Abstract

Abstract
The Database Management System ( DBMS) used to be a commodity software component, with well known standard interfaces and semantics. However, the performance and reliability expectations being placed on DBMSs have increased the demand for a variety add-ons, that augment the functionality of the database in a wide range of deployment scenarios, offering support for features such as clustering, replication, and self-management, among others. A well known software engineering approach to systems with such requirements is reflection. Unfortunately, standard reflective interfaces in DBMSs are very limited. Some of these limitations may be circumvented by implementing reflective features as a wrapper to the DBMS server. Unfortunately, these solutions comes at the expense of a large development effort and significant performance penalty.

Abstract

Abstract
This paper investigates the use of partial replication in the Database State Machine approach introduced earlier for fully replicated databases. It builds on the order and atomicity properties of group communication primitives to achieve strong consistency and proposes two new abstractions: Resilient Atomic Commit and Fast Atomic Broadcast. Even with atomic broadcast, partial replication requires a termination protocol such as atomic commit to ensure transaction atomicity. With Resilient Atomic Commit our termination protocol allows the commit of a transaction despite the failure of some of the participants. Preliminary, performance studies suggest that the additional cost of supporting partial replication can be mitigated through the use of Fast Atomic Broadcast.

Abstract
Reliable multicast protocols can strongly simplify the design of distributed applications. However it is hard to sustain a high multicast throughput when groups are large and heterogeneous. In an attempt to overcome this limitation, previous work has focused on weakening reliability properties. In this paper we introduce a novel reliability model that exploits semantic knowledge to decide in which specific conditions messages can be purged without compromising application correctness. This model is based on the concept of message obsolescence: A message becomes obsolete when its content or purpose is overwritten by a subsequent message. We show that message obsolescence can be expressed in a generic way and can be used to configure the system to achieve higher multicast throughput.

Abstract
This work present and demonstrated an applications of artificial neural network approach in optical sensing. The conventional matrix method used in simultaneous measurement of strain and temperature with optical Bragg gratings is compared with artificial neural network approach. The alternative method is proposed for reduced the error.