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Register a new userOptimal Transaction Queue Waiting in Blockchain Mining
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Added by
Gholamreza Ramezan
Publication date
2020
fields
Informatics Engineering
and research's language is
English
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Blockchain systems are being used in a wide range of application domains. They can support trusted transactions in time critical applications. In this paper, we study how miners should pick up transactions from a transaction pool so as to minimize the average waiting time per transaction. We derive an expression for the average transaction waiting time of the proposed mining scheme and determine the optimum decision rule. Numerical results show that the average waiting time per transaction can be reduced by about 10% compared to the traditional no-wait scheme in which miners immediately start the next mining round using all transactions waiting in the pool.
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A blockchain is an append-only linked-list of blocks, which is maintained at each participating node. Each block records a set of transactions and their associated metadata. Blockchain transactions act on the identical ledger data stored at each node. Blockchain was first perceived by Satoshi Nakamoto as a peer-to-peer digital-commodity (also known as crypto-currency) exchange system. Blockchains received traction due to their inherent property of immutability-once a block is accepted, it cannot be reverted.
Multiserver jobs, which are jobs that occupy multiple servers simultaneously during service, are prevalent in todays computing clusters. But little is known about the delay performance of systems with multiserver jobs. We consider queueing models for multiserver jobs in a scaling regime where the total number of servers in the system becomes large and meanwhile both the system load and the number of servers that a job needs scale with the total number of servers. Prior work has derived upper bounds on the queueing probability in this scaling regime. However, without proper lower bounds, the existing results cannot be used to differentiate between policies. In this paper, we study the delay performance by establishing sharp bounds on the mean waiting time of multiserver jobs, where the waiting time of a job is the time spent in queueing rather than in service. We first consider the commonly used First-Come-First-Serve (FCFS) policy and characterize the exact order of its mean waiting time. We then prove a lower bound on the mean waiting time of all policies, and demonstrate that there is an order gap between this lower bound and the mean waiting time under FCFS. We finally complement the lower bound with an achievability result: we show that under a priority policy that we call P-Priority, the mean waiting time achieves the order of the lower bound. This achievability result implies the tightness of the lower bound, the asymptotic optimality of P-Priority, and the strict suboptimality of FCFS.
This exposition presents a novel approach to solving an M/M/m queue for the waiting time and the residence time. The motivation comes from an algebraic solution for the residence time of the M/M/1 queue. The key idea is the introduction of an ansatz transformation, defined in terms of the Erlang B function, that avoids the more opaque derivation based on applied probability theory. The only prerequisite is an elementary knowledge of the Poisson distribution, which is already necessary for understanding the M/M/1 queue. The approach described here supersedes our earlier approximate morphing transformation.
We study the strategic implications that arise from adding one extra option to the miners participating in the bitcoin protocol. We propose that when adding a block, miners also have the ability to pay forward an amount to be collected by the first miner who successfully extends their branch, giving them the power to influence the incentives for mining. We formulate a stochastic game for the study of such incentives and show that with this added option, smaller miners can guarantee that the best response of even substantially more powerful miners is to follow the expected behavior intended by the protocol designer.
Many blockchain-based cryptocurrencies provide users with online blockchain explorers for viewing online transaction data. However, traditional blockchain explorers mostly present transaction information in textual and tabular forms. Such forms make understanding cryptocurrency transaction mechanisms difficult for novice users (NUsers). They are also insufficiently informative for experienced users (EUsers) to recognize advanced transaction information. This study introduces a new online cryptocurrency transaction data viewing tool called SilkViser. Guided by detailed scenario and requirement analyses, we create a series of appreciating visualization designs, such as paper ledger-inspired block and blockchain visualizations and ancient copper coin-inspired transaction visualizations, to help users understand cryptocurrency transaction mechanisms and recognize advanced transaction information. We also provide a set of lightweight interactions to facilitate easy and free data exploration. Moreover, a controlled user study is conducted to quantitatively evaluate the usability and effectiveness of SilkViser. Results indicate that SilkViser can satisfy the requirements of NUsers and EUsers. Our visualization designs can compensate for the inexperience of NUsers in data viewing and attract potential users to participate in cryptocurrency transactions.
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