Blocking reduction for distributed transaction processing within MANETs

Abstract

Atomic commit protocols for distributed transactions in mobile ad-hoc networks have to consider message delays and network failures. We consider ad-hoc network scenarios, in which participants hold embedded databases and offer services to other participants. Services that are composed of several other services can access and manipulate data of physically different databases. In such a scenario, distributed transaction processing can be used to guarantee atomicity and serializability throughout all databases. However, with problems like message loss, node failure, and network partitioning, mobile environments make it hard to get estimations on the duration of a simple message exchange.In this article, we focus on the problem of setting up reasonable time-outs when guaranteeing atomicity for transaction processing within mobile ad-hoc networks, and we show the effect of setting up "wrong" time-outs on the transaction throughput and blocking time. Our solution, which does not depend on time-outs, shows a better performance in unreliable networks and remarkably reduces the amount of blocking.

An Energy-Efficient Concurrency Control Algorithm for Mobile Ad-Hoc Network Databases

“…For example, in a disaster rescue scenario, before sending firefighters out to pursue some actions, the status of their equipment has to be checked to ensure atomic decisions [Obermeier, 2009], where the firefighter database may be stored on one mobile server, and the equipment database may be stored on another mobile server. In a battlefield scene, before a tank fires its cannon, the locations of their own soldiers have to be checked to ensure their safety, where the tank database may be stored on one mobile server, and the soldiers' information may be located on another mobile server.…”

Untitled

“…To minimize the adverse effects of this overhead on the overall system performance, there is a continuing interest in developing more efficient ACPs and optimizations, albeit for different distributed database system environments with inherently different characteristics. These include main memory databases (e.g., [5]), mobile and ad hoc networks (e.g., [6,7,8] ), real-time databases (e.g., [9,10,11]) and component-based architectures (e.g., [12]); besides traditional distributed database systems (e.g., [3,13]).…”