For wireless networks that share time-sensitive information on the fly, it's not enough to transmit data quickly: that data also needs to be fresh. Consider the many sensors in your car. While it may take less than a second for most sensors to transmit a data packet to a central processor, the age of that data may vary depending on how frequently a sensor is relaying readings. In an ideal network, these sensors should be able to transmit updates constantly, providing the freshest, most current status for every measurable feature, from tire pressure to the proximity of obstacles. But there's only so much data that a wireless channel can transmit without completely overwhelming the network.
How, then, can a constantly updating network of sensors, drones, or data-sharing vehicles, minimize the age of the information that it receives at any moment, while at the same time avoiding data congestion?
Engineers in MIT's Laboratory for Information and Decision Systems are tackling this question and have come up with a way to provide the freshest possible data for a simple wireless network. They say their method may be applied to simple networks, such as multiple drones that transmit position coordinates to a single control station, or sensors in an industrial plant that relay status updates to a central monitor.
Eventually, the team hopes to tackle even more complex systems, such as networks of vehicles that wirelessly share traffic data. Congestion information that is shared wirelessly should be as fresh as possible — If it's dated, you might make the wrong decision.
Traditional networks are designed to maximize the amount of data that they can transmit across channels and minimize the time it takes for that data to reach its destination. Only recently have researchers considered the age of the information — how fresh or stale information is from the perspective of its recipient.
The motivation for working on this problem arose when Eytan Modiano, professor of aeronautics and astronautics, was thinking about unmanned aerial vehicles (UAVs) that are moving around in an environment. They need to exchange position information often enough to avoid colliding with one another.
In this paper, Modiano's team looked for ways to provide the freshest possible data to a simple wireless network. They modeled a basic network, consisting of a single data receiver, such as a central control station, and multiple nodes, such as several data-transmitting drones.
The researchers assumed that only one node can transmit data over a wireless channel at any given time. They wanted to determine which node should transmit data at which time, to ensure that the network receives the freshest possible data, on average, from all nodes. Since they were limited in bandwidth, they had to be selective about what and when nodes were transmitting. Their problem was how to minimize age.
The team's solution lies in a simple algorithm that essentially calculates an “index” for each node at any given moment. A node's index is based on several factors: the age, or freshness of the data that it's transmitting; the reliability of the channel over which it is communicating; and the overall priority of that node. For example, there may be a more expensive drone or a faster drone. Nodes with a higher priority, a more reliable channel, and older data, are assigned a higher index, versus nodes that are relatively low in priority, communicating over spottier channels, with fresher data.
A node's index can change from moment to moment. At any given moment, the algorithm directs the node with the highest index to transmit its data to the receiver. In this prioritizing way, the team found that the network is guaranteed to receive the freshest possible data on average, from all nodes, without overloading its wireless channels.
The team calculated a lower bound, meaning an average age of information for the network that is fresher than any algorithm could ever achieve. They found that their algorithm performs very close to this bound — that it is close to the best that any algorithm could do in terms of providing the freshest possible data for a simple wireless network.
The team is planning to test its index scheme on a simple network of radios, in which one radio may serve as a base station, receiving time-sensitive data from several other radios. The group is also developing algorithms to optimize the age of information in more complex networks. They intend to look beyond just one base station, to a network with multiple base stations, to see how that interacts.