OPMSS: Optimal Producer Mobility Support Solution for Named Data Networking

Hussaini, Muktar; Naeem, Muhammad Ali; Kim, Byung-Seo

doi:10.3390/app11094064

Cited by 14 publications

(11 citation statements)

References 44 publications

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“…If data is not available at any caching node, the Interest calls the data producer, which delivers the content with a longer delay. However, there are still challenges when the data producer moves to another location, and the Interest is still not delivered [75]. The new name prefix of the producer might be unknown to any ICN router until the network converges.…”

Section: Requirements For Fault-tolerant Sdic-iotmentioning

confidence: 99%

Complementing IoT Services Using Software-Defined Information Centric Networks: A Comprehensive Survey

Rafique

Hafid

Cherkaoui

2022

IEEE Internet Things J.

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IoT connects a large number of physical objects with the Internet that capture and exchange real-time information for service provisioning. Traditional network management schemes face challenges to manage vast amounts of network traffic generated by IoT services. Software-Defined Networking (SDN) and Information-Centric Networking (ICN) are two complementary technologies that could be integrated to solve the challenges of different aspects of IoT service provisioning. ICN offers a clean-slate design to accommodate continuously increasing network traffic by considering content as a network primitive. It provides a novel solution for information propagation and delivery for large-scale IoT services. On the other hand, SDN allocates overall network management responsibilities to the central controller, where network elements act merely as traffic forwarding components. An SDN-enabled network flexibly supports ICN without deploying ICN-capable hardware. Therefore, the integration of SDN and ICN provides benefits for large-scale IoT services. This paper provides a comprehensive survey on Software-Defined Information-Centric Internet of Things (SDIC-IoT) for IoT services provisioning. We present critical enabling technologies of SDIC-IoT, discuss its architecture, and elaborate its benefits for IoT services provisioning. We elaborate on key IoT service provisioning requirements and discuss how SDIC-IoT supports different aspects of IoT services. We develop different taxonomies of SDIC-IoT literature based on various performance parameters. Furthermore, an extensive discussion on different use cases, synergies, and advances is presented to envision the SDIC-IoT concept. Finally, we provide current challenges, causes, and future research directions of IoT services provisioning using SDIC-IoT.

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Section: Requirements For Fault-tolerant Sdic-iotmentioning

confidence: 99%

Complementing IoT Services Using Software-Defined Information Centric Networks: A Comprehensive Survey

Rafique

Hafid

Cherkaoui

2022

IEEE Internet Things J.

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“…Producer mobility is more complicated since the NDN naming scheme does not include location information. A number of studies, such as those of [111][112][113][114][115], address producer mobility. Four producer mobility approaches have been presented in the literature: location resolution, triangular, locator/identifier separation, and routing-based.…”

Section: Mobility Support For Iiovmentioning

confidence: 99%

“…Similarly, in [119], the authors proposed supporting producer mobility via named data networking in an integrated space-terrestrial scheme. The optimal producer mobility support solution (OPMSS) [111] is proposed to minimize unnecessary interest packet losses and delay, while providing an optimization path for data when the mobile producer relocates. In [115], the authors propose a lightweight machine-learning-based strategy to predict the position of the producer in advance and to determine whether or not handover occurs.…”

Section: Mobility Support For Iiovmentioning

confidence: 99%

Convergence of Information-Centric Networks and Edge Intelligence for IoV: Challenges and Future Directions

et al. 2022

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Recently the Internet of Vehicles (IoV) has become a promising research area in the field of the Internet of Things (IoT), which enables vehicles to communicate and exchange real-time information with each other, as well as with infrastructure, people, and other sensors and actuators through various communication interfaces. The realization of IoV networks faces various communication and networking challenges to meet stringent requirements of low latency, dynamic topology, high data-rate connectivity, resource allocation, multiple access, and QoS. Advances in information-centric networks (ICN), edge computing (EC), and artificial intelligence (AI) will transform and help to realize the Intelligent Internet of Vehicles (IIoV). Information-centric networks have emerged as a paradigm promising to cope with the limitations of the current host-based network architecture (TCP/IP-based networks) by providing mobility support, efficient content distribution, scalability and security based on content names, regardless of their location. Edge computing (EC), on the other hand, is a key paradigm to provide computation, storage and other cloud services in close proximity to where they are requested, thus enabling the support of real-time services. It is promising for computation-intensive applications, such as autonomous and cooperative driving, and to alleviate storage burdens (by caching). AI has recently emerged as a powerful tool to break through obstacles in various research areas including that of intelligent transport systems (ITS). ITS are smart enough to make decisions based on the status of a great variety of inputs. The convergence of ICN and EC with AI empowerment will bring new opportunities while also raising not-yet-explored obstacles to realize Intelligent IoV. In this paper, we discuss the applicability of AI techniques in solving challenging vehicular problems and enhancing the learning capacity of edge devices and ICN networks. A comprehensive review is provided of utilizing intelligence in EC and ICN to address current challenges in their application to IIoV. In particular, we focus on intelligent edge computing and networking, offloading, intelligent mobility-aware caching and forwarding and overall network performance. Furthermore, we discuss potential solutions to the presented issues. Finally, we highlight potential research directions which may illuminate efforts to develop new intelligent IoV applications.

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“…In GR, content and source mobility is another issue that needs to be addressed because when a consumer, a producer, or both are in transit, routing becomes complicated. In NDN, there are many challenges with producer mobility that date back to the initial design of the network, such as long handoff latency, high handoff signaling costs, table size scalability issues, unnecessary interest packet loss, and high bandwidth utilization costs [123].Another challenge that arises as a result of mobility in GR is NDN's reverse path mechanism.…”

Section: Ndn Routing Challenges and Open Issuesmentioning

confidence: 99%

Named Data Networking: A Survey on Routing Strategies

et al. 2022

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Data has become an increasingly significant component of the Internet as it has increased in popularity. Where people care more about the data than the location of data. The Named Data Network (NDN) took this concept and paired it with the idea of making data a core component rather than host addresses. Because of its in-network caching capability, NDN will become a better contender than current Transmission Control Protocol and Internet Protocol (TCP/IP) based networks as data traffic grows exponentially. NDNrelated challenges are available for investigation as NDN becomes more important. Routing in NDN is another essential domain that needs to be addressed, and several approaches have been presented to address routing concerns in NDN. In this study, we discuss and highlight NDN and its routing strategies comprehensively. In addition, this research illustrates a comparison of important routing paradigms to emphasis the breadth of routing research in NDN. Also, we investigate the routing attributes of NDN and expose the latest literature on this critical topic. Finally, this study provides useful insights into the emerging areas of guidance in the NDN to assist future studies in addressing challenges and open research issues. INDEX TERMSNamed Data Networks, Open Research issues in NDN, Routing in NDN I.

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OPMSS: Optimal Producer Mobility Support Solution for Named Data Networking

Cited by 14 publications

References 44 publications

Complementing IoT Services Using Software-Defined Information Centric Networks: A Comprehensive Survey

Complementing IoT Services Using Software-Defined Information Centric Networks: A Comprehensive Survey

Convergence of Information-Centric Networks and Edge Intelligence for IoV: Challenges and Future Directions

Named Data Networking: A Survey on Routing Strategies

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