With the emergence of many-core systems, managing blocking costs effectively will soon become a critical issue in the design of real-time systems. In contrast to previous works on multicore real-time task scheduling algorithms and synchronization protocols, this paper proposes a dedicated-core framework to separate the executions of application tasks and (system) services over cores such that blocking among tasks can be better explored and managed. The rationale behind the framework is that we can exploit the characteristics of many-core systems to resolve the challenges raised by the systems themselves. We define three core minimization problems with respect to the constraints on core configurations, and present corresponding task allocation algorithms with optimal, approximate, and heuristic solutions. The results of simulations conducted to evaluate the proposed framework provide further insights into task scheduling in many-core real-time systems.

In recent years, many researchers and vendors have proposed their XML storage approaches based on relational databases (RDB), which are called XML-relational databases (XRDB). To manipulate XML data in XRDB, many excellent model-mapping schemas were proposed to provide schema definitions to translate various XML documents with different structures into relational tables. Such an approach can support any sophisticated applications and well-formed XML documents. When XML data stored in an XRDB, the user query must be translated into the corresponding SQL commands, then executed in the relational database. However, most model-mapping-schema-based approaches have a potential performance problem for retrieving XML data from an XRDB, because a large number of join operations are needed. In this paper, a novel query preprocessing technique will be proposed to reduce the number of join operations from the corresponding SQL commands. The rationale behind our approach is to replace join operations by predefined constant-mapping selection operations. By reducing the number of join operations, the performance of query processing can be greatly improved. The capability of our proposed approach was verified by experiments, for which we have some encouraging results.

A major challenge in the design of multicore embedded systems is how to tackle the communications among tasks with performance requirements and precedence constraints. In this paper, we consider the problem of scheduling real-time tasks over multilayer bus systems with the objective of minimizing the communication cost. We show that the problem is N P-hard and determine the best possible approximation ratio of approximation algorithms. First, we propose a polynomial-time optimal algorithm for a restricted case where one multilayer bus, and the unit execution time and communication time are considered. The result is then extended as a pseudopolynomial-time optimal algorithm to consider multiple multilayer buses with arbitrary execution and communication times, as well as different timing constraints and objective functions. We compare the performance of the proposed algorithm with that of some popular heuristics, and provide further insights into the multilayer bus system design.

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