Fog computing is a paradigm that brings computational resources and services to the network edge in the vicinity of user devices, lowering latency and connecting with cloud computing resources. Unlike cloud computing, fog resources are based on constrained and heterogeneous nodes whose connectivity can be unstable. In this complex scenario, there is a need to define and implement orchestration processes to ensure that applications and services can be provided, considering the settled agreements. Although some publications have dealt with orchestration in fog computing, there are still some diverse definitions and functional intersection with other areas, such as resource management and monitoring. This article presents a systematic review of the literature with focus on orchestration in fog computing. A generic architecture of fog orchestration is presented, created from the consolidation of the analyzed proposals, bringing to light the essential functionalities addressed in the literature. This work also highlights the main challenges and open research questions.

Fog computing is a paradigm that allows the provisioning of computational resources and services at the edge of the network, closer to the end devices and users, complementing cloud computing. The heterogeneity and large number of devices are challenges to obtaining optimized resource allocation in this environment. Over time, some surveys have been presented on resource management in fog computing. However, they now lack a broader and deeper view about this subject, considering the recent publications. This article presents a systematic literature review with a focus on resource allocation for fog computing, and in a more comprehensive way than the existing works. The survey is based on 108 selected publications from 2012 to 2022. The analysis has exposed their main techniques, metrics used, evaluation tools, virtualization methods, architecture, and domains where the proposed solutions were applied. The results show an updated and comprehensive view about resource allocation in fog computing. The main challenges and open research questions are discussed, and a new fog computing resource management cycle is proposed.

Cloud computing is a new platform that offers potential cost reduction and reduced infrastructure management effort. Organizations are migrating legacy systems to the cloud to take advantage of its benefits. In this work, the authors propose a risk perception indicator (RPI) to bring objectivity to the decision about which systems could be migrated and about their migration order. The main goal of this article is to validate the RPI in the government domain. Through a case study with three government legacy systems and an experimental analysis based on a survey with 248 IT government employees, the RPI was evaluated and adjusted. The adjustments were made based on survey's results and appear to improve its accuracy and representativeness. The results showed that the use of the reference model and the risk perception indicator is sound and important regarding government legacy systems migration to the cloud. Request access from your librarian to read this article's full text.