A Numerical Approach to Stability of Multiclass Queueing Networks

The Multi-class Queueing Network (McQN) arises as a natural multi-class extension of the traditional (single-class) Jackson network. In a single-class network subcriticality (i.e. subunitary nominal workload at every station) entails stability, but this is no longer sufficient when jobs/customers of different classes (i.e. with different service requirements and/or routing scheme) visit the same server; therefore, analytical conditions for stability of McQNs are lacking, in general. In this note we design a numerical (simulation-based) method for determining the stability region of a McQN, in terms of arrival rate(s). Our method exploits certain (stochastic) monotonicity properties enjoyed by the associated Markovian queue-configuration process. Stochastic monotonicity is a quite common feature of queueing models and can be easily established in the single-class framework (Jackson networks); recently, also for a wide class of McQNs, including first-come-first-serve (FCFS) networks, monotonicity properties have been established. Here, we provide a minimal set of conditions under which the method performs correctly. Eventually, we illustrate the use of our numerical method by presenting a set of numerical experiments, covering both single and multi-class networks

Molecular identification of trichostrongylus axei on European brown hare (Lepus Europaeus) in Western Romania - case report

Trichostrongylosis is a cosmopolitan parasitic disease affecting domestic and wild ruminants, equines, and last but not least, leporids. Three species of strongyles commonly parasitize the digestive tracts of leporids, the most prevalent being Trichostrongylus retortaeformis. This paper describes the first case of Trichostrongylus axei infestation in a wild hare in western Romania. A female wild hare carcass found in Timis County was examined at the Parasiology Department of the Faculty of Veterinary Medicine in Timisoara. A clinical, post-mortem and PCR examination was performed to establish a diagnosis, with molecular analysis confirming the presence of the nematode Trichostrongylus axei in European brown hare

PUBLICITÉ, ICONICITÉ, VERBALISATION DE L’IMAGE / PUBLICITY, ICONICITY, IMAGE VERBALIZATION / PUBLICITATE, ICONICITATE, VERBALIZAREA IMAGINII

Structure sémiologique mixte, la publicité écrite se fonde sur un double système, iconique et verbal. Les différents niveaux s’interpénètrent et se confondent. Les signes linguistiques du texte publicitaire sont en étroite relation de dépendance avec les signes iconiques de l’image. Le sens est le résultat d’une amalgamation recherchée des deux niveaux de lecture. Le texte et l’image ne jouent pas le même rôle et n’ont pas le même poids au sein de l’annonce

Bag-of-Tasks Scheduling under Budget Constraints

Commercial cloud offerings, such as Amazon’s EC2, let users allocate compute resources on demand, charging based on reserved time intervals. While this gives great flexibility to elastic applications, users lack guidance for choosing between multiple offerings, in order to complete their computations within given budget constraints. In this work, we present BaTS, our budget-constrained scheduler. BaTS can schedule large bags of tasks onto multiple clouds with different CPU performance and cost, minimizing completion time while respecting an upper bound for the budget to be spent. BaTS requires no a-priori information about task completion times, and learns to estimate them at run time. We evaluate BaTS by emulating different cloud environments on the DAS-3 multi-cluster system. Our results show that BaTS is able to schedule within a user-defined budget (if such a schedule is possible at all.) At the expense of extra compute time, signifcant cost savings can be achieved when comparing to a cost-oblivious round-robin scheduler.

TEXTES ET ARGUMENTATION PUBLICITAIRE

There four essential types of advertising texts : demonstrative, narrative, descriptive and prescriptive. They all exhibit both the general characteristics of the genre, as well as certain particular characteristics. However, in any type of text, advertising is always argumentative. The article will present these four types of texts and will examine the way in which argumentation is organised in each of them

Budget Estimation and Control for Bag-of-Tasks Scheduling in Clouds

Commercial cloud offerings, such as Amazon’s EC2, let users allocate compute resources on demand, charging based on reserved time intervals. While this gives great flexibility to elastic applications, users lack guidance for choosing between multiple offerings, in order to complete their computations within given budget constraints. In this work, we present BaTS, our budget-constrained scheduler. Using a small task sample, BaTS can estimate costs and makespan for a given bag on different cloud offerings. It provides the user with a choice of options before execution and then schedules the bag according to the user’s prferences. BaTS requires no a-priori information about task completion times. We evaluate BaTS by emulating different cloud environments on the DAS-3 multi-cluster system. Our results show that BaTS correctly estimates budget and makespan for the scenarios investigated; the user-selected schedule is then executed within the given budget limitations.

Towards resource disaggregation - Memory scavenging for scientific workloads

Compute clusters, consisting of many, uniformly built nodes, are used to run a large spectrum of different workloads, like tightly coupled (MPI) jobs, MapReduce, or graph-processing data-analytics applications, each of which with their own resource requirements. Many studies consistently highlight two types of under-utilized cluster resources: memory (up to 50%) and network. In this work, we take a step towards (software) resource disaggregation, and therefore increased resource utilization, by designing a memory scavenging technique that makes unused memory available to applications on other cluster nodes. We implement this technique in MemFSS, an inmemory distributed file system. The scavenging MemFSS extends its storage space by taking advantage of the unused memory and bandwidth of cluster nodes already running other tenants' applications. Our experiments show that our memory scavenging approach incurs negligible overhead (below 10%) for most tenant applications, while the compute resource comsumption of MemFSS applications is largely reduced (by 17%-74%)

Stochastic tail-phase optimization for bag-of-tasks execution in clouds

Abstract—Elastic applications like bags of tasks benefit greatly from Infrastructure as a Service (IaaS) clouds that let users allocate compute resources on demand, charging based on reserved time intervals. Users, however, still need guidance for mapping their applications onto multiple IaaS offerings, both minimizing execution time and respecting budget limitations. For budgetcontrolled execution of bags of tasks, we built BaTS, a scheduler that estimates possible budget and makespan combinations using a tiny task sample, and then executes a bag within the user’s budget constraints. Previous work has shown the efficacy of this approach. There remains, however, the risk of outlier tasks causing the execution to exceed the predicted makespan. In this work, we present a stochastic optimization of the tail phase for BaTS ’ execution. The main idea is to use the otherwise idling machines up until the end of their (already paidfor) allocation time. Using the task completion time information acquired during the execution, BaTS decides which tasks to replicate onto idle machines in the tail phase, reducing the makespan and improving the tolerance to outlier tasks. Our evaluation results show that this effect is robust w.r.t. the quality of runtime predictions and is the strongest with more expensive schedules in which many fast machines are available. Index Terms—Scheduling, Budget, Task Replication I