Collaboration Strategies for Fog Computing under Heterogeneous Network-bound Scenarios

The success of IoT applications increases the number of online devices and motivates the adoption of a fog computing paradigm to support large and widely distributed infrastructures. However, the heterogeneity of nodes and their connections requires the introduction of load balancing strategies to guarantee efficient operations. This aspect is particularly critical when some nodes are characterized by high communication delays. Some proposals such as the Sequential Forwarding algorithm have been presented in literature to provide load balancing in fog computing systems. However, such algorithms have not been studied for a wide range of working parameters in an heterogeneous infrastructure; furthermore, these algorithms are not designed to take advantage from highly heterogeneous network delays that are common in fog infrastructures. The contribution of this study is twofold: First, we evaluate the performance of the sequential forwarding algorithm for several load and delay conditions; second, we propose and test a delay-aware version of the algorithm that takes into account the presence of highly variable node connectivity in the infrastructure. The results of our experiments, carried out using a realistic network topology, demonstrate that a delay-blind approach to sequential forwarding may determine poor performance in the load balancing when network delay represents a major contribution to the response time. Furthermore, we show that the delay-aware variant of the algorithm may provide a benefit in this case, with a reduction in the response time up to 6%.