Utility‐Aware Network Slicing for Optimal Cell Planning in Emergency Scenarios

Content‐based network slicing is a key technology to enable the transition from the network as infrastructure to network‐as‐services and offer services to business verticals. Its efficient use of limited network resources makes it a promising future wireless technique. This article presents a novel network slicing–based model for optimal cell planning while maximizing the content‐based fairness utility. The users are divided in two categories: (i) emergency users (EUs) and (ii) normal users (NUs). Here, emergency services are limited to text and voice to prevent congestion, whereas NUs have access to all services (text, voice, and video). Both user types are considered across two emergency scenarios: zone‐specific and random. Random EUs are those needing medical, safety, or security assistance, whereas zone‐specific EUs are users within a disaster‐affected area. Simulations are performed to observe the trade‐off between the NU and EU association with the optimal BS while satisfying the demanded rate of service. The effectiveness of the proposed hybrid Dragonfly Algorithm with Differential Evolution (DADE) and Buyer Inspired Meta‐heuristic Algorithm (BIMA) with Fuzzy C‐means algorithm is demonstrated using simulation results. Comparative simulations show that the proposed DADE‐based algorithm significantly outperforms other state‐of‐the‐art algorithms in maximizing network utility.