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Srimathi, H.
- An Analysis on the Performance of Tree and Trie Based Dictionary Implementations with Different Data Usage Models
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Authors
M. Thenmozhi
1,
H. Srimathi
2
Affiliations
1 Department of Information Technology, SRM University, Chennai, IN
2 Department of Computer Applications, SRM University, Chennai, IN
1 Department of Information Technology, SRM University, Chennai, IN
2 Department of Computer Applications, SRM University, Chennai, IN
Source
Indian Journal of Science and Technology, Vol 8, No 4 (2015), Pagination: 364-375Abstract
Tree and Trie are the Abstract Data Types (ADTs) that provide efficient implementation of ordered dictionary. The performance of a data structure will depend on hardware capabilities of the computing devices such as RAM size, Cache memory size and even the speed of the physical storage media. Hence, an application which will be running on real or virtualized hardware environment certainly will have restricted access to memory and other resources of the real hardware. Further, the time taken for any operation on a data structure rely on the data usage model and the most significant operations/tests are very much depend on the size of the "character payload objects" which we use in dictionary like implementations. In this work, we do an analysis on the performance of Tree and Trie based Dictionary ADT Implementations with different data usage models. We consider data usage models such as a typical electronic dictionary with more than million of words or a typical electronic encyclopedia with large string data elements. In this work, we studied the performance of three popular Tree based Dictionary Implementations rbtree, googlebtree, stxbtree, and three Trie based Dictionary Implementations tommy-trie, tommy-trie-inplace, nedtrie under different hardware and software configurations. Among all, tommy trie is proved to be the best for character payload objects with 16 bytes and 4096 bytes. In some operations/tests googlebtree seems to be better. Our evaluation on different tree and trie structures shows tommy trie implementations perform well irrespective of size of application.Keywords
Cache, Googlebtree, Rbtree, Stx Btree, Tommy Trie, Trie.- Survey and analysis on Task scheduling in Cloud environment
Abstract Views :186 |
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Authors
Affiliations
1 Survey and Analysis on Task Scheduling in Cloud Environment, IN
1 Survey and Analysis on Task Scheduling in Cloud Environment, IN
Source
Indian Journal of Science and Technology, Vol 9, No 37 (2016), Pagination:Abstract
Objectives: In cloud environment many scheduling algorithms are available to achieve the quality of service, but the scalability of task execution increases, scheduling becomes more complex. So there is a need for better scheduling. This paper deals with the survey of dynamic scheduling, different classification and scheduling algorithms currently used in cloud providers. Analysis: This paper focuses on a comparative study of static and dynamic task scheduling currently used and various researchers work on dynamic task scheduling for many applications. Findings: Scheduling methods/techniques used by various cloud service providers, advantages and limitations of each method are discussed. Scheduling algorithms in cloud setup in each paper is analyzed. Application: Analyzing task scheduling in cloud environment, uniform standard can be applied for all cloud providers. Online scheduling and dynamic scheduling can be further improvedKeywords
Cloud Computing, Cloud Setup, Static and Dynamic Scheduling, Task Scheduling Algorithms, Various Metrics.- Dynamic Scheduling in Cloud Computing using Particle Swarm Optimization
Abstract Views :156 |
PDF Views:0
Authors
Affiliations
1 Computer Science and Engineering, SRM University, Chennai 603203, Tamil Nadu, IN
1 Computer Science and Engineering, SRM University, Chennai 603203, Tamil Nadu, IN