Network Calculus.- Application of Network Calculus to the Internet.- Basic Min-plus and Max-plus Calculus.- Min-plus and Max-plus System Theory.- Optimal Multimedia Smoothing.- FIFO Systems and Aggregate Scheduling.- Adaptive and Packet Scale Rate Guarantees.- Time Varying Shapers.- Systems with Losses.

Network Calculus: A Theory of Deterministic Queuing Systems for the Internet

As organizations start to use data-intensive cluster computing systems like Hadoop and Dryad for more applications, there is a growing need to share clusters between users. However, there is a conflict between fairness in scheduling and data locality (placing tasks on nodes that contain their input data). We illustrate this problem through our experience designing a fair scheduler for a 600-node Hadoop cluster at Facebook. To address the conflict between locality and fairness, we propose a simple algorithm called delay scheduling: when the job that should be scheduled next according to fairness cannot launch a local task, it waits for a small amount of time, letting other jobs launch tasks instead. We find that delay scheduling achieves nearly optimal data locality in a variety of workloads and can increase throughput by up to 2x while preserving fairness. In addition, the simplicity of delay scheduling makes it applicable under a wide variety of scheduling policies beyond fair sharing.

/pdf/delay-scheduling-a-simple-technique-for-achieving-locality-30rhka6951.pdf

Delay scheduling: a simple technique for achieving locality and fairness in cluster scheduling

The range of user requirements on multicast protocols is so wide that no single protocol will ever satisfy them. The set of multicast protocols can be classified using the user requirements, and the architectures, mechanisms, communications patterns, and policies used to satisfy these requirements. We provide such a classification, and illustrate it with several example protocols chosen to cover the range of features described.

A Classification of

While today's computer networks support only best-effort service, future packet-switching integrated-services networks will have to support real-time communication services that allow clients to transport information with performance guarantees expressed in terms of delay, delay jitter, throughput, and loss rate. An important issue in providing guaranteed performance service is the choice of the packet service discipline at switching nodes. In this paper, we survey several service disciplines that are proposed in the literature to provide per-connection end-to-end performance guarantees in packet-switching networks. We describe their mechanisms, their similarities and differences and the performance guarantees they can provide. Various issues and tradeoffs in designing service disciplines for guaranteed performance service are discussed, and a general framework for studying and comparing these disciplines are presented. >

/pdf/service-disciplines-for-guaranteed-performance-service-in-yk74mpzi11.pdf

Service disciplines for guaranteed performance service in packet-switching networks

We consider the problem of fair resource allocation in a system containing different resource types, where each user may have different demands for each resource. To address this problem, we propose Dominant Resource Fairness (DRF), a generalization of max-min fairness to multiple resource types. We show that DRF, unlike other possible policies, satisfies several highly desirable properties. First, DRF incentivizes users to share resources, by ensuring that no user is better off if resources are equally partitioned among them. Second, DRF is strategy-proof, as a user cannot increase her allocation by lying about her requirements. Third, DRF is envy-free, as no user would want to trade her allocation with that of another user. Finally, DRF allocations are Pareto efficient, as it is not possible to improve the allocation of a user without decreasing the allocation of another user. We have implemented DRF in the Mesos cluster resource manager, and show that it leads to better throughput and fairness than the slot-based fair sharing schemes in current cluster schedulers.

https://static.usenix.org/event/nsdi11/tech/full_papers/Ghodsi.pdf

Dominant resource fairness: fair allocation of multiple resource types

The generalized processor sharing (GPS) discipline is proven to have two desirable properties: (a) it can provide an end-to-end bounded-delay service to a session whose traffic is constrained by a leaky bucket; (b) it can ensure fair allocation of bandwidth among all back logged sessions regardless of whether or not their traffic is constrained. The former property is the basis for supporting guaranteed service traffic while the later property is important for supporting best-effort service traffic. Since GPS uses an idealized fluid model which cannot be realized in the real world, various packet approximation algorithms of the GPS have been proposed. Among these, weighted fair queueing (WFQ) also known as packet generalized processor sharing (PGPS) has been considered to be the best one in terms of accuracy. In particular, it has been proven that the delay bound provided by WFQ is within one packet transmission time of that provided by GPS. We show that, contrary to popular belief there could be large discrepancies between the services provided by the packet WFQ system and the fluid GPS system. We argue that such a discrepancy will adversely effect many congestion control algorithms that rely on services similar to those provided by GPS. A new packet approximation algorithm of GPS called worst-case fair weighted fair queueing (WF/sup 2/Q) is proposed. The service provided by WF/sup 2/Q is almost identical to that of GPS, differing no more than one maximum size packet.

