EFM: An Edge-Computing-Oriented Forwarding Mechanism for Information-Centric Networks

Shi, Shanshan; Li, Jun; Wu, Haibo; Ren, Yongmao; Zhi, Junge

doi:10.1109/hoticn50779.2020.9350827

Cited by 5 publications

(3 citation statements)

References 17 publications

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“…An open and sharing network model is considers in [24] with the idea of sharing data across multiple managed network domains. Information-Centric Networking (ICN) has attracted much attention as a promising future network design and [25] discusses the rational behind this approach. Edge computing is an important pillar for green computing [26].…”

Section: Related Workmentioning

confidence: 99%

Snap IoT: A Decentralized Network Design Model

Reed,

Şaman Tosun,

Korkmaz

2024

IEEE Access

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IoT edge computing is a network design model that captures and processes data at the network edge. The results are forwarded to a cloud service or, if additional processing is needed, a middle tier. By processing data at the edge and middle tier, edge networks achieve better load-balancing and improve performance; however, traditional edge network deployments represent a rigid participation model. Edge networks require physical access to an IoT device and often lock the device to a single edge network. These constraints make it difficult to construct the ideal network, as they reject IoT devices deployed at the network edge but not owned by the network administrator. Our goal is to remove these limitations by creating a network protocol that supports broader participation of IoT devices, cryptographically secures network data, and improves network performance by increasing captured data at the network edge. The protocol is named Snap to symbolize the ease of self assembly. Our experimental research focuses on temperature stability and the cycle efficiency of an HVAC system by utilizing a Snap network to combine two existing edge networks and increase the number of temperature measurement points. The additional measurement points improved the efficiency of the HVAC cycle strategy by increasing the square footage of measured building space. The additional temperature capture points supported an adjustment to the HVAC cycle strategy which resulted in reducing the disparity between the requested temperature and the resulting temperatures. Snap networks support a broader range of IoT sensors leading to increased measurement density, sample rate frequency, and coverage of the network edge.

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Section: Related Workmentioning

confidence: 99%

Snap IoT: A Decentralized Network Design Model

Reed,

Şaman Tosun,

Korkmaz

2024

IEEE Access

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“…However, tracking the whereabouts of the probable content store in vehicular networks is difficult. The work of [25] is an edge computing enabled forwarding technique. Few edge nodes are used to assist content retrieval.…”

Section: The Related Workmentioning

confidence: 99%

Optimized interest forwarding in information centric vehicular networks using general secretary problem

Samantha

Dutta

2023

Preprint

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Vehicular networks of current era is not limited only to road safety and traffic management. It is been widely accepted as a network for information sharing, social networking and entertainment. With the advent of smart vehicles, the demand of vehicular network centric applications are getting popular. In one way, these applications demand faster data access and on the other hand, the underlying challenges of vehicular networks such as intermittent connectivity, low bandwidth and unpredictable vehicle movements impose considerable hindrance on communications. That is why, the vehicular communication is moving towards information centric approach so that the benefits of Information Centric Network (ICN) can be utilized. However, inherent challenges of vehicular communication and the lack of adequate protocols to implement content centric approach makes the extension of ICN into vehicular communications difficult. In ICN, a node generates interest packets to find a content. The interest is forwarded to an appropriate cache store to get the data. Hence, efficient forwarding of interest packets can considerably improve the content retrieval delay and can reduce network load. The interest forwarding techniques designed for wired ICN are not suitable for vehicular network due to computational complexity and bandwidth crisis. Hence, Information Centric Vehicular Network (ICVN) demands a new design for interest forwarding. Influenced by the need of the current time in vehicular communication, this research is aimed at developing an efficient interest forwarding mechanism for ICVN. The proposed algorithm models the interest forwarding task as a general secretary problem and finds the best node (or set of nodes) in the network to forward the interest packet. The protocol performance is examined in a simulation testbed designed in ndnSim-2.0 and compared with existing forwarding approaches. Observation demonstrates a better performance of the said vehicle with respect to content retrieval latency and network overhead.

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“…Though the authors have not significantly addressed the scalability issues related to the protocol in comparison with state-of-the-art methods. An edge-computingoriented forwarding mechanism for ICN (EFM) has been proposed in [33]. The objective is to make the edge nodes smarter that can act as agents for both requestors and content providers to improve the data distribution and retrieval.…”

Section: Related Workmentioning

confidence: 99%

CCJRF-ICN: A Novel Mechanism for Coadjuvant Caching Joint Request Forwarding in Information Centric Networks

2021

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Information centric networking (ICN) shifts the focus of existing internet architecture from host-oriented to content-oriented model by enabling in-network caching and content-based forwarding. These ICN features help to increase network performance by decreasing content discovery delay, content server load, and network congestion. To route a content interest inside network such that content can be fetched with minimal time is a challenging task in ICN. The performance of the ICN routing protocol can be significantly improved if the decisions related to content chunk placement and request forwarding are taken in a cooperative fashion. This paper describes a novel strategy for co-operative caching joint request forwarding in ICN, focusing on decreasing content retrieval latency. To do so, the caching strategy leverages the concept of connected dominating set (CDS) for creating a virtual backbone network to eliminate caching redundancy and reduce content discovery delay. It considers content chunk placement and request forwarding tasks as strongly co-related procedures. It exploits the caching information so that the request is forwarded to a content router (CR) with the maximum likelihood of carrying needed data using the betweenness centrality (BC) of CR. The proposed approach also uses the Markov chain-based model to estimate CS hit likelihood and use it as decisional parameter while forwarding the interest packet. This mechanism helps to fetch the content within the shortest possible time duration. The CCJRF-ICN adopts the Dijkstra's shortest path routing and works in collaboration with the CDS-driven caching joint forwarding mechanism. The simulation study of CCJRF-ICN is done inside ns-3 based ndnSIM-2.0 simulator with performance measures like content store (CS) hit ratio, content discovery delay, mean hop distance, network load, and network overhead. The simulation outcomes demonstrate that CCJRF-ICN outperforms the state-of-the-art strategies for realistic topologies (GEANT, US-26, Euro-28) and shows improvement up to 5-35% against stated performance measures.

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EFM: An Edge-Computing-Oriented Forwarding Mechanism for Information-Centric Networks

Cited by 5 publications

References 17 publications

Snap IoT: A Decentralized Network Design Model

Snap IoT: A Decentralized Network Design Model

Optimized interest forwarding in information centric vehicular networks using general secretary problem

CCJRF-ICN: A Novel Mechanism for Coadjuvant Caching Joint Request Forwarding in Information Centric Networks

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