Leveraging SDN for Smart City Applications Support

Rbii, Emna; Jemili, Imen

doi:10.1007/978-3-030-65810-6_6

Cited by 4 publications

(4 citation statements)

References 97 publications

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“…It implements the needs of IoT-based smart city networks by providing routing efficiency, managing the network, and optimizing resources by virtualizing IoT devices of the access network [42]. Deploying an SDN for smart cities solves many issues with traditional networks, including scalability, heterogeneity, interoperability between IoT devices, lack of dynamic services, bandwidth reduction, quality of services improvement, and adapting new services [43]. These achieved solutions can be classified into management, security, and architectural solutions.…”

Section: Sdn For Smart Citiesmentioning

confidence: 99%

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Enabling Technologies for Next-Generation Smart Cities: A Comprehensive Review and Research Directions

Ali,

Elsaid,

Ateya

et al. 2023

Future Internet

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The concept of smart cities, which aim to enhance the quality of urban life through innovative technologies and policies, has gained significant momentum in recent years. As we approach the era of next-generation smart cities, it becomes crucial to explore the key enabling technologies that will shape their development. This work reviews the leading technologies driving the future of smart cities. The work begins by introducing the main requirements of different smart city applications; then, the enabling technologies are presented. This work highlights the transformative potential of the Internet of things (IoT) to facilitate data collection and analysis to improve urban infrastructure and services. As a complementary technology, distributed edge computing brings computational power closer to devices, reducing the reliance on centralized data centers. Another key technology is virtualization, which optimizes resource utilization, enabling multiple virtual environments to run efficiently on shared hardware. Software-defined networking (SDN) emerges as a pivotal technology that brings flexibility and scalability to smart city networks, allowing for dynamic network management and resource allocation. Artificial intelligence (AI) is another approach for managing smart cities by enabling predictive analytics, automation, and smart decision making based on vast amounts of data. Lastly, the blockchain is introduced as a promising approach for smart cities to achieve the required security. The review concludes by identifying potential research directions to address the challenges and complexities brought about by integrating these key enabling technologies.

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Section: Sdn For Smart Citiesmentioning

confidence: 99%

“…By deploying SDN technology, smart cities can have a more adaptive, secure, and efficient network structure, enabling the efficient implementation of diverse smart city applications and services. Table 3 summarizes the benefits of implementing SDN for smart cities [42][43][44].…”

Section: Sdn For Smart Citiesmentioning

confidence: 99%

Enabling Technologies for Next-Generation Smart Cities: A Comprehensive Review and Research Directions

Ali,

Elsaid,

Ateya

et al. 2023

Future Internet

View full text Add to dashboard Cite

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“…The author of [10] has studied the limited energy utilisation for server farms using GAs for energy optimization [10]. In order to create a model that takes into account the superior features of GAs and a combinational ordering first fit (COFF) algorithm, in [11], a combined COFF-based genetic algorithm (COFF-GA) was proposed.…”

Section: Related Workmentioning

confidence: 99%

“…Our suggested fitness function satisfies the second prerequisite of a general fitness function. According to Equation (10), the use of PMs should be in wrinkle with respect to energy consumption (input). However, in our suggested fitness function, the values that matter are those that reflect a sustained energy expenditure across time.…”

Section: Prerequisite IImentioning

confidence: 99%

A Residual Resource Fitness-Based Genetic Algorithm for a Fog-Level Virtual Machine Placement for Green Smart City Services

et al. 2023

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Energy efficient information and communication technology (ICT) infrastructure at all levels of a city’s edifice constitutes a core requirement within the sustainable development goals. The ICT infrastructure of smart cities can be considered in three levels, namely the cloud layer infrastructure, devices/sensing layer infrastructure, and fog layer infrastructure at the edge of the network. Efficiency of a data-centre’s energy infrastructure is significantly affected by the placement of virtual machines (VMs) within the data-centre facility. This research establishes the virtual machine (VM) placement problem as an optimisation problem, and due to its adaptability for such complicated search issues, this paper applies the genetic algorithm (GA) towards the VM placement problem solution. When allocating or reallocating a VM, there is a large quantity of unused resources that might be used, however these resources are inefficiently spread over several different active physical machines (PMs). This study aims to increase the data-centre’s efficiency in terms of both energy usage and time spent on maintenance, and introduces a novel fitness function to streamline the process of computing the fitness function in GAs, which is the most computationally intensive component in a GA. A standard GA and first fit decreasing GA (FFD-GA) are applied on benchmark datasets to compare their relative performances. Experimental results obtained using data from Google data-centres demonstrate that the proposed FFD-GA saves around 8% more energy than a standard GA while reducing the computational overhead by approximately 66%.

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SDVN-Based Smart Data Dissemination Model for High-Speed Road Networks

Garg

Bali

et al. 2021

Internet of Things

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Leveraging SDN for Smart City Applications Support

Cited by 4 publications

References 97 publications

Enabling Technologies for Next-Generation Smart Cities: A Comprehensive Review and Research Directions

Enabling Technologies for Next-Generation Smart Cities: A Comprehensive Review and Research Directions

A Residual Resource Fitness-Based Genetic Algorithm for a Fog-Level Virtual Machine Placement for Green Smart City Services

SDVN-Based Smart Data Dissemination Model for High-Speed Road Networks

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