KEYWORDS: Video, Distributed computing, Internet, Copper, Video processing, Failure analysis, Computer simulations, Local area networks, System integration, Systems modeling
Online media server scheduling algorithms in distributed video-on-demand (VoD) systems are studied in this work. We first identify the failure rate and the server-side network bandwidth consumption as two main cost factors in a distributed VoD service model. The proposed distributed server scheduler consists of two parts: the request migration scheme and the dynamic content update strategy. By improving the random early migration (REM) scheme, we propose a cost-aware REM (CAREM) scheme to reduce the network bandwidth consumption due to the migration process. Furthermore, to accommodate the change in video popularity and/or client population, we use the server-video affinity to measure the potential server-side bandwidth cost after placing a specific video copy on that server. The dynamic content update strategy uses the server-video affinity to reconfigure video copies on media servers. We conduct extensive simulations to evaluate the performance of the proposed algorithm. It can be shown that CAREM together with the dynamic content
update strategy can improve the system performance by reducing the
request failure rate as well as the server bandwidth consumption.
Online media server scheduling algorithms in distributed video-on-demand (VoD) systems are studied in this work. We first formulate a general server scheduling problem based on the VoD service model, where the failure rate and the server-side network bandwidth consumption are identified as two main cost factors in the system. The distributed server scheduler consists of two parts; namely, the request migration scheme and the dynamic content update strategy. By improving the random early migration (REM) scheme, we propose a cost-aware REM (CAREM) scheme to reduce the network bandwidth consumption in the migration process. Furthermore, to accommodate the video popularity and/or client population change, we use the server-video affinity to measure the importance of placing a specific video copy on that server. The dynamic content update strategy uses the server-video affinity metric to reconfigure video copies on media servers. We conduct extensive simulations to measure the performance of proposed algorithms. It can be shown that CAREM together with the dynamic content update strategy can improve the system performance by reducing the request failure rate as well as the server bandwidth consumption.
Media server scheduling in video-on-demand (VOD) systems includes video content allocation and request migration among servers. In this paper, we present a greedy algorithm to allocate video copies to media servers. It uses a graph model and minimizes the average shortest distance among media servers at each step. To facilitate the performance analysis of the random early migration (REM) algorithm proposed in our previous work, we introduce a formal description of the media service. Based on this system formalization, we develop a state transition method to study the parameter effect on the REM performance and compare the real time performance between REM and traditional migration with early start (TMES). The analytical result shows that REM introduces smoother migrations between media servers and thus leads to less real time system load than TMES.
Media server scheduling in video-on-demand systems includes video
content allocation and request migration among servers. In this paper,
we present a greedy algorithm to allocate video copies to media servers. It uses a graph model and minimizes the average shortest distance among media servers at each step. In order to study the request migration process, we introduce a state matrix representation that stores the service load information of each media server and plays an important role in the determination of migration paths. Based on this representation, we develop a state transition method to simulate the request migration process and calculate the performance metrics such as failure rates and service delay. The derived results match very well with numerical experiments. It is further demonstrated that the random early migration (REM) algorithm proposed in our previous work outperforms the normal migration scheme with lower failure rates and shorter service delay.
The random early migration (REM) scheme was proposed in our previous work to balance the load of multiple media servers to decrease the average service delay. When an user request arrives, it is randomly directed to a media server that has the designated video content cached on. When the load of this server exceeds a preset threshold, REM is executed by choosing one of its in-service requests and migrating it to another media server with a certain probability, where the exact probability is a function of the service load. We introduce a state matrix representation that stores the service load information of each media server and plays an important role in the determination of migration paths. All possible state matrices can be mapped to a vector space called the state matrix space (SMS). With SMS, we can analyze the performance of VoD systems such as the failure rate and service delay, and these derived results are verified by numerical experiments. It is demonstrated that REM outperforms the normal migration scheme with shorter service delay and lower failure rates.
KEYWORDS: Video, Computer simulations, Failure analysis, Multimedia, Video processing, System integration, Databases, Data storage servers, Electrical engineering, Visual information processing
Effective management of multiple media servers integrated to deliver real-time multimedia content to users for video-on-demand (VoD) applications is examined in this research. We propose a random early migration (REM) scheme to reduce the service rejection rate, to balance the load of media servers and to reduce the service delay. When a new request is dispatched to a media server, REM compares the current service load with preset thresholds and decides whether request migration is needed with a certain probability, which is a function of the service load. To control the video access rate, we apply a time window to predict the video access probability in the near future and dynamically update the video content in media servers. Simulation results demonstrate that REM alone and/or REM with dynamic content update can achieve an enhanced system performance.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.