With the technology of Network function Virtualization (NFV), a multicast service (e.g., real-time multimedia streaming or event monitoring) may be accommodated with a servicefunction Chain (SFC). The SFC consists of...
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ISBN:
(纸本)9781728116860
With the technology of Network function Virtualization (NFV), a multicast service (e.g., real-time multimedia streaming or event monitoring) may be accommodated with a servicefunction Chain (SFC). The SFC consists of an ordered set of network functions running on generic physical hardware to provide services from source node to each destination node of the multicast service. In this paper, we define the problem of Multicast-aware service function tree Embedding (M-SFTE), which allows the multicast flows to traverse through network servicefunctions before reaching destination nodes. The M-SFTE maps user's SFC-based multicast requests onto a shared substrate network while considering the constraints of network functionality, computing demand of each virtual network function node, and the bandwidth demand of the request. We propose a novel algorithm, called Minimum Cost Multicast service function tree (MC-MSFT) to jointly optimize the process of constructing SFC-based multicast tree and allocating requested resource to embed the tree onto the physical network. The experimental results show that the MC-MSFT algorithm outperforms the traditional greedy-based algorithms as much as by 35% in terms of the total bandwidth consumption.
Fog computing offers increased performance and efficiency for Industrial Internet of Things (IIoT) applications through distributed data processing in nearby proximity to sensors. Given resource constraints and their ...
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ISBN:
(纸本)9798350368567;9798350368550
Fog computing offers increased performance and efficiency for Industrial Internet of Things (IIoT) applications through distributed data processing in nearby proximity to sensors. Given resource constraints and their contentious use in IoT networks, current strategies strive to optimise which data processing tasks should be selected to run on fog devices. In this paper, we advance a more effective data processing architecture for optimisation purposes. Specifically, we consider the distinct functions of sensor data streaming, multi-stream data aggregation and event handling, required by IoT applications for identifying actionable events. We retrofit this event processing pipeline into a logical architecture, structured as a service function tree (SFT), comprising servicefunction chains. We present a novel algorithm for mapping the SFT into a fog network topology in which nodes selected to process SFT functions (microservices) have the requisite resource capacity and network speed to meet their event processing deadlines. We used simulations to validate the algorithm's effectiveness in finding a successful SFT mapping to a physical network. Overall, our approach overcomes the bottlenecks of single service placement strategies for fog computing through composite service placements of SFTs.
To comply with security and performance policies, multicast communication requires inline service that chains an ordered sequence of virtualized network functions (VNFs) with an emerging paradigm of network function v...
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To comply with security and performance policies, multicast communication requires inline service that chains an ordered sequence of virtualized network functions (VNFs) with an emerging paradigm of network function virtualization (NFV). As many-to-many multicast pattern is widely used especially in current MEC, multimedia and big data industries, in this paper we focus on multi-source NFV-enabled multicasting in software-defined networks (SDN). By jointly investigating VNF placement and multicast tree routing strategy, it is envisioned to construct service function tree with minimum network resource expenditure while yielding lower delay. We explore this problem in static and online scenarios individually. In static situation with a bunch of multicast requests to be served, a column generation based computing model is first formulated, based on which an approximation algorithm MDNM that leverages logic of Viterbi and puts emphasis on resource optimization and segmental delay satisfaction is developed. In online situation with a single incoming request, another ILP model to enhance VNF instance reuse is established. Then, SVM algorithm giving importance to source determination and VNF instance consolidation is designed to efficiently construct a service function tree with minimum resource usage and delay. Simulation results show that the gap between each of the two proposed algorithms and their respective ILP models is marginal, and both MDNM and SVM outperform the state-of-art work.
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