33255633
Optimizing channel allocation in a unified video-on-demand system
Unified video-on-demand (UVoD) is an architecture that integrates multicast transmission with unicast transmission to improve system efficiency. Streaming channels in a UVoD system are divided into unicast and multicast channels, with the multicast channels further divided equally among all videos. This uniform channel-allocation scheme is simple to design and implement, but the performance may not be optimal due to differences in video popularity. This paper investigates this channel-allocation problem with the goal of optimizing system efficiency. First, the uniform allocation assumption is removed and the channel-allocation problem formulated as a nonlinear integer optimization problem. This optimization model results in nonuniform channel allocations that can save up to 10% of channels. Second, to reduce the computational complexity in solving the nonlinear optimization model, an approximate model is derived and solved under small-latency conditions to obtain a closed-form solution. Third, a much simpler class-based popularity model is proposed and shown to achieve good efficiency, even if the precise popularity of each video is not known. Lastly, a zero-multicast channel-optimization algorithm is introduced that can further reduce channel requirement for systems with a large number of video selections. Numerical results show that optimized nonuniform channel-allocation policies can achieve channel reduction over uniform channel allocation by as much as 50% for a 1000-video system.
18632465
Automatic Recovery from Disk Failure in Continuous-Media Servers
Continuous-media (CM) servers have been around for some years. Apart from server capacity, another important issue in the deployment of CM servers is reliability. This study investigates rebuild algorithms for automatically rebuilding data stored in a failed disk into a spare disk. Specifically, a block-based rebuild algorithm is studied with the rebuild time and buffer requirement modeled. A buffer-sharing scheme is then proposed to eliminate the additional buffers needed by the rebuild process. To further improve rebuild performance, a track-based rebuild algorithm that rebuilds lost data in tracks is proposed and analyzed. Results show that track-based rebuild, while it substantially outperforms block-based rebuild, requires significantly more buffers (17-135 percent more) even with buffer sharing. To tackle this problem, a novel pipelined rebuild algorithm is proposed to take advantage of the sequential property of track retrievals to pipeline the reading and writing processes. This pipelined rebuild algorithm achieves the same rebuild performance as track-based rebuild, but reduces the extra buffer requirement to insignificant levels (0.7-1.9 percent). Numerical results computed using models of five commercial disk drives demonstrate that automatic rebuild of a failed disk can be done in a reasonable amount of time, even at relatively high server utilization (e.g., less than 1.5 hours at 90 percent utilization).
9924413
On a unified architecture for video-on-demand services
Current video-on-demand (VoD)) systems can be classified into two categories: 1) true-Voll) (TVoD) and 2) near-VoD (NVod)). TVoD systems allocate a dedicated channel for every user to achieve short response times so that the user can select what video to play, when to play it, and perform interactive VCR-like controls at will. By contrast, NVoD systems transmit videos repeatedly over multiple broadcast or multicast channels to enable multiple users to share a single video channel so that system cost can be substantially reduced. The tradeoffs are limited video selections, fixed playback schedule, and limited or no interactive control. TVoD systems can be considered as one extreme where service quality is maximized, while NVoD systems can be considered as the other extreme where system cost is minimized. This paper proposes a novel architecture called Unified VoD) (UVoD) that can be configured to achieve cost-performance tradeoff anywhere between the two extremes (i.e., TVoD and NVoD). Assuming that a video client can concurrently receive two video channels and has local buffers for caching a portion of the video data, the proposed UVoD architecture can achieve significant performance gains (e.g., 400% more capacity for a 500-channel system) over TVoD under the same latency constraint. This paper presents the UVoD architecture, establishes a performance model, and analyzes UVoD's performance via numerical and simulation results.
7513516
A monotonic-decreasing rate scheduler for variable-bit-rate video streaming
Variable-bit-rate (VBR) encoded videos can provide a more consistent visual quality than constant-bit-rate (CBR) encoded videos. However, the long-range bit-rate variations in VBR videos make it difficult to efficiently provide quality-of-service control in a video-on-demand system. Existing scheduling algorithms such as Optimal Smoothing, which requires both downward and upward bandwidth reallocations to adapt to the video bit-rate variations, simply cannot guarantee video delivery in networks with mixed video and data traffic. This study tackles this limitation by investigating a new scheduling algorithm with monotonic-decreasing rate allocations for scheduling video data transmissions. By eliminating upward bandwidth reallocations, the proposed scheduler can guarantee video delivery even in the presence of other data traffic in the same network. Moreover, results show that the proposed scheduler can achieve such performance guarantee without tradeoff in performance or resource requirements. This work presents this new monotonic-decreasing rate scheduler, analyzes its fundamental properties, and evaluates its performance using a large number of real-world VBR video traces (274 DVD movies) in extensive trace-driven simulations.
