Solving Atomic Broadcast with Indirect Consensus

Connected and automated vehicle (CAV) technology is one of the promising solutions to addressing the safety, mobility and sustainability issues of our current transportation systems. Specifically, the control algorithm plays an important role in a CAV system, since it executes the commands generated by former steps, such as communication, perception, and planning. In this study, we propose a consensus algorithm to control the longitudinal motion of CAVs in real time. Different from previous studies in this field where control gains of the consensus algorithm are pre-determined and fixed, we develop algorithms to build up a lookup table, searching for the ideal control gains with respect to different initial conditions of CAVs in real time. Numerical simulation shows that, the proposed lookup table-based consensus algorithm outperforms the authors' previous work, as well as van Arem's linear feedback-based longitudinal motion control algorithm in all four different scenarios with various initial conditions of CAVs, in terms of convergence time and maximum jerk of the simulation run.

FIFO broadcast provides application ordering semantics of messages broadcast by the same sender and have been mostly implemented on top of unreliable static networks. In this article, we propose a round-based FIFO broadcast algorithm with both termination detection and bounded message size for dynamic networks with recurrent connectivity (Class <tex>$\mathcal{TC}^{\mathcal{R}}$</tex> of Time-varying Graph formalism [1]). Initially, processes only know the number of processes <tex>$N$</tex> in the system and their identifier. Due to the dynamics of the network links, messages can be lost. Since no unbounded timestamp is used to identify a message, its size is bounded to <tex>$2N+O(log(N))+msgSize$</tex> bits where msgSize is the bound size in bits of the broadcast data. We also present a FIFO atomic broadcast algorithm for dynamic networks with recurrent connectivity that uses the proposed FIFO broadcast and deliver primitives. This algorithm provides causal total order broadcast primitives.

Atomic broadcast is an important communication primitive often used to implement state-machine replication. Despite the large number of atomic broadcast algorithms proposed in the literature, few papers have discussed how to turn these algorithms into efficient executable protocols. This paper focuses on a class of atomic broadcast algorithms based on Paxos, with its corresponding desirable properties: safety under asynchrony assumptions, liveness under weak synchrony assumptions, and resiliency-optimality. The paper presents two protocols, M-Ring Paxos and U-Ring Paxos, derived from Paxos. The protocols inherit the properties of Paxos and can be implemented very efficiently. We report a detailed performance analysis of M-Ring Paxos and U-Ring Paxos and compare them to other atomic broadcast protocols.

In this paper, we study distributed consensus algorithms in topology varying networks where there is communication delay between transmissions and receptions. In previous work, it is shown that the ultimate convergence of averaging based consensus algorithms is not affected by bounded delay. In the present work, we establish the same fact by showing that a finite power of the delay augmented system matrix is scrambling. Furthermore, we investigate the effect of bounded delay on convergence speed, and show by constructing certain topologies that delay does not always reduce convergence speed.

Silicon nanocrystals (Si NCs) embedded in a dielectric matrix is regarded as one of the most promising materials for the third generation photovoltaics, owing to their tunable bandgap that allows fabrication of optimized tandem devices. Previous work has demonstrated fabrication of Si NCs based tandem solar cells by sputter-annealing of thin multi-layers of silicon rich oxide and SiO2. However, these device efficiencies were much lower than expected given that their theoretical values are much higher. Thus, it is necessary to understand the practical conversion efficiency limits for these devices. In this article, practical efficiency limits of Si NC based double junction tandem cells determined by fundamental material properties such as minority carrier, mobility, and lifetime are investigated. The practical conversion efficiency limits for these devices are significantly different from the reported efficiency limits which use Shockley-Queisser assumptions. Results show that the practical efficiency limit of a double junction cell (1.6 eV Si NC top cell and a 25% efficient c-Si PERL cell as the bottom cell) is 32%. Based on these results suggestions for improvement to the performance of Si nanocrystal based tandem solar cells in terms of the different parameters that were simulated are presented.

In the last few decades, there has been an increase in food safety and traceability issues. To prevent accidents and misconduct, it became essential to establish Food Safety Traceability System (FSTS) to trace the food from producer to consumer. The traceability systems can help track food in supply chains from farms to retail. Numerous technologies such as Radio Frequency Identification (RFID), sensor networks, and data mining have been integrated into traditional food supply chain systems to remove unsafe food products from the chain. But, these are not adequate for the current supply chain market. The emerging technology of blockchain can overcome safety and tracking issues. This can be possible with the help of blockchain features like transparent, decentralized, distributed, and immutable. Most of the previous works missed the discussion of the systematic process and technology involved in implementing the FSTS using blockchain. In this paper, we have discussed an organized state of research of the existing FSTS using blockchain. This survey paper aims to outline a detailed analysis of blockchain technology, FSTS using blockchain, consensus algorithms, security attacks, and solutions. Several survey papers and solutions based on blockchain are included in this research paper. Also, this work discusses some of the open research issues related to FSTS.

