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Last Updated: Apr 25, 2025 | Study Period: 2023-2030
The study of Data center traffic generators is gaining more traction as the efficiency and scalability of cloud computing are demonstrated. Hyper Clouds are presently made to hold 10,000â100,000 hosts because the economic efficiency of cloud computers increases with their scale. Since it is too expensive to construct an experimental data center traffic generator of a reasonable size, this high scale presents a challenge to data center traffic generator researchers.
As a result, the availability of formally defined traffic patterns that characterize Hyperscale data center traffic generators is extremely important to the research community. Over the years, a number of studies detailing specific-cloud traffic were produced, but no formal model was ever published or adopted as the industry standard.
The Global data center traffic generator market accounted for $XX Billion in 2022 and is anticipated to reach $XX Billion by 2030, registering a CAGR of XX% from 2023 to 2030.
As they depend on the addressing scheme, which is meant to be simulation model-specific, the OMNeT++ simulations model should define a subclass of the data center traffic generator class and must offer at least these two virtual functions:
The capability of producing a new message: createMsg(string dstAddr, unsigned int msgPackets, unsigned int pktSize_B);the virtual string get Addr(), which records the local address of a particular traffic generator;The emit_dstAddr method can optionally be defined to fill the vector of destinations.
Additionally, understanding how addresses are coded, which depends on the model, is necessary. Since strings cannot be tracked by the vector, a conversion to an int or double is needed.GITHUB abbreviates that subclass as TG. The simulation model should then launch a selection .
Data center traffic generator repository:You need to have installed omnet++ >= 4.6 and have its bin directory in your PATH Run make makefiles; make; make MODE=release in the root directory.The resulting library ought to be accessible in the out/gcc-release or out/gcc-debug src directories.
Sl no | Topic |
1 | Market Segmentation |
2 | Scope of the report |
3 | Abbreviations |
4 | Research Methodology |
5 | Executive Summary |
6 | Introduction |
7 | Insights from Industry stakeholders |
8 | Cost breakdown of Product by sub-components and average profit margin |
9 | Disruptive innovation in the Industry |
10 | Technology trends in the Industry |
11 | Consumer trends in the industry |
12 | Recent Production Milestones |
13 | Component Manufacturing in US, EU and China |
14 | COVID-19 impact on overall market |
15 | COVID-19 impact on Production of components |
16 | COVID-19 impact on Point of sale |
17 | Market Segmentation, Dynamics and Forecast by Geography, 2023-2030 |
18 | Market Segmentation, Dynamics and Forecast by Product Type, 2023-2030 |
19 | Market Segmentation, Dynamics and Forecast by Application, 2023-2030 |
20 | Market Segmentation, Dynamics and Forecast by End use, 2023-2030 |
21 | Product installation rate by OEM, 2023 |
22 | Incline/Decline in Average B-2-B selling price in past 5 years |
23 | Competition from substitute products |
24 | Gross margin and average profitability of suppliers |
25 | New product development in past 12 months |
26 | M&A in past 12 months |
27 | Growth strategy of leading players |
28 | Market share of vendors, 2023 |
29 | Company Profiles |
30 | Unmet needs and opportunity for new suppliers |
31 | Conclusion |
32 | Appendix |