Pierre Sens

Performance analysis of a hierarchical failure detector

We present a new failure detector implementation. This implementation, a variant of the heartbeat failure detector, is both adaptable and designed for scalability. Its first specificity lies in the fact that it is designed as a shared service among several applications by way of an adaptation layer. This layer adapts the quality of service according to application needs. The second specificity is the hierarchic organization of the detection service: it allows to decrease the number of messages and the processor load. Through an experimentation evaluation, we show that our implementation is adaptable to the environment characteristics and usable with large scale applications.

DARX - a framework for the fault-tolerant support of agent software

This paper presents DARX, our framework for building applications that provide adaptive fault tolerance. It relies on the fact that multi-agent platforms constitute a very strong basis for decentralized software that is both flexible and scalable, and makes the assumption that the relative importance of each agent varies during the course of the computation. DARX regroups solutions which facilitate the creation of multi-agent applications in a large-scale context. Its most important feature is adaptive replication: replication strategies are applied on a per-agent basis with respect to transient environment characteristics such as the importance of the agent for the computation, the network load or the mean time between failures. Firstly, the interwoven concerns of multi-agent systems and fault-tolerant solutions are put forward. An overview of the DARX architecture follows, as well as an evaluation of its performances. We conclude, after outlining the promising outcomes, by presenting prospective work.

Towards QoS-Oriented SLA Guarantees for Online Cloud Services

Cloud Computing provides a convenient means of remote on-demand and pay-per-use access to computing resources. However, its ad hoc management of quality-of-service and SLA poses significant challenges to the performance, dependability and costs of online cloud services. The paper precisely addresses this issue and makes a threefold contribution. First, it introduces a new cloud model, the SLAaaS (SLA aware Service) model. SLAaaS enables a systematic integration of QoS levels and SLA into the cloud. It is orthogonal to other cloud models such as SaaS or PaaS, and may apply to any of them. Second, the paper introduces CSLA, a novel language to describe QoS-oriented SLA associated with cloud services. Third, the paper presents a control theoretic approach to provide performance, dependability and cost guarantees for online cloud services, with time-varying workloads. The proposed approach is validated through case studies and extensive experiments with online services hosted in clouds such as Amazon EC2. The case studies illustrate SLA guarantees for various services such as a MapReduce service, a cluster-based multi-tier e-commerce service, and a low-level locking service.

SLA guarantees for cloud services

Quality-of-service and SLA guarantees are among the major challenges of cloud-based services. In this paper we first present a new cloud model called SLAaaS - SLA?aware Service. SLAaaS considers QoS levels and SLA as first class citizens of cloud-based services. This model is orthogonal to other SaaS, PaaS, and IaaS cloud models, and may apply to any of them. More specifically we make three contributions: (i) we provide a novel domain specific language that allows to describe QoS-oriented SLA associated with cloud services; (ii) we present a general control-theoretic approach for managing cloud service SLA; (iii) we apply the proposed language and control approach to guarantee SLA in various case studies, ranging from cloud-based MapReduce service, to locking service, and higher-level e-commerce service; these case studies successfully illustrate SLA management with different QoS aspects of cloud services such as performance, dependability, financial energetic costs. We provide a domain specific language that allows to describe SLA in cloud services.We present a general control-theoretic approach for managing cloud service SLA.We apply our approach on MapReduce, locking, and e-commerce services.

Distributed mutual exclusion algorithms for grid applications: A hierarchical approach

The majority of current distributed mutual exclusion algorithms are not suited for parallel or distributed applications on a Grid as they do not consider the heterogeneity of latency on Grids. We propose two distributed mutual exclusion algorithms, based on Naimi-Trehels token-based algorithm, which take into account latency gaps, especially those between local and remote clusters of machines. Our first algorithm exploits cluster locality by giving higher priority to critical section requests issued from nodes of the same cluster when compared to those from remote nodes. Our second algorithm adds a router layer to the first algorithm, bringing it closer to Grid network topology. Viewing each cluster as a single node, the Naimi-Trehel algorithm is applied to this router layer. Redirection of inter-cluster messages to clusters nodes is then minimized.

Service Level Agreement for Distributed Mutual Exclusion in Cloud Computing

In Cloud Computing, Service Level Agreement (SLA) is a contract that defines a level and a type of QoS between a cloud provider and a client. Since applications in a Cloud share resources, we propose two tree-based distributed mutual exclusion algorithms that support the SLA concept. The first one is a modified version of the priority-based Kanrar-Chaki algorithm [1] while the second one is a novel algorithm, based on Raymond algorithm [2], where a deadline is associated with every request. In both cases, our aim is to improve Critical Section execution rate and to reduce the number of SLA violations, which, for the first algorithm represents the number of priority inversions (i.e. a higher priority request is satisfied after a lower one) and for the second one, the number of requests whose deadline is not respected. Performance evaluation results show that our solutions significantly reduce SLA violations avoiding message overhead.

A fault-tolerant token-based mutual exclusion algorithm using a dynamic tree

This article presents a fault tolerant extension for the Naimi-Trehel token-based mutual exclusion algorithm. Contrary to the extension proposed by Naimi-Trehel, our approach minimizes the use of broadcast support by exploiting the distributed queue of token requests kept by the original algorithm. It also provides good fairness since, during failure recovery, it tries to preserve the order in which token requests would have been satisfied had the failure not occurred.

Eventually Strong Failure Detector with Unknown Membership

The distributed computing scenario is rapidly evolving for integrating self-organizing and dynamic wireless networks. Unreliable failure detectors (FDs) are classical mechanisms that provide information about process failures and can help systems to cope with the high dynamics of these networks. A number of failure detection algorithms have been proposed so far. Nonetheless, most of them assume a global knowledge about the membership as well as a fully communication connectivity; additionally, they are time-based, requiring that eventually some bound on the message transmission will permanently hold. These assumptions are no longer appropriate to the new scenario. This paper presents a new FD protocol that implements a new class of detectors, namely ⋄ SM, which adapts the properties of the ⋄ S class to a dynamic network with an unknown membership. It has the interesting feature of being time-free, so that it does not rely on timers to detect failures; moreover, it tolerates the mobility of nodes and message losses.

A Composition Approach to Mutual Exclusion Algorithms for Grid Applications

We propose a new composition approach to mutual exclusion algorithms for applications spread over a grid which is composed of a federation of clusters. Taking into account the heterogeneity of communication latency, our hierarchical architecture combines intra and inter cluster algorithms. We focus on token-based algorithms and study different compositions of algorithms. Performance evaluation tests have been conducted on a national grid testbed whose results show that our approach is scalable and that the choice of the most suitable inter cluster algorithm depends on the behavior of the application.

Predicting durability in DHTs using Markov chains

We consider the problem of data durability in low-bandwidth large-scale distributed storage systems. Given the limited bandwidth between replicas, these systems suffer from long repair times after a hard disk crash, making them vulnerable to data loss when several replicas fail within a short period of time. Recent work has suggested that the probability of data loss can be predicted by modeling the number of live replicas using a Markov chain. This, in turn, can then be used to determine the number of replicas necessary to keep the loss probability under a given desired value. Previous authors have suggested that the model parameters can be estimated using an expression that is constant or linear on the number of replicas. Our simulations, however, show that neither is correct, as these parameter values grow sublinearly with the number of replicas. Moreover, we show that using a linear expression will result in the probability of data loss being underestimated, while the constant expression will produce a significant overestimation. Finally, we provide an empirical expression that yields a good approximation of the sublinear parameter values. Our work can be viewed as a first step towards finding more accurate models to predict the durability of this type of systems.