Programmable data plane technologies enable the systematic reconfiguration of the low-
level processing steps applied to network packets and are key drivers toward realizing the …

Identifying the" heavy hitter" flows or flows with large traffic volumes in the data plane is
important for several applications eg, flow-size aware routing, DoS detection, and traffic …

Data centers are widely used for big data analytics, which often involve data-parallel jobs,
including query and web service. Meanwhile, cluster frameworks are rapidly developed for …

Recent years, Software Defined Routers (SDRs)(programmable routers) have emerged as a
viable solution to provide a cost-effective packet processing platform with easy extensibility …

Network performance monitoring today is restricted by existing switch support for
measurement, forcing operators to rely heavily on endpoints with poor visibility into the …

The trend towards simple datacenter network fabric strips most network functionality,
including load balancing, out of the network core and pushes it to the edge. This slows …

Memory disaggregation promises transparent elasticity, high resource utilization and
hardware heterogeneity in data centers by physically separating memory and compute into …

Many algorithms for congestion control, scheduling, network measurement, active queue
management, and traffic engineering require custom processing of packets in the data plane …

Programmable packet scheduling enables scheduling algorithms to be programmed into the
data plane without changing the hardware. Existing proposals either have no hardware …

Remote Direct Memory Access (RDMA) is widely used in high-performance computing
(HPC) and data center networks. In this paper, we first show that RDMA does not work well …