Many distributed systems use a replication mechanism for reliability and availability. On the other hand, application developers have to consider minimum consistency requirement for each application. Therefore, a replication protocol that supports multiple consistency models is required. Multi-Consistency Data Replication (McRep) is a proxy-based replication protocol and can support multiple consistency models. However, McRep has a potential problem in that a replicator relaying all request and reply messages between clients and replicas can be a performance bottleneck and a Single-Point-of-Failure (SPoF). In this paper, we introduce the multi-consistency support mechanism of McRep to a combined state-machine and deferred-update replication protocol to eliminate the performance bottleneck and SPoF. The state-machine and deferred-update protocols are well-established approaches for fault-tolerant data management systems. But each method can ensure only a specific consistency model. Thus, we adaptively select a replication method from the two replication bases. In our protocol, the functionality of the McRep's replicator is realized by clients and replicas. Each replica has new roles in serialization of all transactions and managing all views of the database, and each client has a new role in managing status of its transactions. We have implemented and evaluated the proposed protocol and compared to McRep. The evaluation results show that the proposed protocol achieved comparable throughput of transactions to McRep. Especially the proposed protocol improved the throughput up to 16% at a read-heavy workload in One-Copy. Finally, we demonstrated the proposed failover mechanism. As a result, a failure of a leader replica did not affect continuity of the entire replication system unlike McRep.

Data query is one of the most important issues in wireless ad hoc networks, since the ultimate goal of these networks is to support efficient data sharing among wireless nodes. In this paper, we study the issue of data query for delay-sensitive applications in dense wireless ad hoc networks. We focus our attention on step-by-step expanding ring-based data query, which provides an upper bound on query delay to any expanding ring based query strategies. Two replication strategies including Index Replication (IR) and Data Replication (DR) are considered, to improve the delay performance of data query. We analyze the probabilistic behavior of query delay for both DR and IR by theoretical methods, and develop analytical models to approximate the minimum number of replicas required for both query strategies if an application-specified delay bound is imposed. Our work is validated through extensive simulations.

This letter presents the globally optimal data replication in the distributed networks. We propose a distributed approach based on the metropolis-hastings algorithm to achieve the globally optimal data replication without requiring any global information. Experimental results show that the proposed approach works well and the error can be held below 0.6% easily.

We propose an Edge-write architecture which performs eager update propagation for update requests for the corresponding secondary server, whereas it lazily propagates updates from other secondary servers. Our architecture resolves consistency problems caused by read/update decoupling in the conventional lazy update propagation-based system. It also improves overall scalability by alleviating the performance bottleneck at the primary server in compensation for increased but bounded response time. Such relaxed consistency management enables a read request to choose whether to read the replicated data immediately or to refresh it. We use the age of a local data copy as the freshness factor so that a secondary server can make a decision for freshness control independently. As a result, our freshness-controlled edge-write architecture benefits by adjusting a tradeoff between the response time and the correctness of data.

This paper proposes a decentralized and asynchronous replica control method based on a fair assignment of the variation in numerical data that has weak consistency for loosely coupled database systems managed or used by different organizations of human activity. Our method eliminates the asynchronous abort of already committed transactions even if replicas in all network partitions continue to process transactions when network partitioning occurs. A decentralized and asynchronous approach is needed because it is difficult to keep a number of loosely coupled systems in working order, and replica operations performed in a centralized and synchronous way can degrade the performance of transaction processing. We eliminate the transaction abort by fairly distributing the variation in numerical data to replicas according to their demands and updating the distributed variation using only asynchronously propagated update transactions without calculating the precise global state among reachable replicas. In addition, fairly assigning the variation of data to replicas equalizes the disadvantages of processing update transactions among replicas. Fairness control for assigning the data variation is performed by averaging the variation requested by the replicas. A simulation showed that our system can achieve extremely high performance for processing update transactions and fairness among replicas.

In this paper, we propose a new location tracking method for pointer forwarding with distributed HLRs schemes to decrease the location tracking cost. Similar to the distributed HLR schemes, the location information is replicated on all HLRs in our scheme. However, unlike the traditional distributed HLR schemes, we propagate the most recent location changes from an HLR to reset the forwarding pointers in other HLRs, and thus reduce the cost of location tracking for call deliveries. The signaling cost of location propagation may be too costly to be practical. Therefore, we allow some inconsistency to exist among the location data of HLRs and defer the propagation of location changes to reduce the propagation cost. Three delay propagation policies are also proposed and analyzed using simulation. The performance result shows that the delay propagation policies reduce the propagation cost and the propagation resetting process degrades the location tracking cost. Our method preserves a low total cost for call deliveries, registrations and propagations in distributed HLRs.

In this paper we present and analyze multi-level quorum schemes for maintaining the consistency of replicated data in the presence of concurrency and failures in a large distributed environment. The multi-level quorum method operates on a logical hierarchy of the nodes in the network and applies well known flat voting algorithms for replicated data concurrency control in a layered fashion. We show how the number of hierarchy levels, the number of logical entities per level and the voting algorithms used on each level affect the costs and the degree of availability associated with a wide range of multi-level quorum schemes. The results of the analysis are used to provide guidelines for designing the most suitable multi-level quorum strategy for a given application scenario. Comparative performance measurements in a simulated network are presented to illustrate the properties of multi-level approaches when some of the assumptions of the analytical investigation do not hold.