II2202, Fall 2018, Period 1-2 Draft project report November 14, 2023
Towards a Green Cloud: A Comparative Analysis of Routing and Circuit Design
Abstract
The challenge is to implement green cloud computing in network services, addressing energy inefficiency, carbon footprint, initial investments, and uncertainty about long-term benefits. The goal is to assess and compare energy-efficient routing and network design methods for transitioning to a greener network structure. An analytic model will be developed to demonstrate the advantages of green cloud computing techniques over traditional approaches, potentially challenging existing hypotheses. The project will primarily employ the empirical method for research but will leverage AWS cloud resources to enhance scalability and data diversity, expediting the research process. – Results and conclusions?? –
Contents
1 Aims, Objectives, Goals, Research questions, hypotheses 3
2 Background and rationale 3
3 Theory/literature 3
4 Research Methodology 4
5 Participants, Procedures, Data Collection, and Analysis 4
5.1 Participants .......................................... 4
5.2 Procedures........................................... 4
5.3 DataCollection........................................ 4
5.4 DataAnalysis......................................... 4
6 Expected outcomes 5
7 Milestones/schedule, budget 5
7.1 ProjectProposalWriting(October1-October8) ...................... 5
7.2 ResearchPlanDevelopment(October9-October15) . . . . . . . . . . . . . . . . . . . . 5
7.3 Virtual Network Establishment and Preliminary Testing (October 16 - November 2) . . . . 5
7.4 Quantitative Testing and Data Collection (November 3 - November 26) . .
7.5 First-Draft and Presentation Preparation (November 27 - December 10) . .
7.6 Opposition Report Writing (December 11 - December 17) . . . . . . . . .
7.7 Final Research Report and Seminar Preparation (December 18 - January 7)
7.8 FinalSeminar(January8)...........................
II2202, Fall 2018, Period 1-2
Draft project report
November 14, 2023
8 Risks
9 Outline
10 Appendix/Appendices
List of Acronyms and Abbreviations
II2202, Fall 2018, Period 1-2 Draft project report November 14, 2023
1 Aims, Objectives, Goals, Research questions, hypotheses
This project stems from the environmental necessity to make internet networks and computational load more sustainable. In this project, two different systems for energy efficiency will be analyzed to determine whether these systems are suitable for all networks (already displayed) or only for future networks. The project will investigate how to introduce green cloud computing into network services, recognizing the constant increase in demand, the fact that many networks and data centers were designed years ago without consideration for energy efficiency, the significant carbon footprint resulting from intensive network infrastructure use, and the growing energy requirements as companies expand their cloud operations. In addition, these changes require an initial investment and a shift in mindset towards adopting more eco- friendly practices. There is also uncertainty among companies about investing in new solutions without being sure of their long-term effectiveness and profitability. Introducing green cloud computing aligns environmental responsibility with operational efficiency and economic benefits. The key question is which techniques to employ and how to apply them effectively. The techniques depend on whether the network is an existing one or a new one, as for the former case, energy efficient routing could be implemented, while for the latter, energy-efficient network design could be implemented. The purpose is to present, analyze, and compare energy-efficient routing and network design techniques to gradually transform the current network structure into a more sustainable and environmentally friendly one. An analytic and comparative model showing the advantage of using green cloud computing techniques versus traditional techniques will be derived based on fitting curves to the experimental data for both forms of energy efficiency designing and routing. This model can be used to invalidate the hypothesis.
We aim to address two key questions: First, does the implementation of green routing or green circuit design result in a reduction of energy consumption, and if so, what percentage decrease can be observed? Second, when considering cost-effectiveness, which of the two alternatives—green routing or green circuit design—proves to be more advantageous?
2 Background and rationale
In the past, numerous comprehensive studies [1] [2] [3] [4] [5] [6] have been diligently undertaken, all driven by a common goal: to unearth diverse solutions capable of curtailing the prodigious energy consumption observed within the realm of internet networks. These rigorous examinations have meticulously categorized the expansive spectrum of energy usage into three distinct categories, namely data centers, personal devices, and the intricate web of communication networks. Beyond this overarching research, it is pertinent to note that dedicated inquiries have been directed towards dissecting and comprehending the intricate dynamics of energy consumption within communication networks alone. It is within this focused domain that the present document finds its primary purpose and scope. [?]. [?]
