Fast and Efficient Multiview Access Control Mechanism for Cloud Based Agriculture Storage Management System

Fast and Efficient Multiview Access Control Mechanism for Cloud Based Agriculture Storage Management System

Kuldeep Sambrekar (Gogte Institute of Technology, Belgaum, India) and Vijay S. Rajpurohit (Gogte Institute of Technology, Belgaum, India)
Copyright: © 2019 |Pages: 17
DOI: 10.4018/IJCAC.2019010103

Abstract

Agriculture and its related industries are the backbone of many countries' economic growth. To achieve an efficient agricultural management system, remote sensing forecasting and GIS technology are providing information to users/stakeholders of various agricultural application uses. This information is huge in size and is stored in the cloud computing storage environment. Minimizing data access and storage costs on such an environment is desired. For achieving fine-grained role-based access control mechanisms, researchers are now focusing on ensuring such roles are enforced correctly. Existing models, though they are using role-based access control at various levels, are facing challenges like high computation rates and storage overhead. Currently, existing systems are using XML and UML for role and user creation. To address these research challenges, this article presents a model Fast and Efficient Multi View Access Control (FEMVAC) using the Amazon S3 public cloud environment for agriculture. The model minimizes storage overhead by adopting a banarization method over UML/XML method. The experimental outcome shows that the FEMVAC method is efficient compared with existing models.
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1. Introduction

Agriculture is the spine of Indian economy that contributes about 40 percent towards Gross National Product (GNP) and 70 per cent of the population depend on it. So, for a country that is primarily dependent on agriculture, requires accurate and timely information of data such as type of crop grown, crop yield, and crop growth condition. This information is important factor in meeting country’s food security and distribution system. Pre-harvest assessments of crop production are required for obtaining optimal strategies for planning, distribution, price fixation, transportation and storage of critical agricultural products (Bernard, 2003).

The space borne remote sensing forecasting and GIS Technology are providing information to user for various agricultural applications. They provide information such as marginal crop grown in fragmented land holdings, quantification of its effect on crops yield and detection of crop stress due to nutrients and diseases. Efficient agro-data access and storage methodologies is needed for improving crop yield models (David, 2006).

With the enormous growth of information technology such as Internet of Things, Cloud computing etc., huge volumes of data are being continuously generated by various organizations for various application uses. An efficient storage and access mechanism of large scale data with minimal cost is most desired. Achieving data sharing and collaboration between stake holders at various levels are the research challenges for organizations/enterprises (Sengupta et al., 2015). To solve the research problem cloud storage service is adopted, which is low cost and convenient.

Cloud storage service is a significant part of cloud computing environment (Wu et al., 2010), where data is stored in storage resources in cloud environment. The user/stake holders can access the storage resource anytime and anywhere through the Internet. Adopting Cloud computing for Agro services offers following benefits/features such as 1) Ease to expand- as per application needs the storage size can be increased. 2) Reliable and secure- it can automatically backup data even during node failure and offers guarantee of data availability to end users. 3) Resource control- it offers user to create different access policies for controlling data access permission. 4) High resource utilization- cloud can abstract all the storage resource and offers a integrated access interface to end clients. 5) Low cost- it efficiently minimize the cost of each users and organization (i.e. no upkeep cost for procuring removable storage devices).

Recently, number of cloud storage systems such as Microsoft OneDrive, Dropbox, Google Drive, S3 etc. are offered by Microsoft, IBM, Google, Amazon etc. All these cloud storage systems are primarily designed to offer storage services for individual user’s requirement and they cannot meet the demand of enterprises (cloud based agro service). For provisioning cloud storage for enterprises following features need to be considered. 1) Flexible fine-grained access control mechanism- a grained access control policy need to be defined for users to access the data from any directory/buckets. 2) Multi-user sharing and cooperation- the cloud storage access system should allow bucket sharing among users to access same resource, 3) Capacity expansion- it should offer convenient cluster expansion when requirement arise. 4) Data security and privacy- it should offer continuous access of data to user during node failure. 5) Flexible user disk space quota management- it should offer storage services to user based on roles defined for achieving flexible storage assignment for different users. 6) Ease of use- the system should offer service convenient to user with minimal cost and latency.

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