On the Integration of Information Centric Networking and Fog Computing for Smart Home Services

Amadeo, Marica; Giordano, Andrea; Mastroianni, Carlo; Molinaro, Antonella

doi:10.1007/978-3-319-96550-5_4

Cited by 13 publications

(13 citation statements)

References 40 publications

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“…Amadeo et al [76] developed an architecture based on fog-cloud computing for a Smart Energy scenario. The authors validated the architecture by deploying it in a smart home and its lighting system based on the detection of movement or people.…”

Section: • Architecturesmentioning

confidence: 99%

“…Other studies worth mentioning, are those presented by Amadeo et al [76] and Li et al [77] which included algorithms and encryption packets for data security in an intermediate layer of the architecture. The paper presented by Sittón-Candanedo et al [6] described an architecture that includes Blockchain and data encryption in its three levels, however, the proposal would have been stronger if the authors had implemented Crypto-IoT boards in IoT devices, thus improving the system in terms of security, traceability, and data integrity.…”

Section: • Architecturesmentioning

confidence: 99%

“…Amadeo et al [76] Presented a reference architecture for a Smart Energy scenario, in this case, a home, where automation, control, supervision, and optimization were required. The architecture's main component is an IoT platform that includes Edge Computing and all its general capabilities.…”

Section: Rq2: How Do Smart Energy Scenarios Benefit From Edge Computing?mentioning

confidence: 99%

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A Review on Edge Computing in Smart Energy by means of a Systematic Mapping Study

et al. 2019

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Context: Smart Energy is a disruptive concept that has led to the emergence of new energy policies, technology projects, and business models. The development of those models is driven by world capitals, companies, and universities. Their purpose is to make the electric power system more efficient through distributed energy generation/storage, smart meter installation, or reduction of consumption/implementation costs. This work approaches Smart Energy as a paradigm that is concerned with systemic strategies involving the implementation of innovative technological developments in energy systems. However, many of the challenges encountered under this paradigm are yet to be overcome, such as the effective integration of solutions within Smart Energy systems. Edge Computing is included in this new technology group. Objective: To investigate developments that involve the use of Edge Computing and that provide solutions to Smart Energy problems. The research work will be developed using the methodology of systematic mapping of literature, following the guidelines established by Kitchenham and Petersen that facilitate the identification of studies published on the subject. Results: Inclusion and exclusion criteria have been applied to identify the relevant articles. We selected 80 papers that were classified according to the type of publication (journal, conferences, or book chapter), type of research (conceptual, experience, or validation), type of activity (implement, validate, analyze) and asset (architecture, framework, method, or models). Conclusion: A complete review has been conducted of the 80 articles that were closely related to the questions posed in this research. To reach the goal of building Edge Computing architectures for Smart Energy environments, several lines of research have been defined. In the future, such architectures will overcome current problems, becoming highly energy-efficient, cost-effective, and capacitated to process and respond in real-time.Electronics 2020, 9, 48 2 of 33 Ledger Technologies (such as blockchain) [15]; or distributed sensing and actuation technologies such as the Internet of Things (IoT) [3,16].Regarding the Internet of Things (IoT), its recognition as a paradigm dates back to 2011-2012, when renowned companies and institutions such as Gartner, Forbes, or Wired started using this term to refer to the emerging technology [17]. The Internet of Things implies the connection of different heterogeneous objects, including buildings, machinery, vehicles, and electronic devices, such as sensors and actuators interconnected by means of communication protocols and forming wireless or wired networks [18] to collect information and extract knowledge [19]. Since then, the scope of IoT has spread throughout a great variety of environments and disciplines, including solutions for development of Smart Cities [20,21], Industry 4.0 [22][23][24], transportation and logistics [25,26], smart homes and hotels [13,27,28] or, more relevant to this research, energy efficiency [8,29,30]. IoT provid...

