Amazon.com

About: Amazon.com is a company organization based out in Seattle, Washington, United States. It is known for research contribution in the topics: Service (business) & Service provider. The organization has 13363 authors who have published 17317 publications receiving 266589 citations.

Managing resources using resource expiration data

Abstract: Resource management techniques, such as cache optimization, are employed to organize resources within caches such that the most requested content (e.g., the most popular content) is more readily available. A service provider utilizes content expiration data as indicative of resource popularity. As resources are requested, the resources propagate through a cache server hierarchy associated with the service provider. More frequently requested resources are maintained at edge cache servers based on shorter expiration data that is reset with each repeated request. Less frequently requested resources are maintained at higher levels of a cache server hierarchy based on longer expiration data associated with cache servers higher on the hierarchy.

Managing CDN registration by a storage provider

Abstract: A system, method, and computer readable medium for managing registration, by a network storage provider, of one or more resources with a CDN service provider are provided. A network storage provider storing one or more resources on behalf of a content provider obtains registration information for registering the one or more resources with a CDN service provider. The registration information may include a request to publish one or more resources to a CDN service provider, an identification of the one or more resources, CDN selection criteria provided by the content provider or otherwise selected, and the like. The network storage provider transmits a CDN generation request corresponding to the registration information to the CDN service provider. Then, the network storage provider manages and processes data pursuant to registration of the one or more resources with the CDN service provider.

Optimisation of photosynthetic carbon gain and within-canopy gradients of associated foliar traits for Amazon forest trees

Abstract: . Vertical profiles in leaf mass per unit leaf area (MA), foliar 13C composition (δ13C), nitrogen (N), phosphorus (P), carbon (C) and major cation concentrations were estimated for 204 rain forest trees growing in 57 sites across the Amazon Basin. Data was analysed using a multilevel modelling approach, allowing a separation of gradients within individual tree canopies (within-tree gradients) as opposed to stand level gradients occurring because of systematic differences occurring between different trees of different heights (between-tree gradients). Significant positive within-tree gradients (i.e. increasing values with increasing sampling height) were observed for MA and [C]DW (the subscript denoting on a dry weight basis) with negative within-tree gradients observed for δ13C, [Mg]DW and [K]DW. No significant within-tree gradients were observed for [N]DW, [P]DW or [Ca]DW. The magnitudes of between-tree gradients were not significantly different to the within-tree gradients for MA, δ13C, [C]DW, [K]DW, [N]DW, [P]DW and [Ca]DW. But for [Mg]DW, although there was no systematic difference observed between trees of different heights, strongly negative within-tree gradients were found to occur. When expressed on a leaf area basis (denoted by the subscript "A"), significant positive gradients were observed for [N]A, [P]A and [K]A both within and between trees, these being attributable to the positive intra- and between-tree gradients in MA mentioned above. No systematic within-tree gradient was observed for either [Ca]A or [Mg]A, but with a significant positive gradient observed for [Mg]A between trees (i.e. with taller trees tending to have a higher Mg per unit leaf area). Significant differences in within-tree gradients between individuals were observed only for MA, δ13C and [P] A. This was best associated with the overall average [P]A for each tree, this also being considered to be a surrogate for a tree's average leaf area based photosynthetic capacity, Amax. A new model is presented which is in agreement with the above observations. The model predicts that trees characterised by a low upper canopy Amax should have shallow, or even non-existent, within-canopy gradients in Amax, with optimal intra-canopy gradients becoming sharper as a tree's upper canopy Amax increases. Nevertheless, in all cases it is predicted that the optimal within-canopy gradient in Amax should be substantially less than for photon irradiance. Although this is also shown to be consistent with numerous observations as illustrated by a literature survey of gradients in photosynthetic capacity for broadleaf trees, it is also in contrast to previously held notions of optimality. A new equation relating gradients in photosynthetic capacity within broadleaf tree canopies to the photosynthetic capacity of their upper canopy leaves is presented.

Use of temporarily available computing nodes for dynamic scaling of a cluster

Abstract: Techniques are described for managing distributed execution of programs, including by dynamically scaling a cluster of multiple computing nodes performing ongoing distributed execution of a program, such as to increase and/or decrease computing node quantity. An architecture may be used that has core nodes that each participate in a distributed storage system for the distributed program execution, and that has one or more other auxiliary nodes that do not participate in the distributed storage system. Furthermore, as part of performing the dynamic scaling of a cluster, computing nodes that are only temporarily available may be selected and used, such as computing nodes that might be removed from the cluster during the ongoing program execution to be put to other uses and that may also be available for a different fee (e.g., a lower fee) than other computing nodes that are available throughout the ongoing use of the cluster.