Abstract:Fog computing has emerged as a promising technology that can bring cloud applications closer to the physical IoT devices at the network edge. While it is widely known what cloud computing is, how data centers can build the cloud infrastructure and how applications can make use of this infrastructure, there is no common picture on what fog computing and particularly a fog node, as its main building block, really is. One of the first attempts to define a fog node was made by Cisco, qualifying a fog computing system as a "mini-cloud" located at the edge of the network and implemented through a variety of edge devices, interconnected by a variety, mostly wireless, communication technologies. Thus, a fog node would be the infrastructure implementing the said mini-cloud. Other proposals have their own definition of what a fog node is, usually in relation to a specific edge device, a specific use case or an application. In this paper, we first survey the state of the art in technologies for fog computing nodes, paying special attention to the contributions that analyze the role edge devices play in the fog node definition. We summarize and compare the concepts, lessons learned from their implementation, and end up showing how a conceptual framework is emerging towards a unifying fog node definition. We focus on core functionalities of a fog node as well as in the accompanying opportunities and challenges towards their practical realization in the near future.

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Objective:To describe the prevalence of diagnosed depression, anxiety, bipolar disorder, and schizophrenia in people with HIV (PWH) and the differences in HIV care continuum outcomes in those with and without mental health disorders (MHDs).Design:Observational study of participants in the North American AIDS Cohort Collaboration on Research and Design.Methods:PWH (≥18 years) contributed data on prevalent schizophrenia, anxiety, depressive, and bipolar disorders from 2008 to 2018 based on International Classification of Diseases code mapping. Mental health (MH) multimorbidity was defined as having two or more MHD. Log binomial models with generalized estimating equations estimated adjusted prevalence ratios (aPR) and 95% confidence intervals for retention in care (≥1 visit/year) and viral suppression (HIV RNA ≤200 copies/ml) by presence vs. absence of each MHD between 2016 and 2018.Results:Among 122 896 PWH, 67 643 (55.1%) were diagnosed with one or more MHD: 39% with depressive disorders, 28% with anxiety disorders, 10% with bipolar disorder, and 5% with schizophrenia. The prevalence of depressive and anxiety disorders increased between 2008 and 2018, whereas bipolar disorder and schizophrenia remained stable. MH multimorbidity affected 24% of PWH. From 2016 to 2018 (N = 64 684), retention in care was marginally lower among PWH with depression or anxiety, however those with MH multimorbidity were more likely to be retained in care. PWH with bipolar disorder had marginally lower prevalence of viral suppression (aPR = 0.98 [0.98–0.99]) as did PWH with MH multimorbidity (aPR = 0.99 [0.99–1.00]) compared with PWH without MHD.Conclusion:The prevalence of MHD among PWH was high, including MH multimorbidity. Although retention and viral suppression were similar to people without MHD, viral suppression was lower in those with bipolar disorder and MH multimorbidity.

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