In-network live stream processing with named functions

Scherb, Christopher; Marxer, Claudio; Schnurrenberger, Urs; Tschudin, Christian

doi:10.23919/ifipnetworking.2017.8264868

Cited by 5 publications

(4 citation statements)

References 8 publications

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“…Such architectures do not provide support for forwarding and processing of periodic data streams. Several solutions building on top of NDN [44], [28] and NFN [43], [42], [47] try to solve this problem by continuously polling the producer with Interest packets. This approach works well when the producer sends the data stream at lower rates, but at higher event rates a lot of traffic is generated.…”

Section: Icn Architecturesmentioning

confidence: 99%

“…INP and IoT Architectures in ICNs: Authors in work [43], [38] propose an approach to distribute computational tasks in the network by extending the NFN architecture similar to our work. However, the authors do not deal with the lack of abstractions required for processing continuous data stream.…”

Section: A Icn Architecturesmentioning

confidence: 99%

“…Additionally, exploiting data plane programmability on in-network elements of ICN can offer high throughput by processing packets at line rate, while delivering them at low latency, typically known as in-network processing. However, existing ICN architectures like Named Data Networking (NDN) and Named Function Consumer initiated (pull) Producer initiated (push) Anonymous Request-Reply [27,30,37,38,41,42,44] Event-based communication [1,2,20,23,24] Push and pull based [3] (not unified), [10] (only simple events) [19] (focus on routing), [34] (only pub/sub),…”

Section: Introductionmentioning

confidence: 99%

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INetCEP: In-Network Complex Event Processing for Information-Centric Networking

Luthra

Koldehofe

Höchst

et al. 2019

2019 ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS)

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Section: Icn Architecturesmentioning

confidence: 99%

Section: A Icn Architecturesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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INetCEP: In-Network Complex Event Processing for Information-Centric Networking

Luthra

Koldehofe

Höchst

et al. 2019

2019 ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS)

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“…Forwarding schemes for managing long and/or interactive computation [37] and for managing live stream processing [40].…”

mentioning

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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