WF/sup 2/Q: worst-case fair weighted fair queueing

It is a widely held belief that packet reordering in the Internet is a pathological behavior, or more precisely, that it is an uncommon behavior caused by incorrect or malfunctioning network components. Some studies of Internet traffic have reported seeing occasional packet reordering events and ascribed these events to "route fluttering", router "pauses" or simply to broken equipment. We have found, however, that parallelism in Internet components and links is causing packet reordering under normal operation and that the incidence of packet reordering appears to be substantially higher than previously reported. More importantly, we observe that in the presence of massive packet reordering transmission control protocol (TCP) performance can be profoundly effected. Perhaps the most disturbing observation about TCP's behavior is that large scale and largely random reordering on the part of the network can lead to self-reinforcingly poor performance from TCP.

Packet reordering is not pathological network behavior

We propose to use the idealized hierarchical generalized processor sharing (H-GPS) model to simultaneously support guaranteed real-time, rate-adaptive best-effort, and controlled link-sharing services. We design hierarchical packet fair queueing (H-PFQ) algorithms to approximate H-GPS by using one-level variable-rate PFQ servers as basic building blocks. By computing the system virtual time and per packet virtual start/finish times in unit of bits instead of seconds, most of the PFQ algorithms in the literature can be properly defined as variable-rate servers. We develop techniques to analyze delay and fairness properties of variable-rate and hierarchical PFQ servers. We demonstrate that in order to provide tight delay bounds with an H-PFQ server, it is essential for the one-level PFQ servers to have small worst-case fair indices (WFI). We propose a new PFQ algorithm called WF/sup 2/Q+ that is the first to have all the following three properties: (1) providing the tightest delay bound among all PFQ algorithms; (2) having the smallest WFI among all PFQ algorithms; and (3) having a relatively low asymptotic complexity of O(log N). Simulation results are presented to evaluate the delay and link-sharing properties of H-WF/sup 2/Q+, H-WFQ, H-SFQ, and H-SCFQ.

Hierarchical packet fair queueing algorithms

Hierarchical Packet Fair Queueing (H-PFQ) algorithms have the potential to simultaneously support guaranteed real-time service, rate-adaptive best-effort, and controlled link-sharing service. In this paper, we design practical H-PFQ algorithms by using one-level Packet Fair Queueing (PFQ) servers as basic building blocks, and develop techniques to analyze delay and fairness properties of the resulted H-PFQ servers. We demonstrate that, in order to provide tight delay bounds in a H-PFQ server, it is essential for the one-level PFQ servers to have small Worst-case Fair Indices (WFI). We propose a new one-level PFQ algorithm called WF2Q+ that is the first to have all the following three properties: (a) providing the tightest delay bound among all PFQ algorithms; (b) having the smallest WFI among all PFQ algorithms; and (c) having a relatively low implementation complexity of O(log N). We show that practical H-PFQ algorithms can be implemented by using WF2Q+ as the basic building block and prove that the resulting H-WF2Q+ algorithms provide similar delay bounds and bandwidth distribution as those provided by a H-GPS server. Simulation experiments are presented to evaluate the proposed algorithm.

A system and method for managing the storage of data in non-volatile memory is described. In an aspect, the data may be described by metadata and a transaction log file that are checkpointed from a volatile memory into the non-volatile memory. Actions that take place between the last checkpointing of a metadata segment and log file segment are discovered by scanning the non-volatile memory blocks, taking account of a record of the highest sector in each block that is known to have been recorded. Any later transactions are discovered and used to update the recovered metadata so that the metadata correctly represents the stored data.

Jon C. R. Bennett

Papers

WF/sup 2/Q: worst-case fair weighted fair queueing

Packet reordering is not pathological network behavior

Hierarchical packet fair queueing algorithms

Hierarchical packet fair queueing algorithms

Method and system for storage of data in non-volatile media