## 2 Related Work
[13] proposed a method for reducing cellular traffic by uploading only image data that are requested by drivers to a data server. In their target system, cars upload image data that they take with onboard cameras to the server, and the server provides the image data of a location requested by a driver. They propose a method in which the server can find cars that hold necessary image data efficiently and ask one of the cars to upload the necessary image data by having cars exchange metadata about an image (e.g., the location where and time when the image was acquired) through D2D communication and by having the cars report to the server the metadata about themselves and the cars next to them. Their method handles image data taken and retained by cars spontaneously, and cars send metadata about their image data to the server with the help of D2D communication. They do not mention how to apply their approach to pull-type RevAuc. [PERSON] et al. [14] proposed an MCS method in which a mobile host requesting data sends information on a data request and payable reward to a mobile host (MH-A) that it communicates with via D2D communication while moving around. The requester receives information on the quality of data that MH-A can provide and determines whether to ask MH-A to send data. They propose an algorithm for a requester to determine which mobile hosts it will ask to obtain and transmit data. The method proposed in [14] has two constraints. One is that it can only deal with data requests by mobile hosts. Another is that current data at a location far away from the current location of the data requester cannot be obtained because the data requester tries to find mobile hosts only via D2D communication. These constraints impose a restriction on the location of a POI. Thus, their method is applicable only to some of the services providing current sensing data. [PERSON] et al. [15] proposed a crowdsensing algorithm in which mobile hosts obtain data at POIs and aggregate data received from other mobile hosts through D2D communication while relaying data to an access point, which acts as a server collecting data. The incentive given to a mobile host is determined by the value of the contribution made by the mobile host for obtaining data. Their algorithm determines which mobile hosts should obtain data and how obtained data should be aggregated and relayed to the access point through D2D communication under the condition that the movement of mobile hosts can be predicted. They did not mention how a server can send information to mobile hosts with less cellular traffic nor how to apply their method to pull-type RevAuc. [PERSON] et al. [16] proposed a crowdsensing algorithm that collects data obtained by mobile hosts spontaneously (i.e., without prior knowledge of a POI) to a server through D2D communication with incentives. A mobile host can relay data received from another mobile host via D2D communication. They propose a lightweight joint sensing rate control and dynamic routing algorithm in a D2D network, OptMPSS. They also proposed an algorithm for determining incentives for mobile hosts, Backpressure Meets Taxes. They did not mention how to carry out pull-type RevAuc with their method. [PERSON] et al. (2017) proposed an algorithm to determine which mobile hosts are to participate in MCS to minimize the cellular communication cost under the condition that some mobile hosts pay based on the amount of cellular traffic that they use, that is, pay as you go (PAYG), and other mobile hosts pay a constant fee regardless of the amount of cellular traffic, that is, pay monthly (PAYM). They try to minimize the cellular communication cost by uploading data to a server via PAYM hosts as much as possible, while PAYG hosts relay data to PAYM hosts through D2D communication. They did not mention how to carry out pull-type RevAuc with their method. Additionally, their method can be used only when PAYM hosts exist in a system. [PERSON] et al.