MIT engineers develop WiSwarm to prioritize wi-fi data transfer

LinkedIn +

When using drones to search for survivors within a disaster zone, or robots to for building inspections, it is crucial that the freshest data is used to enable survivors or hazards to be found. One issue, however, is that if several robots relay time-sensitive information over a wireless network simultaneously, a data traffic jam can occur. As a result, information which does get through, can often be too old and subsequently becomes unusable within a real-time report.

To overcome this, MIT engineers have developed a method to tailor any wireless network to handle a high load of time-sensitive data coming from multiple sources. The team’s new approach, called WiSwarm, configures a wireless network to control the flow of information from multiple sources while ensuring the network is relaying the freshest data.

The method – which was used to tweak a conventional wi-fi router – proved the tailored network could act like an efficient traffic cop, capable of prioritizing and relaying the freshest data to keep multiple vehicle-tracking drones on task. Furthermore, the process enables multiple robots to communicate over available wi-fi networks without having to carry bulky and expensive communications and processing hardware on board.

The authors of the MIT study include Vishrant Tripathi, Ezra Tal, Muhammad Shahir Rahman, Alexander Warren, Sertac Karaman and Eytan Modiano of the Laboratory for Information and Decision Systems (LIDS). Igor Kadota from Columbia University was also involved in devising the method.

“What happens in most standard networking protocols is an approach of first come, first served,” explained Tripathi. “A video frame comes in, you process it. Another comes in, you process it. But if your task is time-sensitive, such as trying to detect where a moving object is, then all the old video frames are useless. What you want is the newest video frame.”

“Age-of-information is a new metric for information freshness that considers latency from the perspective of the application,” added Modiano. “For example, the freshness of information is important for an autonomous vehicle that relies on various sensor inputs. A sensor that measures the proximity to obstacles in order to avoid collision requires fresher information than a sensor measuring fuel levels.”

By incorporating a last-in, first-out protocol for multiple robots working together on time-sensitive tasks, the MIT team aimed to prioritize the age of information. They aimed to do this using conventional wireless networks, as wi-fi is pervasive and doesn’t require bulky onboard communication hardware to access.

There is one large drawback of wireless networks, however. Wireless networks are distributed in nature and do not prioritize receiving data from any one source. A wireless channel can then quickly clog up when multiple sources simultaneously send data. Even if a last-in, first-out protocol is used, data collisions still occur. Furthermore, in a time-sensitive exercise, the system would break down.

To overcome this, the MIT team developed WiSwarm — a scheduling algorithm capable of running on a centralized computer and paired with any wireless network to manage multiple data streams and prioritize the freshest data.

Instead of trying to take in every data packet from every source all of the time, the algorithm works out which source in a network should send data next. That source (a drone or robot) would then observe the last-in, first-out protocol to send their freshest piece of data through the wireless network to a central processor.

Additionally, the algorithm determines which source should relay data next by assessing three parameters consisting of a drone’s general weight, or priority (for instance, a drone that is tracking a fast vehicle might have to update more frequently, and therefore would have higher priority over a drone tracking a slower vehicle); a drone’s age of information, or how long it’s been since a drone has sent an update; and a drone’s channel reliability, or likelihood of successfully transmitting data.

By multiplying the three parameters for each, the algorithm can schedule drones to report updates through a wireless network one at a time, without causing a data traffic jam. This ensures that the freshest data is provided to enable time-sensitive tasks to be conducted successfully.

The algorithm was tested by the team by using multiple mobility-tracking drones fitted with a small camera and a basic wi-fi-enabled computer chip. The drone used this to continuously relay images to a central computer rather than using a bulky onboard computing system. The team also programmed the drones to fly over and follow small vehicles moving randomly on the ground.

Once the team had paired the network with its algorithm, the computer was able to receive the freshest images from the most relevant drones. The computer then used these to send commands back to the drones to keep them on the vehicle’s track.

The team stated that when the researchers ran experiments with two drones, the method was able to relay data which was two times fresher. This resulted in six times better tracking compared to when the two drones carried out the same experiment with wi-fi alone.

When five drones and five ground vehicles were tested, wi-fi alone could not accommodate the heavier data traffic, and the drones quickly lost track of the ground vehicles. With WiSwarm, the network was better equipped and enabled all drones to keep tracking their respective vehicles.

“Ours is the first work to show that age-of-information can work for real robotics applications,” commented Tal.

The team envisages that in the near future, inexpensive and nimble drones may be capable of working in partnership and communicating over wireless networks to inspect buildings, agricultural fields, and wind and solar farms. In coming years, the team sees the method being essential for managing data streaming throughout smart cities.

“Imagine self-driving cars come to an intersection that has a sensor that sees something around the corner,” said Karaman. “Which car should get that data first? It’s a problem where timing and freshness of data matters.”

Share this story:

About Author


After spending six years working as a mechanic for various motorsport and high-end performance car companies, Callum joined UKi Media & Events in February 2020 as an assistant editor. In this role he uses his vast practical knowledge and passion for automotive to produce informative news pieces for multiple vehicle-related sectors. Currently, he is responsible for content across UKi Media & Events' portfolio of websites while also writing for the company's print titles.

Comments are closed.