# Next-Generation Payment System for Device-to-Device Content and Processing Sharing
## 1 Introduction  
Recent decades have witnessed a huge and sharp increase in the transmission of multimedia data. Although this is a direct consequence of the advances in communication technologies, the increase in the need for larger bandwidth, higher data rates, and larger processing power have surpassed improvements in the underlying technologies. The rapid increase in the need for higher data rates and better processing power has led researchers to consider unused resources at the edge of the networks to improve the performance of end user devices. A device can speed up the execution of its tasks by using the idle processing power of the devices in its proximity. Internet Service Providers can utilize the device-to-device (D2D) data transmission concept [1] to reduce data traffic load on its servers, backbone network, and access points, as well as to reduce the latency of accessing resources, which is meaningful especially for services with low latency demands. D2D data delivery can be used to deliver data from an access point to a single device and relay it to other requesting devices in the same network. Making use of these idle resources, however, comes with its problems [2], namely the following: coordination and housekeeping, privacy concerns, and unwillingness of the nodes to share their resources. In this study, we propose a D2D data delivery framework that employs a cryptocurrency-based payment system to provide incentives for sharing unused bandwidth and computation resources between devices. Data streaming, specifically bulky multimedia data such as high definition videos requires vast bandwidth. D2D data transmission facilitates these types of applications. The requesting device sends its request to the access point, which maintains a list of current users of the stream. If a device downloading the stream is interested in providing it to the devices in its signal range, the access point informs both devices to establish the connection. Another important parameter regarding multimedia communications is latency, which can also be considered one of the major reasons hindering the usage of Internet of Things (IoT) in time-restricted applications or applications running on networks with limited bandwidth connections where the latency mainly stems from sending data to cloud servers and processing them there. Some applications include data coming from thousands of sensors, which report the current status of the systems under control for which transmission to the cloud is not necessary. As a solution to this problem, processing at local servers has been proposed. This solution entails the usage of micro-processing power available at end-user devices in a distributed form. It encourages end users to share the processing power of their devices in a local network, where the initial processing of data can be carried out, and the need for forwarding the data to cloud will mostly be eliminated. Imagine that you have tens of sensors collecting data from a building's security system. The use of local computing power of a node within the cell would help you to process raw data with the ability to access them at high speeds. Then, the peer would send a report (processed result) to the owner of the data, which then could be sent to the network operation center. Such scenarios are the promise of Edge Computing. Edge Computing [3] involves assigning a task to a device, processing the task, and sending back the results to the requester. In a similar manner to data sharing, edge processing requires scheduling, solving security and privacy problems, and, more importantly, providing incentives for the owners of the devices to share their computing resources. Edge computing incentive system is one of the use-cases that we consider for our proposed system. P2P video streaming systems suffered the mechanisms of managing incentives before the rise of block-chain based systems [4; 5].