Concurrency Control Algorithm Research Articles

RCBench: an RDMA-enabled transaction framework for analyzing concurrency control algorithms

RCBench: an RDMA-enabled transaction framework for analyzing concurrency control algorithms

Institutional innovation essence and knowledge innovation goal of intellectual property law in the big data era

This work aims to expand the understanding on the nature of institutional innovation and the goal of knowledge innovation of intellectual property (IP) law in the era of big data (BD) and to avoid the risks of information security in the IP service system. On the basis of the era of BD, the nature of institutional innovation and the goal of knowledge innovation in IP law are systematically discussed. Combined with smart contract (SC) technology, an IP service system based on blockchain technology is designed to ensure the security of IP services. The SC is optimized from the perspective of concurrency, and the contract transactions (CTs) are clustered. Moreover, considering the execution time (ET) and available resources of CTs, a speculative concurrency control algorithm that can realize intelligent contract scheduling is proposed. On the basis of the ciphertext-policy attribute-based encryption (CP-ABE) algorithm, a policy-updatable attribute encryption algorithm is designed. The improved CP-ABE algorithm includes six steps: system initialization, attribute private key generation, encryption, decryption, ciphertext policy generation, and ciphertext policy update. The identity parameter of the traceability manager is introduced into the improved CP-ABE scheme, which significantly increases the amount of computation of bilinear mapping, thus resulting in the time cost of encryption and decryption being approximately 350 ms and 300 ms higher than that of the CP-ABE scheme. Using the technical mode of “blockchain + SC,” the design of the IP service system is realized, which has important reference value for the institutional innovation of IP law.

A two-part multi-algorithm concurrency control optimization strategy for distributed database systems

In this paper, we propose a novel holistic approach to address the issues of concurrency control after an exhaustive examination of the problem and the various forms it can transpire. The proposed strategy was formulated depending on different perspectives that are based on exploring a wide range of algorithms, methods, and strategies proposed in practice and theory that attempted to address the problem and its forms, but only partially succeeded in doing so. Here we proposed a two-part holistic strategy to optimize concurrency control in distributed environments that address a wide range of concurrency control anomalies by taking advantage of several concurrency control algorithms' strengths while minimizing their weaknesses. The novelty of our approach transpires from two interconnected parts that can be applied regardless of the type of distributed database environment. The first is a structured tier-based data classification system based on data sensitivity with respect to serializability requirements and ranges from strict to very relaxed forms of serializability constraints. The second is a concurrency management algorithm that allocates the appropriate concurrency control algorithm to each transaction depending on the type of transaction and/or type of data being accessed from the aforementioned tier-based classification method. Our proposed method also incorporates a priority allocation mechanism within the concurrency management algorithm. Priority is allocated to different tier transactions depending on the tier's level, which in turn reflects data importance and sensitivity. Although our proposed strategy remains an algorithmic approach as we encountered various challenges regarding performance testing of a novel multi-algorithm approach for handling concurrency control in distributed database systems. However, future work involves testing the performance of our proposed strategy either through real-time systems after considerable adjustments or by constructing an appropriate customized simulation framework. Finally, the potentials of the strategy presented here are very promising, hence, we recommend as we are also optimistic that other scholars are encouraged to further exploit the concept of using multiple concurrency control algorithms within the same distributed database environment.

Lotus

This paper revisits the H-Store/VoltDB concurrency control scheme for partitioned main-memory databases, which we term run-to-completion-single-thread (RCST), with an eye toward improving its poor performance on multi-partition (MP) workloads. The original scheme focused on maximizing single partition (SP) performance, producing results in millions of transactions per second on modest clusters, but at the expense of dismal MP performance. In this paper, we show that original RCST algorithms be made to dramatically improve MP performance with very limited impact on SP performance. That makes RCST superior to popular optimistic and pessimistic schemes without optimizations for batch execution, including OCC and 2PL, on a wide range of multi-node workloads with up to 60% throughput improvement. Our second contribution is to propose a multiplexed-execution-single-thread (MEST) algorithm based on RCST to amortize the network stalls from MP transactions over a batch of MP transactions. This scheme delivers up to 21X higher throughput for SP transactions and comparable MP throughput compared to state-of-the-art distributed deterministic concurrency control algorithms that are optimized for batch execution. Finally, our MEST scheme offers dramatically superior performance when straggler transactions are present in the workload. Our conclusion is that the H-Store/VoltDB concurrency control scheme can be dramatically improved and dominates state-of-the-art algorithms over a variety of MP workloads.