The Internet of Things (IoT) is vulnerable to leakage of private information during data sharing. To avoid this problem, access control and secure data sharing have been introduced in IoT; however, many challenges are faced because of centralized access control and single delegator selection. Additionally, blockchain is integrated into IoT to enhance the security of the environment. For that purpose, this research proposes dynamic secure access control using the blockchain (DSA-Block) model, which performs secure access control and data sharing. Initially, the IoT device attributes and user attributes are registered at a local domain authority (LDA) for generating private and public keys using the hyperelliptic curve cryptography (HECC) algorithm, which ensures the legitimacy of the users and devices. Then, the IoT devices send a request message to the edge nodes (ENs) via a gateway, which performs request filtration by validating the user’s authenticity. The filtered requests are sent to the edge server to perform access delegation using rock hyraxes swarm optimization (RHSO), which selects a set of delegator nodes. The access control decision is made by using the Trusted practical Byzantine fault tolerance (PBFT) consensus algorithm. The IoT data are stored in the cloud server for secure storage, in which the data are secured using a differential privacy mechanism. Finally, dual revocations, such as user attribute revocation and user revocation, are used to maintain security. The performance of DSA-Block is evaluated and the results demonstrate that the proposed DSA-Block model achieves superior performance compared to previous works.

Blockchain's popularity has seen a historic rise over the last decade. However, existing blockchain systems have a major issue with scalability, which has become one of the main obstacles in technology's adoption in mainstream. There have been several attempts to address this limitation by identifying Blockchain's scalability/performance bottlenecks (e.g. those mainly related to consensus algorithms), and thus proposed different solutions (e.g., new consensus protocols) to address such limitations. Other works applied sharding to tackle the issue. All solutions however have mainly focused on Cryptocurrency applications, and thus addressing the scalability of blockchain systems for general applications remains a concern. This work proposes a scalable blockchain protocol for general applications (i.e., not restricted to Cryptocurrencies). To improve the two major factors affecting transaction scalability, namely throughput and latency, we needed to modify both the blockchain structure as well as the block generation process. ZyConChain, the proposed Blockchain system, introduces three types of blocks that form three separate chains: parentBlock, sideBlock and state block. These blocks are generated based on different consensus algorithms, as each algorithm has specific properties that make it suitable for each type of block. To improve the overall performance, ZyConChain generates sideBlocks (that carry transactions) at a high rate and keep them in a pool. To generate parentBlock, miners, instead of packing transactions into a block as they do in conventional blockchains, pack sideBlocks into a parentBlock. SideBlocks are generated based on an adapted Zyzzyva consensus protocol, with O(\log n) complexity. This has reduced the final consensus complexity per transaction, in comparison to previous work. To enable the protocol to scale out with the increase in the number of nodes, ZyConChain applied sharding technique. Parallel state chains have also been introduced to address cross-shard transactions.

This paper builds on previous work in which simple structure ILC algorithms were experimentally evaluated on a non-minimum phase plant. The phase-lead update law, the most promising of those implemented, is examined using an established performance criterion. The use of a forgetting factor is found to overcome the problem of instability, but at the expense of increased final error. This is verified through experimentation. The phase-lead algorithm is improved using additional phase-leads to remove the instability and improve convergence and final error. This technique is generalized to produce an optimization routine which leads to greatly improved results. The learning law utilizing the plant adjoint is found to fit naturally into this framework and practical results are presented to compare their respective performance. This algorithm, which requires a model of the plant, is reformulated into one which does not. Results are presented using this technique and practical guidelines are produced and tested to improve its performance. A simple method of increasing the learning at higher frequencies is proposed and practical limitations are addressed and verified experimentally. All the algorithms tested are compared with respect to their performance, practicality and robustness.

The performance of closed reactor grade plutonium–thorium fuel cycles in reduced-moderation pressurised water reactors

Adaptability and graceful degradation are important features in distributed systems. Yet, consensus and other agreement protocols, basic building blocks of reliable distributed systems, lack these features and must perform expensive reconfiguration even in face of single failures. In this paper we describe multicoordinated mode of execution for agreement protocols that has improved availability and tolerates failures in a graceful manner. We exemplify our approach by presenting a generic broadcast algorithm. Our protocol can adapt to environment changes by switching to different execution modes. Finally, we show how our algorithm can solve the generalized consensus and its many instances (e.g., consensus and atomic broadcast).

