Mutual exclusion and concurrency are two fundamental and essentially opposite features in distributed systems. However, in some applications such as Computer Supported Cooperative Work (CSCW) we have found it necessary to impose mutual exclusion on dierent groups of processes in accessing a resource, while allowing processes of the same group to share the resource. To our knowledge, no such design issue has been previously raised in the literature. In this paper we address this issue by presenting a new problem, called Congenial Talking Philosophers, to model group mutual exclusion. We also propose several criteria to evaluate solutions of the problem and to measure their performance. Finally, we provide an ecient and highly concurrent distributed algorithm for the problem in a sharedmemory model where processes communicate by reading from and writing to shared variables. The distributed algorithm meets the proposed criteria, and has performance similar to some naive but...

Distributed database systems implement a transaction commit protocol to ensure transaction atomicity. A commit protocol guarantees the uniform commitment of distributed transaction execution, that is, it ensures that all the participating sites agree on the final transaction outcome (commit or abort). Most importantly, this guarantee is valid even in the presence of site or network failures. Over the last two decades, a variety of commit protocols have been proposed by database researchers. These include the classical two phase commit (2PC) protocol, its variations such as Presumed Commit and Presumed Abort , nested 2PC , broadcast 2PC and three phase commit . To achieve their functionality, these commit protocols typically require exchange of multiple messages, in multiple phases, between the participating sites where the distributed transaction executed. In addition, several log records are generated, some of which have to be "forced", that is, flushed to disk immediately. Due to these costs, commit processing can result in a significant increase in transaction execution times, and therefore the choice of commit protocol becomes an important decision in the design of a distributed database system. Surprisingly, however, no systematic studies are available on the relative performance of these protocols with respect to their quantitative impact on transaction processing performance, rendering it difficult for designers to make an informed choice. In this thesis, we address this lacuna for two kinds of distributed database systems: (1) Distributed OnLine Transaction Processing Systems (OLTP), and (2) Distributed Real-Time Database Systems (RTDB). A special feature of our study is that we consider both blocking commit protocols, wherein site or network failures can lead ...

Abstract. We incorporate a prewrite operation before a write operation in a mobile transaction to improve data availability. A prewrite operation does not update the state of a data object but only makes visible the future value that the data object will have after the final commit of the transaction. Once a transaction reads all the values and declares all the prewrites, it can pre-commit at mobile host (MH) (computer connected to unreliable mobile communication network). The remaining transaction’s execution (writes on database) is shifted to the mobile service station (MSS) (computer connected to the reliable fixed network). Writes on database consume time and resources and are therefore shifted to MSS and delayed. This reduces wireless network traffic congestion. Since the responsibility of expensive part of the transaction’s execution is shifted to the MSS, it also reduces the computing expenses at mobile host. A pre-committed transaction’s prewrite values are made visible both at mobile and at fixed database servers before the final commit of the transaction. Thus, it increases data availability during frequent disconnection common in mobile computing. Since a pre-committed transaction does not abort, no undo recovery needs to be performed in our model. A mobile host needs to cache only prewrite values of the data objects which take less memory, transmission time, energy and can be transmitted over low bandwidth. We have analysed various possible schedules of running transactions concurrently both at mobile and fixed database servers. We have discussed the concurrency control algorithm for our transaction model and proved that