Portraits

The intent of this thesis is to draw particular focus to my fascination with seemingly unimportant, mostly flat paper surfaces. In the tradition of 17th century trompe l\u27oeil Letter Rack paintings, I create portraits of my experiences engaging with the subject matter of flattened cardboard boxes, large folded pieces of paper, and small found paper scraps of various, and often indistinct, purposes. These paintings are executed and arranged to draw attention to the inherent abstraction and the hints of the sublime, which I perceive through a Color Field approach to viewing. By producing oil paintings and watercolors that employ methods of illusion, I seek to draw the viewer into experiencing the depiction in a more engaged manner

Portraits

The intent of this thesis is to draw particular focus to my fascination with seemingly unimportant, mostly flat paper surfaces. In the tradition of 17th century trompe l\u27oeil Letter Rack paintings, I create portraits of my experiences engaging with the subject matter of flattened cardboard boxes, large folded pieces of paper, and small found paper scraps of various, and often indistinct, purposes. These paintings are executed and arranged to draw attention to the inherent abstraction and the hints of the sublime, which I perceive through a Color Field approach to viewing. By producing oil paintings and watercolors that employ methods of illusion, I seek to draw the viewer into experiencing the depiction in a more engaged manner

BubbleStorm: Rendezvous Theory in Unstructured Peer-to-Peer Search

This thesis presents BubbleStorm, which attempts to bridge the gap between peer-to-peer and databases. BubbleStorm is a peer-to-peer search system, which solves large-scale rendezvous problems over the unreliable global internet. It provides a concept of user-defined bubble types, loosely corresponding to table schemas. Queries follow the fully general black-box model, allowing powerful queries to be evaluated exhaustively. The system tracks usage statistics with a system-wide measurement service, used to automatically tune search performance. As strong consistency guarantees are impossible, BubbleStorm instead aims for user-controlled probabilistic guarantees. The key contribution of this thesis is to develop rendezvous theory and reformulate the black-box query model within this framework. This reformulation allows us to interpret any black-box system as solving a rendezvous problem, allowing an elegant and tight lower-bound. BubbleStorm leverages rendezvous theory to substantially reduce bandwidth consumption (both practically and asymptotically) while simultaneously improving query latency. The resulting system, which has a full fledged implementation, sports a simple to understand interface, which abstracts away the underlying details, much like the database systems before it

A Peer-to-Peer Approach to Content-Based Publish/Subscribe

Publish/subscribe systems are successfully used to decouple distributed applications. However, their e#ciency is closely tied to the topology of the underlying network, the design of which has been neglected. Peer-to-peer network topologies can o#er inherently bounded delivery depth, load sharing, and self-organisation. In this paper, we present a contentbased publish/subscribe system routed over a peer-to-peer topology graph. The implications of combining these approaches are explored and a particular implementation using elements from Rebeca and Chord is proven correct

BubbleStorm: Rendezvous Theory in Unstructured Peer-to-Peer Search

This thesis presents BubbleStorm, which attempts to bridge the gap between peer-to-peer and databases. BubbleStorm is a peer-to-peer search system, which solves large-scale rendezvous problems over the unreliable global internet. It provides a concept of user-defined bubble types, loosely corresponding to table schemas. Queries follow the fully general black-box model, allowing powerful queries to be evaluated exhaustively. The system tracks usage statistics with a system-wide measurement service, used to automatically tune search performance. As strong consistency guarantees are impossible, BubbleStorm instead aims for user-controlled probabilistic guarantees. The key contribution of this thesis is to develop rendezvous theory and reformulate the black-box query model within this framework. This reformulation allows us to interpret any black-box system as solving a rendezvous problem, allowing an elegant and tight lower-bound. BubbleStorm leverages rendezvous theory to substantially reduce bandwidth consumption (both practically and asymptotically) while simultaneously improving query latency. The resulting system, which has a full fledged implementation, sports a simple to understand interface, which abstracts away the underlying details, much like the database systems before it

Distributed sql queries with bubblestorm

Abstract. Current peer-to-peer (p2p) systems place the burden of application-level query execution on the application developer. Not only do application developers lack the expertise to implement good distributed algorithms, but this approach also limits the ability of overlay architects to apply future optimizations. The analogous problem for data management was solved by the introduction of SQL, a high-level query language for application development and amenable to optimization. This paper attempts to bridge the gap between current access-oriented p2p systems and relational database management systems (DBMS). We outline how to implement every relational operator needed for SQL queries in the BubbleStorm peer-to-peer overlay. The components of BubbleStorm map surprisingly well to components in a traditional DBMS.

Survey on Location Privacy in Pervasive Computing

The goal of ubiquitous computing research is refine devices to the point where their use is transparent. For many applications with mobile devices, transparent operation requires that the device be locationaware