Rapid growth of Technology enabled several newer scientific and commercial applications to be developed. These applications demand more and more computing power. Distributed computing is the area of focus to satisfy the increasing demand of these applications. Almost every commercial/ scientific application is developed as either web applications or web services or both. The users of such system are increasing day by day. Generally, these web applications are dynamic in nature. The high demand servers receive thousands of requests in a second. This overloads the database and degrades the overall performance of such applications. In multitier web applications and web services the web based frontend, business logic and databases are deployed over the different servers. To avoid the network delay and to improve the performance of such applications a new distributed hash-based database caching (DHBDC) is already presented by us. However, to use DHBDC the applications must be modified to access the data from the cache. Hence, this paper modifies the DHBDC in such a manner that these applications need not to be modified. Hence, this new strategy called Dependency Free Distributed Database Caching (DFDDC). It is integrated with a custom JDBC driver to achieve the dependency freedom. The prototype of new strategy is implemented and promising results have been from the prototype.

1. Apache Tomcat Application Server, http://tomcat.apache.org/.
2. Apache Web Server, http://www.apache.org/.
3. Bornhövd, C., Altinel, M., Krishnamurthy, S., Mohan, C., Pirahesh, H. and Reinwald, B. 2003. DBCache: Middle-tier Database Caching for Highly Scalable e-Business Architectures. In Proceedings of ACM SIGMOD International Conference on Management of Data (San Diego, California, USA, June, 2003). SIGMOD’03, 662-662.
4. Distributed Hash Tables, Available Online at, http://en.wikipedia.org/wiki/Distributed_hash_table.
5. Java Enterprise Edition, http://java.sun.com/javaee/.
6. Java Middleware Open Benchmarking (JMOB), http://jmob.ow2.org/jvm.html.
7. JMeter Load Testing Tool, http://jakarta.apache.org/ jmeter/.
8. Least Recently Used, Available Online at, http://en.wikipedia.org/wiki/Cache_algorithms#Least_Recently_Used.
9. Memcached Distributed Memory Cashing System, http://memcached.org/.
10. MySQL Enterprise Server, http://www.mysql.com.
11. Tolia, N. and Satyanarayanan, M. 2007. No-Compromise Caching of Dynamic Content from Relational Databases. In Proceedings of 16th International World Wide Web Conference (Banff, Canada, May 2007). WWW’07, 311-320.
12. Oracle Times Ten In-Memory Database, http://www.oracle.com/database/timesten.html.
13. Larson, P.A., Goldstein, J. and Zhou J. 2004. MTCache: Transparent Mid-Tier Database Caching in SQL Server. In Proceedings of 20th International Conference on Data Engineering (Boston, Mar-Apr 2004). ICDE’04, 177-189.
14. Luo, Q., Krishnamurthy, S., Mohan, C., Woo, H., Pirahesh, H., Lindsay B. and Naughton, J. 2002. Middle-tier Database Caching for e-Business. In Proceedings of ACM SIGMOD International Conference on Management of Data, (Madison,WI, Jun 2002). SIGMOD’02, 600-611.
15. Remote Method Invocation, http://java.sun.com/javase/ technologies/core/basic/rmi/index.jsp.
16. Paul, S., and Fei, Z. 2001. Distributed Caching with Centralized Control. Computer Communications, Elsevier Press. 24, 2 (Feb 2001), 256-268.
17. TimesTen Team. 2002 Mid-Tier Caching: The TimesTen Approach. In Proceedings of ACM SIGMOD International Conference on Management of Data (Madison,WI, Jun 2002), SIGMOD’02, 588-593.Bowman, M., Debray, S. K., and Peterson, L. L. 1993. Reasoning about naming systems.
18. Mehta, H., Kanungo, P. and Chandwani M. 2011. Distributed Database Caching for Web Applications and Web Services. Accepted in ACM International Conference and Workshop on Emerging Trends and Technology (Mumbai, February 2011). ICWET 2011.

Database Database Caching DHT Multitier Web Applications Web Service