Dzaky Zakiyal Fawwaz  Sang-Hwa Chung

10.5626/JOK.2020.47.5.535

dynamic task allocation Fog Computing Internet of Things Software-Defined Network Shortest Path

The Internet of Things requires that resources are allocated for it to execute tasks. Utilizing fog computing may have many benefits in these circumstances since it offers distributed resources that could give lower latency, lower bandwidth, and various other advantages compared to cloud computing. If we wish to use fog computing, we need to consider how to perform task allocation over multiple fog nodes. The kind of networks used are likely to have not only continuous incoming IoT tasks but also other dynamic network conditions. Hence, we introduce dynamic task allocation that utilizes a Software-Defined Network. Our system handles each incoming task by considering network and fog node statistics. The task allocation method must select the optimal pair of fog nodes and also the path because there are multiple fog nodes and many feasible related paths to deal with. Thus, we define the problem to be one of finding the multi-source, single-target, shortest path on a network graph, to help solve the problem we formulate the joint fog node-link utilization cost. We also propose a Many-to-One Shortest Path algorithm to solve such a problem. The experiments we performed to evaluate our system show that it outperforms the previous state-of-the-art work. Averaging over all the experiment"s topologies, our method achieves higher tasks per second completion rate, a lower response time and lower fog node/link utilization with scores of 37 tasks/sec, 676ms and 65%/24% utilization, respectively.