A development framework for artificial intelligence based distributed operations support systems

Advanced automation is required to reduce costly human operations support requirements for complex space-based and ground control systems. Existing knowledge based technologies have been used successfully to automate individual operations tasks. Considerably less progress has been made in integrating and coordinating multiple operations applications for unified intelligent support systems. To fill this gap, SOCIAL, a tool set for developing Distributed Artificial Intelligence (DAI) systems is being constructed. SOCIAL consists of three primary language based components defining: models of interprocess communication across heterogeneous platforms; models for interprocess coordination, concurrency control, and fault management; and for accessing heterogeneous information resources. DAI applications subsystems, either new or existing, will access these distributed services non-intrusively, via high-level message-based protocols. SOCIAL will reduce the complexity of distributed communications, control, and integration, enabling developers to concentrate on the design and functionality of the target DAI system itself

Superdatabases for Composition of Heterogeneous Databases

Superdatabases are designed to compose and extend databases. In particular, superdatabases allow consistent update across heterogeneous databases. The key idea of superdatabase is hierarchical composition of element databases. For global crash recovery, each element database must provide local recovery plus some kind of agreement protocol, such as two-phase commit. For global concurrency control, each element database must have local synchronization with an explicit serial order, such as two-phase locking, timestamps, or optimistic methods. Given element databases satisfying the above requirements, the superdatabase can certify the serializability of global transactions through a concatenation of local serial order. Combined with previous work on heterogeneous databases, including unified query languages and view integration, now we can build heterogeneous databases which are consistent, adaptable, and extensible by construction

Snapshot isolation for transactional stream processing

Transactional database systems and data stream management systems have been thoroughly investigated over the past decades. While both systems follow completely different data processing models, the combined concept of transactional stream processing promises to be the future data processing model. So far, however, it has not been investigated how well-known concepts found in DBMS or DSMS regarding multi-user support can be transferred to this model or how they need to be redesigned. In this paper, we propose a transaction model combining streaming and stored data as well as continuous and ad-hoc queries. Based on this, we present appropriate protocols for concurrency control of such queries guaranteeing snapshot isolation as well as for consistency of transactions comprising several shared states. In our evaluation, we show that our protocols represent a resilient and scalable solution meeting all requirements for such a model

Unification of Transactions and Replication in Three-Tier Architectures Based on CORBA

In this paper, we describe a software infrastructure that unifies transactions and replication in three-tier architectures and provides data consistency and high availability for enterprise applications. The infrastructure uses transactions based on the CORBA object transaction service to protect the application data in databases on stable storage, using a roll-backward recovery strategy, and replication based on the fault tolerant CORBA standard to protect the middle-tier servers, using a roll-forward recovery strategy. The infrastructure replicates the middle-tier servers to protect the application business logic processing. In addition, it replicates the transaction coordinator, which renders the two-phase commit protocol nonblocking and, thus, avoids potentially long service disruptions caused by failure of the coordinator. The infrastructure handles the interactions between the replicated middle-tier servers and the database servers through replicated gateways that prevent duplicate requests from reaching the database servers. It implements automatic client-side failover mechanisms, which guarantee that clients know the outcome of the requests that they have made, and retries aborted transactions automatically on behalf of the clients

Multi-Master Replication for Snapshot Isolation Databases

Lazy replication with snapshot isolation (SI) has emerged as a popular choice for distributed databases. However, lazy replication requires the execution of update transactions at one (master) site so that it is relatively easy for a total SI order to be determined for consistent installation of updates in the lazily replicated system. We propose a set of techniques that support update transaction execution over multiple partitioned sites, thereby allowing the master to scale. Our techniques determine a total SI order for update transactions over multiple master sites without requiring global coordination in the distributed system, and ensure that updates are installed in this order at all sites to provide consistent and scalable replication with SI. We have built our techniques into PostgreSQL and demonstrate their effectiveness through experimental evaluation.1 yea