This paper proposes a, namely, asynchronous chain and presents a Variable Bulk Arrival and Asynchronous Bulk Service (VBAABS) model of the type in order to provide a quantitative method to design an asynchronous chain as a basis in its initial theoretical design stage. Note that the proposed chain is precisely and namely asynchronous along with adaptive-sized blocks in a proactive manner versus the conventional chain that controls the block posting in a strictly synchronous manner to the fixed-sized blocks. The model of the type (i.e., VBAVBS) is considered as the theoretical and quantitative baseline model for the proposed model, namely, an adaptive chain model, yet with a rather reactively dynamic size of blocks, while the proposed asynchronous model carries a proactively dynamic (or adaptive) size of blocks. The proposed asynchronous chain model assumes variable bulk arrivals of transactions in Poisson distribution, i.e., , where represents the number of slots across all the mined transactions, and variable asynchronous services of transactions, each of which applies to a block potentially of different capacity in terms of the number of slots in it, in exponential time, i.e., , for being posted in the current block, namely, VBAABS. The major quantitative distinction between the adaptive model, i.e., VBAVBS, and the asynchronous model, i.e., VBAABS, is that in VBAVBS, every state , where , transitions back into while in VBAABS, every state , where , transitions back into , where , as well as back into , and is the state in which the transaction up in execution is to be discarded, in other words, that the current block capacity is in excess of the required capacity for the transaction in execution to result in a potentially excessive delay as much as than an otherwise ordinarily fully synchronous block posting delay that is as much as . VBAABS will reveal the performance advantages of the asynchronous chain versus the baseline chain, i.e., VBASBS [30] and the adaptive chain, i.e., VBAVBS, with respect to the average time for a slot to wait in the block and the average spatial requirement by the slots in the block, in a quantitative manner. Extensive numerical simulations are conducted on Matlab. Further, for feasibility validation purpose, an asynchronous chain algorithm will be developed and implemented by redesigning the Ethereum open source and analyzed.
In Ethereum, miners are responsible for expanding the blockchain ledger by appending new blocks of transactions in exchange for incentives. Within the current Ethereum incentive mechanism, miners can still receive a significant amount of reward when creating non-full or even empty blocks, despite their negative impact on the system performance. We provide an extensive data-driven analysis of the impact of non-full blocks on the system performance, with the help of the BlockSim simulation tool. We collect the data for 500,000 Ethereum blocks and fit the appropriate probability distributions to the data to provide input suitable for the simulator. We show that the performance of Ethereum can be improved by over 50% if all blocks were filled with transactions. We propose an adjustment to the current Ethereum incentive model to assure the received incentive is always proportional to the block utilization level. Using our proposed approach, the incentive for non-full blocks is significantly reduced, making this behavior less attractive for miners. This implies that miners would be enforced to fill their blocks with transactions, and thus the performance is pushed to its optimal level. We show that our approach can work in practice without any crucial security issues.
Dynamic Spectrum Sharing (DSS) is proposed as a solution to the spectrum scarcity and under-utilization problem in a world of ever-increasing spectrum demand. Enabling DSS, however, requires overcoming many technical, regulatory, and economic challenges. Cognitive Radio (CR) provided a solution for some of the technical issues of DSS by equipping wireless devices with intelligent sensing and decision making capabilities to enable dynamic sharing of the surrounding spectrum between devices. However, CR alone has been unable to provide a fully dynamic ecosystem for spectrum sharing that guarantees protection for spectrum owners. This has led multiple spectrum regulators to implement frameworks that enable DSS through a centralized spectrum management system that complements the CR capabilities to ensure compliance with spectrum access policies and regulations. However, these frameworks require trusting a third party to manage spectrum access and do not provide intrinsic mechanisms to incentives spectrum owners to share their spectrum. Blockchain technology provides a distributed platform for autonomous asset trading that can be utilized to implement a fully dynamic spectrum sharing system, ensuring transparency and trust between devices without the need for a third party. This paper provides a blockchain-based model for a DSS that represents spectrum access rights as tokenized assets and enables trading of these spectrum tokens between multiple users on a distributed ledger using smart contracts. The proposed model is implemented using Hyperledger Fabric (HLF) as a permissioned blockchain network and the details of the implemented Chaincode transactions are outlined.
Jongho Seol, Jinfu Ke, Shital Joshi, N. Park · 5 authors
This paper proposes a quantitative model to assess the performance of a NFT (Non-Fungible Token)-centered chain as referred to as a NFT Chain in this paper. NFT chain in general stores its data distributed across on chain (e.g. NFT registration data and an address pointing at the data located off chain such as meta data table and ultimate digital asset's data) due to the high cost to store the potentially high volume of data for digital assets. Therefore, it is expected that the overall performance of NFT chain is primarily to be dominated and bound by the off-chain performance. The proposed performance model employing an embedded Markovian queueing process model, tracks a bivariate state of the NFT chain such that$(i,j)$where$i$stochastically tracks the number of slots of the transactions executed on chain and$j$stochastically tracks the number of transactions off chain as well, and the states transition as determined by$\lambda_{on}, \lambda_{off}, \mu$, and the number of slots in the current block. Extensive numerical simulations are performed to validate the efficacy of the model. The primary set of variables used in the simulations consists of$\lambda_{on}, \lambda_{off}, \mu$and the average number of slots of the transactions during a block posting,$L$, is simulated based on both$L_{on}$and$L_{off}$; and the average waiting time$W$based on both$W_{on}$and$W_{off}$, in an intermingled manner in order to take into account of the nature of NFT transactions executed across on- and off-chain without loss of generality. The simulation results demonstrate a good agreement with the expected and intuitive trends and the proposed NFT chain performance model serves as a sound theoretical foundation for the design of an NFT chain from the system's perspective.
