We investigate scheduling algorithms for distributed transactional memory systems where transactions residing at nodes of a communication graph operate on shared, mobile objects. A transaction requests the objects it needs, executes once those objects have been assembled, and then sends the objects to other waiting transactions. We study scheduling algorithms with provable performance guarantees. Previously, only the offline batch scheduling setting was considered in the literature where transactions are known a priori. Minimizing execution time, even for the offline batch scheduling, is known to be NP-hard for arbitrary communication graphs. In this paper, we analyze for the very first time scheduling algorithms in the online dynamic scheduling setting where transactions are not known a priori and the transactions may arrive online over time. We provide efficient and near-optimal execution time schedules for dynamic scheduling in many specialized network architectures. The core of our technique is a method to convert offline schedules to online. We first describe a centralized scheduler which we then adapt to a purely distributed scheduler. To our knowledge, these are the first attempts to obtain provably efficient online execution schedules for distributed transactional memory.

我们研究分布式事务内存系统的调度算法，其中驻留在通信图节点上的事务对共享的移动对象进行操作。一个事务请求它需要的对象，一旦这些对象被组装就执行，然后将这些对象发送给其他等待的事务。我们研究具有可证明性能保证的调度算法。以前，在先验已知事务的文献中只考虑了离线批处理调度设置。最小化执行时间，即使对于离线批处理调度，对于任意通信图也是 NP-hard 已知的。在本文中，我们首次分析了在线动态调度中的调度算法。设置先验不知道交易并且交易可能会随着时间的推移在线到达的设置。我们为许多专业网络架构中的动态调度提供了高效且接近最优的执行时间安排。我们技术的核心是一种将离线时间表转换为在线时间表的方法。我们首先描述一个集中式调度器，然后我们将其适配为一个纯分布式调度器。据我们所知，这是为分布式事务内存获得可证明有效的在线执行计划的第一次尝试。