3 Theory/literature
According to the latest data at our disposal, we are aware that one-third of the global consumption in ICT (Information and Communication Technology) stems from communication networks. To specify further, this includes customer premises equipment, office networks, and telecommunication operator networks.
Furthermore, data has been scrutinized concerning the consumption of a high-end router, where 35% of the energy usage is attributed to Power and Heat management, 11% to the control-plane, and the remaining 54% to theyes';font-family:'Arial Unicode MS';mso-fareast-font-family:MicrosoftYaHei;
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II2202, Fall 2018, Period 1-2 Draft project report November 14, 2023
4 Research Methodology
The research methodology is based on creating a traditional communication network in a virtual manner using AWS (Amazon Web Services) software. The traditional network will undergo testing, with packet delivery rates varied to simulate peak-hour traffic as well as low-traffic scenarios. Subsequently, packet routing changes will be implemented in an attempt to enhance the energy efficiency of the network, such as routing packets through specific links and placing other links in a ’sleep’ state. The same tests will be conducted with these changes.
This data will be compared with that of a virtual communication network designed efficiently from the outset, which will also undergo identical testing procedures. In the efficient design, minor protocol adjustments will be made to ensure that resources, such as buffers and processors, remain in a ’sleep’ state whenever they are not required.
5 Participants, Procedures, Data Collection, and Analysis 5.1 Participants
Names: Jiarui Liang and Maialen Loinaz
Qualifications: Both participants are master’s students specializing in cloud and network engineering, with a solid foundation in various network architectures and protocols.
5.2 Procedures
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Virtual Network Establishment: Set up a basic test virtual network environment using EC2 instances on the AWS platform. Configure basic network settings including subnets, routing tables, and security groups.
Energy Efficiency Improvements: Design and implement routing strategies to reduce energy consumption, such as using fewer hops or low-power modes. Utilize AWS Elastic Load Balancing (ELB) and Auto Scaling to optimize resource usage.
Traffic Testing under Different Conditions: Use AWS traffic generation tools or custom scripts to simulate peak and off-peak traffic. Record network performance and energy consumption data under various traffic conditions.
Iterative Improvement Scheme: Adjust network configurations and routing strategies based on preliminary test results. Repeat testing until the most energy-efficient solution is found.
Data Collection
Data Types: Capture network traffic data packets using Wireshark. Monitor and record energy
consumption and performance metrics using AWS CloudWatch.
Collection Tools: Configure Wireshark to capture data on specific network interfaces. Set up CloudWatch alarms and dashboards to monitor key metrics in real-time.
Data Recording: Ensure all data is timestamped and properly labeled for subsequent analysis. Data Analysis
Energy Saving Percentage: Calculate and compare the percentage of energy savings using the collected energy consumption data. Analyze the impact of different routing strategies and network configurations on energy consumption.
II2202, Fall 2018, Period 1-2 Draft project report November 14, 2023
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Cost Analysis: Analyze the cost-effectiveness of different strategies, including AWS costs and potential operational costs.
Analytical Model Construction: Build models based on experimental data to demonstrate the advantages of green computing technologies. Use statistical software such as R or Python’s Pandas library for data analysis.
Predictive Analysis: Apply probability and statistical methods to predict network performance under large data flow conditions. Machine learning algorithms may be used to handle and predict large-scale datasets.
Expected outcomes
We expect the results to clearly demonstrate the percentage of energy savings in both scenarios. We will also take into consideration the costs associated with changes to a traditional network and a new implementation from scratch. While one of the two may be more energy-efficient, it’s possible that it could be financially more costly, and this is a factor that companies take into account, and thus, we do too.
Milestones/schedule, budget
Project Proposal Writing (October 1 - October 8)
• Determine research topic and objectives.
• Complete the initial draft of the project proposal.
Research Plan Development (October 9 - October 15)
• Revise project proposal based on feedback.
• Finalize the detailed framework of the research plan.
Virtual Network Establishment and Preliminary Testing (October 16 - November 2)
• Establish a basic virtual network on AWS.
