The next generation of advanced mechatronic syst.ms is expected to enhance their functionality and improve their performance by context-dependent behavior. Therefore, these syst.ms require to repres.nt information abo...
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The next generation of advanced mechatronic syst.ms is expected to enhance their functionality and improve their performance by context-dependent behavior. Therefore, these syst.ms require to repres.nt information about the complex environment and changing sets of collaboration partners internally. This requirement is in contrast to the usually assumed static structures.for embeddedsyst.ms. In this paper, we pres.nt a model-driven approach which overcomes this situation by supporting dynamic data structures.while still guaranteeing that valid worst-case execution times can be derived. It supports a flexible res.urce management which avoids to operate with the prohibitive coarse worst-case boundaries but instead supports to run applications in different profiles which guarantee different res.urce requirements and put unused res.urces in a profile at other applications' disposal. By supporting the proper estimation of worst case execution time (WCET) and worst case number of iteration (WCNI) at runtime, we can further support to create new profiles, add or remove them at runtime in order to minimize the over-approximation of the res.urce consumption res.lting from the dynamic data structures.required for the outlined class of advanced syst.ms.
Business Intelligence (BI) has gained a new lease of life through Cloud computing as its demand for unlimited hardware and platform res.urces expandability is fulfilled by the Cloud elasticity features. BI can be seam...
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Business Intelligence (BI) has gained a new lease of life through Cloud computing as its demand for unlimited hardware and platform res.urces expandability is fulfilled by the Cloud elasticity features. BI can be seamlessly deployed on the Cloud given that its multilayered model coincides with the Cloud models. It is considered by many Cloud service providers as one of the prominent applications services on public, outsourced private and outsourced community Clouds. However, in the shared domains of Cloud computing, BI is exposed to security and privacy threats by virtue of exploits, eavesdropping, distrib.ted attacks, malware attacks, and such other known challenges on Cloud computing. Given the multi-layered model of BI and Cloud computing, its protection on Cloud computing needs to be ensured through multilayered controls. This paper proposed a multi-layered hierarchical inter-cloud connectivity model for sequential packet inspection of tenant sessions accessing BI as a service on cloud computing through an algorithm for ensuring multi-level session inspections, and ensuring maximum security controls at all the seven layers, and prevent an attack from occurring. The simulations pres.nt the effects of distrib.ted attacks on the BI syst.ms by attackers posing as genuine Cloud tenants. The res.lts reflect how the attackers are blocked by the multilayered security and privacy controls deployed for protecting the BI servers and databases.
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