Agri-Info: Cloud Based Autonomic System for Delivering Agriculture as a Service

Abstract

Cloud computing has emerged as an important paradigm for managing and delivering services efficiently over the Internet. Convergence of cloud computing with technologies such as wireless sensor networking and mobile computing offers new applications' of cloud services but this requires management of Quality of Service (QoS) parameters to efficiently monitor and measure the delivered services. This paper presents a QoS-aware Cloud Based Autonomic Information System for delivering agriculture related information as a service through the use of latest Cloud technologies which manage various types of agriculture related data based on different domains. Proposed system gathers information from various users through preconfigured devices and manages and provides required information to users automatically. Further, Cuckoo Optimization Algorithm has been used for efficient resource allocation at infrastructure level for effective utilization of resources. We have evaluated the performance of the proposed approach in Cloud environment and experimental results show that the proposed system performs better in terms of resource utilization, execution time, cost and computing capacity along with other QoS parameters. IntroductionCloud computing has emerged as an important paradigm for managing and delivering the new emerging applications in the field of healthcare, agriculture, education, finance, etc. efficiently over the internet. However, providing dedicated cloud services that ensure application's dynamic QoS (Quality of Service) requirements and user satisfaction is a big research challenge in cloud computing. As dynamism, heterogeneity and complexity of applications is increasing rapidly, this makes cloud systems unmanageable in service delivery. To overcome these problems, cloud systems require self-management of services. Autonomic cloud computing systems provide the environment in which applications can be managed efficiently by fulfilling QoS requirements of applications without human involvement [1] [2].In our earlier work [1] [14] [15] [16] [27], we have identified various research issues related to QoS and SLA for cloud resource scheduling and have developed a QoS based resource provisioning technique (Q-aware) to map the resources to the workloads based on used requirements described in the form of SLA. Further, resource scheduling framework (QRSF) has been proposed, in which provisioned resources have been scheduled by using different resource scheduling policies (cost, time, cost-time and bargaining based). The concept of QRSF has been further extended by proposing energy-aware autonomic resource scheduling technique (EARTH), in which IBM's autonomic computing concept has been used to schedule the resources automatically by optimizing energy consumption and resource utilization where user can easily interact with the system using available user interface. In this work, we have proposed a cloud based autonomic information system which delivers Agriculture as a Service (AaaS) through cloud infrastructure and se...

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