Archive for the ‘Semantic Overlay Network’ Category

Managing context data for diverse operating spaces

Wednesday, May 16th, 2012

Managing context data for diverse operating spaces by Wenwei Xuea, Hung Keng Pungb, and Shubhabrata Senb.


Context-aware computing is an exciting paradigm in which applications perceive and react to changing environments in an unattended manner. To enable behavioral adaptation, a context-aware application must dynamically acquire context data from different operating spaces in the real world, such as homes, shops and persons. Motivated by the sheer number and diversity of operating spaces, we propose a scalable context data management system in this paper to facilitate data acquisition from these spaces. In our system, we design a gateway framework for all operating spaces and develop matching algorithms to integrate the local context schemas of operating spaces into a global set of domain schemas upon which SQL-based context queries can be issued from applications. The system organizes the operating space gateways as peers in semantic overlay networks and employs distributed query processing techniques over these overlays. Evaluation results on a prototype implementation demonstrate the effectiveness of our system design.

This article came up in a sweep for “semantic overlay networks.”

Encouraging recognition that results may need to vary based on physical context. Who knows? Perhaps recognition that the terminology for one domain and its journals/authors/monographs has different semantics than other domains.

Imagine that, a system that manages queries across semantic domains for users, as opposed to users having to understand all the possible semantic domains in advance to have useful query results (or better query results).

Perhaps the “context” metaphor may be a useful one in marketing topic maps. Less aggressive than “silo.” Let the client come up with that to characterize competing agencies or information sources.

“Context” in the sense of physical space is popular among the smart phone crowd so don’t neglect that as an avenue for topic maps as well. (Looking at your surroundings would mean breaking eye contact with your phone. Might miss an ad or something.)

Semantic Overlay Networks for P2P Systems

Wednesday, December 1st, 2010

Semantic Overlay Networks for P2P Systems Authors: Garcia-Molina, Hector and Crespo, Arturo

Date: 2003


In a peer-to-peer (P2P) system, nodes typically connect to a small set of random nodes (their neighbors), and queries are propagated along these connections. Such query flooding tends to be very expensive. We propose that node connections be influenced by content, so that for example, nodes having many “Jazz” files will connect to other similar nodes. Thus, semantically related nodes form a Semantic Overlay Network (SON). Queries are routed to the appropriate SONs, increasing the chances that matching files will be found quickly, and reducing the search load on nodes that have unrelated content. We have evaluated SONs by using an actual snapshot of music-sharing clients. Our results show that SONs can significantly improve query performance while at the same time allowing users to decide what content to put in their computers and to whom to connect.

The root article for the term Semantic Overlay Network that I mentioned last summer, Semantic Overlay Networks.

The emphasis on query and query efficiency seems particularly relevant for work on TMQL.

Semantic Overlay Networks

Tuesday, June 8th, 2010

GridVine: Building Internet-Scale Semantic Overlay Networks sounds like they are dealing with topic map like issues to me. You be the judge:

This paper addresses the problem of building scalable semantic overlay networks. Our approach follows the principle of data independence by separating a logical layer, the semantic overlay for managing and mapping data and metadata schemas, from a physical layer consisting of a structured peer-to-peer overlay network for efficient routing of messages. The physical layer is used to implement various functions at the logical layer, including attribute-based search, schema management and schema mapping management. The separation of a physical from a logical layer allows us to process logical operations in the semantic overlay using different physical execution strategies. In particular we identify iterative and recursive strategies for the traversal of semantic overlay networks as two important alternatives. At the logical layer we support semantic interoperability through schema inheritance and semantic gossiping. Thus our system provides a complete solution to the implementation of semantic overlay networks supporting both scalability and interoperability.

The concept of “semantic gossiping” enables semantic similarity to be established the combination of local mappings, that is by adding the mappings together. (Similar to the set behavior of subject identifiers/locators in the TMDM. That is to say if you merge two topic maps, any additional subject identifiers, previously unknown to the first topic map, with enable those topics to merge with topics in later merges where previously they may not have.)

Open Question: If everyone concedes that:

  • we live in a heterogeneous world
  • we have stored vast amounts of heterogeneous data
  • we are going to continue to create/store even vaster amounts of heterogeneous data
  • we keep maintaining and creating more heterogeneous data structures to store our heterogeneous data

If every starting point is heterogeneous, shouldn’t heterogeneous solutions be the goal?

Such as supporting heterogeneous mapping technologies? (Granting there will also be a limit to those supported at any one time but it should be possible to extend to embrace others.)

Author Bibliographies:

Karl Aberer

Phillipe Cudré-Mauroux

Manfred Hauswirth

Tim Van Pelt