Abstract

Causal ordering is a useful tool for mobile distributed systems (MDS) to reduce the non-determinism induced by three main aspects: host mobility, asynchronous execution, and unpredictable communication delays. Several causal protocols for MDS exist. Most of them, in order to reduce the overhead and the computational cost over wireless channels and mobile hosts (MH), ensure causal ordering at and according to the causal view of the Base Stations. Nevertheless, these protocols introduce certain disadvantage, such as unnecessary inhibition at the delivery of messages. In this paper, we present an efficient causal protocol for groupware that satisfies the MDS's constraints, avoiding unnecessary inhibitions and ensuring the causal delivery based on the view of the MHs. One interesting aspect of our protocol is that it dynamically adapts the causal information attached to each message based on the number of messages with immediate dependency relation, and this is not directly proportional to the number of MHs.

Highlights

  • IntroductionThe deployment of mobile distributed systems (MDS), in conjunction with wireless communication technologies and Internet, enables portable computing devices (referred in this paper as mobile hosts), such as smart phones and personal digital assistants (PDAs), to communicate from anywhere and at anytime

  • The deployment of mobile distributed systems (MDS), in conjunction with wireless communication technologies and Internet, enables portable computing devices, such as smart phones and personal digital assistants (PDAs), to communicate from anywhere and at anytime

  • We propose a new protocol that ensures the causal ordering according to the causal view that the mobile hosts perceive in the MDS, avoiding the unnecessary inhibition at the message delivery, while maintaining a low overhead and computational cost

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Summary

Introduction

The deployment of mobile distributed systems (MDS), in conjunction with wireless communication technologies and Internet, enables portable computing devices (referred in this paper as mobile hosts), such as smart phones and personal digital assistants (PDAs), to communicate from anywhere and at anytime. Causal ordering algorithms are an essential tool to exchange information. The use of causal ordering provides built-in message synchronization and reduces the non-determinism induced by three main aspects: host mobility, asynchronous execution, and unpredictable communication delays. Causal ordering delivery is based on the happened-before relation (HBR) defined by Lamport [11]. This relation establishes causal precedence dependencies over a set of events without using physical clocks. It is a partial order defined as follows: Definition 1. The causal relation ‘‘R’’ is the least partial order relation on a set of events satisfying the following properties:.

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