Our new paper on producer selection in wireless edge environments has been published at the ACM Conference on Information-Centric Networking (ICN). The paper, titled “OPSEL: optimal producer selection under data redundancy in wireless edge environments,” was co-authored with Stony Brook PhD student Mohammed Elbadry and Professor Fan Ye.
Abstract: In wireless edge environments, data redundancy among multiple neighboring nodes is common due to the need to support application performance, mitigate faults, or the intrinsic nature of applications (e.g., AR/VR, edge storage). Further, under data centric paradigms (e.g., Named Data Networking (NDN)), consumers that request the same data may leverage multicast so data are sent only once (e.g., VR games with data cached at multiple edge nodes). Naive strategies such as selecting a random neighbor or the prevailing wisdom of choosing the one with the strongest received signal strength (RSSI) cause more severe loss than other available producers. In this paper, we propose OPSEL, a single-hop dynamic producer(s) selection protocol that enables single and multiple consumers to continuously identify the optimal producer(s) (e.g., lowest loss) under constantly varying medium conditions. When Data is available single-hop, OPSEL’s goal is to have the minimum number of producers sending to all consumers and meeting their performance needs without explicit coordination messages. Experiments on a real prototype show that OPSEL is 3% away in loss rate and has the same latency as the theoretical ideal, while naive timer methods can incur up to 60% more loss and 2-3× latency.
This entry was posted on September 06, 2022.