研究発表

In this paper, we propose a real-time extension scheme for SpaceWire.

This paper presents a new algorithm for fixed-priority scheduling of sporadic task systems on multiprocessors. The algorithm is categorized to such a scheduling class that qualifies a few tasks to migrate across processors, while most tasks are fixed to particular processors. We design the algorithm so that a task is qualified to migrate, only if it cannot be assigned to any individual processors, in such a way that it is never returned to the same processor within the same period, once it is migrated from one processor to another processor. The scheduling policy is then conformed to Deadline Monotonic. According to the simulation results, the new algorithm significantly outperforms the traditional fixed-priority algorithms in terms of schedulability.

リアルタイム処理用プロセッサResponsive Multithreaded Processorは，スレッド数が8スレッド以内であればコンテキストスイッチを行わずに優先度順に同時実行可能なRMT実行機構を持つ．しかしながら，9スレッド以上を実行する場合，ソフトウェアスケジューラによってコンテキストスイッチを行わなければならない．また周期タスクのリリースの為にはソフトウェアスケジューラを定期的に呼び出し，リリース時間をチェックしなければならない．本論文では，RMT Processorを対象としたハードウェアによるスレッドスケジューリング機構の設計と実装について述べる．本スレッドスケジューリング機構では，RMT ProcessorのプロセッシングコアであるRMT PUが全スレッドの周期を保持し，周期スレッドをハードウェアで起床させる．更に，コンテキストキャッシュ内のスレッドと実行スレッドを比較し，ハードウェアでコンテキストスイッチを行う．本スレッドスケジューリング機構によってソフトウェアによるスケジューリングを不要とし，スケジューリングオーバヘッドを大幅に削減する．

マルチメディア処理を高速に実行するためのアーキテクチャとして，SIMD 演算器やベクトル演算器が挙げられる．これらのアーキテクチャでは複数のデータに対して同時に同じ処理を実行できるが，メモリがプロセッサと比較して低速であるため，演算性能を十分に活かすだけのデータを供給できていない．本論文では，マルチメディア処理のメモリアクセスパターンから次にアクセスされるアドレスを予測し，プリフェッチを行うことでメモリアクセスレイテンシを低減する手法を提案する．EEMBC のDENBench の一部を用いて評価を行った結果，IPC の向上を確認した．

Modular component-based robot systems require not only an infrastructure for component management, but also scalability as well as real-time properties. Robot Technology (RT)-Middleware is a software platform for such component-based robot systems. Each component in the RT-Middleware, so-called “RT-Component” supporting particular robot functions, is based on Common Object Request Broker Architecture (CORBA). Unfortunately, the RT-Middleware lacks the mechanism for real-time control. In this paper, we extend the framework of the RT-Components to take care of timing constraints. We first enable tasks to have different periods within each RT-Component. We then modify the packet format of the General Inter-ORB Protocol (GIOP) to transfer the information of timing constraints over RT-Components. The performance evaluation on ART-Linux shows that the extended RT-Component framework improves the schedulability of distributed real-time tasks, without causing critical overheads in unmarshaling the modified GIOP packets.

This paper presents a scheduling algorithm, called Earliest Deadline Critical Laxity (EDCL), for the scheduling of sporadic real-time tasks on multiprocessors systems. EDCL is a derivative of the Earliest Deadline Zero Laxity (EDZL) algorithm in that the priority of a job reaching certain laxity is imperiously promoted to the top, but it differs in that the occurrence of priority promotion is confined to at the release time or the completion time of a job. This modification enables EDCL to bound the number of scheduler invocations and to relax the implementation complexity of scheduler, while the schedulability is still competitive with EDZL. A schedulability test of EDCL is designed by theoretical analysis. An error in the traditional schedulability test of EDZL is also corrected. The effectiveness of EDCL is demonstrated in terms of guaranteed schedulability and exhaustive schedulability through simulation studies, compared with traditional efficient scheduling algorithms.

T-R Plane Abstraction (TRPA) proposed in this paper is an abstraction technique of real-time scheduling on multiprocessors. This paper presents that NNLF (No Nodal Laxity First) based on TRPA is work-conserving and optimally solves the problem of scheduling periodic tasks on a multiprocessor system. TRPA can accommodate to dynamic environments due to its dynamic time reservation, while T-N Plane Abstraction (TNPA) and Extended TNPA (E-TNPA) reserve processor time statically at every task release.