Concurrent Control Algorithm for Large-scale Remote Multi-user Information Management System

When the current concurrency control algorithm is used to control of the multi-user information management system, the system’s channel transmission capability is low, and the time it takes is long. In this paper, a concurrency control algorithm for large-scale remote multi-user information management system is proposed. According to the average use rate of the large-scale remote multi-user information management system, the concurrency control structure and state of the system are analyzed and judged; Through the analysis of the results, the delay of data link layer in multi-user information management system is carried out modeling; Combined with the queuing delay and accessing delay, the large-scale remote multi-user information management system control can be realized. Experimental results show that the channel utilization rate of the proposed algorithm is over 98.3%, which can transmit large amounts of information in a relatively short time and concurrency control of information management system. Therefore, the proposed algorithm has high channel utilization and efficiency of information transmission

Experimental Study of Concurrency Control Algorithms in Main-memory Database Systems

The concurrency control algorithm is a key approach for a database system to guarantee the correctness and efficiency of the transaction execution. Thus, substantial effort has been devoted to proposing new concurrency control algorithms in both the database industry and academia. In this paper, we take the lead in summarizing the fundamental ideas of concurrency control algorithms as ``ordering-and-verifying''. We then redescribe and sort out the existing concurrency control algorithms following the ordering-and-verifying paradigm. On the basis of extensive comparative experiments on an open-source main-memory distributed transaction testbed called 3TS, we systematically investigate the advantages and disadvantages of the mainstream concurrency control algorithms and finally summarize the preferable application scenario for each algorithm to provide valuable references for follow-up research on concurrency control algorithms used in main-memory databases.

A new secure 2PL real-time concurrency control algorithm (ES2PL)

A secure concurrency control algorithms must be devoid of covert channels originating from data conflicts between transactions, in addition to ensuring database integrity. Current secure concurrency control algorithms mistreat transactions with higher access classes. Because it better solves the priority inversion problem. A widely used concurrency control algorithm is the two-phase locking with high priority (2 PL-HP). The inclusion of cyclic restart, deadlock, unnecessary abort, pseudo-priority inversion, and starvation, on the other hand, may reduce its performance. In this paper, a new enhanced of secure two-phase locking protocol with multilevel secure distributed database systems is presented, the idea of enhanced secure Two-Phase locking protocol by adding the security level to assign the priority to the transaction. The enhanced add a secure manager to decide the level of the security and give the instruction to process the transaction in real lock with data x/virtual lock with version data x0 or decided to Abort the transaction based on the security level. The suggested study intends to reduce transaction miss rate by addressing the following issues: deadlock by splitting the execution stage into locking and processing phases, it reduces unnecessary cycle restart, transaction aborts by checking the security priority level (high, medium, low), and generating virtual lock and versions data. Finally, simulation performance confirms that improvement in transactions miss's percent and reduction in transactions' rollbacks compared to other secure concurrency control.

Concurrency control for real‐time and mobile transactions: Historical view, challenges, and evolution of practices

SummaryRecently, mobile computing has changed the way that spatial data and GIS are processed. Unlike wired and stand‐alone GIS, now the trend has been switched from offline to real‐time data processing using location aware services, such as GPS technology. The increased usage of location aware services in multiuser real‐time environment has made transaction management incredibly significant. If the simultaneous query operations on the same data item are not handled intelligently then this results in data inconsistency issue. Concurrency control protocol is one of the primary aspects that helps in overcoming this issue a in multiuser environment. To the best of our knowledge, the impact of technological advancements on concurrency control has not been thoroughly studied in the literature. In this article, we explored the literature on concurrency control algorithms in depth with respect to real‐time applications and the applications with moving objects. We defined a taxonomy of concurrency control solutions and assessed the maturity of these solutions in the light of characteristics of real‐time and mobile environment. We compared the most recent developments made in the literature and presented meaningful insights. Challenges are also identified and discussed, which can assist in doing research in this domain in future.

