Speculative Concurrency Control Research Articles

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.

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.

QoS management in real-time spatial big data using a feedback control scheduling

Heterogeneous real-time spatial data management is a very active research domain nowadays. We are talking about a real-time spatial big data that process a large amount of heterogeneous data accessed simultaneously by two types of transactions update transactions and user transactions. In these applications, it is desirable to execute transactions within their deadlines using a real-time spatial data. But the real-time spatial big data can be overloaded and many transactions may miss their deadlines, or real-time spatial data can be violated. To address these problems, we proposed, as a first contribution, a new architecture called feedback control scheduling architecture for real-time spatial big data (FCSA-RTSBD) (Hamdi et al., 2015). Then, we propose, as a second contribution, two-shadow speculative concurrency control (SCC-2S) with priority and imprecise computation (SCC-2S-P-IC). Finally, a simulation study is shown to prove that our contributions can achieve a significant performance improvement using the TPC-DS (TPC, 2014) benchmark.

Concurrency Control Protocol for Real-Time Database and the Analysis Base on Petri Net

In the article a new concurrency control protocol for real-time database (RTCC) is proposed. The protocol based on the traditional speculative concurrency control protocol (SCC). It dynamically establish the maximum of shadow to reasonably use the resources of system and add the quasi-commit phase to avoid many unnecessary restarting and enhance the concurrency of transaction. The theory of Petri net proof and results of experiment show that this protocol is feasible and effective , and it can meet the needs of real-time transaction. Speculative Concurrency Control is suitable especially for real-time database[1]. On the one hand, SCC is similar to PCC, to detect potentially harmful conflict as early as possible, so as to start a replacement schedule, thereby increasing the opportunities for transactions to meet time limits. On the other hand, SCC is similar to OCC, it allows the concurrency of conflict transaction and, therefore, avoids unnecessary matters that may affect the timely submission of delay. As a result, it alleviates the congestion problems and PCC restart OCC's problems, in order to better meet the transaction deadline. Based on the fact above mentioned, we propose a suitable real-time database concurrency control protocol [2,3] (RTCC: Concurrency Control protocol for Real-Time). The protocol of the SCC protocol on the traditional basis with a series of improvements can avoid a large number of unnecessary transaction restart and improve concurrency. Finally, by Petri net theory it can be proved feasible and correct.

Value-cognizant speculative concurrency control for real-time databases

Speculative Concurrency Control (SCC) is a new concurrency control approach, especially suited for real-time databases. SCC capitalizes on the availability of unused resources in the system to ensure that serializable executions are discovered and adopted as early as possible, thus increasing the likelihood of the timely commitment of transactions with strict timing constraints. Using SCC, several shadow transactions execute on behalf of a given uncommitted transaction so as to protect against the hazards of blockages and restarts, which are characteristics of Pessimistic and Optimistic Concurrency Control algorithms, respectively. We describe the basic Order-Based SCC (SCC-OB) algorithm and demonstrate its excessive (exponential) use of shadowing. Next, we present SCC-kS, a more practical class of SCC algorithms that operate under a limited resources assumption. SCC-kS does not allow more than k shadows to execute on behalf of any given uncommitted transaction in the system. SCC-kS allows the system to constrain the level of speculation that each transaction is allowed to perform. This provides a straightforward mechanism for trading resources for timeliness. SCC-kS is proved correct by showing that it only admits serializable histories. Next, SCC with Deferred Commit (SCC-DC) is proposed. SCC-DC is a value-cognizant protocol because it utilizes information about transactions, such as deadline and criticalness, to improve timeliness through the controlled deferment of transaction commitments. We conclude our paper with an evaluation of the performance of SCC algorithms. We present simulation results, which show that SCC-based algorithms provide significant performance gains over other widely used concurrency control protocols for real-time databases.

Speculative Concurrency Control for Multidatabases with Real-Time Interoperable Subsystems

Speculative concurrency control (SCC) (Bestavros, 1992) is a new concurrency control approach, especially suited for multidatabases with real-time interoperable subsystems. SCC uses redundancy to ensure that serializable executions are discovered and