Proxy caching that estimates page load delays
Selected papers from the sixth international conference on World Wide Web
Replication strategies in unstructured peer-to-peer networks
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Coordinated enroute multimedia object caching in transcoding proxies for tree networks
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Optimal methods for coordinated enroute web caching for tree networks
ACM Transactions on Internet Technology (TOIT)
Trusted Computing Platforms: TCPA Technology in Context
Trusted Computing Platforms: TCPA Technology in Context
Cache Replacement Algorithms with Nonuniform Miss Costs
IEEE Transactions on Computers
Exploiting client caches to build large Web caches
The Journal of Supercomputing
Multimedia Object Placement for Transparent Data Replication
IEEE Transactions on Parallel and Distributed Systems
Cost-aware WWW proxy caching algorithms
USITS'97 Proceedings of the USENIX Symposium on Internet Technologies and Systems on USENIX Symposium on Internet Technologies and Systems
Cooperative caching: using remote client memory to improve file system performance
OSDI '94 Proceedings of the 1st USENIX conference on Operating Systems Design and Implementation
Hi-index | 0.00 |
Trusted Computing is a technology proposed by the Trusted Computing Group (TCG) to solve security problems in computers. A lot of work has been conducted to support Trusted Computing for individual computers; however little has been done for distributed systems (e.g., clusters). If malicious or unqualified applications are deployed on cluster nodes, users may obtain forged results or their data may be leaked out. In this paper, a methodology of the Trusted Cluster Computing (TCC) is proposed to automatically construct user-trustable cluster computing environments. User-specified applications are downloaded from user-specified locations and automatically and dynamically deployed on cluster nodes. To reduce the dynamic-deployment overhead, a novel Heuristics-based Overhead-Reducing (HOR) replacement strategy is also proposed. A highly configurable simulator has been implemented to perform a series of simulations. The simulation results demonstrate that the HOR can produce Average Speedup with up to 14% (light workload), 10% (medium workload), 8% (heavy workload) higher than that of LRU-based strategies, with a typical setting of the Average Ratio of Deployment time to Execution time (ARDE) being 0.2.