Task Offloading Algorithms for Novel Load Balancing in Homogeneous Fog Network

Fog computing has become an emerging distributed computing paradigm to provide services with low latency and high throughput. However, load unbalance is serious due to the difference in geography, which results in performance deterioration and low utilization of resources in the fog network. In this paper, the load is the tradeoff between the delay and energy consumption for fog nodes. Meanwhile, the problem of minimizing the maximum load in the homogeneous fog network is formulated and its NP-hardness is proved. Then, a greedy algorithm is proposed for solving the problem by giving the preference to offloading the task in the fog node with the maximum load to the fog node with the minimum load in the network. Moreover, for solving the problem with consideration of selfishness of fog nodes, a coalition based algorithm is proposed to encourage the fog nodes with a light load to share their resources to reduce the maximum load. We evaluate the performance of the proposed algorithms on NS-3 and simulation results show that the proposed algorithms outperform the existing algorithm about 40% in terms of the maximum load.