BLEH: Bit-Less Extendible Hashing for DBMS and Hard Disk Drives
G M Sridevi1, D V Ashoka2

1G M Sridevi*, Department of ISE, SJB Institute of Technology, Bengaluru, India.
2Dr. D V Ashoka, Department of ISE, JSS Academy of Technical Education, Bengaluru, India

Manuscript received on November 15, 2019. | Revised Manuscript received on 20 November, 2019. | Manuscript published on December 10, 2019. | PP: 2191-2197 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7539129219/2019©BEIESP | DOI: 10.35940/ijitee.B7539.129219
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Abstract: Indexing techniques such as extendible hashing and B-trees are widely used to store, retrieve and search for data on files in most file systems. These techniques have been comprehensively explored to enhance the data structure for increasing the faster access to file contents. Extendible hashing is a dynamic hashing technique which handles dynamic files that keep changing in size. Traditional extendible hashing uses bit addresses to hash the data to buckets and restricts the directory size to be a power of 2 which has corresponding complications in implementation. Restriction on directory size also results in uneven distribution of data which increases the possibility of overflows. This in turn increases the cost of index maintenance. In this paper, an efficient and simpler to implement variation of Extendible hashing method named Bit-Less Extendible Hashing (BLEH) for dynamic files is proposed. The proposed method eliminates the need for binary representation of the hash address which reduces the complexity of implementation. Furthermore, it eliminates the need for the directory size to be a power of 2 providing flexibility in the choice of initial directory size. The experimental results show that the proposed method provides better performance in terms of split count upon insertion when compared to the traditional extendible hashing method with good space utilization. 
Keywords: Dynamic Hashing, Extendible Hashing, Hashing, Universal Hash Functions.
Scope of the Article: Artificial Intelligence Approaches to Software Engineering