Online Bi-Objective Scheduling for IaaS Clouds Ensuring Quality of Service

This paper focuses on a bi-objective experimental evaluation of online scheduling in the Infrastructure as a Service model of Cloud computing regarding income and power consumption objectives. In this model, customers have the choice between different service levels. Each service level is associated with a price per unit of job execution time, and a slack factor that determines the maximal time span to deliver the requested amount of computing resources. The system, via the scheduling algorithms, is responsible to guarantee the corresponding quality of service for all accepted jobs. Since we do not consider any optimistic scheduling approach, a job cannot be accepted if its service guarantee will not be observed assuming that all accepted jobs receive the requested resources. In this article, we analyze several scheduling algorithms with different cloud configurations and workloads, considering the maximization of the provider income and minimization of the total power consumption of a schedule. We distinguish algorithms depending on the type and amount of information they require: knowledge free, energy-aware, and speed-aware. First, to provide effective guidance in choosing a good strategy, we present a joint analysis of two conflicting goals based on the degradation in performance. The study addresses the behavior of each strategy under each metric. We assess the performance of different scheduling algorithms by determining a set of non-dominated solutions that approximate the Pareto optimal set. We use a set coverage metric to compare the scheduling algorithms in terms of Pareto dominance. We claim that a rather simple scheduling approach can provide the best energy and income trade-offs. This scheduling algorithm performs well in different scenarios with a variety of workloads and cloud configurations.     

Real time motion estimation using a neural architecture implemented on GPUs

This work describes a neural network based architecture that represents and estimates object motion in videos. This architecture addresses multiple computer vision tasks such as image segmentation, object representation or characterization, motion analysis and tracking. The use of a neural network architecture allows for the simultaneous estimation of global and local motion and the representation of deformable objects. This architecture also avoids the problem of finding corresponding features while tracking moving objects. Due to the parallel nature of neural networks, the architecture has been implemented on GPUs that allows the system to meet a set of requirements such as: time constraints management, robustness, high processing speed and re-configurability. Experiments are presented that demonstrate the validity of our architecture to solve problems of mobile agents tracking and motion analysis.     

Cell-protection mechanism through autophagy in HGFs/<Emphasis Type="Italic">S. mitis</Emphasis> co-culture treated with Chitlac-nAg

Silver-based products have been proven to be effective in retarding and preventing bacterial growth since ancient times. In the field of restorative dentistry, the use of silver ions/nanoparticles has been explored to counteract bacterial infections, as silver can destroy bacterial cell walls by reacting with membrane proteins. However, it is also cytotoxic towards eukaryotic cells, which are capable of internalizing nanoparticles. In this work, we investigated the biological effects of Chitlac-nAg, a colloidal system based on a modified chitosan (Chitlac), administered for 24–48?h to a co-culture of primary human gingival fibroblasts and Streptococcus mitis in the presence of saliva, developed to mimic the microenvironment of the oral cavity. We sought to determine its efficiency to combat oral hygiene-related diseases without affecting eukaryotic cells. Cytotoxicity, reactive oxygen species production, apoptosis induction, nanoparticles uptake, and lysosome and autophagosome metabolism were evaluated. In vitro results show that Chitlac-nAg does not exert cytotoxic effects on human gingival fibroblasts, which seem to survive through a homoeostasis mechanism involving autophagy. That suggests that the novel biomaterial Chitlac-nAg could be a promising tool in the field of dentistry.     

The renaming problem in shared memory systems: An introduction

Exploring the power of shared memory communication objects and models, and the limits of distributed computability are among the most exciting research areas of distributed computing. In that spirit, this paper focuses on a problem that has received considerable interest since its introduction in 1987, namely the renaming problem. It was the first non-trivial problem known to be solvable in an asynchronous distributed system despite process failures. Many algorithms for renaming and variants of renaming have been proposed, and sophisticated lower bounds have been proved, that have been a source of new ideas of general interest to distributed computing. It has consequently acquired a paradigm status in distributed fault-tolerant computing.In the renaming problem, processes start with unique initial names taken from a large name space, then deciding new names such that no two processes decide the same new name and the new names are from a name space that is as small as possible.This paper presents an introduction to the renaming problem in shared memory systems, for non-expert readers. It describes both algorithms and lower bounds. Also, it discusses strong connections relating renaming and other important distributed problems such as set agreement and symmetry breaking.     

Solving identity delegation problem in the e-government environment

At present, many countries allow citizens or entities to interact with the government outside the telematic environment through a legal representative who is granted powers of representation. However, if the interaction takes place through the Internet, only primitive mechanisms of representation are available, and these are mainly based on non-dynamic offline processes that do not enable quick and easy identity delegation. This paper proposes a system of dynamic delegation of identity between two generic entities that can solve the problem of delegated access to the telematic services provided by public authorities. The solution herein is based on the generation of a delegation token created from a proxy certificate that allows the delegating entity to delegate identity to another on the basis of a subset of its attributes as delegator, while also establishing in the delegation token itself restrictions on the services accessible to the delegated entity and the validity period of delegation. Further, the paper presents the mechanisms needed to either revoke a delegation token or to check whether a delegation token has been revoked. Implications for theory and practice and suggestions for future research are discussed.     

The k-simultaneous consensus problem

This paper introduces and investigates the k-simultaneous consensus task: each process participates at the same time in k independent consensus instances until it decides in any one of them. It is shown that the k-simultaneous consensus task is equivalent to the k-set agreement task in the wait-free read/write shared memory model, and furthermore k-simultaneous consensus possesses properties that k-set does not. In particular we show that the multivalued version and the binary version of the k-simultaneous consensus task are wait-free equivalent. These equivalences are independent of the number of processes. Interestingly, this provides us with a new characterization of the k-set agreement task that is based on the fundamental binary consensus problem.     

RUSHES—an annotation and retrieval engine for multimedia semantic units

Multimedia analysis and reuse of raw un-edited audio visual content known as rushes is gaining acceptance by a large number of research labs and companies. A set of research projects are considering multimedia indexing, annotation, search and retrieval in the context of European funded research, but only the FP6 project RUSHES is focusing on automatic semantic annotation, indexing and retrieval of raw and un-edited audio-visual content. Even professional content creators and providers as well as home-users are dealing with this type of content and therefore novel technologies for semantic search and retrieval are required. In this paper, we present a summary of the most relevant achievements of the RUSHES project, focusing on specific approaches for automatic annotation as well as the main features of the final RUSHES search engine.     

Temperature sensor based on the Er green upconverted emission in a fluorotellurite glass

The temperature dependence of the green upconverted emission from the two thermally coupled ²H_11/2 and ⁴S_3/2 levels of the Er³⁺ ion in a fluorotellurite glass has been analyzed as a function of the optically active ion concentration in order to check its availability as a temperature sensor. The infrared-to-green upconverted emission have been observed by the naked eyes after a cw laser diode excitation at 800 nm. The fluorescence intensity ratio between the thermally coupled emitting levels as well as the temperature sensitivity has been experimentally obtained up to 540 K. A better behaviour as a temperature sensor has been obtained for the less Er³⁺ concentrated glass with a maximum sensitivity of 54 × 10⁻⁴ K⁻¹ at 540 K, one of the highest found in rare-earth doped transparent materials.