Saúl E. Pomares Hernández

Learn More
In this paper we present a study on the subject of the Immediate Dependency Relation (IDR), and we show how by extending the IDR relation, one can ensure a global causal delivery in group communication, including in the overlapping group case. The main objective of this paper is to show that the use of the Immediate Dependency Relation (IDR) obliterates the(More)
The preservation of temporal relations for real-time distributed continuos media is a key issue for emerging multimedia applications, such as Tele-Immersion and Tele-Engineering. Although several works try to model and execute distributed continuous media scenarios, they are far from resolving the problem. The present paper proposes a viable solution based(More)
The preservation of temporal dependencies among different media data, such as text, still images, video and audio, and which have simultaneous distributed sources as origin, is an open research area and an important issue for emerging distributed multimedia systems, such as Teleimmersion, Telemedicine, and IPTV. Although there are several works oriented to(More)
In this work we propose an efficient real-time causal broadcast algorithm with fault tolerance to unreliable networks. The algorithm allows for the delivery of causal messages with recovering capabilities on real-time systems by using the concept of redundancy. Redundancy, in our work, is calculated based on the causal distance. The concept of causal(More)
Several algorithms of different domains in distributed systems are designed over the principle of the Happened-Before Relation (HBR). One common aspect among them is that they intend to be efficient in their implementation by identifying and ensuring the necessary and sufficient dependency constraints. In this pursuit, some previous works talk about the use(More)
The accuracy of a model to forecast a time series diminishes as the prediction horizon increases, in particular when the prediction is carried out recursively. Such decay is faster when the model is built using data generated by highly dynamic or chaotic systems. This paper presents a topology and training scheme for a novel artificial neural network, named(More)
Emerging distributed multimedia systems such as Telemedicine, TeleConference and IPTV, deal with simultaneous geographically distributed sources by transmitting heterogeneous data, such as text, images, graphics, video and audio. The preservation of temporal relations that consider different data types and simultaneous distributed sources is an open(More)
The paper presents a causal protocol for very large group communication systems. The protocol does not make any assumption concerning the group structure nor the network topology. It aims to minimize and control the flow of causal information through two mechanisms. First, it reduces the amount of causal information (CI) timestamped per message by avoiding(More)
Although the initiative of Autonomic Computing was introduced a dozen years ago, several challenges remain open. One of these challenges is the efficient monitoring at runtime oriented to the detection, diagnosis, and repair of problems that result from failures or bugs in software and/or hardware components. For this purpose, Communication-induced(More)