Modern latency-sensitive applications such as real-time multi-camera video analytics
require networked computing to meet the time constraints. We present Jupiter, an open …

We provide a highly-efficient solution to the classical problem of scheduling task graphs
corresponding to complex applications on distributed computing systems. A number of …

The amalgamation of multiple Edge and Cloud clusters into an Edge-Cloud continuum
requires efficient scheduling techniques to cope with high numbers of infrastructure nodes …

Collaborative edge computing (CEC) is an emerging paradigm enabling sharing of the
coupled data, computation, and networking resources among heterogeneous geo …

Scheduling diverse applications in large, shared clusters is particularly challenging. Recent
research on cluster scheduling focuses either on scheduling speed, using sampling to …

Executing complex, burst-parallel, directed acyclic graph (DAG) jobs poses a major
challenge for serverless execution frameworks, which will need to rapidly scale and …

While there have been several proposals of high-performance global computing systems,
scheduling schemes for the systems have not been well investigated. The reason is …

We present Eagle, a new hybrid data center scheduler for data-parallel programs. Eagle
dynamically divides the nodes of the data center in partitions for the execution of long and …

The performance variation of cloud resources makes it difficult to run certain scientific
applications in the cloud because of their unique synchronization and communication …

Scheduling is essentially a decision-making process that enables resource sharing among a
number of activities by determining their execution order on the set of available resources …