Bringing Named Data Networks into Smart Cities

Ahmed, Syed Hassan; Kim, Dongkyun; Sarkar, Mitali

doi:10.1002/9781119226444.ch10

Cited by 2 publications

(1 citation statement)

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“…Ahmed et al [37] discussed the importance of an NDN network in maintaining smart cities. In his research, different scenarios related to smart cities have been presented, such as vehicular networks, healthcare systems, and wireless sensor networks, where NDN can play an important role.…”

Section: Naming and Forwarding Approaches Used With The Named Data Ne...mentioning

confidence: 99%

Named Data Networking for Efficient IoT-based Disaster Management in a Smart Campus

et al. 2020

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Disasters are uncertain occasions that can impose a drastic impact on human life and building infrastructures. Information and Communication Technology (ICT) plays a vital role in coping with such situations by enabling and integrating multiple technological resources to develop Disaster Management Systems (DMSs). In this context, a majority of the existing DMSs use networking architectures based upon the Internet Protocol (IP) focusing on location-dependent communications. However, IP-based communications face the limitations of inefficient bandwidth utilization, high processing, data security, and excessive memory intake. To address these issues, Named Data Networking (NDN) has emerged as a promising communication paradigm, which is based on the Information-Centric Networking (ICN) architecture. An NDN is among the self-organizing communication networks that reduces the complexity of networking systems in addition to provide content security. Given this, many NDN-based DMSs have been proposed. The problem with the existing NDN-based DMS is that they use a PULL-based mechanism that ultimately results in higher delay and more energy consumption. In order to cater for time-critical scenarios, emergence-driven network engineering communication and computation models are required. In this paper, a novel DMS is proposed, i.e., Named Data Networking Disaster Management (NDN-DM), where a producer forwards a fire alert message to neighbouring consumers. This makes the nodes converge according to the disaster situation in a more efficient and secure way. Furthermore, we consider a fire scenario in a university campus and mobile nodes in the campus collaborate with each other to manage the fire situation. The proposed framework has been mathematically modeled and formally proved using timed automata-based transition systems and a real-time model checker, respectively. Additionally, the evaluation of the proposed NDM-DM has been performed using NS2. The results prove that the proposed scheme has reduced the end-to-end delay up from 2 % to 10 % and minimized up to 20 % energy consumption, as energy improved from 3 % to 20 % compared with a state-of-the-art NDN-based DMS.

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Section: Naming and Forwarding Approaches Used With The Named Data Ne...mentioning

confidence: 99%