Measuring the Fog, Gently

Brogi, Antonio; Forti, Stefano; Gaglianese, Marco

doi:10.1007/978-3-030-33702-5_40

Cited by 13 publications

(7 citation statements)

References 27 publications

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“…Similarly, we assume that nodes feature decentralised monitoring capabilities (e.g. those of FogMon [20,21] or of the monitoring tools surveyed in [22]), enabling application management agents to access information about their current deployment context. Pursuing our analogy, bacteria sensing capabilities correspond to the fact that application management agents can access information on the hardware resources at their current deployment node and on the amount of client requests they receive from each neighbouring node, along with the client-to-application latency such requests experience.…”

Section: Modelling Bacteria-inspired Declarative Application Managementmentioning

confidence: 99%

“…Then, in case (1a) holds and not (1b) (viz. the list of requests not satisfying latency constraints is empty), M is chosen to be the node from which most requests are arriving to Si (lines [20][21][22], and it can be one among the current deployment node (self) or its neighbours (lines 24-26) as in Policy 1. Otherwise, if (1b) holds, the target node M is the neighbour of self from which most requests to Si not satisfying the maximum latency constraint are arriving (line 30) as in Policy 2.…”

Section: Declaring Management Policiesmentioning

confidence: 99%

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Declarative Application Management in the Fog

et al. 2021

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Orchestrating next-gen applications over heterogeneous resources along the Cloud-IoT continuum calls for new strategies and tools to enable scalable and application-specific managements. Inspired by the self-organisation capabilities of bacteria colonies, we propose a declarative, fully decentralised application management solution, targeting pervasive opportunistic Cloud-IoT infrastructures. We present a customisable declarative implementation of the approach and validate its scalability through simulation over motivating scenarios, also considering end-user’s mobility and the possibility to enforce application-specific management policies for different (classes of) applications.

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Section: Modelling Bacteria-inspired Declarative Application Managementmentioning

confidence: 99%

Section: Declaring Management Policiesmentioning

confidence: 99%

Declarative Application Management in the Fog

et al. 2021

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“…Our decentralised management solution relies upon a declarative Prolog implementation that makes use of four key components (Figure 1). Namely, each MARIO node contains the following: Knowledge base , a simple representation of monitored infrastructure data, application deployment data, an application orchestration data available at each given node. Data collector , a decentralised monitoring tool (like FogMon 17,18 or one of the monitoring tools surveyed in 19 ), which seamlessly runs on the involved Fog nodes, enabling access to local monitoring information on the infrastructure close to them or traversed by user requests targeting the application instances they host, and on hosted application instances. Application managers (AMs), distributed agents that enforce custom application management policies defined via four well‐defined Osmotic operations (i.e. undeploy, adapt, migrate and replicate) that can be used to optimise application performance by specifying ( i ) the infrastructure and deployment conditions that should trigger them, and ( ii ) the effects on the managed application instance.…”

Section: Declarative Decentralised Service Managementmentioning

confidence: 99%

Osmotic management of distributed complex systems: A declarative decentralised approach

Forti

Lera

Guerrero

et al. 2021

J Software Evolu Process

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Osmotic computing encompasses emerging Cloud‐Internet of Things (IoT) computing paradigms, by featuring the possibility for application services to adapt into different functionally equivalent flavours, depending on the contextually available resources and on specific requirements of running applications. This article proposes a fully decentralised declarative framework that enables both application and infrastructure operators to declare management policies for the service instances and the nodes they manage, respectively. Policies are composed of a simple and well‐defined set of management operations, declared in Prolog, which trigger based on locally available contextual information on application requests and infrastructure resources. A prototype implementation of the framework is showcased and assessed via simulation over a lifelike Smart Campus use case with multiple applications, at increasing infrastructure sizes and number of mobile users. Experimental results show that the proposed management framework scales to large infrastructure sizes and suits the needs of multiflavoured Osmotic applications in dynamic deployment conditions, by improving the trade‐off between their response times and suitable service usage.

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“…All this has to happen with a minimal resource footprint, to prevent overloading the device and to ensure other processes can still run on-device. Recent state of the art is attempting to develop efficient monitoring tools, with for example Fogmon, provided by Brogi et al [9]. We chose to develop a monitoring tool which runs on Linux devices capable of running the Java Virtual Machine (JVM).…”

Section: A Monitoringmentioning

confidence: 99%

A Generalized Approach For Practical Task Allocation Using A MAPE-K Control Loop

Eyckerman

Reiter

Mercelis

et al. 2021

2021 International Conference on Information and Communication Technology Convergence (ICTC)

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Fog and edge computing paradigms were adopted to enable Internet of Things (IoT) applications, improving response time and reducing network load. Task allocation algorithms are used on IoT-enabled networks to determine the optimal software placement. However, managing such a network is considerably more complex than allocating the tasks. To simplify management, we propose a general Monitor -Analyze -Plan -Execute over a Knowledge base (MAPE-K) framework in which all requirements for task allocation are fulfilled, and where components can easily be adapted to the use case at hand. This research identifies several pitfalls and proposes solutions. Additionally, we apply this approach to a distributed testbed, comparing it to traditional cloud approaches. ACKNOWLEDGMENTThis research received funding from the Flemish Government (AI Research Program). This article describes work in the context of the DEDICAT 6G project under the European Union (EU) H2020 research and innovation programme (Grant Agreement No. 101016499). The contents of this publication are the sole responsibility of the authors and do not in any way reflect the views of the EU.

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Measuring the Fog, Gently

Cited by 13 publications

References 27 publications

Declarative Application Management in the Fog

Declarative Application Management in the Fog

Osmotic management of distributed complex systems: A declarative decentralised approach

A Generalized Approach For Practical Task Allocation Using A MAPE-K Control Loop

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