A Balanced Dissemination of Time Constraint Tasks in Mobile Crowdsourcing: A Double Auction Perspective

Abstract

Mobile crowdsourcing (MCS) is gaining real attention in recent years as it has found widespread applications such as traffic monitoring, pollution control surveillance, locating endangered species, and many others. This paradigm of research is showing an interesting power of smart devices that are held by intelligent agents (such as human beings). In MCS, the tasks which are outsourced are executed by the task executors (intelligent agents carrying smart devices). In this paper, how overlapping tasks (with a deadline) can be disseminated in slots and leveraged as evenly as possible to the stakeholders (task executors or sellers) is addressed through a scalable scheduling (interval partitioning) and economic mechanism (double auction). It is proved that our mechanism is truthful and also shown via simulation that our proposed mechanism will perform better when the agents are manipulative in nature.