Improving timeliness of information through replicating requests

The Internet of Things has created an influx of data-generating devices. Applications that use these devices require the generated data to be transmitted in a timely manner. In this paper, we consider a Pull model, where remote clients will send requests to retrieve the information generated by multiple sources from the same random process. We assume that the update processes and response times of different sources are different. The timeliness, measured by age of information, depends not only on the freshness of information at the sources but also on the response times. Getting information from a fresh source with a large response time may lead to a larger age of information compared to getting information from a slightly less fresh source with a much smaller response time. Hence, an important objective is to optimize the timeliness of information obtained by the clients, accounting for the tradeoff between the freshness at the sources and the response times. We propose a replication scheme that improves age of information by replicating requests to multiple sources and waiting for a certain number of responses. We show through simulation that depending on the system parameters, the number of responses to wait for could be different for optimizing the information timeliness.