Software Architecture-Based Adaptation for Pervasive Systems
ARCS '02 Proceedings of the International Conference on Architecture of Computing Systems: Trends in Network and Pervasive Computing
Software Architecture-Based Adaptation for Grid Computing
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Adaptive On-the-Fly Compression
IEEE Transactions on Parallel and Distributed Systems
Dynamic adaptation of CORBA component-based applications
Proceedings of the 2007 ACM symposium on Applied computing
QDSL: a queuing model for systems with differential service levels
SIGMETRICS '08 Proceedings of the 2008 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Energy and performance evaluation of lossless file data compression on server systems
SYSTOR '09 Proceedings of SYSTOR 2009: The Israeli Experimental Systems Conference
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Abstract: Internet computing is facilitated by the remote execution methodology in which programs transfer to a destination for execution. Since transfer time can substantially degrade performance of remotely executed (mobile) programs, file compression is used to reduce the amount that transfers. Compression techniques however, must trade off compression ratio for decompression time due to the algorithmic complexity of the former since the latter is performed at runtime in this environment. With this work, we define Tot al Del ay as the time for both transfer and decompression of a compressed file. To minimize total delay, a mobile program should be com-pressed in a format that minimizes total delay. Since both the transfer and decompression time are dependent upon the current, underlying resource performance, selection of the "best" format varies and no one compression format minimizes total delay for all resource performance characteristics. We present a system called Dynamic Compression Format Selection (DCFS) for automatic and dynamic selection of competitive, compression formats based on predicted values of future resource performance. Our results show that DCFS reduces 52% of total delay imposed by compressed transfer of Java archives (jar files) on average, for the networks, compression techniques, and benchmarks studied.