Global deadlock detection for concurrency control in multidatabase systems

To enforce global serializability in a multidatabase environment the multidatabase transaction manager must take into account the indirect (transitive) conflicts between multidatabase transactions caused by local transactions. Such conflicts are difficult to resolve because the behavior or even the existence of local transactions is not known to the multidatabase system. To overcome these difficulties, we propose to incorporate additional data manipulation operations in the subtransactions of each multidatabase transaction. We show that if these operations create direct conflicts between subtransactions at each participating local database system, indirect conflicts can be resolved even if the multidatabase system is not aware of their existence. Based on this approach, we introduce optimistic and conservative multidatabase transaction management methods that require the local database systems to ensure only local serializability. The proposed methods do not violate the autonomy of the local database systems and guarantee global serializability by preventing multidatabase transactions from being serialized in different ways at the participating database systems. Refinements of these methods are also proposed for multidatabase environments where the participating database systems allow schedules that are cascadeless or transactions have analogous execution and serialization orders. In particular, we show that forced local conflicts can be eliminated in rigorous local systems, local cascadelessness simplifies the design of a global scheduler, and that local strictness offers no significant advantages over cascadelessness.

Transaction management for global serializability and local autonomy in multidatabase systems

Achieving high degree of concurrency in multidatabase transaction scheduling: MTOS

A multidatabase system (MDBS) is a database system which integrates pre-existing databases, called component local database systems (LDBSs), to support global applications accessing data at more than one LDBS. An important research issue in MDBS is query optimization. The query optimization problem in MDBS is quite different from the case of distributed database system (DDBS) since, due to schema heterogeneity and local autonomy of component LDBSs, is not possible to assume that the query optimizer has a complete information on the execution cost and database statistics. In this paper we present a distributed query optimization algorithm that works under very general assumptions for MDBSs with relational global data model. The algorithm is based on the idea of delegating the evaluation of the execution cost of the elementary steps in a query execution plan to the LDBS where the computation is performed. The optimization process is organized as a sequence of steps, in which at each step all LDBSs work in parallel to evaluate the cost of execution plans for partial queries of increasing size, and send their cost estimates to the other LDBS that need them for the next step. The computation is totally distributed, and organized in order to perform no duplicate computation, and to discard as soon as possible the execution plans that may not lead to an optimal solution.KeywordsExecution ModelExecution PlanQuery OptimizationQuery ExecutionExecution CostThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The thesis examines issues of consistency maintenance in advanced database systems; primarily, multidatabase systems. A multidatabase system consists of a number of pre-existing local database systems. A local database system is unaware of its participation in the multidatabase system and, likewise, the multidatabase system has no knowledge of local transaction executions. Enforcing global constraints in such an environment is clearly a challenging task. A methodology for constraint enforcement is presented which utilises existing technology for the replication of data in an attempt to enforce global consistency. While it is shown to have limited applicability, it is nonetheless an interesting study and serves to qualify the limits of such a solution. An alternative method for global consistency maintenance, which relies on the existence of triggers at each of the participant local databases, is then discussed. This method is shown to be particularly suitable when the issue of local database autonomy is of concern. It is, however, only suited to systems where each of the local databases provides a capability for triggering external actions based on the occurrence of particular database events. As a result of this methodology, the requirement for identification of enforcement actions which access sites where the instigating transaction originated becomes apparent. Such enforcement actions can cause deadlock in certain circumstances when they are executed at the same site which initially triggered the global constraint. This issue is dealt with in a novel way by proposing a methodology for statically checking relations at each participant site with a view to determining their susceptibility to this form of deadlock. The method, a graphical representation of the constraint enforcement process in a distributed system, is also shown to have other desirable properties. Arising from the requirements of other work within the thesis, an algorithm for detecting all cycles in a given directed graph is presented. It is shown that, while the well-known adaptation of the Depth First Search algorithm to cycle detection in directed graphs can detect the existence of cycles, it cannot in all circumstances identify all cycles. An algorithm which performs this task is presented together with an analysis of its complexity and correctness. In a more general sense, the issue of deferred constraint enforcement is discussed. Several scenarios where deferred enforcement of constraints is required are presented, together with a method for detecting the presence of cyclic dependencies within a given database schema.

A major concurrency control problem that we have to cope in multidatabase systems is the global deadlock detection and resolution problem. This detection must take into account the autonomy of local systems, which make impossible the visibility of the state of local transactions. A well-known approach to detect such deadlocks, called potential global deadlocks, is one based on the potential conflict graph (PCG) appropriate for the multidatabase transaction model with a global commit protocol. This classical transaction model is very constraining for applications manipulating great volumes of information, and where subtransaction terminations (commit or abort) of global transactions are not totally dependant. In this paper we present an effective potential global deadlock characterization, and an efficient potential global deadlock detection algorithm, in multidatabase systems with an extended transaction model more suited for such applications.

A multidatabase system consists of several heterogeneous local database systems. Most studies of multidatabase transaction management are concerned with the centralized transaction management in which there is only one coordinator. All global transactions are submitted to the coordinator site, and thus it can be overloaded. If the coordinator site fails, the multidatabase systems cannot serve any global transactions. In decentralized transaction management, since the site to which a global transaction is submitted becomes its coordinator, the load is naturally balanced and the multidatabase system is gradually degraded even though a coordinator site fails. This paper proposes a decentralized transaction management algorithm which guarantees global serializability and local autonomy.

