Joint Computing, Communication, and Interface Resource Allocation for Heterogeneous Edge Systems
DOI:
https://doi.org/10.66238/smsrj.v4i2.65Keywords:
Edge Computing, Resource Allocation, Optimization Theory, Heterogeneous NetworksAbstract
The proliferation of ubiquitous internet of things devices and computationally intensive applications has fundamentally transformed the landscape of modern wireless networks. Heterogeneous edge computing has emerged as a promising paradigm to alleviate the burden on centralized cloud infrastructures by migrating computational resources to the network periphery. However, the extreme heterogeneity in device capabilities, varying communication channels, and diverse network interfaces poses significant challenges for efficient resource orchestration. This paper presents a comprehensive investigation into the joint allocation of computing, communication, and interface resources in heterogeneous edge systems. We formulate a multi-objective optimization problem aimed at minimizing the system wide computational delay and energy consumption while accommodating the strict constraints of multidimensional resource capacities. Given the highly non-convex nature of the formulated problem, we propose an iterative optimization framework grounded in block coordinate descent and successive convex approximation techniques. By decoupling the original complex problem into tractable subproblems, the proposed algorithmic methodology achieves near optimal performance with manageable computational complexity. Extensive theoretical analyses and simulated experiments demonstrate that the proposed joint allocation strategy significantly outperforms conventional isolated resource management schemes, providing a robust, scalable, and highly efficient solution for next generation edge computing environments.
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Copyright (c) 2026 Brandon C. Khan, Zoe K. Hernandez, Joshua Roberts
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