The lithium-ion battery (LIB) has been at the forefront of innovations in energy storage since its commercialisation over 30 years ago. As we reach the practical specific capacity limit of current state-of-the-art materials, novel and innovative battery technologies are required to satiate the requirements of energy intensive applications such as electric vehicles. 1 The use of a lithium metal negative electrode has been proposed to increase the energy density, however the high reactivity causes poor cycling performance due to electrolyte degradation, dendrite formation and safety issues. 2 The magnesium electrode offers a solution that has double the theoretical volumetric capacity of the lithium electrode while simultaneously mitigating dendritic growth, reducing raw material costs and greatly increasing sustainability. 3,4 Previous work has shown that traditional LIB electrolytes are not compatible with magnesium metal, and the plating and stripping mechanism that underpins how magnesium electrodes cycle is poorly understood. 5 Here we explored the mechanism of magnesium plating and stripping in glyme-based electrolytes with a range of additional additives. We show that in the pure electrolyte solution, interphase formation is critical to stable cycling but that this is accompanied by significant degradation and accumulation of inactive Mg.6 We establish the three-dimensional chemical composition of Mg deposits in the different electrolyte formulations using a combination of focused ion beam-scanning electron microscopy (FIB-SEM), energy dispersive x-ray spectroscopy (EDX) and transmission electron microscopy (TEM). We use these findings to develop a mechanistic understanding that explains the electrochemical cycling performance of magnesium metal negative electrodes. In situ electrochemical quartz crystal microbalance (EQCM) measurements are used to evaluate the plating and stripping efficiency of the electrodes and to identify non-electrochemical degradation reactions between Mg and the electrolyte solutions.

Cellular processes are governed by macromolecular complexes inside the cell. Study of the native structures of macromolecular complexes has been extremely difficult due to lack of data. With recent breakthroughs in Cellular Electron Cryo-Tomography (CECT) 3D imaging technology, it is now possible for researchers to gain accesses to fully study and understand the macro-molecular structures single cells. However, systematic recovery of macromolecular structures from CECT is very difficult due to high degree of structural complexity and practical imaging limitations. Specifically, we proposed a deep learning-based image classification approach for large-scale systematic macromolecular structure separation from CECT data. However, our previous work was only a very initial step toward exploration of the full potential of deep learning-based macromolecule separation. In this paper, we focus on improving classification performance by proposing three newly designed individual CNN models: an extended version of (Deep Small Receptive Field) DSRF3D, donated as DSRF3D-v2, a 3D residual block-based neural network, named as RB3D, and a convolutional 3D (C3D)-based model, CB3D. We compare them with our previously developed model (DSRF3D) on 12 datasets with different SNRs and tilt angle ranges. The experiments show that our new models achieved significantly higher classification accuracies. The accuracies are not only higher than 0.9 on normal datasets, but also demonstrate potentials to operate on datasets with high levels of noises and missing wedge effects presented.

Dealing with existential questions is a constitutive part of palliative care. Interestingly, if we admit that borderline situations at the end-of life give rise to philosophical questions, in the contexts of practice, these questions are perceived (nearly) without any reference to explicit philosophical traditions or to Philosophical Practice. Philosophical Practice is a modern movement for a non-elitist philosophy. It aims to enable people—in the Socratic tradition—to reflect on their experiences in a philosophical way in everyday life. In the recently launched research project Philosophical Practice in Palliative Care and Hospice Work, we are investigating the opportunities and limits of Philosophical Practice for the development of death literacy. Building on previous theoretical work, we analyse, discuss, and illustrate concrete models of Philosophical Practice in this chapter. Our conclusions refer to practical indications for relating Philosophical Practice productively to relevant contexts of death literacy development, such as caring communities, Last Aid courses, and everyday ethics.

Interactive stereoscopic images can be viewed on a graphics workstation by producing side-by-side images and viewing through a simple mirror device. However, it is important that the viewing device have pairs of adjustable nonparallel mirrors so large windows can be viewed without the human's sightlines needing to diverge, or 'look wall-eyed'. Transformations to produce the correct images for this viewing method are described. Previous work applied to the case where both left and right images were to be superimposed and multiplexed in the same region of the screen, often called anaglyphs. Such cases are adequately handled by a translation and an off-axis perspective transformation. The same kind of transformation can be used with a parallel-mirror device, but such devices have practical limitations. This paper shows that nonparallel mirrors require a somewhat more complicated transformation involving scene rotations as well. Derivation of the correct angle of rotation of the main difficulty in computing this transformation. The transformation can be implemented by a sequence of graphics library procedures. Advantages and disadvantages of nonparallel mirror methods are discussed.