Evolve Aggregation Management of Data for Heterogeneity

Cloud computing is the most emerging technology. It has the capability to provide various services like infrastructure, security, data management, databases, and network over the internet. Several cloud service providers in the market provide computing resources. Cloud brokering in cloud computing is a crucial part as it acts as a middleware between cloud users and cloud services providers. In this paper we aim to provide an overview on adaptive data management middleware for cloud brokers. To manage the heterogeneous data and other factors, policy-based task scheduling can be integrated with the cloud broker, which supports dynamic data placement and takes decisions and actions at the runtime considering the SLA (service level agreements) and QoS (quality of service) requirements without any manual involvement. By aggregation of data, the next task of scheduling and assigning priority will be taken carefully. At the end service requests should be fulfilled by utilizing minimum resources.

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Publication Details

Published
2024-10-17
DOI
https://doi.org/10.1109/icbds61829.2024.10837360
Primary Topic
Cloud Computing and Resource Management
Type
article
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article

Evolve Aggregation Management of Data for Heterogeneity

Vikas K. Kolekar, Monika Patil, Shreyash Shete
Cloud Computing and Resource Management
article

Evolve Aggregation Management of Data for Heterogeneity

Vikas K. Kolekar, Monika Patil, Shreyash Shete
article en

Abstract

Cloud computing is the most emerging technology. It has the capability to provide various services like infrastructure, security, data management, databases, and network over the internet. Several cloud service providers in the market provide computing resources. Cloud brokering in cloud computing is a crucial part as it acts as a middleware between cloud users and cloud services providers. In this paper we aim to provide an overview on adaptive data management middleware for cloud brokers. To manage the heterogeneous data and other factors, policy-based task scheduling can be integrated with the cloud broker, which supports dynamic data placement and takes decisions and actions at the runtime considering the SLA (service level agreements) and QoS (quality of service) requirements without any manual involvement. By aggregation of data, the next task of scheduling and assigning priority will be taken carefully. At the end service requests should be fulfilled by utilizing minimum resources.

International Institute of Information Technology (IN)
Openalex Percentile: Top 59%
Cloud Computing and Resource Management
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