Supporting distributed computation over wide area gigabit networks

The advent of high bandwidth fibre optic links that may be used over very large distances has lead to much research and development in the field of wide area gigabit networking. One problem that needs to be addressed is how loosely coupled distributed systems may be built over these links, allowing many computers worldwide to take part in complex calculations in order to solve "Grand Challenge" problems. The research conducted as part of this PhD has looked at the practicality of implementing a communication mechanism proposed by Craig Partridge called Late-binding Remote Procedure Calls (LbRPC). LbRPC is intended to export both code and data over the network to remote machines for evaluation, as opposed to traditional RPC mechanisms that only send parameters to pre-existing remote procedures. The ability to send code as well as data means that LbRPC requests can overcome one of the biggest problems in Wide Area Distributed Computer Systems (WADCS): the fixed latency due to the speed of light. As machines get faster, the fixed multi-millisecond round trip delay equates to ever increasing numbers of CPU cycles. For a WADCS to be efficient, programs should minimise the number of network transits they incur. By allowing the application programmer to export arbitrary code to the remote machine, this may be achieved. This research has looked at the feasibility of supporting secure exportation of arbitrary code and data in heterogeneous, loosely coupled, distributed computing environments. It has investigated techniques for making placement decisions for the code in cases where there are a large number of widely dispersed remote servers that could be used. The latter has resulted in the development of a novel prototype LbRPC using multicast IP for implicit placement and a sequenced, multi-packet saturation multicast transport protocol. These prototypes show that it is possible to export code and data to multiple remote hosts, thereby removing the need to perform complex and error prone explicit process placement decisions

Suitable areas for <i>Diabrotica virgifera virgifera</i> and value of assets.

<p>A: Area where the ecoclimatic index (EI) is above zero, B: Growth index (GI) (source for A and B: Kriticos et al. 2012), C: Percentage of area covered by grain and forage maize, and D: Value of grain and forage maize in euros per km² (source for C and D: McGill University 2011).</p

Frequency distribution of the potential economic impact of pest invasion in three scenarios of model A in a case study based on <i>Diabrotica virgifera virgifera</i>.

<p>The potential economic impact is quantified by accumulating the asset value in invaded cells in 2010. These three figures correspond to (A) best case scenario, (B) worst case scenario (C) random case scenario. Spread model A is based on logistic increase (<i>r</i> = 0.33 yr⁻¹) in the number of invaded cells on the map.</p

Experts’ assessment of the level difficulty to obtain data for model parameterisation in their case study (numbers indicate how often a score was given).

1<p>Model A was deemed not applicable in 6 out of 8 cases, mostly because of the effort involved in obtaining spatially explicit data on the value of assets at risk. The spread model component of model A is relatively simple to apply, but was not tested separately.</p

Experts’ assessment regarding the level of difficulty of parameter estimation in their case study (numbers indicate how often a score was given).

<p>Experts’ assessment regarding the level of difficulty of parameter estimation in their case study (numbers indicate how often a score was given).</p

Sensitivity analysis: effect of parameter changes in models C and D on the total population.

<p>The population size (y-axis) is given as a multiple of the population size in the base line scenario (3.2×10¹⁰ in model C and 1.6×10¹² in model D). The total population represents the total number of insects in the area of potential establishment.</p

Experts’ feedback on the suitability of four models in practical pest risk assessment based on their experience on specific case studies (numbers indicate how often a score was given).

<p>Experts’ feedback on the suitability of four models in practical pest risk assessment based on their experience on specific case studies (numbers indicate how often a score was given).</p

Spread simulation of <i>Diabrotica virgifera virgifera</i> for the year 2010 using model C with the baseline parameter values.

<p>There was virtually no difference between scenarios, therefore only the baselines scenario is given.</p

Experts’ assessment of the uncertainty of parameter estimates in their case study (numbers indicate how often a score was given).

<p>Experts’ assessment of the uncertainty of parameter estimates in their case study (numbers indicate how often a score was given).</p

Perturbation of invaded area with time for each model.

<p>A value of zero means that the scaled area does not change with a combination of parameters +/−10%. (*) ND means that the value is not defined because the invaded area for the baseline value is 0. (¤) Since a change in the parameter values of model D has negligible effects on the invaded area at time t  = 18 yrs (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0043366#pone-0043366-t002" target="_blank">Table 2</a>), it was not possible to define worst and best cases associated with this variable, and the sensitivity was set to 0.</p