The introduction of the 5G network Telecommunications have been changed Telecommunications completely, which has made a variety of services and applications such as enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (uRLLC), and massive machine-type communications (mMTC). These services necessitate a strict level of service quality (QoS), including high bandwidth, little delay, and high reliability, which is difficult for old network infrastructures. The mixture of network slicing and edge computing is an appropriate answer since it allows the formation of different logical networks based on one physical infrastructure. Nevertheless, successfully managing network slices in edge systems is a challenging process due to high operational costs related to slice reconfigurations, sophisticated structures of multi-hop routing, and the balancing of different resource constraints. This article defines a unique system for slicing edge networks that has a fuzzy logic-based ranking mechanism integrated with the request selection step. This mechanism adjusts the priority of slice requests by measuring resource utilization, potential benefits, penalties for reallocating, and deadline limitations. The proposed approach operates through two distinct phases: (1) Best Slice Selection Phase, which employs fuzzy logic to rank and prioritize incoming slice requests, and (2) Edge Cloud (EC) Selection Phase, which assigns prioritized requests to optimal ECs based on available computational and storage resources. The very comprehensive simulations exhibited the done work not just had a higher total revenue than the existing methods but also were the ones that reconfigured the slices less often without any problems in the stringent QoS metrics.