Uma abordagem sensível à latência e ao custo de comunicação para alocação de aplicações modulares em uma névoa hierárquica

Abstract

Over the years, cloud computing has provided infrastructure for processing applications and services. However, the distance between Cloud computing resources and Internet of Things (IoT) devices can cause delays in response times for some services and applications that have time-sensitive constraints. In this context, fog computing emerges as a computational paradigm that seeks to bring cloud computing resources closer to IoT devices, geographically distributing micro-data centers (Cloudlets) and reducing response time. Studies using fog computing present solutions for the application allocation, addressing that it is possible to meet different types of requirements. These studies evaluate certain requirements for decision making, such as response time and communication cost. However, it is observed that as a requirement is prioritized, another is neglected. Thus, this work proposes an approach for allocating modular applications in a fog computing architecture with multiple hierarchical levels, which seeks to reduce the response time of latency-sensitive applications and reduce data traffic on the network. To achieve this goal, the proposed approach, Least Impact - X (LI-X), seeks to reduce the idleness of resources at the lowest levels of the fog and takes into account the communication between application modules when deciding on the allocation. LI-X was compared to predecessor studies in a simulated iFogSim environment. The results show that the LI-X was able to overcome these studies in most of the proposed scenarios, reducing the response time and the cost of data communication on the network.