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Peer-to-Peer Time-shifted Streaming Systems
, 2009
"... In live streaming systems (IPTV, life-stream services, etc.), an attractive service consists in allowing users to access past portions of the stream. This is called a time-shifted streaming system. In our vision, a centralized time-shifted streaming system face scalability and ethical issues, theref ..."
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In live streaming systems (IPTV, life-stream services, etc.), an attractive service consists in allowing users to access past portions of the stream. This is called a time-shifted streaming system. In our vision, a centralized time-shifted streaming system face scalability and ethical issues, therefore, we address the problem of designing a peer-to-peer system where peers store and deliver past chunks. We first attempt to identify the main characteristics of time-shifted streaming system from well-known measurements of VoD and IPTV systems. These overlays are the first structures specifically designed for time-shifted streaming system. Although no evaluation is presented, these preliminary description aim to foster discussions on a critical service. 1
A Quantitative Comparison of Reactive and Proactive Replicated Storage Systems
"... Abstract—Replicated storage systems allow their stored data objects to outlive the life of the nodes storing them through replication. In this paper, we focus on durability, and more specifically on the concept of an object’s lifetime, i.e., the duration of time between the creation of an object and ..."
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Abstract—Replicated storage systems allow their stored data objects to outlive the life of the nodes storing them through replication. In this paper, we focus on durability, and more specifically on the concept of an object’s lifetime, i.e., the duration of time between the creation of an object and when it is permanently irretrievable from the system. We analyze two main replication strategies: reactive, in which replication occurs in response to failures, and proactive, in which replication occurs in anticipation of failures. Our work presents a quantitative analysis that compares reactive and proactive through analytical models and simulations, considering exponentially distributed failures and reactive repairs, and periodic proactive replications. We also present a derivation of the analytical formula for the variance of the lifetime in the reactive model. Our results indicate that a proactive strategy leads to multiple times higher storage requirements than a reactive strategy. In addition, reactive systems are only moderately bursty in terms of bandwidth consumption, with rare peaks of at most five times the bandwidth consumption in proactive systems (given input parameter values that are compatible with real systems). Finally, for both strategies, the standard deviation is very close to the expected lifetime, and consequently, the lifetimes close to being exponentially distributed. I.
Storage and Network Resource Usage in Reactive and Proactive Replicated Storage Systems
"... Abstract—Replicated storage systems allow their stored data to outlive the life of the nodes storing them by use of replication. In such systems, failed replicas are “repaired ” by copying remaining replicas from other nodes. We consider two main replication strategies: reactive, in which replicatio ..."
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Abstract—Replicated storage systems allow their stored data to outlive the life of the nodes storing them by use of replication. In such systems, failed replicas are “repaired ” by copying remaining replicas from other nodes. We consider two main replication strategies: reactive, in which replication occurs in response to failures, and proactive, in which replication occurs in anticipation of failures. There is no consensus in the literature about which strategy is better. Our work presents a quantitative analysis that compares reactive and proactive through simulations and verified analytically where possible. In particular, we systematically compare how the strategy of replication affects the usage of storage and network resources, at peak consumption as well as on average, to achieve a given lifetime for a replicated object. Our results indicate that a proactive strategy leads to multiple times higher storage requirements than a reactive strategy, with the exact number depending on parameter values for failure and replication rates. Reactive systems are moderately bursty in terms of bandwidth consumption, with rare peaks of at most five times (for realistic parameter values) that of proactive systems, the latter of which is constant by design given that replications are periodic for proactive. I.