In this paper, we present a simulation study of a Proof of Stake (PoS) consensus algorithm used in a public blockchain called Nxt. We first provide an overview of Nxt and its PoS consensus algorithm design, and introduce a concise mathematical analysis of the Nxt PoS algorithm. We then present an experimental study on the Nxt PoS behavior in a simulated environment and in a small network running Nxt private nodes. We show that the fractions of the blocks generated by forgers in the system are generally proportional to their weight in stakes provided that the weight is relatively small, which is consistent with the mathematical analysis. We consider two scenarios of double-spending attacks: (1) a single dominating forger with large stakes; and (2) a group of colluding forgers that collectively control large stakes. The simulation results show that the single-forger attack is more advantageous over using a pool of forgers in launching successful double-spending attacks. Finally, we propose a quota-based mechanism to limit the fraction of blocks that any forger could generate. We show that the mechanism is highly effective in mitigating the single-forger attack, but has limited success in preventing the double-spending attacks based on forging pools.
In blockchains , transaction fees are fixed by the users. The probability for a transaction to be processed quickly increases with the fee level. In this paper, we study the transaction fee optimization problem in the Ethereum blockchain. This problem consists of determining the minimum price a user should pay so that its transaction is processed with a given probability in a given amount of time. To reach this goal, we define a new solution method based on a Monte Carlo approach to predict the probability that a transaction will be mined within a given time limit. Numerical results on real data highlight the quality of the results.
V Anupama, Vishnu Vardhan Battu, B. Srinivasa Rao, Chitturi Prasad
The Ethereum blockchain is intended to move from a Proof-of-Work agreement convention to a Proof-of-Stake one. Right by Construction Casper conveys a theoretical group of numerical Proof-of-Stake agreement conventions however it doesn't give block creation methodologies to hubs which this the undertaking plan to take care of them. A testing system in the view of a current Casper library has been carried out to reproduce blockchains managed by the proposed fundamental techniques and idleness, and hub count and upward are estimated during the reproductions. The carried-out structure has been approved utilizing the essential methodologies and grants the execution of more intricate ones through a conventional code design. The proposed model offers a decent method for contrasting inactivity and upward for techniques yet isn't proficient to assess the manner in which a procedure scales with the quantity of hubs in the organization
Francesc Wilhelmi, Sergio Barrachina‐Muñoz, Paolo Dini
Due to the increasing interest in blockchain technology for fostering secure, auditable, decentralized applications, a set of challenges associated with this technology need to be addressed. In this letter, we focus on the delay associated with Proof-of-Work (PoW)-based blockchains, whereby participants validate the new information to be appended to a distributed ledger via consensus to confirm transactions. We propose a novel end-to-end latency model based on batch-service queuing theory that characterizes timers and forks for the first time. Furthermore, we derive an estimation of the optimal block size analytically. Endorsed by analytical and simulation results, we show that the optimal block size approximation is a consistent method that leads to close-to-optimal performance by significantly reducing the overheads associated with blockchain applications.
This article studies the PBFT-based sharded permissioned blockchain, which executes in either a local datacenter or a rented cloud platform. In such permissioned blockchain, the transaction (TX) assignment strategy could be malicious such that the network shards may possibly receive imbalanced transactions or even bursty-TX injection attacks. An imbalanced transaction assignment brings serious threats to the stability of the sharded blockchain. A stable sharded blockchain can ensure that each shard processes the arrived transactions timely. Since the system stability is closely related to the blockchain throughput, how to maintain a stable sharded blockchain becomes a challenge. To depict the transaction processing in each network shard, we adopt the Lyapunov Optimization framework. Exploitingdrift-plus-penalty(DPP) technique, we then propose an adaptive resource-allocation algorithm, which can yield the near-optimal solution for each network shard while the shard queues can also be stably maintained. We also rigorously analyze the theoretical boundaries of both the system objective and the queue length of shards. The numerical results show that the proposed algorithm can achieve a better balance between resource consumption and queue stability than other baselines. We particularly evaluate two representative cases of bursty-TX injection attacks, i.e., the continued attacks against all network shards and the drastic attacks against a single network shard. The evaluation results show that the DPP-based algorithm can well alleviate the imbalanced TX assignment, and simultaneously maintain high throughput while consuming fewer resources than other baselines.
