A Survey on Carbon Emission Management and Intelligent System using Cloud

Transcription

1 A Survey on Carbon Emission Management and Intelligent System using Cloud Dr.P EZHILARASU 1 (Associate Professor, Department of Computer Science and Engineering [email protected]) S SARANYA 2 (PG scholar, Department of Computer Science and Engineering [email protected]) D SATHEESH KUMAR 3 ( Assistant Professor, Department of Computer Science and Engineering [email protected] M GANESAN 4 ( Assistant Professor, Department of Information Technology [email protected] Abstract: Now days global warming is increasing at a high rate mainly due to the emission of greenhouse gases released by industries which results in environmental pollution this can be controlled by various cloud hosted systems. Cloud computing is a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. The concept incorporates Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS).The cloud hosted system generates statistical and non-statistical, sustainability performance from various industries which is used for emission reduction. The amount of gases emitted is monitored using cloud and CAP(Carbon Adjust Profit) values is adjusted.the CAP value is calculated using carbon footprint analysis. Keywords: Environment, Green house gases, Greenhouse gas (GHG) emission management, CAP & trade values.

2 1 INTRODUCTION The environmental problems are increasing day by day in recent days. Due to various climatic changes the environment is facing problems for sustainable economies. The major source of this climatic change problem is the greenhouse gas emission. Due to this emission the environment is prone to various type of climatic changes. In order to reduce his issue standard practice has been maintained called as cap and trade value which will achieve reduction charges for greenhouse gas emission If the emission emitted by the companies is capped legally similar to capital or human resources it will impact on the financial result of the company because of the environmental taxes. So, adequate emission management is quite important. Hence the companies want to manage energy consumption. But managing this is especially difficult and expensive for small and medium business. so unified and flexible system is beneficial for many companies. This paper proposes a cloud hosted system for efficiently calculating analyzing and monitoring the data. Cloud computing is a form of computing which employs services such as SaaS, IaaS, PaaS over the internet. Figure 1: Basic cloud architecture Software as a Service (SaaS) is a software deployment application in which it is licensed for use of service on demand. Infrastructure as a Service (IaaS) is a platform virtualization environment. Platform as a Service (PaaS) is used fro building and supporting web application.

3 2 VARIOUS REDUCTION METHODS Table 1 Analysis of various carbon emission and control methods S.no Title Process Future work 1. Cloud based infrastructure for managing and analyzing environmental resources [1] 2. Design of control system for energy saving and carbon reduction [2] 3. Optimal flexible operation of carbon dioxide capture power plant and emission market [3] Energy management systems with sensor on cloud infrastructure that manage and collect data using XBRL cloud Boiler efficiency that uses oxy hydrogen fuel is used for achieving optimization of energy consumption Carbon Capture and Storage (CCS) technology is used in the reduction of carbon dioxide Focuses on adding sustainability performance on XBRL Focus on improving efficiency and in seeking energy breakthrough Profit maximization 4. Carbon aware load balancing for geodistributed cloud services [4] Lyapunov optimization technique is used for analyzing carbon aware control framework Minimization electricity costs of 5. Carbon flow tracing method for assessment of carbon emission obligation [7] 6. Low Carbon Power System Dispatch Incorporating Carbon Capture Power Plants 7. Reducing carbon emission rate using billboard manager Carbon accounting at the regional level to reduce the emission Low-carbon power system dispatch (LCPSD) incorporating CCPPs (Carbon Capture power plant) is used. Billboard manager which efficiently manages several virtual machines to increase throughput Improve the assessment results with electricity sources and network transmissions Reduction in operational costs. Prioritize the task in order to reduce the waiting time.

4 8. Environmental conscious scheduling of Near optimal scheduling policies Increase in energy saving high performance computer on distributed that exploit heterogeneity across process cloud oriented datacenter multiple data centers 9. A cloud control system for efficient carbon emission management [5] A relational database and key value store combined cloud data management for efficiently monitoring the sensor [5] data across different regions to reduce emissions Performance in large scale sensors based systems using postgresql 10. Intelligent cloud system for efficient carbon emission management [6] Intelligent energy management system that minimizes power consumption Optimization and total energy consumption. 11. Carbon footprint optimization as PLC control strategy in solar power system automation Carbon dioxide impact optimization algorithm Implementation of offgrid rural power generation systems. 3 CONCLUSION Cloud computing is used for reducing emission of greenhouse gases at the regional levels. Our cloud infrastructure can manage sensors and provide a unified interface to access data from applications in order to maintain cap and trade value. Vast amount of data is maintained by the cloud and can be used accurately based on the requirements of the users. 4 REFERENCES [1] The GHG Protocol, The Greenhouse Gas Protocol Initiative, [2] Hong-Tao Si and Wen-Qing Liu, Energy saving of steam boiler and introduction of pollution reduction technology, Chemical technology, 98, PP.246-, [3] H. Chalmers et al., Flexible operation of coal fired power plants with post-combustion capture of carbon dioxide, Environ. Eng., vol. 135, pp , [4] L. Rao, X. Li, M. D. Ilic, and J. Liu, Distributed coordination of inter- net data centers under multiregional electricity markets, Proceedings of IEEE, vol. 100, no. 1, pp , [5] Chang F, Dean J, Ghemawat S, et. al. Bigtable: A distributed storage system for structured data. Proc. of 7th Symposium on Operating Systems Design and Implementation (OSDI '06), USA. Nov

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