An Improved Stochastic Modeling of Opportunistic Routing in Vehicular CPS

Zeng, Deze; Guo, Song; Barnawi, Ahmed; Yu, Shui

doi:10.1109/tc.2014.2349509

Cited by 21 publications

(6 citation statements)

References 35 publications

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“…Cellular-based V2X Figure 2: Illustration of a heterogeneous MDVNET in an urban area either using a "hop-by-hop" mechanism or "store-and-forward" one [56]. The main difference between these two mechanisms is whether the intermediate vehicles forward the received packets immediately or carry them until the corresponding routing algorithm makes a forward decision [57]. In the existing research, unicast routing protocols have been investigated in two ways: greedy and opportunistic.…”

Section: B Routing Protocolsmentioning

confidence: 99%

Vehicular Communications: A Network Layer Perspective

Peng

Liang

Shen

et al. 2019

IEEE Trans. Veh. Technol.

251

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Vehicular communications, referring to information exchange among vehicles, pedestrians, and infrastructures, have become very popular and been widely studied recently due to its great potential to support intelligent transportation and various safety applications. Via vehicular communications, manually driving vehicles and autonomous vehicles can collect useful information to improve traffic safety and support infotainment services. In this paper, we provide a comprehensive overview of recent research on enabling efficient vehicular communications from the network layer perspective. First, we introduce general applications and unique characteristics of vehicular networks and the corresponding classifications. Based on different driving patterns of vehicles, we divide vehicular networks into two categories, i.e., manually driving vehicular networks and automated driving vehicular networks, and then discuss the available communication techniques, network structures, routing protocols, and handoff strategies applied in these vehicular networks. Finally, we identify the challenges confronted by the current vehicular communications and present the corresponding research opportunities. Index TermsVehicular communications; manually driving vehicles; autonomous vehicles; routing protocols; handoff strategies; communication technologies. from the perspective of the physical layer in [1]. Via enabling vehicles to exchange information with other vehicles (i.e., vehicle-to-vehicle, V2V), pedestrians (i.e., vehicle-to-pedestrian, V2P), and infrastructures (i.e., vehicle-to-infrastructure, V2I), vehicular communications are expected to support a variety of applications, including intelligent transportation and safety applications [2], [3]. However, due to the high mobility and complicated communications environments, it is very challenging to provide efficient vehicular communications to satisfy the different requirements, especially, higher reliability and lower latency for sharing safety-related information.Manually driving vehicular networks (MDVNETs), referring to communications among vehicles with only manually driving patterns, are one of the main applications of vehicular communications and have been widely considered in the existing works [4]. MDVNETs can help manually driving vehicles to improve the traffic safety and provide infotainment services to drivers and passengers [3].Owing to the advances in sensor technologies, wireless communications, computational power, and intelligent control, a new driving pattern, named automated driving, is gradually applied in vehicles, and then autonomous vehicles (AVs) are generated and begin to be test-driven on the roads. According to a report from the National Highway Safety Administration (NHTSA) [5], passenger vehicles can be classified into five distinct levels of autonomy, as shown in Table I.Manually driving vehicles mentioned in this paper refer to the vehicles with level 0 autonomy while AVs refer to vehicles with level 4 autonomy. It is expected that no human actions o...

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Section: B Routing Protocolsmentioning

confidence: 99%

Vehicular Communications: A Network Layer Perspective

Peng

Liang

Shen

et al. 2019

IEEE Trans. Veh. Technol.

251

View full text Add to dashboard Cite

show abstract

“…In such a network, all nodes in the network are always active. Under the circumstance of no channel conflict, the sender transmits data to the node nearest to the sink within its communication range, which is the classic shortest routing algorithm [29], [49], [50]. The advantage of this kind of network is that the delay of data transmission is minimal.…”

Section: A Data Collection In Wsns With Non-duty Cycle Modementioning

confidence: 99%

Adding Duty Cycle Only in Connected Dominating Sets for Energy Efficient and Fast Data Collection

et al. 2019

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In wireless sensor networks (WSNs), energy efficiency and low delay are two pivotal issues for data collection. Wireless sensor networks are composed of energy-constrained sensor nodes. While sensing the environment, the rapid transmission of data to the sink is critical for many applications. In order to save energy, the duty cycle based mode is adopted in most studies, but this method increases the data transmission delay. Thus, an Adding Duty Cycle Only in Connected Dominating Sets (ADCOCDS) approach is proposed in this paper, which can effectively reduce network energy consumption and delay. The main innovations of the ADCOCDS scheme are as follows: (1) Unlike the mode of the duty cycle for all nodes in the previous WSNs, in ADCOCDS scheme, we choose a part of nodes to construct as a connected dominating set, and these nodes adopt the mode of duty cycle. For other nodes in the network, the radio transmitter is turned off to save energy when there is no data to transmit, and when these nodes have data to send, they turn on the radio transmitter and send the data to nodes in the dominating set, then nodes in the dominating set transfer the data to sink. In ADCOCDS scheme, since only a small number of nodes adopt the duty cycle mode, the energy efficiency of the network is high; (2) In WSNs, we observed that the energy consumption of nodes in the near-sink area is higher than that in the far-sink area. Therefore, in the ADCOCDS scheme, we increase the duty cycle of nodes according to their energy consumption to reduce the delay. Through theoretical analysis and experimental results, the ADCOCDS scheme can effectively reduce energy consumption and delay by 12.09%-43.17% and 21.85%-57.96%, respectively, while improving network lifetime by 10.71%-24.13% compared with previous strategies.

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“…The basic algorithm, data management process, visualization technique, and operational interface they use are common to all GIS. The same algorithms and data can be applied to different systems [21]. Therefore, as long as the algorithm combination problem, business parameter input, and task scheduling are solved, the establishment and execution of new business processes can be completed quickly, the coupling degree of the geographic information service platform and the business system is improved, and the difficulty of developing a GIS business system is reduced [22].…”

Section: The On-demand Extended Model For Gis Data Processingmentioning

confidence: 99%

An On-Demand Scalable Model for Geographic Information System (GIS) Data Processing in a Cloud GIS

Zhang

et al. 2019

IJGI

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With the rapid development of information processing technology and continuously evolving technological hardware and software, the scale of spatial data has grown exponentially. This has necessitated that stricter requirements be placed on the way data is processed. The traditional single-machine centralized data processing method is gradually being replaced by the network-based cloud geographic information system (GIS) mode. However, the information processing method of the business system in the existing spatial information network environment is difficult to expand, which limits the application of the business system. This paper proposes an on-demand and extended model for the GIS data processing procedure that considers the three-way separation of algorithm development, business processes, and the operational interface, and can implement an on-demand expansion of business processes by process modeling the business and task scheduling the workflow engine. This can expand the scope of business systems and improve the efficiency of business system construction.

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An Improved Stochastic Modeling of Opportunistic Routing in Vehicular CPS

Cited by 21 publications

References 35 publications

Vehicular Communications: A Network Layer Perspective

Vehicular Communications: A Network Layer Perspective

Adding Duty Cycle Only in Connected Dominating Sets for Energy Efficient and Fast Data Collection

An On-Demand Scalable Model for Geographic Information System (GIS) Data Processing in a Cloud GIS

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