Mary K. Vernon

Minimizing bandwidth requirements for on-demand data delivery

Two recent techniques for multicast or broadcast delivery of streaming media can provide immediate service to each client request, yet achieve considerable client stream sharing which leads to significant server and network bandwidth savings. The paper considers: 1) how well these recently proposed techniques perform relative to each other and 2) whether there are new practical delivery techniques that can achieve better bandwidth savings than the previous techniques over a wide range of client request rates. The principal results are as follows: First, the recent partitioned dynamic skyscraper technique is adapted to provide immediate service to each client request more simply and directly than the original dynamic skyscraper method. Second, at moderate to high client request rates, the dynamic skyscraper method has required server bandwidth that is significantly lower than the recent optimized stream tapping/patching/controlled multicast technique. Third, the minimum required server bandwidth for any delivery technique that provides immediate real-time delivery to clients increases logarithmically (with constant factor equal to one) as a function of the client request arrival rate. Furthermore, it is (theoretically) possible to achieve very close to the minimum required server bandwidth if client receive bandwidth is equal to two times the data streaming rate and client storage capacity is sufficient for buffering data from shared streams. Finally, we propose a new practical delivery technique, called hierarchical multicast stream merging (HMSM), which has a required server bandwidth that is lower than the partitioned dynamic skyscraper and is reasonably close to the minimum achievable required server bandwidth over a wide range of client request rates.

A Generalized Timed Petri Net Model for Performance Analysis

We have developed a Generalized Timed Petri Net (GTPN) model for evaluating the performance of computer systems. Our model is a generalization of the TPN model proposed by Zuberek [1] and extended by Razouk and Phelps [2]. In this paper, we define the GTPN model and present how performance estimates are obtained from the GTPN. We demonstrate the use of our automated GTPN analysis techniques on the dining philosophers example. This example violates restrictions made in the earlier TPN models. Finally, we compare the GTPN to the stochastic Petri net (SPN) models. We show that the GTPN model has capabilities for modeling and analyzing parallel systems lacking in existing SPN models. The GTPN provides an efficient, easily used method of obtaining accurate performance estimates for models of computer systems which include both deterministic and geometric holding times.

Efficient synchronization primitives for large-scale cache-coherent multiprocessors

This paper proposes a set of efficient primitives for process synchronization in multiprocessors. The only assumptions made in developing the set of primitives are that hardware combining is not implemented in the inter-connect, and (in one case) that the interconnect supports broadcast. The primitives make use of synchronization bits (syncbits) to provide a simple mechanism for mutual exclusion. The proposed implementation of the primitives includes efficient (i.e. local) busy-waiting for syncbits. In addition, a hardware-supported mechanism for maintaining a first-come first-serve queue of requests for a syncbit is proposed. This queueing mechanism allows for a very efficient implementation of, as well as fair access to, binary semaphores. We also propose to implement Fetch and Add with combining in software rather than hardware. This allows an architecture to scale to a large number of processors while avoiding the cost of hardware combining. Scenarios for common synchronization events such as work queues and barriers are presented to demonstrate the generality and ease of use of the proposed primitives. The efficient implementation of the primitives is simpler if the multiprocessor has a hardware cache-consistency protocol. To illustrate this point, we outline how the primitives would be implemented in the Multicube multiprocessor [GoWo88].

The performance of multiprogrammed multiprocessor scheduling algorithms

Scheduling policies for general purpose multiprogrammed multiprocessors are not well understood. This paper examines various policies to determine which properties of a scheduling policy are the most significant determinants of performance. We compare a more comprehensive set of policies than previous work, including one important scheduling policy that has not previously been examined. We also compare the policies under workloads that we feel are more realistic than previous studies have used. Using these new workloads, we arrive at different conclusions than reported in earlier work. In particular, we find that the “smallest number of processes first” (SNPF) scheduling discipline performs poorly, even when the number of processes in a job is positively correlated with the total service demand of the job. We also find that policies that allocate an equal fraction of the processing power to each job in the system perform better, on the whole, than policies that allocate processing power unequally. Finally, we find that for lock access synchronization, dividing processing power equally among all jobs in the system is a more effective property of a scheduling policy than the property of minimizing synchronization spin-waiting, unless demand for synchronization is extremely high. (The latter property is implemented by coscheduling processes within a job, or by using a thread management package that avoids preemption of processes that hold spinlocks.) Our studies are done by simulating abstract models of the system and the workloads.

