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Evidence of power-law behavior in cognitive IoT applications., , , , , , , , and . Neural Comput. Appl., 32 (20): 16043-16055 (2020)An Adaptive Modeling and Performance Evaluation Framework for Edge-Enabled Green IoT Systems., , , and . IEEE Trans. Green Commun. Netw., 6 (2): 836-844 (2022)A Non-stationary Analysis of Erlang Loss Model., , , and . ICACIE (1), volume 1198 of Advances in Intelligent Systems and Computing, page 286-294. Springer, (2019)Generation of cubic power-law for high frequency intra-day returns: Maximum Tsallis entropy framework., and . Digit. Signal Process., (2016)An adaptive q-Lognormal model towards the computation of average channel capacity in slow fading channels., and . Telecommun. Syst., 79 (3): 341-355 (2022)A Robust Energy Optimization and Data Reduction Scheme for IoT Based Indoor Environments Using Local Processing Framework., , , and . J. Netw. Syst. Manag., 29 (1): 6 (2021)Adaptive Applications of Maximum Entropy Principle., , , and . ICACIE (1), volume 1198 of Advances in Intelligent Systems and Computing, page 373-379. Springer, (2019)Adaptive Performance Modeling Framework for QoS-Aware Offloading in MEC-Based IIoT Systems., , , and . IEEE Internet Things J., 9 (12): 10162-10171 (2022)Performance Evaluation of Wireless Communication Systems over Weibull/q-Lognormal Shadowed Fading Using Tsallis' Entropy Framework., , and . Wireless Personal Communications, 106 (2): 789-803 (2019)Performance Evaluation of Composite Fading Channels Using q-Weibull Distribution., , and . ICACIE (1), volume 1198 of Advances in Intelligent Systems and Computing, page 317-324. Springer, (2019)