Improved Dynamic Spectrum and Traffic Management Model Based on Demand Response and Heterogeneous Incentives with Perfect Substitute Utility Function
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Keywords:
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C-RAN, Selfish User, Demand Response, Heterogeneous Incentives, Sensitivity Analysis
Abstract
The purpose of this research is to design and optimize a demand response based-selfish user Cloud Radio Access Network (C-RAN) model to demonstrate with a narrow-minded client utilizing three financing plans specifically level charge, usage-based, and two-part tariff. The Traffic data is classified into incoming data and outgoing data, obtained from a local server in Palembang. The optimal solution is obtained by determining the decision variables and parameters used in each case for all models, compiling improved C-RAN models as many as 2 models, namely model I, and model II, and then determining the optimal solution and sensitivity analysis using LINGO 13.0 software. The most optimal solution is obtained from model II with a flat-fee scheme in case 1 of IDR 3299.7/kbps with 45 iterations. The results of the sensitivity analysis is on the variables ak,m that allows the increase and decrease in the objective function coefficient. At the same time, the value 0 will be constant.
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Zheng, N. and N. Geroliminis (2020). Area-Based Equitable Pricing Strategies for Multimodal Urban Networks with Heterogeneous Users. Transportation Research Part A: Policy and Practice, 136; 357–374.
Ashe, M. L. and S. J. Wilson (2020). A Brief Review of Choice Bundling: A Strategy to Reduce Delay Discounting and Bolster Self-Control. Addictive Behaviors Reports, 11; 100262.
Bolurian, A., H. Akbari, S. Mousavi, and M. Aslinezhad (2023). Bi-Level Energy Management Model for the Smart Grid Considering Customer Behavior in the Wireless Sensor Network Platform. Sustainable Cities and Society, 88; 104281.
Bonjean, I. (2019). Heterogeneous Incentives for Innovation Adoption: The Price Effect on Segmented Markets. Food Policy, 87; 101741.
Dai, H., Y. Huang, J. Wang, and L. Yang (2018). Resource Optimization in Heterogeneous Cloud Radio Access Networks. IEEE Communications Letters, 22(3); 494–497.
Derbel, M., W. Hachicha, and A. M. Aljuaid (2021). Sensitivity Analysis of the Optimal Inventory-Pooling Strategies According to Multivariate Demand Dependence. Symmetry, 13(2); 1–24.
Ely, J., A. Galeotti, O. Jann, and J. Steiner (2021). Optimal Test Allocation. Journal of Economic Theory, 193; 105236.
Fagbohun, O. O. (2014). Comparative Studies on 3G, 4G and 5G Wireless Technology. IOSR Journal of Electronics and Communication Engineering (IOSR-JECE), 9(3); 88–94.
Gaudin, S., R. C. Griffin, and R. C. Sickles (2001). Demand Specification for Municipal Water Management: Evaluation of the Stone-Geary Form. Land Economics, 77(3); 399–422.
Gizelis, C. A. and D. D. Vergados (2011). A Survey of Pricing Schemes in Wireless Networks. IEEE Communications Surveys & Tutorials, 13(1); 126–145.
Hemmati, M., S. M. T. Fatemi Ghomi, and M. S. Sajadieh (2023). Separate and Bundling Selling Strategies for Complementary Products in a Participative Pricing Mechanism. Computers and Industrial Engineering, 177; 109018.
Hussein, N. A. A., K. Abdulrahim, F. M. Puspita, K. Seman, and M. Sahrim (2023). Improved Incentive Pricing Model of Wireless Pricing Scheme with End-to-End Delay Attribute. In AIP Conference Proceedings, volume 2913.
Indrawati, F. M. Puspita, R. Resmadona, E. Yuliza, O. Dwipurwani, and S. Octarina (2021). Analysis of Information Service Pricing Scheme Model Based on Customer Self-Selection. Science and Technology Indonesia, 6(4); 157–163.
Indrawati, I., F. M. Puspita, B. O. M. Silaen, E. Yuliza, and O. Dwipurwani (2020). Selfish User Network Optimization with Cellular Network Traffic Management Model Using Lingo 13.0. Science and Technology Indonesia, 5(2); 53–58.
Jiang, M. and T. Mahmoodi (2016). Traffic Management in 5G Mobile Networks: Selfish Users and Fair Network. Transactions on Networks and Communications, 4(1); 1–9.
Lasemi, M. A., S. Alizadeh, M. Assili, Z. Yang, P. T. Baboli, A. Arabkoohsar, A. Raeiszadeh, M. Brand, and S. Lehnhoff (2023). Energy Cost Optimization of Globally Distributed Internet Data Centers by Copula-Based Multidimensional Correlation Modeling. Energy Reports, 9; 631–644.
Mondal, C. and B. C. Giri (2024). Pricing and Bundling Strategies for Complementary Products in a Closed-Loop Green Supply Chain Under Manufacturers’ Different Behaviors. Expert Systems with Applications, 238; 121960.
Nidhi, A. Mihovska, and R. Prasad (2021). Spectrum Sharing and Dynamic Spectrum Management Techniques in 5G and Beyond Networks: A Survey. Journal of Mobile Multimedia, 17(1–3); 65–78.
Puspita, F. M., E. Yuliza, W. Herlina, Y. Yunita, and R. Rohania (2020). Improved Multi Service-Reverse Charging Models for the Multi Link Internet Wireless Using QoS Bit Error Rate QoS Attribute. Science and Technology Indonesia, 5(1); 6–13.
Rodoshi, R. T., T. Kim, and W. Choi (2020). Resource Management in Cloud Radio Access Network: Conventional and New Approaches. Sensors (Switzerland), 20(9); 1–32.
Samunderu, E. and M. Farrugia (2022). Predicting Customer Purpose of Travel in a Low-Cost Travel Environment – A Machine Learning Approach. Machine Learning with Applications, 9; 100379.
Wang, Y., Z. Yang, J. Yu, and J. Liu (2023). An Optimization-Based Partial Marginal Pricing Method to Reduce Excessive Consumer Payment in Electricity Markets. Applied Energy, 352; 121935.
Xu, H., X. Qiu, W. Zhang, K. Liu, S. Liu, and W. Chen (2021). Privacy-Preserving Incentive Mechanism for Multi-Leader Multi-Follower IoT-Edge Computing Market: A Reinforcement Learning Approach. Journal of Systems Architecture, 114; 101932.
Zhang, G., Y. Niu, T. Xie, and K. Zhang (2023). Multi-Level Distributed Demand Response Study for a Multi-Park Integrated Energy System. Energy Reports, 9; 2676–2689.
Zheng, N. and N. Geroliminis (2020). Area-Based Equitable Pricing Strategies for Multimodal Urban Networks with Heterogeneous Users. Transportation Research Part A: Policy and Practice, 136; 357–374.
Authors
Puspita, F. M., Octarina, S., Yunita, Ramadhany, A. P., & Yuliza, E. (2025). Improved Dynamic Spectrum and Traffic Management Model Based on Demand Response and Heterogeneous Incentives with Perfect Substitute Utility Function. Science and Technology Indonesia, 10(3), 766–776. https://doi.org/10.26554/sti.2025.10.3.766-776
This work is licensed under a Creative Commons Attribution 4.0 International License.