An Algorithm for Concurrency control in Transactions for E Wallet

It is a period of online exchanges, managing daily installments through e-wallet for shopping, paying to merchant, also to fulfill all the liquid cash requirement through wallet money with no physical notes or currency involved for transaction, wallet exchange help to web advancements. The cash move and gross repayment is conceivable in only hardly any seconds. The web innovations have been utilizing and still new idea dependent on past encounters are currently coming into exploration and confab. A lot of research papers for wallet creation and inner cycle are accessible. Uncommonly, wallet measure through various methodologies like BC (Bank Channel) Wallet, RBI Wallet, Domestic Pay Service Wallet are principle thought in this exploration work. The exchange cycle faces numerous issues, these issues influence the backer, bank, client regarding misfortune in business. Whereas the client is additionally unsatisfied and unable to do finish wallet procedures. This paper presents a recreation examination of the versatility on simultaneous exchange handling over a combination of portable and fixed exchanges, because of moderate organization availability and down worker might be a similar exchange prepared twofold because of which RBI rules infringement happen and backer, client, bank, specialist all is grieved and misfortune the real business. This paper execution normally utilizes conflict location dependent on the Hidden label bases exchange accommodation through which copying any exchange is preposterous, it ensures that every exchange has prepared just a solitary path under RBI rules or wallet terms.

Design of Monitoring System for Electric Vehicle Charging Facilities Based on Cloud Platform

Faced with the increasingly severe pressure of traditional energy consumption and environmental problems, electric vehicles have become the hotspot and trend of the development of the world automobile industry due to their energy-saving and environmental protection characteristics. The cloud platform in the paper was introduced into the monitoring system of electric vehicle charging facilities, and a model of electric vehicle charging facility monitoring system based on cloud platform was proposed. Aiming at the difficulty of charging facility monitoring system in large concurrent data processing, a M/M/C queuing theory model was presented. Data concurrency control algorithm. The transmission process of the data frame in the monitoring system was analyzed, and the concurrent processing algorithm was applied to the large charging station for analysis experiments. The experimental results showed that the proposed algorithm not only satisfied the real-time and concurrency requirements of data frame transmission, but also proved that the gateway optimization method could accurately derive the optimal number of gateways.

Efficient Concurrent Execution of Smart Contracts in Blockchain Sharding

Throughput performance is a critical issue in blockchain technology, especially in blockchain sharding systems. Although sharding proposals can improve transaction throughput by parallel processing, the essence of each shard is still a small blockchain. Using serial execution of smart contract transactions, performance has not significantly improved, and there is still room for improvement. A smart contract concurrent execution strategy based on concurrency degree optimization is proposed for performance optimization within a single shard. This strategy is applied to each shard. First, it characterizes the conflicting contract feature information by executing a smart contract, analyzing the factors that affect the concurrent execution of the smart contracts, and clustering the contract transaction. Second, in shards with high transaction frequency, considering the execution time, conflict rate, and available resources of contract transactions, finding a serializable schedule of contract transactions by redundant computation and a Variable Shadow Speculative Concurrency Control (SCC-VS) algorithm for smart contract scheduling is proposed. Finally, experimental results show that the strategy increases the concurrency of smart contract execution by 39% on average and the transaction throughput of the whole system by 21% on average.

