Abstract: This described technology generally relates to a data management system configured to implement, among other things, web-scale computing services, data storage and data presentation. Web-scale computing services are the fastest growing segment of the computing technology and services industry. In general, web-scale refers to computing platforms that are reliable, transparent, scalable, secure, and cost-effective. Illustrative web-scale platforms include utility computing, on-demand infrastructure, cloud computing, Software as a Service (SaaS), and Platform as a Service (PaaS). Consumers are increasingly relying on such web-scale services, particularly cloud computing services, and enterprises are progressively migrating applications to operate through web-scale platforms.

Abstract: A logical apparatus and associated methods provide highly scalable and flexible data storage in a network of computers. The apparatus provides flexible organizational and access control mechanisms and a practical and efficient way to work with smaller portions of a data storage system at a given time to enable sparse population, caching, paging and related functions. A data structure, called a virtual container, comprises references to objects stored in a data storage system such that the same object can be visible from different virtual containers, if such virtual containers hold references to said object. Access controls further enhance the effectiveness of the methods and structures to enable multiple simultaneous organizational schemes and selective sharing of objects.

Abstract: Methods, systems, and computer readable storage media for providing virtual access to network services. A virtual storage layer contains reference objects configured to reference network services stored in a network computing environment. Network clients access the reference objects through a resource interface based on a resource identifier associated with the virtual storage layer. Initiation of the virtual service by a network client invokes the service in a native computing environment of the service.

Abstract: A method for making data placement decisions in a computer network uses multiple factors comprising social rules (rules, factors and criteria common to all participating nodes and intended to benefit the community of nodes), as well as rules, factors and criteria driven by individual self-interest of the participating nodes. The method calls for each node to act in a semi-autonomous manner, without the need for a central coordinating node. By considering multiple factors fully, and not eliminating factors by a sequence of True/False decisions, the method may arrive at optimal decisions and may generate a ranked list of node candidates.

Abstract: A method for making optimal decisions includes the ability to consider and weigh multiple factors, where those factors might be numeric, or non-numeric, objective or subjective. Further, the method ensures that factors are not prematurely eliminated. This contrasts with behavior common to decision-tree based approaches. The method further allows for weighting based on multiple statistical means as well as by the application of non-statistical values.