Heavy-Tailed Limits for Medium Size Jobs and Comparison Scheduling

We study the conditional sojourn time distributions of processor sharing (PS), foreground background processor sharing (FBPS) and shortest remaining processing time first (SRPT) scheduling disciplines on an event where the job size of a customer arriving in stationarity is smaller than exactly k>=0 out of the preceding m>=k arrivals. Then, conditioning on the preceding event, the sojourn time distribution of this newly arriving customer behaves asymptotically the same as if the customer were served in isolation with a server of rate (1-\rho)/(k+1) for PS/FBPS, and (1-\rho) for SRPT, respectively, where \rho is the traffic intensity. Hence, the introduced notion of conditional limits allows us to distinguish the asymptotic performance of the studied schedulers by showing that SRPT exhibits considerably better asymptotic behavior for relatively smaller jobs than PS/FBPS. Inspired by the preceding results, we propose an approximation to the SRPT discipline based on a novel adaptive job grouping mechanism that uses relative size comparison of a newly arriving job to the preceding m arrivals. Specifically, if the newly arriving job is smaller than k and larger than m-k of the previous m jobs, it is routed into class k. Then, the classes of smaller jobs are served with higher priorities using the static priority scheduling. The good performance of this mechanism, even for a small number of classes m+1, is demonstrated using the asymptotic queueing analysis under the heavy-tailed job requirements. We also discuss refinements of the comparison grouping mechanism that improve the accuracy of job classification at the expense of a small additional complexity.Comment: 26 pages, 2 figure

Datacenter Traffic Control: Understanding Techniques and Trade-offs

Datacenters provide cost-effective and flexible access to scalable compute and storage resources necessary for today's cloud computing needs. A typical datacenter is made up of thousands of servers connected with a large network and usually managed by one operator. To provide quality access to the variety of applications and services hosted on datacenters and maximize performance, it deems necessary to use datacenter networks effectively and efficiently. Datacenter traffic is often a mix of several classes with different priorities and requirements. This includes user-generated interactive traffic, traffic with deadlines, and long-running traffic. To this end, custom transport protocols and traffic management techniques have been developed to improve datacenter network performance. In this tutorial paper, we review the general architecture of datacenter networks, various topologies proposed for them, their traffic properties, general traffic control challenges in datacenters and general traffic control objectives. The purpose of this paper is to bring out the important characteristics of traffic control in datacenters and not to survey all existing solutions (as it is virtually impossible due to massive body of existing research). We hope to provide readers with a wide range of options and factors while considering a variety of traffic control mechanisms. We discuss various characteristics of datacenter traffic control including management schemes, transmission control, traffic shaping, prioritization, load balancing, multipathing, and traffic scheduling. Next, we point to several open challenges as well as new and interesting networking paradigms. At the end of this paper, we briefly review inter-datacenter networks that connect geographically dispersed datacenters which have been receiving increasing attention recently and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial

Performance Analysis of LAS-based Scheduling Disciplines in a Packet Switched Network

The Least Attained Service (LAS) scheduling policy, when used for scheduling packets over the bottleneck link of an Internet path, can greatly reduce the average flow time for short flows while not significantly increasing the average flow time for the long flows that share the same bottleneck. No modification of the packet headers is required to implement the simple LAS policy. However, previous work has also shown that a drawback of the LAS scheduler is that, when link utilization is greater than 70%, long flows experience large jitter in their packet transfer times as compared to the conventional First-Come-First-Serve (FCFS) link scheduling. This paper proposes and evaluates new differentiated LAS scheduling policies that reduce the jitter for long flows that are identified as "priority" flows

ABSTRACT Performance Analysis of LAS-based Scheduling Disciplines in a Packet Switched Network

The Least Attained Service (LAS) scheduling policy, when used for scheduling packets over the bottleneck link of an Internet path, can greatly reduce the average flow time for short flows while not significantly increasing the average flow time for the long flows that share the same bottleneck. No modification of the packet headers is required to implement the simple LAS policy. However, previous work has also shown that a drawback of the LAS scheduler is that, when link utilization is greater than 70%, long flows experience large jitter in their packet transfer times as compared to the conventional First-Come-First-Serve (FCFS) link scheduling. This paper proposes and evaluates new differentiated LAS scheduling policies that reduce the jitter for long flows that are identified as ”priority” flows. To evaluate the new policies, we develop analytic models to estimate average flow transfer time as a function of flow size, an

Enterprise networks (modern techniques for analysis, measurement and performance improvement)

