The rapid proliferation of the Internet of Things (IoT), coupled with the accelerated deployment of Fifth-Generation (5G) networks and the emergence of Sixth-Generation (6G) communication standards, is placing unprecedented demands on electrical telecommunication infrastructure. Conventional cloud-centric architectures, which rely on distant centralized data centers, are increasingly unable to satisfy the stringent latency, bandwidth, and energy requirements of modern real-time applications. Edge computing has been proposed as a complementary paradigm that relocates computation closer to end devices, thereby reducing propagation distance and improving responsiveness. This study designs, simulates, and evaluates three computing architectures; pure cloud, pure edge, and a hybrid edge-cloud configuration for next-generation electrical telecommunication networks. A co-simulation framework was developed using MATLAB R2024a for network modelling and performance visualization, and Python 3.12 for task scheduling, resource allocation, and statistical analysis. The architectures were assessed under identical traffic conditions using latency, throughput, Packet Delivery Ratio (PDR), energy consumption, CPU utilization, bandwidth utilization, task completion time, and reliability as key performance indicators. Results show that the edge architecture achieved the lowest average latency (18.34 ms), the highest throughput (31.47 Mbps), the lowest energy consumption (1.24 J), and the fastest task completion time (22.1 ms). The cloud architecture recorded the highest latency (60.85 ms) and energy consumption (2.28 J) but retained an advantage for computationally intensive workloads. The hybrid architecture achieved the best overall balance, attaining a 99.63% PDR and 99.27% reliability while sustaining favorable throughput and energy performance. These findings indicate that hybrid edge-cloud architectures offer the most balanced and scalable solution for future electrical telecommunication networks.