By Ernesto Damiani, Doug Schmidt, Beng Chin Ooi (auth.), Robert Meersman, Tharam Dillon, Pilar Herrero, Akhil Kumar, Manfred Reichert, Li Qing, Beng-Chin Ooi, Ernesto Damiani, Douglas C. Schmidt, Jules White, Manfred Hauswirth, Pascal Hitzler, Mukesh Mohania

The two-volume set LNCS 7044 and 7045 constitutes the refereed lawsuits of 3 confederated overseas meetings: Cooperative info structures (CoopIS 2011), allotted items and functions - safe digital Infrastructures (DOA-SVI 2011), and Ontologies, DataBases and functions of SEmantics (ODBASE 2011) held as a part of OTM 2011 in October 2011 in Hersonissos at the island of Crete, Greece. The fifty five revised complete papers provided have been rigorously reviewed and chosen from a complete of 141 submissions. The 28 papers incorporated within the moment quantity represent the court cases of DOA-SVI 2011 with 15 complete papers prepared in topical sections on functionality dimension and optimization, instrumentation, tracking, and provisioning, caliber of carrier, safety and privateness, and versions and strategies, and ODBASE 2011 with nine complete papers geared up in topical sections on acquisition of semantic details, use of semantic info, and reuse of semantic info and four brief papers.

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Additional resources for On the Move to Meaningful Internet Systems: OTM 2011: Confederated International Conferences: CoopIS, DOA-SVI, and ODBASE 2011, Hersonissos, Crete, Greece, October 17-21, 2011, Proceedings, Part II

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A parametrized loop fusion algorithm for improving parallelism and cache locality. The Computer Journal 40(6), 340 (1997) 26. : Instruction cache replacement policies and organizations. IEEE Transactions on Computers, 234–241 (1985) 27. : Increasing processor performance by implementing deeper pipelines. In: Proceedings of the 29th Annual International Symposium on Computer Architecture, 2002, pp. 25–34. IEEE (2002) 28. : Rate monotonic scheduling. In: Embedded Systems Programming, pp. 79–80 (2002) 29.

It is hard to estimate temporal locality, however, due to several factors, such as the presence and degree of data sharing between tasks. 3 Using Cache-Half Life to Drive Cache-Aware Metascheduling While metascheduling can be used to produce new execution schedules that continue to meet scheduling constraints, many of these schedules will not improve, and may even reduce the cache-hit rate and increase execution time of the system. We define a new heuristic, referred to as the cache half-life that can be used to drive the metascheduling process.

Several policies exist, such as Least Recently Used (LRU), Least Frequently Used (LRU), First In First Out (FIFO), and random replacement [11]. The cache replacement policy can substantially influence DRE system performance. For example, LRU is effective for systems in which the same data will likely be accessed again before enough data has been written to the cache to completely overwrite the cache. Performance gains will be minimal, however, if enough new data is written to the cache such that previously cached data is always overwritten before it can be accessed [26].

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