A software design and algorithms for multicore capture in data center forensics

Abstract

With rapid dissemination of cloud computing, data centers are quickly turning into platforms that host highly heterogeneous collections of services. Traditional approach to security and performance management finds it difficult to cope in such environments. Specifically, it is becoming increasingly difficult to capture and process all the necessary information at data centers in real time, where packet capture at data center gateways can serve as a practical example. This paper proposes a generic design for capturing and processing information on multicore architectures. The two main parts of the proposal are (1) the optimization formulation for distributing tasks across cores and (2) practical design and implementation of a shared memory which can be used for communication between processes in a non-traditional way that does not require memory locking or message passing.

Performance Management of Cloud Populations via Cloud Probing

“…Active probing is distinct from passive monitoring which is mostly conducted via packet traffic analysis. Passive monitoring also has a range of practical uses, from packet and flow classification [3], to e2e QoS classification for user communities (o2m and m2m patterns) [8], to the advanced high-performance methods that apply multicore hardware to online analysis of high-rate packet traffic [7]. Specifically in clouds, passive monitoring is part of the topic of VM workload classification [5] and a more generic methodology for inferring VM performance from traffic and other workloads [6].…”