The concept of one event happening before another in a distributed system is examined, and is shown to define a partial ordering of the events. A distributed algorithm is given for synchronizing a system of logical clocks which can be used to totally order the events. The use of the total ordering

between events. Put forward by Lamport in 1978, the logical nature of time is of primary importance when designing or analyzing distributed systems. This paper reviews three ways (linear time, vector time and matrix time) which have been proposed to capture causality between events of a distributed

this paper we defined the notion of bounded clocks and proposed an algorithm to bound vector clocks. The algorithm assumes bounded message delay. In a system with bounded clocks, many messages may have the same timestamp value. The proposed algorithm deals with this ambiguity by dividing

Following TER nets, an approach to the modelling of time in high-level Petri nets, we propose a model of time within (attributed) graph transformation systems where logical clocks are represented as distinguished node attributes. Corresponding axioms for the time model in TER nets

In a Distributed System with N sites, the precise detection of causal relationships between events can only be done with vector clocks of size N. This gives rise to scalability and efficiency problems for accurate logical clocks. In this paper we propose a class of logical clocks called

of trace file is very important to evaluate the scalability of record&replay scheme. This paper proposes an improved clock system, called 1-n clock. By combining local logic clock and vector clock, 1-n clock can compress the size of trace file. This method especially supports record&replay of long

A fundamental problem with runtime monitoring of parallel programs is the intrusion introduced by instrumenting the original program. In order to minimize the amount of intrusion in monitoring parallel programs, the logical clock approach (LCA) was proposed. It uses logical clocks to time

In cloud computing environments, a large number of users access data stored in highly available storage systems. To provide good performance to geographically disperse users and allow operation even in the presence of failures or network partitions, these systems often rely on optimistic replication solutions that guarantee only eventual consistency. In this scenario, it is important to be able to accurately and efficiently identify updates executed concurrently. In this paper, first we review, and expose problems with current approaches to causality tracking in optimistic replication: these either lose information about causality or do not scale, as they require replicas to maintain information that grows linearly with the number of clients or updates. Then, we propose a novel solution that fully captures causality while being very concise in that it maintains information that grows linearly only with the number of servers that register updates for a given data element, bounded by the degree of replication. 1.

" of the distributed algorithm. This capability is unique among protocols which are stable in the face of network partitions, and results in the protocol's high degree of adaptivity. This desirable behavior is achieved through the novel use of a "physical or logical clock" to establish the "

In this paper we present a new logical clock, the barrier-lock clock, whose conception was based on the needs of relaxed consistency DSM systems. Barrier-lock clocks can be used to implement timestamp-based relaxed consistency DSMs since they precisely control the partial order of synchronization