The new paradigm of smart cities is deeply intertwined with the development of large-scale sensing applications. An ever-growing amount of sensors are collecting data to support decision strategies for the management of the city services. Examples of such applications are traffic monitoring, autonomous driving, environmental sensing, real-time power/resource utilization metering. A traditional cloud-based approach for the deployment of such services is likely to suffer from performance and QoS problems due to the risk of congestion on the data center outbound links and due to high latency related to the geographic data exchange. An alternative paradigm to mitigate these problems is the fog computing, where a layer of intermediate fog nodes is placed between the sensors and the cloud data center to reduce the amount of data exchanges (through aggregation and filtering) and to host latency-critical services. The fog computing opens several new issues for the management and deployment of the services, especially if we consider that new applications may be dynamically deployed and also the infrastructure is subject to changes over time (e.g., adding and removing sensors and fog nodes). While this dynamic behavior can be supported by existing technologies such as containers, service orchestration frameworks, and micro-services, the fog paradigm exacerbates the problem of infrastructure and service coordination and management to the point where new solutions must be devised. The critical challenges that should be addressed by future fog infrastructures for smart cities lie in the area of service management, optimization of the infrastructure and automatic deployment of applications. In the present chapter, we discuss advantages and disadvantages of solutions for the management of smart city sensing applications, considering architectures, optimization models, algorithms for the service deployment, and the support for the applications life cycle.

Smart cities in the fog: Clearing the vision of innovative sensing applications / Bicocchi, N.; Canali, C.; Lancellotti, R.. - (2020), pp. 63-88.

Smart cities in the fog: Clearing the vision of innovative sensing applications

Bicocchi N.;Canali C.;Lancellotti R.
2020

Abstract

The new paradigm of smart cities is deeply intertwined with the development of large-scale sensing applications. An ever-growing amount of sensors are collecting data to support decision strategies for the management of the city services. Examples of such applications are traffic monitoring, autonomous driving, environmental sensing, real-time power/resource utilization metering. A traditional cloud-based approach for the deployment of such services is likely to suffer from performance and QoS problems due to the risk of congestion on the data center outbound links and due to high latency related to the geographic data exchange. An alternative paradigm to mitigate these problems is the fog computing, where a layer of intermediate fog nodes is placed between the sensors and the cloud data center to reduce the amount of data exchanges (through aggregation and filtering) and to host latency-critical services. The fog computing opens several new issues for the management and deployment of the services, especially if we consider that new applications may be dynamically deployed and also the infrastructure is subject to changes over time (e.g., adding and removing sensors and fog nodes). While this dynamic behavior can be supported by existing technologies such as containers, service orchestration frameworks, and micro-services, the fog paradigm exacerbates the problem of infrastructure and service coordination and management to the point where new solutions must be devised. The critical challenges that should be addressed by future fog infrastructures for smart cities lie in the area of service management, optimization of the infrastructure and automatic deployment of applications. In the present chapter, we discuss advantages and disadvantages of solutions for the management of smart city sensing applications, considering architectures, optimization models, algorithms for the service deployment, and the support for the applications life cycle.
2020
Virtual Machines: Advances in Applications and Research
Nova Science Publishers, Inc.
Smart cities in the fog: Clearing the vision of innovative sensing applications / Bicocchi, N.; Canali, C.; Lancellotti, R.. - (2020), pp. 63-88.
Bicocchi, N.; Canali, C.; Lancellotti, R.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1330870
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