Exploiting the Solar Energy Surplus for Edge Computing
ABSTARCT :
In the context of the global energy ecosystem transformation, we introduce a new approach to reduce the carbon emissions of the cloud-computing sector and, at the same time, foster the deployment of small-scale private photovoltaic plants. We consider the opportunity cost of moving some cloud services to private, distributed, solar-powered computing facilities. To this end, we compare the potential revenue of leasing computing resources to a cloud pool with the revenue obtained by selling the surplus energy to the grid. We first estimate the consumption of virtualized cloud computing instances, establishing a metric of computational efficiency per nominal photovoltaic power installed. Based on this metric and characterizing the site's annual solar production, we estimate the total return and payback. The results show that the model is economically viable and technically feasible. We finally depict the still many questions open, such as security, and the fundamental barriers to address, mainly related with a cloud model ruled by a few big players.
EXISTING SYSTEM :
? Integrating RE into most existing energy supply systems and end-use sectors at an accelerated rate leading to higher shares of RE is technologically feasible, though will result in a number of additional challenges.
? In the building sector, RE technologies can be integrated into both new and existing structures to produce electricity, heating and cooling.
? They may include additional costs for network infrastructure investment, system operation and losses, and other adjustments to the existing energy supply systems as needed.
? Direct land use change (dLUC) occurs when bioenergy feedstock production modifi es an existing land use, resulting in a change in above- and below-ground carbon stocks.
DISADVANTAGE :
? The servers are among the primary energy consumers of data centers, many green proposals have addressed the problem of the server’s energy-efficiency.
? Such an edge Cloud architecture needs to deal with flexibility, scalability and data privacy issues to allow for efficient computational offloading services.
? The issue resides in having an end-to-end energy estimation of all the involved devices and infrastructures, including network devices from ISP and Cloud servers.
? Internet of Things (IoT) is bringing an increasing number of connected devices that have a direct impact on the growth of data and energy-hungry services.
PROPOSED SYSTEM :
• Space solar power, in which solar power collected in space is beamed via microwaves to receiving antennae on the ground, has also been proposed.
• In addition to the terms above proposed in the communication industry, another term, the grid edge with a similar meaning to EC, has been popularized recently in the power industry.
• These terms have been proposed by different organizations, but overall, they share a common ground with trivial differences.
• Heterogeneous computing and lightweight function libraries are proposed to enhance the performance of existing embedded chips.
• Proposes a vehicular network architecture assisted by EC integrating different types of communication access.
ADVANTAGE :
? Cloud providers expect to improve the performance of their Cloud and to leverage their available infrastructure.
? Dynamic voltage and frequency scaling that exploits server performance knobs is an example of such proposals.
? Although they enable to achieve high performance computing ability and manageability, a powerful cooling system is needed to lower the temperature of this large infrastructure equipment.
? The motivation of this work is to provide a framework that can balance performance and energy cost tradeoffs for real-time data analysis of high-rate data from many devices.
? We evaluate the effects of offloading computation tasks at the edge for system performance of our framework and energy consumption at edge and core.
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