Towards Reasoning Vehicles

Tal, Irina; Muntean, Gabriel‐Miro

doi:10.1145/3125640

Cited by 22 publications

(9 citation statements)

References 86 publications

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“…Three papers [52][53][54] reported on the evolving automotive cyber security, which can use 5G to be faster and more efficient. Presented a peer-to-peer IoT infrastructure, built to OpenFog standards, which moves control out to "things" without involving devices or cloud computing.…”

Section: Review and Survey Articlesmentioning

confidence: 99%

From 5G to 6G Technology: Meets Energy, Internet-of-Things and Machine Learning: A Survey

Mahdi

Ahmad

Qassim³

et al. 2021

Applied Sciences

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Due to the rapid development of the fifth-generation (5G) applications, and increased demand for even faster communication networks, we expected to witness the birth of a new 6G technology within the next ten years. Many references suggested that the 6G wireless network standard may arrive around 2030. Therefore, this paper presents a critical analysis of 5G wireless networks’, significant technological limitations and reviews the anticipated challenges of the 6G communication networks. In this work, we have considered the applications of three of the highly demanding domains, namely: energy, Internet-of-Things (IoT) and machine learning. To this end, we present our vision on how the 6G communication networks should look like to support the applications of these domains. This work presents a thorough review of 370 papers on the application of energy, IoT and machine learning in 5G and 6G from three major libraries: Web of Science, ACM Digital Library, and IEEE Explore. The main contribution of this work is to provide a more comprehensive perspective, challenges, requirements, and context for potential work in the 6G communication standard.

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Section: Review and Survey Articlesmentioning

confidence: 99%

From 5G to 6G Technology: Meets Energy, Internet-of-Things and Machine Learning: A Survey

Mahdi

Ahmad

Qassim³

et al. 2021

Applied Sciences

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“…This section reviews the solutions related to the issue of MH in HetNet [13]. There are numerous studies to investigate this issue and solutions are proposed to perform handover.…”

Section: Related Workmentioning

confidence: 99%

“…User devices do not have the required intelligence to make use of multiple connections and operate with only a single preferred connection while maintaining other remaining connections as standby [6]. There are techniques that have been developed to solve this problem such as handover, mobility, bandwidth aggregation, multiplexing, and load balancing [13].…”

Section: Introductionmentioning

confidence: 99%

An Optimized Load Balance Solution for Multi-homed Host in Heterogeneous Wireless Networks

Naeem

ElAttar

Aboul-Dahab

2019

Sensors

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The imminent wireless technologies are demanding fusion of several networks with diverse technologies. A convenient user device for such an environment is the multihomed host, which is capable of making use of simultaneous multiple connections of heterogeneous networks and smartly distributing/receiving data among them. The aim of this work is to develop a mechanism for assessing the multihoming concept and to propose a system model for increasing its applicability. The proposed model provided a novel user-centric scheme for multihoming for multi-radio access technologies (multi-RAT). It is considered an evolution of traffic offloading for gaining more capacity, higher data rates, and real-time services. This work assumes data classifications, evaluates and ranks the available connections, and utilizes the application data in an unequal load balance scheme. This is achieved by analyzing the performance of three of the most widely used alternative-choice for multiple attributes decision making (MADM) methods. The analytical hierarchy process (AHP), along with a utility equation, is applied to the system model for unequal load balance solution. The proposed model is targeting an energy efficient mechanism which satisfies application needs. Moreover, it reveals an efficient transmission mechanism for a better quality of service, traffic management, and availability solutions. The simulation results show that the proposed system surpassed its former counterparts.

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“…More detailed information will be described in next part. (1) initialization: determine the relationship between RSUs and vehicles periodically (2) if S is covered by a RSU (3) deliver packets to RSU s in V2R mode else fuzzy-rule-based wireless transmission method vehicle-based short-term vehicle speed prediction (4) (1) find potential paths (5) (2) evaluate potential paths (6) (3) determine wireless transmission path (optimum) (7) S sends packets to RSU s (8) if RSU fails to receive packets after threshold time (9) select another path (sub-optimum) (10) go to step (7) else (11) end (12) RSU s sends packets to RSU d (13) if D is covered by a RSU (14) deliver packets to RSU d in V2R mode else machine learning system (15) (1) ML1 predicts D's turning direction (16) (2) ML2 predicts RSU n (highest possibility) (17) (3) ML3 predicts travelling path (18) two-way mode transfer fuzzy-rule-based wireless transmission method (19) if D fails to receive packets after threshold time (20) select RSU n again (second highest possibility) (21) go to step (17) else (22) end Algorithm 1…”

Section: Proposed Modelmentioning

confidence: 99%

“…Fuzzy logic, known for its ability to deal with complex and imprecise problems, is a very promising technology in such a dynamic and complex context [6]. Meanwhile, massive traffic data in the transport system have important guiding significance to data delivery [7].…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy‐Rule Based Data Delivery Scheme in VANETs with Intelligent Speed Prediction and Relay Selection

Zhou

Shi

et al. 2018

Wireless Communications and Mobile Computing

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Data delivery in vehicular networks (VANETs) is a challenging task due to the high mobility and constant topological changes. In common routing protocols, multihop V2V communications suffer from higher network delay and lower packet delivery ratio (PDR), and excessive dependence on GPS may pose threat on individual privacy. In this paper, we propose a novel data delivery scheme for vehicular networks in urban environments, which can improve the routing performance without relying on GPS. A fuzzy-rule-based wireless transmission approach is designed to optimize the relay selection considering multiple factors comprehensively, including vehicle speed, driving direction, hop count, and connection time. Wireless V2V transmission and wired transmissions among RSUs are both utilized, since wired transmissions can reduce the delay and improve the reliability. Each RSU is equipped with a machine learning system (MLS) to make the selected relay link more reliably without GPS through predicting vehicle speed at next moment. Experiments show the validity and rationality of the proposed method.

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Towards Reasoning Vehicles

Cited by 22 publications

References 86 publications

From 5G to 6G Technology: Meets Energy, Internet-of-Things and Machine Learning: A Survey

From 5G to 6G Technology: Meets Energy, Internet-of-Things and Machine Learning: A Survey

An Optimized Load Balance Solution for Multi-homed Host in Heterogeneous Wireless Networks

A Fuzzy‐Rule Based Data Delivery Scheme in VANETs with Intelligent Speed Prediction and Relay Selection

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