>
#include <sys/socket.h>
int socket(int family, int type, int protocol);
Here "family" will be AF_INET for IP communications, protocol will be zero, and type will depend on whether TCP or UDP is used. Two processes wishing to communicate over a network create a socket each. These are similar to two ends of a pipe - but the actual pipe does not yet exist.
JFree Chart
JFreeChart is a free 100% Java chart library that makes it easy for developers to display professional quality charts in their applications. JFreeChart's extensive feature set includes:
A consistent and well-documented API, supporting a wide range of chart types;
A flexible design that is easy to extend, and targets both server-side and client-side applications;
Support for many output types, including Swing components, image files (including PNG and JPEG), and vector graphics file formats (including PDF, EPS and SVG);
JFreeChart is "open source" or, more specifically, free software. It is distributed under the terms of the GNU Lesser General Public Licence (LGPL), which permits use in proprietary applications.
1. Map Visualizations
Charts showing values that relate to geographical areas. Some examples include: (a) population density in each state of the United States, (b) income per capita for each country in Europe, © life expectancy in each country of the world. The tasks in this project include:
Sourcing freely redistributable vector outlines for the countries of the world, states/provinces in particular countries (USA in particular, but also other areas);
Creating an appropriate dataset interface (plus default implementation), a rendered, and integrating this with the existing XYPlot class in JFreeChart;
Testing, documenting, testing some more, documenting some more.
2. Time Series Chart Interactivity
Implement a new (to JFreeChart) feature for interactive time series charts --- to display a separate control that shows a small version of ALL the time series data, with a sliding "view" rectangle that allows you to select the subset of the time series data to display in the main chart.
3. Dashboards
There is currently a lot of interest in dashboard displays. Create a flexible dashboard mechanism that supports a subset of JFreeChart chart types (dials, pies, thermometers, bars, and lines/time series) that can be delivered easily via both Java Web Start and an applet.
4. Property Editors
The property editor mechanism in JFreeChart only handles a small subset of the properties that can be set for charts. Extend (or reimplement) this mechanism to provide greater end-user control over the appearance of the charts.
CONCLUSION
To overcome the problem of applications executing in large systems where the MTTF approaches or sinks below the execution time of the application, two fault-tolerant protocols, TIC and SEL, were introduced. The two protocols take under consideration the heterogeneous and dynamic characteristics of Grid or cluster applications that pose limitations on the effective exploitation of the underlying infrastructure. The flexibility of dataflow graphs has been exploited to allow for a platform-independent description of the execution state. This description resulted in flexible and portable rollback recovery strategies. SEL allowed for rollback at the lowest level of granularity, with a maximal computational loss of one task.
However, its overhead was sensitive to the size of the associated dataflow graph. TIC experienced lower overhead, related to work-stealing, which was shown bounded by the critical path of the graph. By selecting an appropriate application granularity for SEL and period for TIC, the protocols can be tuned to the specific requirements or needs of the application. A cost model was derived, quantifying the induced overhead of both protocols. The experimental results confirmed the theoretical analysis and demonstrated the low overhead of both approaches.

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01-07-2010, 04:41 PM
Post: #4
RE: Flexible Rollback Recovery in Dynamic Heterogeneous Grid Computing full report
read Flexible Rollback Recovery in Dynamic Heterogeneous Grid Computing base paper http://69.50.213.96:8080/ieee2009project...ynamic.pdf

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02-07-2010, 06:20 PM
Post: #5
RE: Flexible Rollback Recovery in Dynamic Heterogeneous Grid Computing full report
Flexible Rollback Recovery in Dynamic Heterogeneous Grid Computing

Abstract


Large applications executing on Grid or cluster architectures consisting of hundreds or thousands of computational nodes create problems with respect to reliability. The source of the problems is node failures and the need for dynamic configuration over extensive runtime. By allowing recovery even under different numbers of processors, the approaches are especially suitable for applications with a need for adaptive or reactionary configuration control. The low-cost protocols offer the capability of controlling or bounding the overhead. A formal cost model is presented, followed by an experimental evaluation. It is shown that the overhead of the protocol is very small, and the maximum work lost by a crashed process is small and bounded.



Algorithm / Technique used:

Logging Methods.

Algorithm Description:

Logging can be classified as pessimistic, optimistic, or causal. It is based on the fact that the execution of a process can be modeled as a sequence of state intervals. The execution during a state interval is deterministic. However, each state interval is initiated by a nondeterministic event now, assume that the system can capture and log sufficient information about the nondeterministic events that initiated the state interval. This is called the piecewise deterministic (PWD) assumption. Then, a crashed process can be recovered by 1) restoring it to the initial state and 2) replaying the logged events to it in the same order they appeared in the execution before the crash. To avoid a rollback to the initial state of a process and to limit the amount of nondeterministic events that need to be replayed, each process periodically saves its local state. Log based mechanisms in which the only nondeterministic events in a system are the reception of messages is usually referred to as message logging.

Existing System:

Communication Induced Check-pointing protocols usually make the assumption that any process can be check-pointed at any time. An alternative approach which releases the constraint of always check-pointable processes, without delaying any do not message reception nor did altering message ordering enforce by the communication layer or by the application. This protocol has been implemented within Pro-Active, an open source Java middleware for asynchronous and distributed objects implementing the ASP (Asynchronous Sequential Processes) model.

Proposed System:

This paper presents two fault-tolerance mechanisms called Theft-Induced Check pointing and Systematic Event Logging. These are transparent protocols capable of overcoming problems associated with both benign faults, i.e., crash faults, and node or subnet volatility. Specifically, the protocols base the state of the execution on a dataflow graph, allowing for efficient recovery in dynamic heterogeneous systems as well as multithreaded applications.



Hardware Requirements & Software Requirements:

Hardware Requirements

¢ SYSTEM : Pentium IV 2.4 GHz
¢ HARD DISK : 40 GB
¢ FLOPPY DRIVE : 1.44 MB
¢ MONITOR : 15 VGA colour
¢ MOUSE : Logitech.
¢ RAM : 256 MB
¢ KEYBOARD : 110 keys enhanced.

Software Requirements

¢ Operating system :- Windows XP Professional
¢ Coding Language :- Java Technology

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