Low Latency V2X Applications and Network Requirements: Performance Evaluation

Amjad, Zubair; Sikora, Axel; Hilt, Benoit; Lauffenburger, Jean-Philippe

doi:10.1109/ivs.2018.8500531

Cited by 42 publications

(33 citation statements)

References 12 publications

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“…Therefore, there are three transmissions at the physical layer: two in the control channel and one in the data channel. Those values are in line with the latency requirements for V2X applications, which normally range between 10 and 100 ms [35], [36].…”

Section: B Latencysupporting

confidence: 70%

An Edge-Based Framework for Enhanced Road Safety of Connected Cars

et al. 2020

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In this paper, we present an enhanced Collision Avoidance (eCA) service that leverages vehicle connectivity through a cellular network to avoid vehicle collisions and increase road safety at intersections. The eCA service is assumed to be deployed at the edge of the network, thus curbing the latency incurred by the communication process. The core of the eCA service is composed of a Collision Avoidance Algorithm (CAA), and a Collision Avoidance Strategy (CAS). The former predicts the vehicle's future trajectory through the positional information advertised by periodic beacons and detects if two vehicles are on a collision course. The latter decides which of the vehicles potentially involved in a collision should yield. The vehicles are then notified of both the impending danger and of the actions needed to avoid it. We have simulated our solution using SUMO (Simulation of Urban MObility) and ns-3 (network simulator 3) with the LENA (LTE-EPC Network simulAtor) framework on a Manhattan-grid road topology, and observed its good performance in terms of avoided collisions percentage as a function of vehicle speed and different vehicles densities. INDEX TERMS Advanced driver assistance systems, automated vehicles, collision avoidance, edge computing, intelligent vehicles, vehicle safety.

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Section: B Latencysupporting

confidence: 70%

An Edge-Based Framework for Enhanced Road Safety of Connected Cars

et al. 2020

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“…As illustrated in Section IV, this work adopts an LTE-based V2X system with three different types of services, namely CAM service, DENM service, and media downloading service. The delay tolerance threshold for these services are set at 20, 50, and 150 ms respectively [42], [46], [47]. Moreover, it is assumed that the computational requirements of the CAM service are that of a medium sized virtual machine (VM) [51], [52].…”

Section: A Simulation Setupmentioning

confidence: 99%

Edge-Enabled V2X Service Placement for Intelligent Transportation Systems

Moubayed

Shami

Heidari

et al. 2021

IEEE Trans. on Mobile Comput.

134

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Vehicle-to-everything (V2X) communication and services have been garnering significant interest from different stakeholders as part of future intelligent transportation systems (ITSs). This is due to the many benefits they offer. However, many of these services have stringent performance requirements, particularly in terms of the delay/latency. Multi-access/mobile edge computing (MEC) has been proposed as a potential solution for such services by bringing them closer to vehicles. Yet, this introduces a new set of challenges such as where to place these V2X services, especially given the limit computation resources available at edge nodes. To that end, this work formulates the problem of optimal V2X service placement (OVSP) in a hybrid core/edge environment as a binary integer linear programming problem. To the best of our knowledge, no previous work considered the V2X service placement problem while taking into consideration the computational resource availability at the nodes. Moreover, a low-complexity greedy-based heuristic algorithm named "Greedy V2X Service Placement Algorithm" (G-VSPA) was developed to solve this problem. Simulation results show that the OVSP model successfully guarantees and maintains the QoS requirements of all the different V2X services. Additionally, it is observed that the proposed G-VSPA algorithm achieves close to optimal performance while having lower complexity. 1) Communication Modes: To cover all possible on-road interactions, the 3GPP project proposed four different communication modes. This includes vehicle-to-network (V2N), vehicle-to-infrastructure (V2I), vehicle-to-vehicle (V2V), and vehicle-to-pedestrian (V2P) communication [5] as shown in Fig. 2. Depending on the service or application, a communication mode can be chosen. A brief overview of each of these communication modes is provided below: a-V2N Communication: V2N communication refers to the communication between a vehicle and a V2X application server. This is typically done using a cellular network such as an LTE network [9], [10]. Through this connection, different services such as infotainment, traffic optimization, navigation, and safety can be offered [11], [12].

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“…On the PHY layer, sTTI and reduced processing time belong to the second step towards latency reduction included in Release 15. The performance of sTTI and SPS as potential techniques to support latency-critical use cases is evaluated in our previous works [26,27]. Transmission time interval lengths of two Orthogonal Frequency Division Multiplexing (OFDM) symbols (2-os) and 7-os together with 14-os legacy TTI are used in this work.…”

Section: State Of the Art On Latency Reductionmentioning

confidence: 99%

“…In our previous work [26], we evaluated control-plane latency of LTE-M UE category with a realistic RA model. Further details about realistic ns-3 RA model can be found in [34].…”

Section: Simulation Setupmentioning

confidence: 99%

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Latency reduction for narrowband URLLC networks: a performance evaluation

et al. 2021

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Fifth-generation (5G) cellular mobile networks are expected to support mission-critical low latency applications in addition to mobile broadband services, where fourth-generation (4G) cellular networks are unable to support Ultra-Reliable Low Latency Communication (URLLC). However, it might be interesting to understand which latency requirements can be met with both 4G and 5G networks. In this paper, we discuss (1) the components contributing to the latency of cellular networks and (2) evaluate control-plane and user-plane latencies for current-generation narrowband cellular networks and point out the potential improvements to reduce the latency of these networks, (3) present, implement and evaluate latency reduction techniques for latency-critical applications. The two elements we detected, namely the short transmission time interval and the semi-persistent scheduling are very promising as they allow to shorten the delay to processing received information both into the control and data planes. We then analyze the potential of latency reduction techniques for URLLC applications. To this end, we develop these techniques into the long term evolution (LTE) module of ns-3 simulator and then evaluate the performance of the proposed techniques into two different application fields: industrial automation and intelligent transportation systems. Our detailed evaluation results from simulations indicate that LTE can satisfy the low-latency requirements for a large choice of use cases in each field.

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Low Latency V2X Applications and Network Requirements: Performance Evaluation

Cited by 42 publications

References 12 publications

An Edge-Based Framework for Enhanced Road Safety of Connected Cars

An Edge-Based Framework for Enhanced Road Safety of Connected Cars

Edge-Enabled V2X Service Placement for Intelligent Transportation Systems

Latency reduction for narrowband URLLC networks: a performance evaluation

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