Resource Management for Cooperative Service Offering with a Generalized Service-Centric Model

The development of the Internet of Things (IoT) witnesses a growing number of intelligent services. Nevertheless, the IoT devices can suffer from limited energy supply and computing ability. Reminiscent of the concept of multi-access edge computing and ubiquitous computing, IoT devices can share the...

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Bibliographic Details
Published in2022 IEEE/CIC International Conference on Communications in China (ICCC) pp. 944 - 949
Main Authors Wu, Xuan, Huang, Yang, Gao, Zhen
Format Conference Proceeding
LanguageEnglish
Published IEEE 11.08.2022
Subjects
Complexity theory
Computational modeling
device scheduling
Energy consumption
Generalized service-centric optimization model
Internet of Things
iterative algorithm
MINLP problem
resource allocation
Resource management
Simulation
Ubiquitous computing
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DOI10.1109/ICCC55456.2022.9880825

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Summary:The development of the Internet of Things (IoT) witnesses a growing number of intelligent services. Nevertheless, the IoT devices can suffer from limited energy supply and computing ability. Reminiscent of the concept of multi-access edge computing and ubiquitous computing, IoT devices can share the network resources and cooperate to offer intelligent services. Nevertheless, state-of-the-art models for resource optimization cannot fully characterize the requirement of services. Therefore, we propose a novel generalized service-centric model for resource allocation optimization in the presence of cooperative service offering. Based on the model, a joint network resource allocation and device scheduling optimization is investigated. This problem is shown to be a mixed integer non-linear programming (MINLP) problem. To solve the problem, alternating optimization is integrated with the Hungarian method, where the device scheduling optimization suffers from the cubic complexity. Simulation results illustrate that the proposed service-centric optimization model can significantly reduce the overall energy consumption, as well as the slope of average energy consumption in the presence of an increasing number of tasks.
DOI:10.1109/ICCC55456.2022.9880825