Distributed data aggregation is an important task, allowing the decentralized determination
of meaningful global properties, which can then be used to direct the execution of other …

Recently, the growing memory demands of embedding tables in Deep Learning
Recommendation Models (DLRMs) pose great challenges for model training and …

The growing memory demands of embedding tables in Deep Learning Recommendation
Models (DLRMs) pose great challenges for model training and deployment. Existing …

In the realm of large-scale Internet-of-Things applications, aggregating data using count-
based windows is a formidable challenge. Current methods, either centralized and slow or …

Aggregation operations are important in WSN applications. Since large numbers of
applications only require approximate aggregation results rather than the exact ones, some …

Sensor networks have been used in many surveillance systems, providing statistical
information about monitored areas. Accurate counting information (eg, the distribution of the …

Wireless Sensor Networks are composed of inexpensive, low powered micro-sensor nodes
capable of sensing, processing, and communicating with limited computational resources …

Sensor networks have received considerable attention in recent years, and are often
employed in the applications where data are difficult or expensive to collect. In these …

In Wireless Sensor Networks (WSN), data gathering using mobile sinks typically incurs
constant propagation of sink location indication messages to guide the direction of data …

Sensor networks have received considerable attention in recent years, and are employed in
many applications. In these applications, statistical aggregates such as Sum over the …