Optimal and efficient merging schedules for video-on-demand servers

The simplest video-on-demand (VOD) delivery policy is to allocate a new media delivery stream to each client request when it arrives. This policy has the desirable properties of “immediate service” (there is minimal latency between the client request and the start of playback, assuming that sufficient server bandwidth is available to start the new stream), of placing minimal demands on client capabilities (the client receive bandwidth required is the media playback rate, and no client local storage is required), and of being simple to implement. However, the policy is untenable because it requires server bandwidth that scales linearly with the number of clients that must be supported simultaneously, which is too expensive for many applications.

Analysis of educational media server workloads

This paper presents an extensive analysis of the client workloads for educational media servers at two major U.S. universities. The goals of the analysis include providing data for generating synthetic workloads, gaining insight into the design of streaming content distribution networks, and quantifying how much server bandwidth can be saved in interactive educational environments by using recently developed multicast streaming methods for stored content.

Performance analysis of mesh interconnection networks with deterministic routing

This paper develops detailed analytical performance models for k-ary n-cube networks with single-hit or infinite buffers, wormhole routing, and the nonadaptive deadlock-free routing scheme proposed by Dally and Seitz (1987). In contrast to previous performance studies of such networks, the system is modeled as a closed queueing network that: includes the effects of blocking and pipelining of messages in the network; allows for arbitrary source-destination probability distributions; and explicitly models the virtual channels used in the deadlock-free routing algorithm. The models are used to examine several performance issues for 2-D networks with shared-memory traffic. These results should prove useful for engineering high-performance systems based on low-dimensional k-ary n-cube networks. >

Scalable on-demand media streaming with packet loss recovery

Previous scalable on-demand streaming protocols do not allow clients to recover from packet loss. This paper develops new protocols that: (1) have a tunably short latency for the client to begin playing the media; (2) allow heterogeneous clients to recover lost packets without jitter as long as each clients cumulative loss rate is within a tunable threshold; and (3) assume a tunable upper bound on the transmission rate to each client that can be as small as a fraction (e.g., 25%) greater than the media play rate. Models are developed to compute the minimum required server bandwidth for a given loss rate and playback latency. The results of the models are used to develop the new protocols and assess their performance. The new protocols, Reliable Periodic Broadcast and Reliable Bandwidth Skimming, are simple to implement and achieve nearly the best possible scalability and efficiency for a given set of client characteristics and desirable/feasible media quality. Furthermore, the results show that the new reliable protocols that transmit to each client at only twice the media play rate have similar performance to previous protocols that require clients to receive at many times the play rate.

Dynamic Skyscraper Broadcasts for Video-on-Demand

Skyscraper Broadcasting is a recently proposed statically scheduled broadcast technique for video-on-demand that addresses the network-I/O bottleneck to provide significantly superior performance over previous approaches. This paper defines a scheme for dynamically scheduling the objects that are broadcast on the skyscraper channels. The dynamic broadcasting scheme is designed to provide all clients with the precise time at which their requested object will be broadcast, or an upper bound on that time if the delay is small. New segment size progressions are proposed that not only improve dynamic scheduling, but also simplify the server disk layout problem and allow clients with inexpensive (single-tuner, limited storage) settops to receive skyscraper broadcasts. Preliminary simulation results show that the proposed dynamic scheme (1) provides factors of two or more improvement in mean client waiting time, (2) outperforms the static system with respect to variability in client waiting time, and (3) delivers reasonable service to clients with inexpensive settops while providing clients that have more expensive settops with a high level of service that is relatively isolated from detrimental performance impact from the diskless clients.

The Impact of More Accurate Requested Runtimes on Production Job Scheduling Performance

The question of whether more accurate requested runtimes can significantly improve production parallel system performance has previously been studied for the FCFS-backfill scheduler, using a limited set of system performance measures. This paper examines the question for higher performance backfill policies, heavier system loads as are observed in current leading edge production systems such as the large Origin 2000 system at NCSA, and a broader range of system performance measures. The new results show that more accurate requested runtimes can improve system performance much more significantly than suggested in previous results. For example, average slowdown decreases by a factor of two to six, depending on system load and the fraction of jobs that have the more accurate requests. The new results also show that (a) nearly all of the performance improvement is realized even if the more accurate runtime requests are a factor of two higher than the actual runtimes, (b) most of the performance improvement is achieved when test runs are used to obtain more accurate runtime requests, and (c) in systems where only a fraction (e.g., 60%) of the jobs provide approximately accurate runtime requests, the users that provide the approximately accurate requests achieve even greater improvements in performance, such as an order of magnitude improvement in average slowdown for jobs that have runtime up to fifty hours.