Improving the Performance of the Distributed File System through Anticipated Parallel Processing

In the emerging Big Data scenario, distributed File systems (DFSs) are used for storing and accessing information in a scalable manner. Many cloud computing systems use DFS as the main storage component. The Big Data applications de-ployed in cloud computing systems more frequently perform read operations and less frequently the write operations. So, improving the performance of read access has become an im-portant research issue in DFS. In the literature, many client side caching with appropriate pre fetching techniques are proposed for improving the performance read access in the DFS. A speculation-based approach which uses client side caching is also proposed in the literature for improving the performance of read access in the DFS. In this paper, we have proposed a new read algorithm for the DFS based on anticipated parallel processing. We have evaluated the per- formance of the proposed algorithm using mathematical and simulation methods and the results indicate that the pro-posed algorithm performs better than the speculation-based algorithm proposed in the literature

Performance Study of the Running Times of well known Pattern Matching Algorithms for Signature-based Intrusion Detection Systems

Intrusion detection system (IDS) is the basic component of any network defense scheme. Signature based intrusion detection techniques are widely used in networks for fast response to detect threats. One of the main challenges faced by signature-based IDS is that every signature requires an entry in the database, and so a complete database might contain hundreds or even thousands of entries. Each packet is to be compared with all the entries in the database. This can be highly resource-consuming and doing so will slow down the throughput and making the IDS vulnerable. Since pattern matching computations dominate in the overall performance of a Signature-based IDS, efficient pattern matching algorithms should be used which use minimal computer storage and which minimize the searching response time. In this paper we present a performance study of the running times of different well known pattern matching algorithms using multiple sliding windows approach. DOI: 10.17762/ijritcc2321-8169.150613