SCARIe on network-aware Grids
SCARIe is a Grid-based software correlator for radio-telescope images requires high-throughput communication, but also specific services such as soft real-time or constant throughput. In addition, the application needs to claim/release resources on-the-fly as result of an optimization process.
Processing a telescope signal requires high
bandwidth due to the high sample rate used by the telescopes. Currently, SCARIe application handles the telescope signal by using
TCP streams between nodes, but other communication protocols such as RTP could
be implemented, too.
Figure 1. Distribute the SCARIe application on a grid: one input node for each telescope to distribute the workload, a certain amount of correlator nodes for signal processing, and one single output node for merging the results.
Although the first experiments done with SCARIe in DAS3 grid [SC08] worked for the minimal setup (4 telescopes streaming 256Mbps each, see Figure 1), one of the most important problem of SCARIe on grid relates to the networking capabilities, especially when going to higher data rates. Despite there is 1Gbps and 10Gbps networking capabilities in grid, the network does not provide a constant throughput for SCARIe application due to the unpredictable bandwidth usage by other nodes, too. Therefore, the nodes were statically assigned to the experiment by setting up firewalling rules.
The future demands of SCARIe application already envision using of 32 telescopes, each streaming up to 4Gbp. Moreover, the more telescopes participate in an experiment, the more flexible the system has to become in order to cope with the incoming/outgoing of telescopes during an experiment (Earth rotates and only a part of the telescopes can observe the target on the sky). In order to allow SCARIe application running on grids with such future demands, we need to provide the following grid characteristics:
· Constant throughput between the nodes involved in SCARIe application;
· Flexibility in choosing specific network characteristics to be guaranteed such as low-delay, high throughput, etc;
· Ability to add/remove nodes on-the-fly during the experiment as part of an optimization process due to the change in the application requirements in terms of both networking and computational resources.
A grid could provide such networking characteristics if the network resources are integrated into the grid middleware. Hence, network resources can be claimed dynamically by any application on-demand, similar to the computational resources are in used nowadays.
Network resource control in Grid middleware
We propose to provide control over network resources in distributed computing by (1) enhancing a grid middleware with a network broker and (2) use a traffic manipulation system, called streamline, installed in every distributed node.
WS-VLAM (http://staff.science.uva.nl/~gvlam/wsvlam) is a grid workflow execution environment which support coordinated execution of distributed Grid-enabled components combined in a workflow. Each Grid application is encapsulated in a container “NAME”, which takes care of state updates to the workflow system and provides an execution environment that allows the manipulation of various aspects of the application. For example, the container can implement a socket interposing mechanism to insert tokens in traffic.
1 - User deploys an experiment: application & basic infrastructure requirements;
2 – WS-VLAM maps the experiment using Actuator onto available Grid resources which were detected by Profiler;
3 - Control loops may occur in which WS-VLAM is a controller to adjust the resources such as to solve the applications demands regardless of the environment changes;
4 - Broker manages the computational resources;
5 - NetBroker programs the networking infrastructure of Grid;
Each grid node supports the applications running under WS-VLAM supervision and provides the application-specific network services through application-components ACs as supported by network elements NEs.
Streamline (http://netstreamline.org) is a software package that allows traffic manipulation at different levels from sockets down to IP packets and Ethernet frames. Streamline operates at both spaces: kernel and user spaces. A host runs the Streamline as a kernel module that can be controlled via a specific interface SLCLI in order to set needed rules to manipulate the IP packets. A host can run a “SL monitor” that can receive remote commands from “SL controller”.
For the purpose of testing the proposed solution we designed and implement a small testbed showing a minimal Grid in which 8 nodes are interconnected through 2 networks, as follows: a default network uses a shared 1Gbps gigabit switch and a second network uses a network processor unit programmed to route IP packets at 1Gbps, too.
A first experiment measures the network performances between applications interconnected in pairs (e.g., DAS1-DAS2, DAS3-DAS4, DAS5-DAS6, DAS7-DAS8) in the following scenario:
1 – WS-VLAM management starts applications and setup the paths one by one on the default network (10.1.0.x);
2 – When measured network performance (throughput) decreased below an application threshold, WS-VLAM receives an application notice and hence, it starts “offloading” the paths from 10.1.0.x network onto 10.10.0.x network;
Due to the shared 1Gbps switch, the per-path performance decreases while more paths are established and exchange data traffic at maximum. The switch offers one single network service: best-effort. We show that we need to use a grid middleware that controls the network resources in grids in order to offer specific network services on behalf of the applications.
A second experiment shows how VLAM manages network resources on behalf of grid-applications (a send/receive TCP application). This application has a threshold in throughput/delay, which if drops below a set point is able to send asynchronous events up to the workflow manager (VLAM) in order to request help in reallocating network resources. The reallocation consists in choosing a different path for pair connectivity: network 10.1.0.x (shared gigabit switch) or the network 10.10.0.x (programmable network processor).