Resource Allocation for Ultra-Reliable and Enhanced Mobile Broadband IoT Applications in Fog Network

• Published in: IEEE transactions on communications 2019-01, Vol.67 (1), p.489-502
• Main Authors: Abedin, Sarder Fakhrul, Alam, Md. Golam Rabiul, Kazmi, S. M. Ahsan, Tran, Nguyen H., Niyato, Dusit, Hong, Choong Seon
• Format: Article
• Language: English
• Subjects: Analytic hierarchy process; Bandwidths; Bit error rate; Broadband; Broadband communication; Cloud computing; Computer simulation; enhanced mobile broadband (eMBB); Fog; Fog computing; Games; Infrastructure; Internet of Things; Internet of Things (IoT); Matching; Mobile communication systems; Mobile computing; Quality of service; Quality of service architectures; Resource allocation; Resource management; Resource scheduling; Stability analysis; ultra-reliable low latency communications (URLLC)
• ISSN: 0090-6778; 1558-0857
• DOI: 10.1109/TCOMM.2018.2870888

In recent years, in order to provide a better quality of service (QoS) to Internet of Things (IoT) devices, the cloud computing paradigm has shifted toward the edge. However, the resource capacity (e.g., bandwidth) in fog network technology is limited and it is essential to efficiently bind the IoT applications with stringent QoS requirements with the available network infrastructure. In this paper, we formulate a joint user association and resource allocation problem in the downlink of the fog network, considering the evergrowing demand of QoS requirements imposed by the ultra-reliable low latency communications and enhanced mobile broadband services. First, we determine the priority of different QoS requirements of heterogeneous IoT applications at the fog network by enforcing the analytical framework using an analytic hierarchy process (AHP). Using the AHP, we then formulate a two-sided matching game to initiate stable association between the fog network infrastructure (i.e., fog devices) and IoT devices. Subsequently, we consider the externalities in the matching game that occurs due to job delay and solve the network resource allocation problem by applying the "best-fit" resource allocation strategy during matching. The simulation results illustrate the stability of the user association and efficiency of resource allocation with higher utility gain.