A cooperative cache architecture in support of caching multimedia objects in MANETs

This paper presents a cooperative caching architecture suitable for continuous media (CM) proxy caching in MANET environments. The proposed scheme introduces an application manager component, which is interposed between traditional Internet CM applications and the network layer. The application manager transparently performs data location and service migration of active CM streaming sessions so as to exploit nearby data sources based on the dynamic topology of a MANET. We propose two data location schemes - Cache-State - a link-state based scheme and Reactive - an on-demand scheme. Since service migration can occur frequently, the application manager uses soft-state signaling techniques to communicate between remote application managers by translating hard-state application signaling, such as Real Time Streaming Protocol (RTSP) into soft-state messages. The proposed schemes are evaluated through simulation studies using the NS simulator. Simulation studies show that both Cache-State and Reactive schemes demonstrate significant QoS improvements and reduced bandwidth consumption.

A flexible receiver-driven cache replacement scheme for continuous media objects in best-effort networks

In this paper, we investigate the potential of caching to improve quality of reception (QoR) in the context of continuous media applications over best-effort networks. Specifically, we investigate the influence of parameters such as loss rate, jitter, delay and area in determining a proxy's cache contents. We propose the use of a flexible cost function in caching algorithms and develop a framework for benchmarking continuous media caching algorithms. The cost function incorporates parameters in which, an administrator and or a client can tune to influence a proxy's cache. Traditional caching systems typically base decisions around static schemes that do not take into account the interest of their receiver pool. Based on the flexible cost function, an improvised Greedy Dual (GD) algorithm called GD-multi has been developed for layered multiresolution multimedia streams. The effectiveness of the proposed scheme is evaluated by simulation-based performance studies. Performance of several caching schemes are evaluated and compared with those of the proposed scheme. Our empirical results indicate GD-multi performs well despite employing a generalized caching policy.

Temporal semantic compression for video browsing

We present a video browsing approach, termed Temporal Semantic Compression (TSC), that uses automated measures of interest to support today's foraging behaviours. Conventional browsers 'compress' a video stream using simple 2x or 8x fast-forward. TSC browsers dynamically filter video based on a single user gesture to leave out more or less of the boring bits. We demonstrate a browser with an example interest measure, derived from an automated estimate of movie tempo, to forage in terms of narrative structures such as crises, climaxes, and action sequence book-ends. Media understanding algorithms facilitate browsing, and interactivity enables the human-in-the-loop to cope when those algorithms fail to cross the semantic gap.

Information retrieval in documents using semantic criteria

The central problem of automatic retrieval from unformatted text is that computational devices are not adequately trained to look for associated information. However for complete understanding and information retrieval, a complete artificial intelligence would have to be built. This paper describes a method for achieving significant information retrieval by using a semantic search engine. The underlying semantic information is stored in a network of clarified words, linked by logical connections. We employ simple scoring techniques on collections of paths in this network to establish a degree of relevance between a document and a clarified search criterion. This technique has been applied with success to test examples and can be easily scaled up to search large documents.

A cache-based mobility-aware scheme for real-time continuous media delivery in wireless networks

Providing real-time or continuous media (CM) application services in wireless networks poses a significant challenge, as it requires timely delivery of data in a best-effort network. In this paper, we propose a cache-based scheme for mobility-aware, CM applications. The proposed scheme exploits a previously proposed caching strategy to complement Mobile-IP by placing services closer to migrated mobile nodes. The central idea of this work is based on the migration of sessions in order to facilitate uninterrupted delivery of CM in mobile environments. The performance of the proposed scheme is investigated by simulation studies. In particular, the effect of the proposed scheme on several QoS parameters under varying conditions of mobility and CM data is measured.

Towards a semantic quality based approach for business process models improvement

Business process (BP) modeling aims at a better understanding of processes, allowing deciders to improve them. We propose to support this modeling with an approach encompassing methods and tools for BP models quality measurement and improvement. In this paper we focus on semantic quality. The latter is evaluated by aligning BP model concepts with domain knowledge. The alignment is conducted thanks to meta-models. We also define validation rules for checking the completeness of BP models. A medical case study illustrates the main steps of our approach.