Focuses on the transaction management and atomic commitment features of HYDRO, a distributed multidatabase system. HYDRO provides global serializability, deadlock and livelock freedom, multiple concurrent global transactions at any site, and a high level of concurrency control parallelism. Two varieties of local HYDRO concurrency control objects are discussed, and the paper concludes with a brief presentation of the HYDRO atomic commitment scheme. >

Even though many global concurrency control (GCC) algorithms have been proposed to ensure global serializability, their performance is not well understood. We address the GCC problem from the performance perspective, and evaluate the performance of several GCC algorithms using a multidatabase simulation model. We also evaluate the performance of alternative deadlock resolution strategies, and analyze its implication with regard to the degree of supporting local autonomy. The simulation results of this study, the first of its kind in the area of multidatabase systems, make it possible to select an appropriate GCC algorithm and a deadlock resolution strategy for a given heterogeneous distributed environment.

An approach to deadlock detection in multidatabases

A reliable global atomic commitment protocol for distributed multidatabase systems

The process network (PN) model, which consists of concurrent processes communicating over first-in first out unidirectional queues, is useful for modeling and exploiting functional parallelism in streaming data applications. The PN model maps easily onto multi-processor and/or multi-threaded targets. Since the PN model is Turing complete, memory requirements cannot be predicted statically. In general, any bounded-memory scheduling algorithm for this model requires run-time deadlock detection. The few PN implementations that perform deadlock detection detect only global deadlocks. Not all local deadlocks, however, will cause a PN system to reach global deadlock. In this paper, we present the first local deadlock detection algorithm for PN models. The proposed algorithm is based on the Mitchell and Merritt algorithm and is suitable for both parallel and distributed PN implementations.

Directly connected multicomputer systems provide massively high computational capacity when connected with an interconnection network, having their own components as local memory, processor and other peripheral devices and connected with some topology as mesh, hypercube, and tree [1]. These nodes communicate with each other by exchanging messages. Each node equipped with a router which deals with communication-related implications [2]. Various switching techniques are used to route the messages from source to destination node. The wormhole routing technique has been proved as most suitable switching technique in these systems [3], but faces challenges like flow control and deadlocks (Mohapatra in Wormhole routing techniques for directly connected multicomputer systems [4]). There are two common approaches to deadlock handling: deadlock detection and deadlock recovery. The proposed work is based on deadlock recovery. This is based on the existing scheme ‘Disha’ (Anjan and Pinkston in An efficient fully adaptive deadlock recovery scheme: DISHA, pp. 201–210 (1995) [5]). Full adaptive routing is allowed without any restriction, and a deadlock detection mechanism is applied to monitor the deadlocks, and if deadlock is detected, then a deadlock recovery mechanism is in place to resolve the deadlock cycles. To optimize the cost the proposed scheme suggests, not equipping every node with additional buffer but alternate nodes in the columns of a mesh can be equipped with additional flit buffer, and blocked packets can switch to the recovery path, and eventually reach to the destination. So enhanced performance is achieved on reduced complexity and optimized cost.

Research on query cost estimation for local database systems in a multidatabase system (MDBS) has attracted many researchers in the database area recently. Obtaining good query cost estimates is crucial for performing effective global query optimization in an MDBS. However, most techniques suggested so far, including database calibrating and query sampling, consider only a static multidatabase environment. Recently, we proposed a qualitative approach to developing cost models for a dynamic multidatabase environment. It has been shown that this approach is promising in estimating the cost of a query run in any given contention state for a dynamic environment. However, a large (cost) query in practice may experience multiple contention states during its execution, which cannot be directly handled by the qualitative approach. In this paper, we propose two new techniques, i.e., fractional analysis and probabilistic approach, to solve the problem. The fractional analysis technique, which is suitable for a system environment that changes contention states gradually and smoothly, estimates a query cost by analyzing its fractions. The probabilistic approach, which is suitable for a system environment that changes contention states rapidly and randomly, estimates a query cost based on the theory of Markov chains. Cost estimation formulas for both techniques are derived, and their properties are studied. Our experimental results demonstrate that the suggested techniques are quite promising in estimating costs for large queries in a dynamic multidatabase environment.

The aim of the study is to compare the deadlock detection algorithms in distributed systems with respective Blockchain technology presented in this paper. Today, detecting deadlocks in distributed systems is a very important challenge. Without the proper deadlock detection mechanism, the system can get stuck in a reject state. The goal of this work is to figure out which algorithm is more suitable for deadlock detection in Blockchain technology based on these factors i-e Security, Time, Performance, Communication, and Correctness. Under the positivism paradigm. The descriptive research design and distributed technique are used to minimize the occurrence of deadlock and to identify the deadlock in parallel collective operation verified up to maximum threads. The algorithms for deadlock detection that are compared in this study are Scalable deadlock detection, Push-relabel algorithm, Knapp’s, Fulgor, and Consensus based on Blockchain technology. Blockchain technology provides a secure environment and helps to build trust. According to this paper, the Fulgor algorithm is more effective at removing deadlocks and maintaining communication security between distributed systems. Both controlled and uncontrolled environments are tested with different algorithms and are compared to define efficiency side-by-side. Deadlock detection requires identifying some properties and message delays in the global state of the distributed system. The number of common parameters has been identified in the selected algorithms to detect deadlocks in a distributed system