A. Cohen, Segmented Information Dispersal, Ph.D. Dissertation, University of California, San Diego, CA (1996). Home/Search Document Details and Download
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Failure Recovery Algorithms for Multimedia servers - Shenoy, Vin (2000) (2 citations) (Correct)
....Furthermore, conventional workloads require good response times but no absolute guarantees, while multimedia workloads, due to their real time nature, need bounded response times. Recently, several research groups have adapted conventional failure recovery techniques for multimedia servers [1, 8, 20, 28]. An admission control algorithm that reserves contingency disk bandwidth to accommodate load increases in the event of a disk failure in a declustered parity based multimedia server was presented in [23] Similarly, in the Streaming RAID server [29] a RAID level 3 array is adapted to exploit the ....
Cohen A, Burkhard WA (1995) Segmented Information Dispersal. Technical Report CS95-444. Department of Computer Science, University of California, San Diego, Calif.
Failure Recovery Algorithms for Multimedia servers - Shenoy, Vin (1999) (2 citations) (Correct)
....Furthermore, conventional workloads require good response times but no absolute guarantees, while multimedia workloads, due to their real time nature, need bounded response times. Recently, several research groups have adapted conventional failure recovery techniques for multimedia servers [1, 8, 20, 28]. An admission control algorithm that reserves contingency disk bandwidth to accommodate load increases in the event of a disk failure in a declustered parity based multimedia server was presented in [23] Similarly, in the Streaming RAID server [29] a RAID level 3 array is adapted to exploit the ....
A. Cohen and W. A. Burkhard. Segmented Information Dispersal. Technical Report CS95-444, Department of Computer Science, University of California, San Diego, 1995.
Segmented Information Dispersal - A New Design with.. - Cohen, Burkhard (1997) Self-citation (Cohen) (Correct)
....in the size of the reconstruction accesses is obtained. A dispersal factor larger than 1 can be achieved by using data organizations which are based on balanced incomplete block designs [7, 8, 12, 15] However, such data organizations do not generally allow contiguous reconstruction accesses (see [5]) SID data organizations achieve high dispersal factors while maintaining the contiguity of the reconstruction accesses (provided that the reconstruction proceeds in units of a predetermined fixed size) Such data layouts are motivated by the problem of reducing the reconstruction load imposed on ....
....accesses (provided that the reconstruction proceeds in units of a predetermined fixed size) Such data layouts are motivated by the problem of reducing the reconstruction load imposed on the surviving disk drives in a fault tolerant disk array for digital video. This problem is described in [5, 6]. Here we consider single erasure correcting solutions. Multiple erasure correcting solutions based on SID and MDS codes are discussed in [5] Figure 11 shows an example of a SID layout for 5 fragments which achieves a dispersal factor of 2 with a redundancy rate of 1=3. In this example, each of ....
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A. Cohen, Segmented Information Dispersal, Ph.D. Dissertation, University of California, San Diego, CA (1996).
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