In image retrieval, deep local features learned in a data-driven manner have been demonstrated effective to improve retrieval performance. To realize efficient on large database, some approaches quantize with codebook and match images aggregated kernel. However, the complexity of these is non-trivial memory footprint, which limits their capability jointly perform feature learning aggregation. g...

For the real-time scheduling in wireless sensor networks, Time Division Multiple Access (TDMA) under cluster architecture is usually considered as reasonable as well as scalable approach. Under this architecture, several type of inferences should be taken into account to allocate time slot. For this goal, we have already proposed a new real-time scheduling algorithm. But, it has several assumpt...

Scalable and efficient broadcast is essential to the large-scale computing infrastructures such as PlanetLab and Grids. By exploiting the greedy routing mechanisms of Distributed Hash Table (DHT), existing DHTbased broadcast algorithms suffer from the limitations of scalability and load balancing, incurring high construction and maintenance overhead for a distributed broadcast tree (DBT). This ...

A number of solutions have been proposed for the problem of mutual exclusion in distributed systems. Some of these approaches have since been extended to a prioritized environment suitable for real-time applications but impose a higher message passing overhead than our approach. We present a new protocol for prioritized mutual exclusion in a distributed environment. Our approach uses a token-ba...

Locating and evaluating relationships among values in multiple streams of data is a di cult and important task. Consider the data owing from monitors in an intensive care unit. Readings from various subsets of the monitors are indicative and predictive of certain aspects of the patient's state. We present an algorithm that facilitates discovery and assessment of the strength of such predictive ...

We study lower bounds on information dissemination in adversarial dynamic networks. Initially, k pieces of information (henceforth called tokens) are distributed among n nodes. The tokens need to be broadcast to all nodes through a synchronous network in which the topology can change arbitrarily from round to round provided that some connectivity requirements are satisfied. If the network is gu...

Real-time multiprocessor systems frequently assume that there exists a dedicated processor for task allocation that never fails. This assumption is, however, too strong in the sense that all the physical objects are subject to failure. Moreover, once the dedicated processor fails, the whole multiprocessor system will fail. As a way to solve this problem, we propose a fault-tolerant scheduling a...

RelHunter is a Machine Learning based method for the extraction of structured information from text. Here, we apply RelHunter to the Hedge Detection task, proposed as the CoNLL-2010 Shared Task1. RelHunter’s key design idea is to model the target structures as a relation over entities. The method decomposes the original task into three subtasks: (i) Entity Identification; (ii) Candidate Relatio...

The approach presented in this article is based on the real time simulation of p-time Petri net for the real time scheduling of batch systems. After defining the different kinds of constraints which can exist in a linear hybrid production system, we present the conflict resolution principle used by a token player algorithm at the global coordination level.