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

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

MAXIMIZING WELFARE THROUGH COOPERATIVE NEGOTIATION IN A MULTI-AGENT INTERNET ECONOMY

E-commerce over the Internet has become an attractive means of conducting business in today's world. However, the principles of classical economics demand a fresh insight before they can be adapted to the market structure presented by the Internet. Here, we investigate markets for goods that are characterized by an experience-limited supply curve. We propose an algorithm that maximizes the welfare in the e-market by maximizing the combined profit of the buyers and sellers. For this, the buyers and sellers must reveal their value and cost curves to a trusted intermediary who can determine the transaction that maximizes their joint welfare. We show that accurate revelation of hidden profits offers better incentives, both to the buyers and the sellers, than inaccurate or incomplete revelation.E-commerce, software agents, game theory, dynamic pricing, supply and demand

Dynamic Tiered Pricing in a Multi-Agent Economy

Shopbots or software agents that enable comparison shopping of items from dierent online sellers have become popular for quick and easy shopping among online buyers. Rapid searches and price comparison by shopbots have motivated sellers to use software agents called pricebots to adjust their prices dynamically so that they can maintain a competitive edge in the market. Existing pricebots charge the same price for an item from all of their customers. Online consumers dier in their purchasing preferences and, therefore, a seller's pro t can be increased by charging two dierent prices for the same good from price-insensitive and price-sensitive consumers. In this paper, we present an algorithm that partitions the buyer population into dierent segments depending on the buyers' purchase criteria and then charges a dierent price for each segment. Simulation results of our algorithm indicate that sellers' pro ts are improved by charging dierent prices to buyers with different purchase criteria