1 research outputs found
eBPF-based Content and Computation-aware Communication for Real-time Edge Computing
By placing computation resources within a one-hop wireless topology, the
recent edge computing paradigm is a key enabler of real-time Internet of Things
(IoT) applications. In the context of IoT scenarios where the same information
from a sensor is used by multiple applications at different locations, the data
stream needs to be replicated. However, the transportation of parallel streams
might not be feasible due to limitations in the capacity of the network
transporting the data. To address this issue, a content and computation-aware
communication control framework is proposed based on the Software Defined
Network (SDN) paradigm. The framework supports multi-streaming using the
extended Berkeley Packet Filter (eBPF), where the traffic flow and packet
replication for each specific computation process is controlled by a program
running inside an in-kernel Virtual Ma- chine (VM). The proposed framework is
instantiated to address a case-study scenario where video streams from multiple
cameras are transmitted to the edge processor for real-time analysis. Numerical
results demonstrate the advantage of the proposed framework in terms of
programmability, network bandwidth and system resource savings.Comment: This article has been accepted for publication in the IEEE
International Conference on Computer Communications (INFOCOM Workshops), 201