A Benchmark for Image Retrieval using Distributed Systems over the Internet: BIRDS-I

The performance of CBIR algorithms is usually measured on an isolated workstation. In a real-world environment the algorithms would only constitute a minor component among the many interacting components. The Internet dramati-cally changes many of the usual assumptions about measuring CBIR performance. Any CBIR benchmark should be designed from a networked systems standpoint. These benchmarks typically introduce communication overhead because the real systems they model are distributed applications. We present our implementation of a client/server benchmark called BIRDS-I to measure image retrieval performance over the Internet. It has been designed with the trend toward the use of small personalized wireless systems in mind. Web-based CBIR implies the use of heteroge-neous image sets, imposing certain constraints on how the images are organized and the type of performance metrics applicable. BIRDS-I only requires controlled human intervention for the compilation of the image collection and none for the generation of ground truth in the measurement of retrieval accuracy. Benchmark image collections need to be evolved incrementally toward the storage of millions of images and that scaleup can only be achieved through the use of computer-aided compilation. Finally, our scoring metric introduces a tightly optimized image-ranking window.Comment: 24 pages, To appear in the Proc. SPIE Internet Imaging Conference 200

Peer to Peer Information Retrieval: An Overview

Peer-to-peer technology is widely used for file sharing. In the past decade a number of prototype peer-to-peer information retrieval systems have been developed. Unfortunately, none of these have seen widespread real- world adoption and thus, in contrast with file sharing, information retrieval is still dominated by centralised solutions. In this paper we provide an overview of the key challenges for peer-to-peer information retrieval and the work done so far. We want to stimulate and inspire further research to overcome these challenges. This will open the door to the development and large-scale deployment of real-world peer-to-peer information retrieval systems that rival existing centralised client-server solutions in terms of scalability, performance, user satisfaction and freedom

Distributed Information Retrieval using Keyword Auctions

This report motivates the need for large-scale distributed approaches to information retrieval, and proposes solutions based on keyword auctions

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

Automatic subscriptions in publish-subscribe systems

In this paper, we describe how to automate the process of subscribing to complex publish-subscribe systems. We present a proof-of-concept prototype, in which we analyze Web browsing history to generate zero-click subscriptions to Web feeds and video news stories. Our experience so far indicates that user attention data is a promising source of data for automating the subscription process

Performance comparison of clustered and replicated information retrieval systems

The amount of information available over the Internet is increasing daily as well as the importance and magnitude of Web search engines. Systems based on a single centralised index present several problems (such as lack of scalability), which lead to the use of distributed information retrieval systems to effectively search for and locate the required information. A distributed retrieval system can be clustered and/or replicated. In this paper, using simulations, we present a detailed performance analysis, both in terms of throughput and response time, of a clustered system compared to a replicated system. In addition, we consider the effect of changes in the query topics over time. We show that the performance obtained for a clustered system does not improve the performance obtained by the best replicated system. Indeed, the main advantage of a clustered system is the reduction of network traffic. However, the use of a switched network eliminates the bottleneck in the network, markedly improving the performance of the replicated systems. Moreover, we illustrate the negative performance effect of the changes over time in the query topics when a distributed clustered system is used. On the contrary, the performance of a distributed replicated system is query independent