Priority Heuristic in MDRTDBS

Background: Mobile distributed real time database is an emerging field of research. Transaction execute in these system should commit before elapsing the deadline. Assigning priority to arrived and executing transaction is the main function of transaction scheduler. Perform correct order of execution enhance the system performance in time constraint environment. In recent years a number of heuristic policies in DRTDBS are developed to enhance the quality estimation of scheduler. However due to various wireless limitations a very little work is investigated in the MDRTDBS. In this paper we have develop two heuristic policies and perform simulation using pessimistic and optimistic concurrency control algorithm to enhance the system performance. Objective: Two heuristic policies based on write only locks and number of same data item existence has been introduced. These heuristic approaches enhance the performance of MDRTDBS scheduler. Methods: Develop two heuristic policies based on data contention which cope with CC policies like DHP-2PL and FBOCC. These policies count the number of write only locks and existence of number of same data item. Ultimately these policies enhance the system performance. Results:: Investigated the performance using simulator which is designed using C language. Based on these simulation results using pessimistic and optimistic CCs different graphs are plotted which shows the performance of system for these developed heuristic approaches. During simulation the low and high workload of transaction arrival is taken to fair investigate of these heuristic approaches. Conclusion: Simulation results show that the system performance is improved using these heuristic approaches. However, NWL_Modified heuristic approach outperform in MDRTDBS than earlier heuristic approaches.

A Surgical Robotic System for Treatment of Pelvic Osteolysis Using an FBG-Equipped Continuum Manipulator and Flexible Instruments.

This paper presents the development and experimental evaluation of a redundant robotic system for the less-invasive treatment of osteolysis (bone degradation) behind the acetabular implant during total hip replacement revision surgery. The system comprises a rigid-link positioning robot and a Continuum Dexterous Manipulator (CDM) equipped with highly flexible debriding tools and a Fiber Bragg Grating (FBG)-based sensor. The robot and the continuum manipulator are controlled concurrently via an optimization-based framework using the Tip Position Estimation (TPE) from the FBG sensor as feedback. Performance of the system is evaluated on a setup that consists of an acetabular cup and saw-bone phantom simulating the bone behind the cup. Experiments consist of performing the surgical procedure on the simulated phantom setup. CDM TPE using FBGs, target location placement, cutting performance, and the concurrent control algorithm capability in achieving the desired tasks are evaluated. Mean and standard deviation of the CDM TPE from the FBG sensor and the robotic system are 0.50 mm, and 0.18 mm, respectively. Using the developed surgical system, accurate positioning and successful cutting of desired straight-line and curvilinear paths on saw-bone phantoms behind the cup with different densities are demonstrated. Compared to the conventional rigid tools, the workspace reach behind the acetabular cup is 2.47 times greater when using the developed robotic system.

Aria

Deterministic databases are able to efficiently run transactions across different replicas without coordination. However, existing state-of-the-art deterministic databases require that transaction read/write sets are known before execution, making such systems impractical in many OLTP applications. In this paper, we present Aria, a new distributed and deterministic OLTP database that does not have this limitation. The key idea behind Aria is that it first executes a batch of transactions against the same database snapshot in an execution phase , and then deterministically (without communication between replicas) chooses those that should commit to ensure serializability in a commit phase. We also propose a novel deterministic reordering mechanism that allows Aria to order transactions in a way that reduces the number of conflicts. Our experiments on a cluster of eight nodes show that Aria outperforms systems with conventional nondeterministic concurrency control algorithms and the state-of-the-art deterministic databases by up to a factor of two on two popular benchmarks (YCSB and TPC-C).

Concurrent Learning Adaptive Control With Directional Forgetting

This paper proposes a new concurrent learning-based adaptive control algorithm. The main objective behind our proposition is to relax the persistent excitation requirement for the stability guarantee, while providing the ability to identify time-varying parameters. To achieve the objective, this paper designs a directional forgetting algorithm, which is then integrated with the adaptive law. The theoretical stability analysis shows that the tracking and parameter estimation error is exponentially stable with the signal only finitely excited, not persistently excited. The analysis also shows that the proposed algorithm can guarantee the stability under time-varying parameters. Moreover, the necessary and sufficient conditions for the stability given the time-varying parameters are derived. The results of numerical simulations confirm the validity of the theoretical analysis results and demonstrate the performance of the proposed algorithm.

