Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles

Wan, Jiafu; Liu, Jianqi; Shao, Zehio; Vasilakos, Athanasios V.; Imran, Muhammad; Zhou, Keliang

doi:10.3390/s16010088

Cited by 215 publications

(99 citation statements)

References 29 publications

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“…At the same time, the authors did research on the optimal constrained path routing in WMNs in the previous paper [20]; following that, the Fast Minimum Path Cost Heuristic (FMPH) algorithm was put forward to deal with the MCMR problem in WMNs. Recently, Athanasios Vasilakos and his co-authors proposed the cross-layer protocol to decrease the delay [21][22][23][24][25] and devised a novel energy-saving algorithm. Alasaad and his co-authors argued for a ring-based multicast routing topology with support from infrastructure nodes for group communications in WMNs [26], and then developed heuristic algorithms to deal with it.…”

Section: Introductionmentioning

confidence: 99%

A Novel QoS Provisioning Algorithm for Optimal Multicast Routing in WMNs

Yang¹,

Chen²

2016

Future Internet

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Abstract:The problem of optimal multicast routing in Wireless Mess Networks (WMNs) with Quality-of-Service (QoS) provisioning, which is Non-Deterministic Polynomial (NP)-complete, is studied in this paper. The existing algorithms are not very efficient or effective. In order to find an approximation optimal solution for WMNs in feasible time from source to the set of destination nodes, combining the previous deterministic algorithm with the well-known Minimum Path Cost Heuristic (MPH) algorithm, a novel multicast heuristic approximation (NMHA) algorithm with QoS provisioning is proposed in this paper to deal with it. The theoretical validations for the proposed algorithm are presented to show its performance and efficiency. After that, the random static networks with different destination nodes are evaluated. Simulations in these networks show that the proposed algorithm can achieve the approximate optimal solution with the approximation factor of 2(1 + ε)(1´1/q) and the time complexity of O(qmn 2 τ K´1 ).

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Section: Introductionmentioning

confidence: 99%

A Novel QoS Provisioning Algorithm for Optimal Multicast Routing in WMNs

Yang¹,

Chen²

2016

Future Internet

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“…Unfortunately, the existing data collection system, VANETs, and the traditional traffic flow prediction model [3] are far from sufficient to solve abovementioned issues. For example, VANETs support a variety of services and achieve success in a certain aspect such as vehicular collision avoidance system using vehicle-to-vehicle or vehicle-to-infrastructure communication [4].…”

Section:  Traffic Prediction and Real-time Responsivenessmentioning

confidence: 99%

High-Efficiency Urban Traffic Management in Context-Aware Computing and 5G Communication

et al. 2017

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Abstract:With the increasing number of vehicle and traffic jams, the urban-traffic management is becoming a serious issue. In this article, we propose novel four-tier architecture for urban-traffic management with the convergence of vehicle ad hoc networks (VANETs), 5G wireless network, software-defined network (SDN), and mobile-edge computing (MEC) technologies. The proposed architecture provides better communication and rapider responsive speed in a more distributed and dynamic manner. The practical case of rapid accident rescue can significantly cut down the time for rescue. Key technologies with respect to vehicle localization, data pre-fetching, traffic lights control, and traffic prediction are also discussed. Obviously, the novel architecture shows noteworthy potential for alleviating the traffic congestion and improving the efficiency of urban-traffic management.

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“…In [26][27][28], the authors presented traffic congestion management strategies using crowd sensing technology.…”

Section: Related Workmentioning

confidence: 99%

Internet data budget allocation policies for diverse smartphone applications

Rahman

Prima

Razzaque

et al. 2016

J Wireless Com Network

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In recent times, there has been a significant growth in the number of smartphone users and number and types of mobile applications (apps). Such a trend has resulted in increased Internet data consumption, particularly for users of "data hungry" apps. Thus, smartphone apps should be allocated to their required budget to minimize resource wastage without compromising on user's quality of experience. In this paper, we develop a prioritized and dynamic budget allocation policy framework for ensuring an optimal budget allocation to each app as well as improving system performance. We formulate the optimal Internet data budget management (O-IDM) problem as a mixed-integer nonlinear programming (MINLP) problem, which maximizes the resource utilization and minimizes user penalties. We also employ runtime monitoring technique to estimate future bandwidth utilization so as to ensure budget reservation as close as to the required amount. A heuristic Internet data budget management algorithm (H-IDM) is also presented, which is designed to reduce time complexity and computational overhead of the O-IDM system. The experimental results from test-bed implementation demonstrate the effectiveness of the proposed IDM systems, in comparison to state-of-the-art approaches.

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Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles

Cited by 215 publications

References 29 publications

A Novel QoS Provisioning Algorithm for Optimal Multicast Routing in WMNs

A Novel QoS Provisioning Algorithm for Optimal Multicast Routing in WMNs

High-Efficiency Urban Traffic Management in Context-Aware Computing and 5G Communication

Internet data budget allocation policies for diverse smartphone applications

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