By leveraging virtual machine (VM) technology which provides performance and fault isolation, cloud resources can be provisioned on demand in a fine grained, multiplexed manner rather than in monolithic pieces. By integrating volunteer computing into cloud architectures, we envision a gigantic self-organizing cloud (SOC) being formed to reap the huge potential of untapped commodity computing […]
A Symbolic Representation of Time Series, with Implications for Streaming Algorithms
Supporting decision making in domains in which the observed phenomenon dynamics have to be dealt with, can greatly benefit of retrieval of past cases, provided that proper representation and retrieval techniques are implemented. In particular, when the parameters of interest take the form of time series, dimensionality reduction and flexible retrieval have to be addresses […]
Mining Web Logs to Improve Web Site Organization
Designing well-structured websites to facilitate effective user navigation has long been a challenge. A primary reason is that the web developers’ understanding of how a website should be structured can be considerably different from that of the users. While various methods have been proposed to relink webpages to improve navigability using user navigation data, the […]
Improved binary partition tree construction for hyperspectral images
The optimal exploitation of the information provided by hyperspectral images requires the development of advanced image-processing tools. Hyperspectral imaging enables the characterization of regions based on their spectral properties which provides a rich amount of information. This paper proposes the construction and the processing of a new region-based hierarchical hyperspectral image representation relying on the […]
Learning Horizontal Connections In A Sparse Coding Model Of Natural Images
Image prior models based on sparse and redundant representations are attracting more and more attention in the field of image restoration. The conventional sparsity-based methods enforce sparsity prior on small image patches independently. Unfortunately, these works neglected the contextual information between sparse representations of neighboring image patches . Sparse coding of image patches extracted from […]
Multimedia Search With Pseudo Revelance Feedback
Search reranking is regarded as a common way to boost retrieval precision. The problem nevertheless is not trivial especially when there are multiple features or modalities to be considered for search, which often happens in image and video retrieval. This paper proposes a new reranking algorithm , named circular reranking, that reinforces the mutual exchange of information across […]
Content Delivery Networks In Load Balancing For A Distributed Control Law
we face the challenging issue of defining and implementing an effective law for load balancing in Content Delivery Networks (CDNs). We base our proposal on a formal study of a CDN system, carried out through the exploitation of a fluid flow model characterization of the network of servers. Starting from such characterization, we derive and […]
Multiattribute Resource Allocation Of Dynamic Optimization In Self-Organizing Clouds
By leveraging virtual machine (VM) technology which provides performance and fault isolation, cloud resources can be provisioned on demand in a fine grained, multiplexed manner rather than in monolithic pieces. By integrating volunteer computing into cloud architectures, we envision a gigantic self-organizing cloud (SOC) being formed to reap the huge potential of untapped commodity computing […]
Location Proof Updating System In A Resistance And Toward Privacy Preserving
we propose A Privacy-Preserving Location proof Updating System (APPLAUS) in which colocated Bluetooth enabled mobile devices mutually generate location proofs and send updates to a location proof server. Periodically changed pseudonyms are used by the mobile devices to protect source location privacy from each other, and from the untrusted location proof server For The Purpose […]
Social Network Data Anonymization In Protecting Sensitive Labels
Privacy is one of the major concerns when publishing or sharing social network data for social science research and business analysis. Recently, researchers have developed privacy models similar to k-anonymity to prevent node reidentification through structure information. However, even when these privacy models are enforced, an attacker may still be able to infer one’s private […]