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IDMaps / SonarHops internet distance estimation service: IDMaps is a global internet host distance estimation service that provides distance information used by SONAR / HOPS query / reply service. IDMaps measures, disseminates internet wide distance information to for example, Distributed Autonomous Virtual Organizations DAVOS. Higher level services for example at the macro-cycle level collect distance information to build a virtual distance map of internet by estimating distance between any IP address pair. 

Location is achieved by use of triangulation Distance information adjusts to “permanent” topology changes e.g., splits, joins, adds, moves, drops, merges in lieu of formal merger / acquisition. IDMaps assists Network Time Protocol (NTP) servers establish long term peering relationships. Distance Metrics focus is on latency (e.g., round-trip delay) and where possible, bandwidth. We improve stochastic harmonization by use of firefly inspired algorithms that strive to achieve synchronization by matching firefly synchronization behavior with the closest matching heartbeat snapshot cycle interval. Read about IDMaps / SonarHops here 

An application of IDMaps / SonarHops is locating data of  Named Data-Networking <interest>  by survey methods / internet triangulation denoting events and alerts in a common geo-spatial temporal intensity metric / meter meme e.g. "Paul Revere" hop by hops for linear, sequential data and "Water Drop" for radius, area spatial intensity and frequency. The Random Number Cyber Beacon from NIST adds an audit feature useful for forensic analysis. 

Vectors are used to define boundaries and to determine thresholds in spaces over time involving magnitude (e.g., earthquake) and direction e.g., Tsunami. Vectors are used to show direction or course followed by an airplane, missile, convoy or land slide. Vectors from a known, surveyed point are used to establish boundaries where discrete distances are established and predicted by hops at set intervals. Objects within defined boundary areas (e.g., boundary boxes, circles) are classified into interest types that are grouped in this case by belonging to organizations by Organizational Identifiers ORG ID by resource types as Uniform Resource Names URN.  

Change detection within borders are displayed by threshold changes e.g., band 1, 2, 3 in the case of concentric circles or squares and over time by histograms. Objects or entities identified by interest types are typed belonging to specific groups where entities and object data describing them (meta-data) are aggregated into folders awaiting processing by algorithms usually in batch mode by keyword / tag.  

Search Technology as catalyst: enhance search geo-spatially in terms of temporal intensity metrics e.g.,. changes in clusters of objects, entities, artifacts i.e., location, epoch time stamp geo-spatially, temporally, used to locate, search, then group into virtual collections using <data_tags> i.e., <rare> in spatial econometric, volumetric operations within network mesh fabrics triggering news-casting invitations to join equitably metered federated group arbitrage events, activities that are triggered by internet search operations followed by invitations to participate in crowd sourcing equitably metered arbitrage within federated groups

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