• Conduct preliminary network performance tests.
Quantitative Testing and Data Collection (November 3 - November 26)
• Energy-Efficient Routing Strategy Implementation Preparation (November 3 - November 5):
– Confirm the initial state of the test network.
– Complete the design and planning of the energy-efficient routing strategy. – Prepare testing scripts and automation tools.
• Preliminary Energy Efficiency Testing (November 6 - November 10):
– Implement preliminary energy-efficient routing strategies on the virtual network.
– Conduct small-scale tests to verify the effectiveness of the strategy. 5
II2202, Fall 2018, Period 1-2 Draft project report November 14, 2023
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– Collect preliminary test data and perform a quick analysis to determine if strategy adjustments are needed.
Comprehensive Energy-Efficient Routing Strategy Implementation (November 11 - November 15):
– Adjust routing strategies based on preliminary test results.
– Implement a comprehensive energy-efficient routing strategy across the entire virtual network.
– Ensure all monitoring tools and data collection systems are functioning correctly.
High Load Testing (November 16 - November 20):
– Simulate high-traffic conditions to test network performance and energy efficiency under high
load.
– Collect data from high load testing.
Low Load Testing (November 21 - November 23):
– Simulate low-traffic conditions to test network performance and energy efficiency under low
load.
– Collect data from low load testing.
Data Organization and Preliminary Analysis (November 24 - November 26):
– Organize and preprocess the collected data.
– Perform a preliminary analysis to identify any apparent trends or issues.
– Prepare a draft of the data analysis report.
First-Draft and Presentation Preparation (November 27 - December 10)
Write the first draft of the research based on the collected data. Prepare presentation materials for the project.
Opposition Report Writing (December 11 - December 17)
Complete the opposition report, preparing to review other projects.
Final Research Report and Seminar Preparation (December 18 - January 7)
Revise the research report based on feedback.
Prepare the presentation and materials for the final seminar.
Final Seminar (January 8)
Present the research findings. Submit the final research report.
II2202, Fall 2018, Period 1-2 Draft project report November 14, 2023
8 Risks
The project involves researching and testing communication network efficiency and energy consumption, but it faces several potential risks. Technical challenges, including software glitches and resource constraints, may disrupt research efforts, while data security concerns must be carefully managed. Ensuring the accuracy of results, considering financial costs, and meeting project timelines are crucial. Regulatory compliance, ethical considerations, and resource availability also pose challenges, along with uncertainties regarding market acceptance and unforeseen environmental factors. Protecting intellectual property rights is essential in case the project yields innovative solutions. To mitigate these risks, a well-defined project plan, thorough risk assessments, and clear communication among stakeholders are necessary, as are contingency plans for potential setbacks.
II2202, Fall 2018, Period 1-2 Draft project report November 14, 2023
9 Outline References
[1] Anand Kannan, Gerald Q. Maguire Jr., Ayush Sharma, Volker Fusenig, and Peter Schoo. N-ary tree based key distribution in a network as a service provisioning model. In ICACCI ’12 Proceedings of the International Conference on Advances in Computing, Communications and Informatics, page 952. ACM Press, 2012.
[2] Brent S. Baxter, Lewis E. Hitchner, and Gerald Q. Maguire Jr. A standard format for digital image exchange. Published for the American Association of Physicists in Medicine by the American Institute of Physics, New York N.Y., 1982.
[3] S. Deering and R. Hinden. Internet protocol, version 6 (IPv6) specification. Internet Request for Comments, RFC 2460 (Draft Standard), December 1998. Updated by RFCs 5095, 5722, 5871.
[4] John Ioannidis and Gerald Q. Maguire Jr. Coherent file distribution protocol. Internet Request for Comments, RFC 1235 (Experimental), June 1991.
[5] Shitan Long. Database synchronization between devices: A new synchronization protocol for sqlite databases. Master’s thesis, KTH Royal Institute of Technology, School of Information and Communication (ICT), Stockholm, May 2011. TRITA-ICT-EX-2011:88.
[6] J. Postel. Internet protocol. Internet Request for Comments, RFC 791 (Standard), September 1981. Updated by RFC 1349.
10 Appendix/Appendices
