6 research outputs found

    An efficient reconfigurable workload balancing scheme for fog computing network using internet of things devices

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    Nowadays a huge amount of data has been communicated using fog nodes spread throughout smarty cities. the communication process is performed using fog nodes which are co-located with cellular base stations (BSs) that can move the computing resources close to internet of things (IoT) devices. In smart cities, a different type of data flow has been communicated through IoT devices. The communication process performs efficiently using the remote cloud. The IoT devices very close to the BS can communicate data without using fog nodes. Due to these phenomena, workload unbalancing occurs in IoT devices communicating in fog computing networks. Hence, it generates communication and computing latency. The task distribution process between the IoT devices is unbalanced. Hence, congestion and loss of information occur in fog computing network. A proposed reconfigurable load balancing algorithm (RLBA) is efficiently balancing the workload by reconfigurable communication channels and deviates the task with respect to the BS locations, IoT devices density and load IoT devices in each fog nodes in a network to minimize the communication and computing latency. As per the performance analysis, the proposed algorithm shows better performance as compared to conventional methods’ average latency ratio, communication latency ratio, computing load and traffic load