2177844
Design, performance analysis, and implementation of a super-scalar video-on-demand system
Despite the availability of video-on-demand (VoD) services in a number of cities around the world, large-scale deployment of VoD services in a metropolitan area is still economically impractical. This study presents a novel super-scalar architecture for building very large-scale and efficient VoD systems. The proposed architecture combines the use of static multicast, dynamic multicast, and intelligent client-side caching to vastly reduce server and network resource requirement. Moreover, in sharp contrast to conventional VoD systems where the system cost increases at least linearly with the system scale, the proposed architecture becomes more efficient as the system scales up and can ultimately be scaled up to serve any number of users while still keeping the startup latency short. This paper presents this new architecture, proposes methods to support interactive playback controls without the need for additional server or client resources, and derives an approximate performance model to relate the startup latency with other system parameters. The performance model is validated using simulation and the architecture is evaluated under various system settings. Lastly, a system implementation is presented and benchmarking results obtained to further verify the architecture, the performance model, and the simulation results.
11623554
Downlink power allocation for multi-class CDMA wireless networks
We use a utility based power allocation framework in the downlink to treat multi-class CDMA wireless services in a unified way. Our goal is to obtain a power allocation which maximizes the total system utility. Natural utility functions for each mobile are non-concave. Hence we cannot use existing techniques on convex optimization problems to derive a social optimal solution. We propose a simple distributed algorithm to obtain an approximation to the social optimal power allocation. The algorithm is based on dynamic pricing and allows partial cooperation between mobiles and the base station. The algorithm consists of two stages. At the first stage, the base station selects mobiles to which power is allocated, considering their partial-cooperative nature. This is called partial-cooperative optimal selection, since in a partial-cooperative setting and pricing scheme, this selection is optimal and satisfies system feasibility. At the next stage, the base station allocates power to the selected mobiles. This power allocation is a social optimal power allocation among mobiles in the partial-cooperative optimal selection, thus, we call it a partial-cooperative optimal power allocation. We compare the partial-cooperative optimal power allocation with the social optimal power allocation for the single class case. From these results, we infer that the system utility obtained by partial-cooperative optimal power allocation is quite close to the system utility obtained by social optimal allocation.
10209884
Downlink power allocation for multi-class wireless systems
In this paper we consider a power allocation problem in multi-class wireless systems. We focus on the downlink of the system. Each mobile has a utility function that characterizes its degree of satisfaction for the received service. The objective is to obtain a power allocation that maximizes the total system utility. Typically, natural utility functions for each mobile are nonconcave. Hence, we cannot use existing convex optimization techniques to derive a global optimal solution. We develop a simple (distributed) algorithm to obtain a power allocation that is asymptotically optimal in the number of mobiles. The algorithm is based on dynamic pricing and consists of two stages. At the mobile selection stage, the base station selects mobiles to which power is allocated. At the power allocation stage, the base station allocates power to the selected mobiles. We provide numerical results that illustrate the performance of our scheme. In particular, we show that our algorithm results in system performance that is close to the performance of a global optimal solution in most cases.
18817570
Long-term location data management for distributed moving object databases
To handle the extreme situation that must manage positional information of a very large volume, at least millions, of moving objects, a cluster-based scalable distributed computing system architecture, called the GALIS, which consists of multiple data processors, each dedicated to keeping records relevant to a different geographical zone and a different time zone, was proposed. In this paper, we propose a valid time management and time-zone shifting scheme, which are essential in realizing the long-term location data subsystem of GALIS, but missed in our previous prototype development. We explain how to manage valid time of moving objects to avoid ambiguity of location information. We also describe time-zone shifting algorithm, with three variations, such as RT-TZS, B-TZS and TPB-TZS. Through experiments related with query processing time and CPU utilization, we show the efficiency of the proposed time-zone shifting schemes
948007
A Microeconomic Approach to Intelligent Resource Sharing in Multiagent Systems
Abstract : We have analyzed characteristics of sharable resources and developed techniques for intelligently sharing resources specifically, communication channels among agents in multiagent systems. Our techniques allow agents to nearly optimize their communication behavior in a self-organizing and distributed fashion, involving the use of a microeconomic pricing system based on economic laws of supply and demand and trading among agents in real-time. Our analyses are based on three measures of performance: fairness of resource allocation, waiting time for resources, and utilization of resources. Our initial analysis indicates that fairness and utilization are conflicting, in that the best utilization with a fair allocation is equivalent to the worst utilization with an unfair resource allocation, assuming the allocation policy is statically defined. To strike a balance in performance, we have developed mechanisms that establish an artificial economy, where agents can dynamically reallocate goods (resource access) using a competitive market pricing mechanism. However, unlike more common market-oriented methods, our approach does not demand convergence to equilibrium, but permits more rapid, heuristic trading, leading to near optimal performance where both buyers and sellers of resources can benefit. Our studies show that agents employing our mechanisms can dramatically improve utilization while still providing fair access to the resources.
6705104
Embracing agile development of usable software systems
The interdisciplinary nature of system design can lead to communication problems between developers in different fields. This is becoming evident in the emerging field of agile software development which has largely ignored or been unable to address usability. This work presents a development process and toolset that draws on extreme programming--an agile software development process, and scenario-based design--a usability engineering process. This approach will allow developers in both fields to better communicate and work together to efficiently design usable systems.