Online Allocation of Splitable Clients to Multiple Servers on Large Scale Heterogeneous Platforms

International audienceDans cet article, nous considérons l'allocation dynamique (online) d'un très grand nombre de tâches identiques et indépendantes sur une plate-forme maîtres-esclaves. Initialement, plusieurs nœuds maîtres possèdent ou génèrent les tâches qui sont ensuite transférées et traitées par des nœuds esclaves. L'objectif est de maximiser le débit (i.e., le nombre fractionnaire de tâches qui peut être traité en une unité de temps, en régime permanent, par la plate-forme). Nous considérons que les communications se déroulent suivant le modèle multi-port à degré borné, dans lequel plusieurs communications peuvent avoir lieu simultanément sous réserve qu'aucune bande passante ne soit dépassée et qu'aucun serveur n'ouvre simultanément un nombre de connections supérieur à son degré maximal. Sous ce modèle, la maximisation du débit correspond au problème Maximum-Througput- Bounded-Degree (MTBD) qui a été analysé dans~\cite{beaumont08}. Il a été montré que le problème est NP-Complet au sens fort mais qu'une augmentation de ressources minimale (de 1) sur le degré maximal des serveurs permet de le résoudre en temps polynomial. Dans cet article, nous considérons une extension de MTBD à la situation plus réaliste, dans le contexte des plates-formes de calcul à grande échelle, dans laquelle les nœuds esclaves rejoignent et quittent dynamiquement la plate-forme à des instants arbitraires (problème online MTBD). Nous montrons tout d'abord qu'aucun algorithme complètement à la volée (c.-à.-d. qui n'autorise pas les déconnections) ne peut conduire à un facteur d'approximation constant, quelle que soit l'augmentation de ressources utilisée. Ensuite, nous montrons qu'il est en fait possible de maintenir à tout instant la solution optimale (avec une augmentation de ressource additive de 1) en ne réalisant à chaque modification de la plate-forme qu'une déconnection et qu'une nouvelle connection par maître

Extended Version: Online Allocation of Splitable Clients to Multiple Servers on Large Scale Heterogeneous Platforms

In this paper, we consider the problem of the online allocation of a very large number of identical tasks on a master-slave platform. Initially, several masters hold or generate tasks that are transfered and processed by slave nodes. The goal is to maximize the overall throughput achieved using this platform, i.e., the (fractional) number of tasks that can be processed within one time unit. We model the communications using the so-called bounded degree multi-port model, in which several communications can be handled by a master node simultaneously, provided that bandwidths limitation are not exceeded and that a given server is not involved in more simultaneous communications than its maximal degree. Under this model, it has been proved that maximizing the throughput (MTBD problem) is NP-Complete in the strong sense but that a small additive resource augmentation (of 1) on the servers degrees is enough to find in polynomial time a solution that achieves at least the optimal throughput. In this paper, we consider the reasonable setting where the set of slave processors is not known in advance but rather join and leave the system at any time, i.e., the online version of MTBD. We prove that no fully online algorithm (where nodes cannot be disconnected even if they do not leave the system) can achieve a constant approximation ratio, whatever the resource augmentation on servers degrees. Then, we prove that it is possible to maintain the optimal solution at the cost of at most one change per server each time a new node joins and leave the system. At last, we propose several other greedy heuristics to solve the online problem and we compare the performance (in terms of throughput) and the cost (in terms of disconnexions and reconnections) of proposed algorithms through a set of extensive simulation results

HIL: designing an exokernel for the data center

We propose a new Exokernel-like layer to allow mutually untrusting physically deployed services to efficiently share the resources of a data center. We believe that such a layer offers not only efficiency gains, but may also enable new economic models, new applications, and new security-sensitive uses. A prototype (currently in active use) demonstrates that the proposed layer is viable, and can support a variety of existing provisioning tools and use cases.Partial support for this work was provided by the MassTech Collaborative Research Matching Grant Program, National Science Foundation awards 1347525 and 1149232 as well as the several commercial partners of the Massachusetts Open Cloud who may be found at http://www.massopencloud.or

The OMII Software – Demonstrations and Comparisons between two different deployments for Client-Server Distributed Systems

This paper describes the key elements of the OMII software and the scenarios which OMII software can be deployed to achieve distributed computing in the UK e-Science Community, where two different deployments for Client-Server distributed systems are demonstrated. Scenarios and experiments for each deployment have been described, with its advantages and disadvantages compared and analyzed. We conclude that our first deployment is more relevant for system administrators or developers, and the second deployment is more suitable for users’ perspective which they can send and check job status for hundred job submissions