In this paper, we consider a K-server threshold-based queueing system with hysteresis in which the number of servers, employed for servicing customers, is governed by a forward threshold vector F= (F1 ; F2 ; : : : ; FK \Gamma1 ) (where F1 ! F2 ! \Delta \Delta \Delta ! FK \Gamma1 ) and a reverse threshold vector R= (R1 ; R2 ; : : : ; RK \Gamma1 ) (where R1 !R2 ! \Delta \Delta \Delta ! RK \Gamma1 ). There are many applications where a thresholdbased queueing system can be of great use. The main motivation for using a threshold-based approach in such applications is that they incur significant server setup, usage, and removal costs. And, as in most practical situations, an important concern is not only the system performance but rather its cost/performance ratio. The motivation for use of hysteresis is to control the cost during momentary fluctuations in workload. An important and distinguishing characteristic of our work is that in our model we consider the time to add a server to be non...

We have designed a stackable file system called Redundant Array of Independent Filesystems (RAIF). It combines the data survivability properties and performance benefits of traditional RAIDs with the unprecedented flexibility of composition, improved security, and ease of development of stackable file systems. RAIF can be mounted on top of any combination of other file systems including network, distributed, disk-based, and memory-based file systems. Existing encryption, compression, antivirus, and consistency checking stackable file systems can be mounted above and below RAIF, to efficiently cope up with slow or unsecure branches. Individual files can be distributed across branches, replicated, stored with parity, or stored with erasure correction coding to recover from failures on multiple branches. Per-file incremental recovery, storage type migration, and load-balancing are especially well suited for grid storages. In this paper we describe the current RAIF design, provide preliminary performance results and discuss current status and future directions. 1

Storage virtualization and data management are well known problems for individual users as well as large organizations. Existing storage-virtualization systems either do not support a complete set of possible storage types, do not provide flexible data-placement policies, or do not support per-file conversion (e.g., encryption). This results in suboptimal utilization of resources, inconvenience, low reliability, and poor performance. We have designed a stackable file system called Redundant Array of Independent Filesystems (RAIF). It combines the data survivability and performance benefits of traditional RAID with the flexibility of composition and ease of development of stackable file systems. RAIF can be mounted on top of directories and thus on top of any combination of network, distributed, disk-based, and memory-based file systems. Individual files can be replicated, striped, or stored with erasure-correction coding on any subset of the underlying file systems. RAIF has similar performance to RAID. In configurations with parity, RAIF’s write performance is better than the performance of driver-level and even entry-level hardware RAID systems. This is because RAIF has better control over the data and parity caching. 1

Abstract—Multimedia-on-Demand (MOD) applications have grown dramatically in popularity, especially in the domains of education, business, and entertainment. Current MOD servers waste precious resources in performing store-and-forward copying. This excessive overhead increases cost and severely limits the scalability of these servers. In this paper, we propose using the Network-Attached Disk (NAD) architecture to design highly scalable and cost-effective MOD servers. In order to ensure enhanced performance, we propose a scheme, called Distributed Interval Caching (DIC), which utilizes the on-disk buffers for caching intervals between successive streams. We also propose another scheme, called Multi-Objective Scheduling (MOS), which increases the degrees of resource sharing by scheduling the waiting requests for service intelligently. We then integrate the two schemes and study the overall performance benefits through extensive simulation. The results demonstrate that the integrated policy works very well in increasing the number of customers that can be serviced concurrently while decreasing their waiting times for service. The performance benefits vary with several architectural, system workload, and scheduling parameters. We conclude this study by developing an analytical model for ideal DIC in order to estimate the performance limits which may be achieved through various optimizations.

Abstract. Recent advances in storage and communication technologies have spurred a strong interest in Video-on-Demand (VOD) services. Providing the customers of VOD servers with time of service guarantees offers two major advantages. First, it makes VOD services more attractive by improving customerperceived quality of service (QoS). Second, it improves throughput through the enhanced resource sharing attained by motivating the customers to wait. In this paper, we propose a new class of scheduling policies, called Next Schedule Time First (NSTF), which provides customers with schedule times and performs scheduling based on these schedule times. NSTF guarantees that customers will be serviced no later than scheduled and ensures that the schedule times are very accurate estimates of the actual times of service. We present alternative implementations of NSTF and show through simulation that NSTF works as expected and delivers outstanding performance benefits. 1

A cost-effective approach to building up scalable Videoon -Demand (VoD) servers is to couple a number of VoD servers together in a cluster. In this article, we study a crucial video replication and placement problem in a distributed storage VoD cluster for high quality and high availability services. We formulate it as a combinatorial optimization problem with objectives of maximizing the encoding bit rate and the number of replicas of each video and balancing the workload of the servers. It is subject to the constraints of the storage capacity and the outgoing network bandwidth of the servers. Under the assumption of single fixed encoding bit rate for all videos, we give an optimal replication algorithm and a bounded placement algorithm for videos with different popularities. To reduce the complexity of the replication algorithm, we present an efficient algorithm that utilizes the Zipf-like video popularity distributions to approximate the optimal solution. For videos with scalable encoding bit rates, we propose a heuristic algorithm based on simulated annealing. We conduct a comprehensive performance evaluation of the algorithms and demonstrate their effectiveness via simulations over a synthetic workload set.

Abstract — Little and Venkatesh conjectured that, for an interactive VoD system with a single random trial resource selection scheme, the blocking probability of a user’s request is minimized when the overall movie traffic load is spread uniformly on each disk in the system. In this paper, we generalize this conjecture to the situation where there can be repeated random trials or where a least busy fit resource selection scheme is used. We support our conjecture with a simulation of a realistic system, and propose a metric following the idea of our conjecture to assess the goodness of movie assignment in the system. I.

Multimedia applications place high demands for quality-of-service (QoS), performance, and reliability on systems. These stringent requirements make design of cost-effective and scalable systems difficult. Therefore efficient adaptive and dynamic resource management techniques in conjunction with data placement techniques can be of great help in improving performance, scalability and reliability of such systems. In this paper, we first focus on data placement.

Dynamic replication is a technique that can be used by clustered multimedia servers to evaluate the demand for individual streams and selectively replicate or move content to facilitate load balancing. In this paper we explain the motivation for using dynamic replication and provide a brief description of some existing dynamic replication policies. We present a new policy called Dynamic RePacking. This policy is based on the existing MMPacking al- gorithm [11], but has been modified to handle nodes and files with varying bandwidth and storage characteristics and to reduce the cost of adapting to changes in client demand or server configuration. Simulation results show that Dynamic RePacking performs better than both the original MMPacking algorithm and the threshold-based scheme which we have simulated for comparison. Our results also show that Dynamic RePacking performs significantly less movement and replication of files than the original MMPacking algorithm.

Cluster architecture is a cost-effective approach to building up scalable servers. For I/O-intensive videoon-demand (VoD) applications, network bandwidth is usually the primary bottleneck. In this paper, we propose a request redirection strategy to balance the network traffic in cluster-based VoD servers. The redirection strategy utilizes the servers ’ internal backbone bandwidth to equalize their external network traffic. Performance of redirection is related with data layouts based on replication. We implemented two replication methods and two placement methods for videos with different popularities. Furthermore, we evaluated redirection strategy with different data layouts. The simulation results verify the effectiveness of the redirection strategy and proposed data layout methods. 1