Dans l'évaluation d'Internet au cours des années, un grand nombre d'applications apparaissent, avec différentes exigences de service en termes de bande passante, délai et ainsi de suite. Pourtant, le trafic Internet présente encore une propriété de haute variabilité. Plusieurs études révèlent que les flux court sont en général liés à des applications interactives-pour ceux-ci, on s'attend à obtenir de bonne performance que l'utilisateur perçoit, le plus souvent en termes de temps de réponse court. Cependant, le schéma classique FIFO/drop-tail déployé des routeurs/commutateurs d'aujourd'hui est bien connu de parti pris contre les flux courts. Pour résoudre ce problème sur un réseau best-effort, nous avons proposé un nouveau et simple algorithme d'ordonnancement appelé EFD (Early Flow Discard). Dans ce manuscrit, nous avons d'abord évaluer la performance d'EFD dans un réseau câblé avec un seul goulot d'étranglement au moyen d'étendu simulations. Nous discutons aussi des variantes possibles de EFD et les adaptations de EFD à 802.11 WLAN - se réfèrent principalement à EFDACK et PEFD, qui enregistre les volumes échangés dans deux directions ou compte simplement les paquets dans une direction, visant à améliorer l'équité à niveau flot et l'interactivité dans les WLANs. Enfin, nous nous consacrons à profiler le trafic de l'entreprise, en plus de elaborer deux modèles de trafic-l'une qui considère la structure topologique de l'entreprise et l'autre qui intègre l'impact des applications au-dessus de TCP - pour aider à évaluer et à comparer les performances des politiques d'ordonnancement dans les réseaux d'entreprise classiques.As the Internet evolves over the years, a large number of applications emerge with varying service requirements in terms of bandwidth, delay, loss rate and so on. Still, the Internet traffic exhibits a high variability property the majority of the flows are of small sizes while a small percentage of very long flows contribute to a large portion of the traffic volume. Several studies reveal that small flows are in general related to interactive applications for which one expects to obtain good user perceived performance, most often in terms of short response time. However, the classical FIFO/drop-tail scheme deployed in today s routers/switches is well known to bias against short flows over long ones. To tackle this issue over a best-effort network, we have proposed a novel and simple scheduling algorithm named EFD (Early Flow Discard). In this manuscript, we first evaluate the performance of EFD in a single-bottleneck wired network through extensive simulations. We then discuss the possible variants of EFD and EFD s adaptations to 802.11 WLANs mainly refer to EFDACK and PEFD. Finally, we devote ourselves to profiling enterprise traffic, and further devise two workload models - one that takes into account the enterprise topological structure and the other that incorporates the impact of the applications on top of TCP - to help to evaluate and compare the performance of scheduling policies in typical enterprise networks.PARIS-Télécom ParisTech (751132302) / SudocSudocFranceF

Task assignment in server farms under realistic workload conditions

Server farms have become very popular in recent years since they effectively address the problem of large delays, a common problem faced by many organisations whose systems receive high volumes of traffic. Recently, there has been a wide use of these server farms in two main areas, namely, Web hosting and scientific computing. The performance of such server farms is highly reliant on the underlying task assignment policy, a specific set of rules that defines how the incoming tasks are assigned to and processed at hosts. The aim of a task assignment policy is to optimise certain performance criteria such as the expected waiting time and slowdown. One of the key factors that affect the performance of these policies is the service time distribution of tasks. There is extensive evidence indicating that the service times of modern computer workloads closely follow heavy-tailed distributions that possess high variance. However, in certain environments, the service time distributions of tasks are unknown. Imposing parametric assumptions in such cases can lead to inaccurate and unreliable inferences. Considerable efforts have been made in recent years to devise efficient policies. Although these policies perform well under specific workload conditions, they have several major limitations. These include the assumption of known service times, inability to efficiently assign tasks in time sharing server farms, poor performance under changing workload conditions and poor performance under multiple server farms. This thesis aims at proposing novel task assignment policies for assigning tasks in server farms under two main classes of realistic workload conditions, namely, the heavy-tailed and arbitrary service time distributions. Arbitrary service time distributions are assumed, for cases where the underlying service time distribution of tasks is unknown. First we investigate ways to optimise the performance in a time-sharing server. We concentrate on a particular scheduling policy called multi-level time sharing policy (MLTP). We provide an extensive performance analysis of MTLP and show that MLTP can result in significant performance improvements under certain traffic conditions. Second we investigate how to improve the performance in time sharing server farms using MLTP. Three task assignment policies are proposed for time sharing server farms. Third we investigate how to design efficient task assignment policies to assign tasks in multiple server farms. We propose MCTPM which is based on a multi-tier host architecture. MCTPM supports preemptive task migration and it controls the traffic flow into server farms via a global dispatching device so as to optimise the performance. Finally, we investigate ways to design adaptive task assignment policies that make no assumptions regarding the underlying service time distribution of tasks. We propose a novel task assignment policy, called ADAPT-POLICY, which is based on a set of static-based task assignment policies. ADAPT-POLICY is based on a set of policies for the server farm and it adaptively changes the task assignment policy to suit the most recent traffic conditions. The experimental performance analysis of ADAPT-POLICY shows that ADAPT-POLICY outperforms other policies under a range of traffic conditions

Effective task assignment strategies for distributed systems under highly variable workloads

Heavy-tailed workload distributions are commonly experienced in many areas of distributed computing. Such workloads are highly variable, where a small number of very large tasks make up a large proportion of the workload, making the load very hard to distribute effectively. Traditional task assignment policies are ineffective under these conditions as they were formulated based on the assumption of an exponentially distributed workload. Size-based task assignment policies have been proposed to handle heavy-tailed workloads, but their applications are limited by their static nature and assumption of prior knowledge of a task's service requirement. This thesis analyses existing approaches to load distribution under heavy-tailed workloads, and presents a new generalised task assignment policy that significantly improves performance for many distributed applications, by intelligently addressing the negative effects on performance that highly variable workloads cause. Many problems associated with the modelling and optimisations of systems under highly variable workloads were then addressed by a novel technique that approximated these workloads with simpler mathematical representations, without losing any of their pertinent original properties. Finally, we obtain advance queuing metrics (such as the variance of key measurements like waiting time and slowdown that are difficult to obtain analytically) through rigorous simulation

Predicting software performance in symmetric multi-core and multiprocessor Environments

With today\u27s rise of multi-core processors, concurrency becomes a ubiquitous challenge in software development.Performance prediction methods have to reflect the influence of multiprocessing environments on software performance in order to help software architects to find potential performance problems during early development phases. In this thesis, we address the influence of the operating system scheduler on software performance in symmetric multiprocessing environments