IoT devices call for optimum resource management solutions regarding edge
computing reliability and performance. This chapter presents an intelligent and fuzzybased adaptive resource management solution for IoT devices in the context of edge
computing. In this specific method, fuzzy support is applied to enable a resource
dynamic allocation according to the devices' IoT needs and requirements. This is
because the resource allocation process is intelligent and adaptive; hence, the system
can modify its past resource allocation decisions to provide better functions. The
proposed approach also acknowledges exploiting the particularities of the edge
computing environment. It entails factors like the availability of the resources at the
edge and the associated limitations, for example, in terms of power consumption and
the processors' capacity. To consider the feasibility of the proposed approach, extensive
simulations and experiments were conducted, and the performance of resource
management by utilizing the proposed approach is compared with those of existing
approaches. From the results obtained, the proposed method is superior to the current
methods concerning resource usage, energy consumption, and system performance. In
general, the presented intelligent and fuzzy-based adaptive resource management
strategy presents great potential in increasing the efficiency and effectiveness of
resource management of IoT devices in the context of edge computing, which would
help establish more effective IoT systems shortly.
Keywords: Edge computing, Energy efficiency, Fuzzy logic, Internet of things, IoT devices, Resource management.
