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TopIntroduction
Cloud computing is a method of delivery in which a group of servers are connected across a network by which data is stored and distributed, and its work relies on DCs spread around the world. DCs consume a lot of energy according to (Alharbi, et al. 2020), increasing the proportion of greenhouse gases in the layers of the atmosphere and resulting in global warming, which is the main cause of climate change (Alkenani & Nassar, 2022). Network designers and developers worldwide are now turning to energy-efficient cloud computing to reduce the environmental impact of DCs. Energy-saving cloud computing supports the goals of green technology, including reducing the energy consumed by electronic devices and computers (Atiewi, et al. (2018). We emphasize the power consumption of servers, core switches, and aggregation switches. The first section explained about escalating operational expenses and environmental concerns, the study delves into innovative energy-efficient solutions within network architectures. Focusing on network topologies, we tackle the challenge of reducing energy consumption. The rest of the paper is organised as follows. Section 2 is a literature review; Section 3 the methodology describes the methodology, empirical study, and green cloud simulator components. Section 4 is a result includes the experiment result, the workflow and the data entry model used to conduct the study are described in section, and the conclusion is in section 5. References can be found in Section 6. In an era marked by the increasing digitalization of our world, the demand for efficient and sustainable network infrastructures has never been more critical. The continuous expansion of DCs and the growing reliance on networked services have raised concerns about escalating energy consumption and its associated environmental impact. Our study addresses the following key problem statement in response to these challenges.
The proliferation of DCs, cloud computing, and networked applications has led to a substantial surge in energy consumption within network infrastructures. Escalating demand for energy imposes significant operational costs on organisations and contributes to rising carbon emissions, exacerbating global environmental issues, including climate change. Consequently, there is a pressing need to explore innovative solutions to address the energy consumption challenges associated with network architectures. Against this backdrop, our research specifically homes in on the role of network topologies in influencing energy consumption. Within this context, we confront the following problem:
- 1.
Numerous network topologies are deployed across DCs and communication networks, each with its own structural characteristics and operational requirements. These range from traditional three-tier network configurations which is access, distribution, and core layers, optimize communication, enhancing performance and scalability. To more contemporary and high-speed alternatives, such as the three-tier architecture “Three-tier architecture: access, distribution, core layers ensure efficient communication, enhancing network scalability and performance.”.
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Understanding how these network topologies impact energy consumption is a complex and critical challenge, as it can significantly affect the efficiency and sustainability of network operations.
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While theoretical models and simulations provide valuable insights, empirical data derived from real-world experiments are indispensable for a comprehensive understanding of the energy consumption dynamics within different network topologies. The scarcity of empirical studies comparing the energy performance of various network architectures underscores the need for rigorous and data-driven investigations to guide informed decision making in network design and management.
The performance evaluation in the study entailed a systematic assessment and comparison of two different network configurations: the conventional three-tier architecture and the innovative high-speed three-tier network topology.
Figure 1. Proposed architecture (Panigrahi et al. 2019)