Informatics Publishing Limited

A. John ¹, M. Sugumaran ², R. S. Rajesh ¹

Affiliations
1 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, IN
2 Department of Computer Science and Engineering, Pondicherry Engineering College, IN

Abstract

Indexing and query processing is an emerging research field in spatio - temporal data. Most of the real-time applications such as location based services, fleet management, traffic prediction and radio frequency identification and sensor networks are based on spatio-temporal indexing and query processing. All the indexing and query processing applications is any one of the forms, such as spatio index access and supporting queries or spatio-temporal indexing method and support query or temporal dimension, while in spatial data it is considered as the second priority. In this paper, give the survey of the various uncertain indexing and query processing techniques. Most of the existing survey works on spatio-temporal are based on indexing methods and query processing, but presented separately. Both the indexing and querying are related, hence state - of - art of both the indexing and query processing techniques are considered together. This paper gives the details of spatio-temporal data classification, various types of indexing methods, query processing, application areas and research direction of spatio-temporal indexing and query processing.

Keywords

Uncertain Data, Spatio-Temporal Index, Spatio-Temporal Queries, Skyline Query, Top-K Query, Nearest-Neighbor Query.

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B. Balamurugan ¹, D. Kamalraj ¹, S. Jegadeeswari ¹, M. Sugumaran ²

Affiliations
1 Bharathiar University, Coimbatore – 641046, Tamil Nadu, IN
2 Pondicherry Engineering College, Pillaichavadi – 605014, Puducherry, IN

Abstract

Cloud computing implements virtualization processing of data service in the internet, where it delivers the conceptual, scalable platforms and applications as on data services. The important problem arises in Cloud infrastructure in storing a very large amount of data and processing on the computational load on the cloud. It is a big challenge to overcome computation complexity on cloud. An effectively predict the data streams process with load factors of ensemble model and data stream are implemented to overcome in cloud. Data stream processes on the cloud infrastructure runs with continuously varying load factors. In this work, we propose an architecture with a load balancing framework for cloud infrastructure by using the Ensemble Tree Metric Space Indexing (E-tree MSI) technique. We developed three techniques to construct our E-tree MSI technique: Fast Predictive Look-ahead Scheduling approach (FPLS) where the scheduling of Spatio-temporal data stream files takes place; Parallel Ensemble Tree Classification (PETC) which performs the process of classification operations on cloud data stream; and a Bilinear quadrilateral Mapping process which adds efficient implementation of cloud infrastructure. We have done an experimental evolution using Cloud Sim, from which it is achieved that the performance of load balancing factor is increased, the accuracy rate of classification is better and it reduced the execution time for mapping.

Keywords

Cloud Security, Data Stream, E-Tree, Load Balancing, Load Factor, Mapping and Metric Space

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M. Veeresha ¹, M. Sugumaran ¹

Affiliations
1 Department of Computer Science and Engineering, Pondicherry Engineering College, Pondicherry − 605014, IN

Abstract

Objectives: Network Coding-based Spatial Air Index (NCSAI) has been proposed for improving query performance of continuous k-nearest neighbor queries in road networks. Methods: Due to unreliable nature of wireless links, network coding has been playing an important role in wireless environments and improves scalability and throughput. In this work,NCSAI has been adapted using XOR-based network coding because it is simple and efficient coding strategy. Findings: Experiments have been conducted for evaluating query performance, the experimental result show that performance of NCSAI better than state-of-the-art Network Partition Index (NPI). Improvements: We can improve the performance of NCSAI by adapting an efficient network coding strategies.

Keywords

Continuous k-Nearest Neighbor Queries, Network Coding-Based Spatial Air Index (NCSAI), Network Partition Index (NPI), Road Networks, Wireless Environments

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M. Veeresha ¹, M. Sugumaran ¹

Affiliations
1 Dept. of Computer Sci. and Engg., Pondicherry Engg. College, Pondicherry, IN

Abstract

Objective of the present work is to improve range query performance using Hybrid Spatial Air Index (HSAI). HSAI has been designed with combination of both cache management and network coding for processing range queries in road networks. HSAI has been utilized the advantage of both cache management and network coding and reduce client search space. The experiments have been conducted for evaluating performance, the experimental results show that HSAI outperform.

Keywords

Hybrid Spatial Air Index, Cache Management, Network Coding, Range Queries, Road Networks.

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M. Veeresha ¹, M. Sugumaran ¹

Affiliations
1 Dept. of Computer Sci. and Engg., Pondicherry Engg. College, Pondicherry, IN

Abstract

Spatial Air Index (SAI) has been proposed for improving query performance of k-nearest neighbour queries in road networks. SAI has been effectively utilized the usage of Adaptive Cooperative Caching (ACC) and reduced search space. Experiments have been conducted for evaluated query result, the experimental result show that SAI outperform compared to state-of-the-art Network Partition Index (NPI).

Keywords

Spatial Air Index, K-Nearest Neighbour Queries, Adaptive Cooperative Caching, Network Partition Index, Road Networks.

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M. Sugumaran ¹, T. Vetrichelvan ¹, S. Darlin Quine ²

Affiliations
1 Adhiparasakthi College of Pharmacy, Melmaruvathur-603319, IN
2 School of Chemical and Biotechnology, SASTRA University, Thanjavur-613402, IN

Abstract

Ethanolic and aqueous leaf extract of Pithecellobium dulce was studied for its antidiabetic activity using streptozotocin-induced diabetic model in rats. The aqueous extract showed significant activity (P<0.01) than the alcoholic extract at the tested dose level which was comparable to glibenclamide, a standard antidiabetic drug. HPTLC fingerprinting profile of the aqueous extract was also developed which would serve as reference standard for quality control of this extract.

Keywords

Alloxan, Anti-Diabetic, Leaf Extracts, Pithecellobium dulce.

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