An optimal multiple stopping rule–based cooperative downloading scheme in vehicular cyber-physical systems

Abstract

In vehicular cyber-physical systems, vehicular users are the edge nodes which are far away from the network core. Content accessing and downloading for vehicular users are expected to heavily rely on the deployment of RoadSide Units in vehicular cyber-physical systems. Although vehicular users can obtain a good content downloading service in the coverage of RoadSide Units, user experience will get worse in highway scenarios, where RoadSide Units are sparsely deployed at service areas or gas stations. In other words, the download process has a property of intermittent connectivity because many no-signal areas (dark areas) exist on the road. In this article, we try to address such shortcomings by exploiting other edge nodes (vehicles) to download contents for clients in dark areas. Considering the cooperation intention of vehicles, we first propose an incentive mechanism to stimulate vehicles to participate in cooperative downloading. Next, with an objective of maximizing the utilization of benefits, we formulate the cooperative vehicle selection problem as an optimal multiple stopping problem and derive the optimal multiple stopping rule for cooperative downloading. Finally, an extensive simulation study has been performed to investigate the effectiveness of our scheme. The results reveal the impact of different parameters on system requirements and demonstrate that the proposed scheme can maximize the throughput of content downloading in dark areas.

An advertisement dissemination strategy with maximal influence for Internet-of-Vehicles

“…which is consistent with Case 3 in equation ( 5). If v is v 8 , we can easily draw that I(9, 8) = I(9) + I(8) À i (8) (9) À i (9) (8) corresponds to Case 2. Finally, it is obvious that I(9, 1) = I(9…”

“…Each vehicle is equipped with an on-board-unit (OBU) for communications with other vehicles and RSUs. 8,16 Let the communication range of the vehicle and the RSU be R A o and R A s , respectively. Assume there exists a controller alongside each RSU in charge of tracking vehicle locations, communications between vehicles within R A s and between vehicles and the RSU.…”

“…It has provided a wide range of services to improve transportation safety, efficiency, and comfort. 6 The existing works on mobile-edge computing for IoV focus on the downloading and off-loading, 7,8 efficient resource allocation, 9,10 date integrity analysis, 11,12 secure data sharing, 13,14 and privacy preserving analysis. 15 IoV is composed of cloud servers and a vehicular ad hoc network (VANET), where the VANET consists of vehicles and road side units (RSUs).…”

BMCGM: A Behavior Economics-Based Message Transmission Cooperation Guarantee Mechanism in Vehicular Ad-hoc NETworks

“…The rewards received by the nodes are determined by factors such as the number of transmission messages and Time To Live (TTL). In Reference [ 21 ], the authors proposed an incentive-based collaborative content download mechanism, the incentives obtained by the nodes are determined by the combination of rewards and consumption to transmit the content. In Reference [ 22 ], the authors studied a network coding-based message forwarding mechanism and constructed an incentive matrix to motivate relay nodes to forward message.…”

“…The above-mentioned incentive-based and reputation-based mechanisms are mostly based on the expected utility theory of traditional economics, such as mechanisms proposed in Reference [ 11 , 12 , 13 , 14 , 20 , 21 , 22 , 23 ]. Those mechanisms assumed that nodes are independent of each other and each decision behavior of a node depends on the utility value itself and does not affected by the decision motivation of other nodes.…”