Fog computing–based node‐to‐node communication and mobility management technique for 5G networks

Babu, Shivnath; Biswash, Sanjay Kumar

doi:10.1002/ett.3738

Cited by 8 publications

(3 citation statements)

References 29 publications

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“…Let E i,j denote the energy consumption on link L i,j and it will depend on distance, user mobility, bandwidth utilization, hop count, distance, and user mobility. Then the energy consumption in cellular communication is written in (14),…”

Section: E Energy Consumptionmentioning

confidence: 99%

Bee System-Based Self Configurable Optimized Resource Allocation Technique in Device-to-Device (D2D) Communication Networks

Mahdi,

Tașpinar

2024

IEEE Access

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With the exponential growth of mobile devices and high capabilities of intelligence, global communication network traffic is expected to experience remarkable growth in the next few years, as it leads us to poor network experience. The Device-to-Device (D2D) is a prominent solution to further expand the user experience and network performance. To improve it many nature-inspired computing algorithms are widely used. In line with this, we use swarm-based algorithms for network performance improvement. In this paper, we propose a swarm optimization-based resource allocation methodology for Device-to-Device communication, especially since we are focusing on the Bee fly pattern to optimize the resource available resources within the network's proximity area. Where all bees are working together to find the best optimal availability of the network's services, hereafter mobile users get served with a respective set of resources. If the performance is not up to the pre-defined threshold value then the system adds another set of available network resources and relay nodes. It leads to relay-assisted D2D pair communication based on the Bee fly pattern. It improves the D2D mobile pair's user experience in terms of energy, delay, and mobility support. To validate our results we compare our outcome with state-of-the-art works and provide detailed observations subject to various listed parameters. INDEX TERMS Device-to-device communication, Resource allocation, Performance analysis, Quality of Service(QoS), Quality of Experience (QoE). I. INTRODUCTION T HE mobile communication network is one of the most popular communication systems. The Device-to-Device (D2D) communication network is a promising method to enhance the performance of networks. It enables the network devices for direct transmission within the closely located users [1], [2], it may happen without or at least network dependency. The initial studies have proven that direct communication improves spectrum reuse, throughput maximization, energy consumption, coverage, and minimum end-to-end latency, user performance in terms of Quality of Service (QoS) and Quality of Experience (QoE). Thereafter it motivated the researchers to add it and became an integral part of Fifth Generation (5G) network technology [3], [4], [5], [6], [7]. The 5G and beyond (5GB) communication system is supported by an all-IP backbone. It consists of mobile users, radio access technologies (RAT), and network hardware such as eNBs, mobile switching center (MSC), mobile databases, mobility management devices, etc. [8], [9], [10]. The current era of 5G research was not enough for user-based QoS/QoE. 5GB networks provide used for better amalgamation of devicecentric communication technology, it is an emerging concept to improve cellular network performance with intelligent gNBs, and dynamic network database support [11]. It is the core motivation behind cloud-based network embodiment with 5G technologies, where a centralized cellular network is not capable of overcoming the cutting-edge network issue...

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Section: E Energy Consumptionmentioning

confidence: 99%

Bee System-Based Self Configurable Optimized Resource Allocation Technique in Device-to-Device (D2D) Communication Networks

Mahdi,

Tașpinar

2024

IEEE Access

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“…Simulation findings demonstrate that GDTMS performs more efficiently than other related algorithms. The authors of [38] offer a node-to-node communication architecture for 5G networks that is based on fog computing. It permits communication that is purely network infrastructure-dependent.…”

Section: Related Literaturementioning

confidence: 99%

Energy-Aware Next-Generation Mobile Routing Chains with Fog Computing for Emerging Applications

et al. 2023

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The Internet of Things (IoT) provides robust services to connected sensors in a distributed manner, and maintains real-time communication using wireless standards. The smart network has offered many autonomous smart systems to collect information from remote nodes, and share it by exploring the network layer. Researchers have recently offered a variety of ways to increase the effectiveness of emerging applications using trustworthy relaying systems. However, there are still many issues with route reformulation due to frequent disconnections of mobile devices and resource limitations. Furthermore, most of the existing methods for IoT systems are unable to utilize network resources, which lowers the performance of green networks. Thus, providing a foolproof solution for the autonomous system with energy efficiency is a challenging task. Therefore, this paper presents an algorithm for the mobile network using fog computing to reduce network disconnectivity. Furthermore, using security services, the proposed algorithm efficiently explores the characteristics of the device, and avoids malicious traffic to drain the additional energy consumption of the network. The main aspects of the proposed algorithm are as follows: (i) using the adjustable transmission power, the proposed algorithm offers a fault-tolerant solution to transmit the aggregated data over the unpredictable wireless system; (ii) with the support of fog nodes, the data load is reduced among devices with the offering of a secured authentication scheme. Using simulations, the proposed algorithm is tested, and its significance is demonstrated against other related studies.

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“…In the sequel of 5G networks, fog-networks is proposed in Ref. [ 3 , 4 , 5 ]. They also propose a similar line of performance for ultra-dense deployment of mobile base stations (BSs) and frequent fog nodes installation to achieve QoS and QoE.…”

Section: Introductionmentioning

confidence: 99%

A Fog Computing-Based Device-Driven Mobility Management Scheme for 5G Networks

Biswash

Jayakody

2020

Sensors

Self Cite

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The fog computing-based device-driven network is a promising solution for high data rates in modern cellular networks. It is a unique framework to reduce the generated-data, data management overheads, network scalability challenges, and help us to provide a pervasive computation environment for real-time network applications, where the mobile data is easily available and accessible to nearby fog servers. It explores a new dimension of the next generation network called fog networks. Fog networks is a complementary part of the cloud network environment. The proposed network architecture is a part of the newly emerged paradigm that extends the network computing infrastructure within the device-driven 5G communication system. This work explores a new design of the fog computing framework to support device-driven communication to achieve better Quality of Service (QoS) and Quality of Experience (QoE). In particular, we focus on, how potential is the fog computing orchestration framework? How it can be customized to the next generation of cellular communication systems? Next, we propose a mobility management procedure for fog networks, considering the static and dynamic mobile nodes. We compare our results with the legacy of cellular networks and observed that the proposed work has the least energy consumption, delay, latency, signaling cost as compared to LTE/LTE-A networks.

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Fog computing–based node‐to‐node communication and mobility management technique for 5G networks

Cited by 8 publications

References 29 publications

Bee System-Based Self Configurable Optimized Resource Allocation Technique in Device-to-Device (D2D) Communication Networks

Bee System-Based Self Configurable Optimized Resource Allocation Technique in Device-to-Device (D2D) Communication Networks

Energy-Aware Next-Generation Mobile Routing Chains with Fog Computing for Emerging Applications

A Fog Computing-Based Device-Driven Mobility Management Scheme for 5G Networks

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