In recent years, the use of consensus mechanism to maintain the security of blockchain system has become a considerable concern of the community. Delegated proof of stake (DPoS) and practical Byzantine fault tolerant (PBFT) consensus mechanisms are key technologies in maintaining the security of blockchain system. First, this study proposes a consensus mechanism combining DPoS and PBFT, which can rapidly deal with malicious witness nodes and shorten the time of block verification. Second, the M/PH/1 queuing model is used to analyze the performance of the proposed consensus mechanism, and the performance of the improved practical Byzantine fault tolerant consensus mechanism is evaluated from steady-state conditions and key performance measure of the system. Third, the current study uses the theoretical method of open (Jackson) queuing network, combined with the blockchain consensus process, and provides theoretical analysis with special cases. Lastly, this research utilizes numerical examples to verify the computability of the theoretical results. The analytic method is expected to open a series of potentially promising research in queueing theory of blockchain systems.
We review the recent developments in dynamic inventory models with financial flow considerations. The focus is on the literature that introduces cash flow dynamics into the classic inventory models that do not explicitly consider the interactions between physical (or material) and financial flows. These augmented models serve two important purposes. First, they help understand the impact of financial flows on inventory dynamics and decisions. Second, with the connection to the classic inventory models, one can leverage the extant results to derive the optimal control policy or to evaluate/optimize the performance of any given type of policy and reveal insights. We summarize models for both single-stage and multi-stage inventory systems, and discuss the implications and applications to decentralized systems within a broader topic of supply chain finance.
Abstract We analyze the protocol of the bitcoin blockchain by using the PRISM probabilistic model checker. In particular, we (i) extend PRISM with the ledger data type , (ii) model the behavior of the key participants in the protocol—the miners —and (iii) describe the whole protocol as a parallel composition of processes. The probabilistic analysis of the model highlights how forks happen and how they depend on specific parameters of the protocol, such as the difficulty of the cryptopuzzle and the network communication delays. Our results confirm that considering transactions in blocks at depth larger than 5 as confirmed is reasonable because the majority of miners have consistent blockchains up‐to that depth with probability of almost 1. We also study the behavior of networks with churn miners, which may leave the network and rejoin afterwards, and with different topologies.
To quickly manufacture multi-variety and low-volume products, manufacturing factories are increasingly sharing resources on collaborative production networks. However, the reliability of communication between factories cannot be fully guaranteed using traditional centralised approaches. Emerging blockchain technology can solve this problem due to its characteristics such as decentralisation and security. In this context, an integrated optimisation problem of multi-factory production and blockchain-secured collaborative maintenance is studied in this paper. Two scenarios are introduced with respective Q learning-based solution frameworks to solve the integrated problem. In the simulation scenario, preventive maintenance (PM) with flexible time windows is integrated with multi-factory production scheduling for reducing the probability of machine failures, and an initial integrated optimisation scheme is obtained. To make it more realistic, inevitable failures are considered in the actual production scenario, and the proposed collaborative maintenance strategy is triggered. Specifically, a corrective maintenance (CM) strategy is carried out immediately on the failed machine in case of a failure, followed by the PM on machines of the same type as the failed machine in other factories and the rescheduling of unprocessed jobs. Through a series of numerical studies, the effectiveness of the proposed optimisation approach and maintenance strategy is validated, and some interesting managerial implications also rise.
Befekadu G. Gebraselase, Bjarne E. Helvik, Yuming Jiang
Blockchain is a technology that provides a distributed ledger that stores previous records while maintaining consistency and security. Bitcoin is the first and largest decentralized electronic cryptographic system that uses blockchain technology. It faces a challenge in making all the nodes synchronize and have the same overall view with the cost of scalability and performance. In addition, with miners' financial interest playing a significant role in choosing transactions from the backlog, small fee or small fee per byte value transactions will exhibit more delays. To study the issues related to the system's performance, we developed an $M(t)/M^N/1$ model. The backlog's arrival follows an inhomogeneous Poison process to the system that has infinite buffer capacity, and the service time is distributed exponentially, which removes $N$ transactions at time. Besides validating the model with measurement data, we have used the model to study the reward distribution when miners take transaction selection strategies like fee per byte, fee-based, and FIFO. The analysis shows that smaller fee transactions exhibit higher waiting times, even with increasing the block size. Moreover, the miner transaction selection strategy impacts the final gain.
Xu Wang, Wei Ni, Xuan F. Zha, Guangsheng Yu · 7 authors
As distributed ledgers, blockchains run consensus protocols which trade capacity for consistency, especially in non-ideal networks with incomplete connectivity and erroneous links. Existing studies on the tradeoff between capacity and consistency are only qualitative or rely on specific assumptions. This paper presents discrete-time Markov chain models to quantify the capacity of Proof-of-Work based public blockchains in non-ideal networks. The comprehensive model is collapsed to be ergodic under the eventual consistency of blockchains, achieving tractability and efficient evaluations of blockchain capacity. A closed-form expression for the capacity is derived in the case of two miners. Another important aspect is that we extend the ergodic model to analyze the capacity under strong consistency, evaluating the robustness of blockchains against double-spending attacks. Validated by simulations, the proposed models are accurate and reveal the effect of link quality and the distribution of mining rates on blockchain capacity and the ratio of stale blocks.