Alexandru Agache

Re-architecting datacenter networks and stacks for low latency and high performance

Modern datacenter networks provide very high capacity via redundant Clos topologies and low switch latency, but transport protocols rarely deliver matching performance. We present NDP, a novel data-center transport architecture that achieves near-optimal completion times for short transfers and high flow throughput in a wide range of scenarios, including incast. NDP switch buffers are very shallow and when they fill the switches trim packets to headers and priority forward the headers. This gives receivers a full view of instantaneous demand from all senders, and is the basis for our novel, high-performance, multipath-aware transport protocol that can deal gracefully with massive incast events and prioritize traffic from different senders on RTT timescales. We implemented NDP in Linux hosts with DPDK, in a software switch, in a NetFPGA-based hardware switch, and in P4. We evaluate NDPs performance in our implementations and in large-scale simulations, simultaneously demonstrating support for very low-latency and high throughput.

An Ontology-Based Dynamic Service Composition Framework for Intelligent Houses

In order to improve users ability to interact with devices in an intelligent house, we propose a platform for intelligent device composition, based on Service Oriented Architecture. In such an environment, devices can be controlled and monitored using Service invocations, or they can interoperate in order to fulfil complex tasks, using Service composition. As part of our platform, we define a language for dynamic service composition, called MetaBPEL. It extends the WS-BPEL 2.0 language with semantic information, and acts as an abstract workflow definition mechanism. Unlike BPEL and other conventional composition languages, MetaBPEL does not bind to actual service implementations, but merely describes capabilities that services must have, in order to participate in a workflow. This feature allows both workflow migration between different environments as well as service replacement without modifying the composition scheme. In the article, we describe the MetaBPEL structure and the associated creation, generalization and instantiation mechanisms.

A modeling method and declarative language for temporal reasoning based on fluid qualities

Current knowledge representation mechanisms focus more on providing a static description of a modeled universe and less on capturing evolution. Ontology modeling languages, such as OWL, have no inherent means for describing time or time-dependent properties. In such settings, time is usually represented along with other applicationdependent concepts, yielding complex models that are difficult to maintain, extend, and reason about. On the other hand, in imperative languages that allow the definition of time-dependent behavior and interactions such as WS-BPEL, the emphasis is on specifying the control flow in a service-oriented environment. In contrast, we argue that a declarative approach is more suitable. We propose a modeling method and a declarative language, designed for representing and reasoning about time-dependent properties. The method is applicable in areas such as ubiquitous computing, allowing the specification of intelligent device behaviour.

CloudTalk: Enabling Distributed Application Optimisations in Public Clouds

Clouds offer an opaque I/O API to their customers: details of the underlying resources (network topology, disk drives) or their current load are kept hidden. Tenants can profile the I/O performance in their VMs and optimise accordingly, but the side effect is increased load. Certain cloud providers try to discourage profiling by enforcing strict I/O isolation, at the cost of reduced utilisation in the average case. In this paper we challenge this status quo and propose CloudTalk, an API that allows tenants to communicate with the cloud provider and receive hints used to optimise their workloads. We have built a distributed implementation of CloudTalk that scales to hundreds of machines and provides significant performance benefits in many cases. Further, we have implemented changes to Hadoop and HDFS that use CloudTalk to decide which machines to use for task placement and replica selection. Our experiments in a local cluster and on Amazon EC2 show that CloudTalk helps improve performance by as much as two times for a wide range of scenarios.