… NiFi) stream processing workflow proposed in this paper is to first identify atomic tasks in a
workflow and then parallelize them. This is quite a trivial approach, since a stream processing …

… to enable distributed data processing within a cluster of edge devices, based on a stream
processing architecture. By pushing intelligence to the very edge of the network topology – that …

… Many edge devices are … stream processing applications using Cloud and edge resources
where certain tasks are performed at the edge for reducing the end-toend latency of processing …

… As the number of IoT devices increases, large amounts of data get … stream processing
optimization problem and illustrate how Amnis extends the current distributed stream processing …

… These devices are generating and consuming unprecedented amounts of data at the edges
… core of the infrastructure to process data. As the number of devices and the amount of data …

… edge computing for data stream processing. This paper surveys state of the art on stream
processing … features of cloud computing in stream processing. Resource elasticity allows for an …

… The aforementioned approach for the stream processing … the network edge and stream
processing applications hosted … of connected devices in the network edge (50 billion devices by …

… data in IoT devices). Operators with stringent requirements are placed on the edge while non-…
with up to 25 devices. The work also ignores states when computing the end-toend latency. …

… With the increasing computational power of mobile processors, we believe these edge
devices that are located closer to the end users, have potential that is not being fully utilised [19]. …

… These streaming nodes collect data from sensors of … , an edge device can host both a CQELS
node and a streaming node, but we can assume they communicate via an internal process. …