Redesign of the communications network based on high availability of traffic management technologies to improve the communication

Yousif, Ali N. Taresh; Zghair, A.F. Noor

doi:10.1016/j.measen.2023.100776

Cited by 2 publications

(3 citation statements)

References 5 publications

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“…Across the globe, cities are confronting and surmounting multifaceted challenges by embracing a rich tapestry of inventive concepts [3][4][5][6]. This diverse spectrum of initiatives encompasses novel energy and transportation paradigms [7], groundbreaking innovations in residential construction [3], the proliferation of shared services [11], digitization of administrative processes [4], and a myriad of other pioneering endeavors. These groundbreaking initiatives are a collaborative effort involving cities, established corporations, nimble startups, non-profit organizations, and engaged citizens, all working collectively to advance innovative solutions.…”

Section: Background and Smart Cities Overviewmentioning

confidence: 99%

“…Smart cities, a vision that combines advanced technologies with data-driven decision-making, offer a promising solution to address these complex urban challenges [1,2]. At the heart of the smart city concept [3][4][5][6] lies the ability to optimize and coordinate various urban systems in realtime, from traffic management [7] and energy distribution [8] to public safety and transportation [7]. Achieving this level of sophistication necessitates cutting-edge technologies, and among these, artificial intelligence (AI) stands out as a crucial enabler.…”

Section: Introductionmentioning

confidence: 99%

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Algorithmic Innovations in Multi-Agent Reinforcement Learning: A Pathway for Smart Cities

Agbossou

2023

Artificial Intelligence

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The concept of smart cities has emerged as an instrumental solution to tackle the intricate challenges associated with urbanization in the twenty-first century. Among the myriad of issues that smart cities aim to address, key concerns such as efficient traffic management, sustainable energy usage, resilient infrastructure, and enhanced public safety are at the forefront. Notably, the implementation of multi-agent reinforcement learning (MARL) has garnered significant attention for its potential role in realizing the vision of smart cities. This chapter serves as an exploration of the frontiers of algorithmic innovation within MARL and its direct applicability to address the complex challenges of urban smart grid systems. The integration of MARL principles is vital in comprehensively modeling the intricate, interdependent urban systems that underpin the smart city framework. Particularly, we emphasize the relevance of MARL in providing adaptive solutions to the intricate dynamics of the urban smart grid, ensuring effective management of energy resources and demand-side management.

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Section: Background and Smart Cities Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Algorithmic Innovations in Multi-Agent Reinforcement Learning: A Pathway for Smart Cities

Agbossou

2023

Artificial Intelligence

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“…To address this issue, the High Availability (HA) solution can be employed to ensure network availability and reliability (Mukhopadhyay, 2020;Taresh & Zghair, 2023). FortiGate Firewall offers HA features that allow the configuration of multiple firewalls as a backup system, providing a failover solution that can automatically take over if the primary firewall encounters issues.…”

Section: Figure 1 Illustration Of An Inactive Fortigate Devicementioning

confidence: 99%

High Availability’s Implementation on the Fortigate Firewall Using SD-WAN Zone and HA Cluster Active-Passive

Fattahilah,

Nurfadila,

Setiawan

2023

IJOMS

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Networks that contain sensitive data or have high-security requirements require reliable and dependable network security solutions. FortiGate Firewall, as one of the popular network security solutions, provides High Availability (HA) features that ensure network availability and reliability. This study aims to analyze the implementation of HA on FortiGate Firewall in specific scenarios, such as networks with sensitive data or networks with high-security requirements. A real-world case study is applied to evaluate the effectiveness of HA implementation on FortiGate Firewall in enhancing network reliability and security. In this research, the implementation of HA on FortiGate Firewall at PT ABC was successfully built using the PPDIOO method and deploying SD-WAN load balancing and failover configurations, along with the utilization of a high-availability cluster mechanism. The HA implementation on FortiGate proves to be an effective solution, as demonstrated in the SD-WAN Zone testing of the Source-destination SD-WAN load balancing mode, which showed effectiveness in evenly and optimally distributing traffic among multiple available links, resulting in a 93.3% reduction in downtime. Furthermore, the testing of HA cluster mode in active-passive configuration achieved a 91.8% reduction in downtime compared to the pre-HA implementation state.

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Redesign of the communications network based on high availability of traffic management technologies to improve the communication

Cited by 2 publications

References 5 publications

Algorithmic Innovations in Multi-Agent Reinforcement Learning: A Pathway for Smart Cities

Algorithmic Innovations in Multi-Agent Reinforcement Learning: A Pathway for Smart Cities

High Availability’s Implementation on the Fortigate Firewall Using SD-WAN Zone and HA Cluster Active-Passive

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