Dynamically predicting protein functions from semantic associations of proteins

Predicting functions of un-annotated proteins is a significant challenge in the post-genomics era. Among existing computational approaches, exploiting interactions between proteins to predict functions of un-annotated proteins is widely used. However, it remains difficult to extract semantic associations between proteins (i.e. protein associations in terms of protein functionality) from protein interactions and incorporate extracted semantic associations to more effectively predict protein functions. Furthermore, existing approaches and algorithms regard the function prediction as a one-off procedure, ignoring dynamic and mutual associations between proteins. Therefore, deriving and exploiting semantic associations between proteins to dynamically predict functions are a promising and challenging approach for achieving better prediction results. In this paper, we propose an innovative algorithm to incorporate semantic associations between proteins into a dynamic procedure of protein function prediction. The semantic association between two proteins is measured by the semantic similarity of two proteins which is defined by the similarities of functions two proteins possess. To achieve better prediction results, function similarities are also incorporated into the prediction procedure. The algorithm dynamically predicts functions by iteratively selecting functions for the un-annotated protein and updating the similarities between the un-annotated protein and its neighbour annotated proteins until such suitable functions are selected that the similarities no longer change. The experimental results on real protein interaction datasets demonstrated that our method outperformed the similar and non-dynamic function prediction methods. Incorporating semantic associations between proteins into a dynamic procedure of function prediction reflects intrinsic relationships among proteins as well as dynamic features of protein interactions, and therefore, can significantly improve prediction results.

Cache and carry : hoarding behavior of arctic fox

Food-hoarding animals are expected to preferentially cache items with lower perishability and/or higher consumption time. We observed arctic foxes (Alopex lagopus) foraging in a greater snow goose (Anser caerulescens atlanticus) colony where the main prey of foxes consisted of goose eggs, goslings, and lemmings (Lemmus and Dicrostonyx spp.). We recorded the number of prey consumed and cached and the time that foxes invested in these activities. Foxes took more time to consume a goose egg than a lemming or gosling but cached a greater proportion of eggs than the other prey type. This may be caused by the eggshell, which presumably decreases the perishability and/or pilfering risk of cached eggs, but also increases egg consumption time. Arctic foxes usually recached goose eggs but rarely recached goslings or lemmings. We tested whether the rapid-sequestering hypothesis could explain this recaching behavior. According to this hypothesis, arctic foxes may adopt a two-stage strategy allowing both to maximize egg acquisition rate in an undefended nest and subsequently secure eggs in potentially safer sites. Foxes spent more time carrying an egg and traveled greater distances when establishing a secondary than a primary cache. To gain further information on the location and subsequent fate of cached eggs, we used dummy eggs containing radio transmitters. Lifespan of primary caches increased with distance from the goose nest. Secondary caches were generally located farther from the nest and had a longer lifespan than primary caches. Behavioral observations and the radio-tagged egg technique both gave results supporting the rapid-sequestering hypothesis.

Semantic photo synthesis

Composite images are synthesized from existing photographs by artists who make concept art, e.g., storyboards for movies or architectural planning. Current techniques allow an artist to fabricate such an image by digitally splicing parts of stock photographs. While these images serve mainly to “quickly”convey how a scene should look, their production is laborious. We propose a technique that allows a person to design a new photograph with substantially less effort. This paper presents a method that generates a composite image when a user types in nouns, such as “boat”and “sand.”The artist can optionally design an intended image by specifying other constraints. Our algorithm formulates the constraints as queries to search an automatically annotated image database. The desired photograph, not a collage, is then synthesized using graph-cut optimization, optionally allowing for further user interaction to edit or choose among alternative generated photos. An implementation of our approach, shown in the associated video, demonstrates our contributions of (1) a method for creating specific images with minimal human effort, and (2) a combined algorithm for automatically building an image library with semantic annotations from any photo collection.