Multi-Version-PulsatingSTM: A Multi-Version Optimistic Concurrency Control Scheme for Highly Parallel in-Memory Workload in a Multi Core Environment

Large in-memory data structures have a significant application in the fields of graphics, gaming, military and all the possible areas where Big Data can be employed. Their fame in the area of science and technology is attributable to fast in-memory access by the processor as compared to on-disk data structures. These enormous data structures can be accessed still fast and efficiently through parallel computing. For employing highly parallel computations, equally parallel algorithms are required. One of the most desirable attributes of such algorithms is their ability to control concurrency and avoid any deadlocks while being time and energy efficient. This paper presents a multi-version optimistic concurrency control algorithm based on timestamping. This algorithm is lock free and is tested on 64 simulated CPU cores on a multi core simulator. The algorithm is a Software Transactional Memory approach employing 16, 32, 40 and 50 threads in different tests running on the simulator. Half of the threads are doing reading and half are doing writing operation in each case while accessing an in-memory dynamic array. Being lock free and employing lazy timestamp calculations, this approach is better than other existing concurrency control approaches.

Cooperative Manipulation of an Unknown Payload With Concurrent Mass and Drag Force Estimation

In this letter, we consider a team of robots that cooperatively transport a payload with an unknown mass in the presence of unknown drag forces. We develop a concurrent learning-based adaptive control algorithm that estimates the drag forces and the unknown mass and drives the agents and the payload to a common desired velocity. The algorithm also regulates the contact forces on the payload. We prove that the estimated parameters, including the mass of the payload, converge to their true values. We validate the effectiveness of the proposed algorithm using two simulation examples.

Concurrency Control in Database Systems

Concurrency control mechanisms including the wait, time-stamp and rollback mechanisms have been briefly discussed. The concepts of validation in optimistic approach are summarized in a detailed view. Various algorithms have been discussed regarding the degree of concurrency and classes of serializability. Practical questions relating arrival rate of transactions have been presented. Performance evaluation of concurrency control algorithms including degree of concurrency and system behavior have been briefly conceptualized. At last, ideas like multidimensional timestamps, relaxation of two-phase locking, system defined prewrites, flexible transactions and adaptability for increasing concurrency have been summarized.

STAR

In this paper, we present STAR, a new distributed in-memory database with asymmetric replication. By employing a single-node non-partitioned architecture for some replicas and a partitioned architecture for other replicas, STAR is able to efficiently run both highly partitionable workloads and workloads that involve cross-partition transactions. The key idea is a new phase-switching algorithm where the execution of single-partition and cross-partition transactions is separated. In the partitioned phase, single-partition transactions are run on multiple machines in parallel to exploit more concurrency. In the single-master phase, mastership for the entire database is switched to a single designated master node, which can execute these transactions without the use of expensive coordination protocols like two-phase commit. Because the master node has a full copy of the database, this phase-switching can be done at negligible cost. Our experiments on two popular benchmarks (YCSB and TPC-C) show that high availability via replication can coexist with fast serializable transaction execution in distributed in-memory databases, with STAR outperforming systems that employ conventional concurrency control and replication algorithms by up to one order of magnitude.

SolarDB

Efficient transaction processing over large databases is a key requirement for many mission-critical applications. Although modern databases have achieved good performance through horizontal partitioning, their performance deteriorates when cross-partition distributed transactions have to be executed. This article presents SolarDB, a distributed relational database system that has been successfully tested at a large commercial bank. The key features of SolarDB include (1) a shared-everything architecture based on a two-layer log-structured merge-tree; (2) a new concurrency control algorithm that works with the log-structured storage, which ensures efficient and non-blocking transaction processing even when the storage layer is compacting data among nodes in the background; and (3) find-grained data access to effectively minimize and balance network communication within the cluster. According to our empirical evaluations on TPC-C, Smallbank, and a real-world workload, SolarDB outperforms the existing shared-nothing systems by up to 50x when there are close to or more than 5% distributed transactions.