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Section: • Architecturesmentioning

confidence: 99%

Section: • Architecturesmentioning

confidence: 99%

Section: Rq2: How Do Smart Energy Scenarios Benefit From Edge Computing?mentioning

confidence: 99%

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A Review on Edge Computing in Smart Energy by means of a Systematic Mapping Study

et al. 2019

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“…ICN-isapiens [44,45] Centralized A software component called deployer is in charge of loading the IoT services in specific fog nodes depending on the physical IoT devices they control.…”

Section: Iot-ncn [7]mentioning

confidence: 99%

“…In References [44,45], a 3-level framework called ICN-isapiens is presented, where a fog layer, consisting of smart home servers (HSs), is introduced between the physical world and the remote cloud to support real-time services and to hide the heterogeneity of IoT devices. In ICN-isapiens, HSs are installed in houses and provided with a multi-agent software application to manage predefined low-latency monitoring and actuation services.…”

Section: Centralized Mechanismsmentioning

confidence: 99%

Fog Computing in IoT Smart Environments via Named Data Networking: A Study on Service Orchestration Mechanisms

et al. 2019

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By offering low-latency and context-aware services, fog computing will have a peculiar role in the deployment of Internet of Things (IoT) applications for smart environments. Unlike the conventional remote cloud, for which consolidated architectures and deployment options exist, many design and implementation aspects remain open when considering the latest fog computing paradigm. In this paper, we focus on the problems of dynamically discovering the processing and storage resources distributed among fog nodes and, accordingly, orchestrating them for the provisioning of IoT services for smart environments. In particular, we show how these functionalities can be effectively supported by the revolutionary Named Data Networking (NDN) paradigm. Originally conceived to support named content delivery, NDN can be extended to request and provide named computation services, with NDN nodes acting as both content routers and in-network service executors. To substantiate our analysis, we present an NDN fog computing framework with focus on a smart campus scenario, where the execution of IoT services is dynamically orchestrated and performed by NDN nodes in a distributed fashion. A simulation campaign in ndnSIM, the reference network simulator of the NDN research community, is also presented to assess the performance of our proposal against state-of-the-art solutions. Results confirm the superiority of the proposal in terms of service provisioning time, paid at the expenses of a slightly higher amount of traffic exchanged among fog nodes.Smart home, smart building, smart transportation, and smart energy are just a few examples of IoT application domains. In these contexts, the cloud and fog computing paradigms will play a crucial role in supporting the variety of expected services (e.g., data aggregation, filtering, manipulation for monitoring, and surveillance purposes) and in fulfilling their requirements in the presence of a huge number of heterogeneous connected devices. According to References [3,4], fog and cloud computing will complement each other to form a service continuum between the cloud and the IoT devices by providing computing, storage, control, and networking resources.On the one side, by leveraging remote data centers and centralized control, the cloud becomes the perfect candidate for managing long-term data storage and for executing complex analytics algorithms. On the other side, the fog brings computing and storage services close to the end-users, where data are generated and/or consumed. The advantages are clear: enabling interactive and delay-sensitive applications, reducing the amount of traffic reaching the core network segment, and guaranteeing high performance also in the presence of limited network bandwidth and intermittent connectivity. In the most ambitious scenario, network edge routers and hosts, ranging from access points, backhaul nodes, and Points of Presence (PoPs) to IoT gateways and user devices like smartphones and tablets, will turn into fog elements that execute services on demand.An ...

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A Review on Interoperability and Integration in Smart Homes

Sharma

2020

Futuristic Trends in Networks and Computing Technologies

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On the Integration of Information Centric Networking and Fog Computing for Smart Home Services

Cited by 13 publications

References 40 publications

A Review on Edge Computing in Smart Energy by means of a Systematic Mapping Study

A Review on Edge Computing in Smart Energy by means of a Systematic Mapping Study

Fog Computing in IoT Smart Environments via Named Data Networking: A Study on Service Orchestration Mechanisms

A Review on Interoperability and Integration in Smart Homes

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