| 1. |
- Bergman, Sara, et al.
(författare)
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Permissioned Blockchains and Distributed Databases : A Performance Study
- 2020
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Ingår i: Concurrency and Computation. - : John Wiley & Sons. - 1532-0626 .- 1532-0634. ; 32:12
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Tidskriftsartikel (refereegranskat)abstract
- Blockchains are increasingly studied in the context of new applications. Permissioned blockchains promise to deal with the issue of complete removal of trust, a notion that is currently the hallmark of the developed society. Before the idea is adopted in contexts where resource efficiency and fast operation is a requirement, one could legitimately ask the question: can permissioned blockchains match the performance of traditional large‐scale databases? This paper compares two popular frameworks, Hyperledger Fabric and Apache Cassandra, as representatives of permissioned blockchains and distributed databases, respectively. We compare their latency for varying workloads and network sizes. The results show that, for small systems, blockchains can start to compete with traditional databases, but also that the difference in consistency models and differences in setup can have a large impact on the resulting performance.
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| 2. |
- Casalicchio, Emiliano, et al.
(författare)
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The state-of-the-art in container technologies : Application, orchestration and security
- 2020
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Ingår i: Concurrency and Computation. - : John Wiley and Sons Ltd. - 1532-0626 .- 1532-0634. ; 32:17
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Tidskriftsartikel (refereegranskat)abstract
- Containerization is a lightweight virtualization technology enabling the deployment and execution of distributed applications on cloud, edge/fog, and Internet-of-Things platforms. Container technologies are evolving at the speed of light, and there are many open research challenges. In this paper, an extensive literature review is presented that identifies the challenges related to the adoption of container technologies in High Performance Computing, Big Data analytics, and geo-distributed (Edge, Fog, Internet-of-Things) applications. From our study, it emerges that performance, orchestration, and cyber-security are the main issues. For each challenge, the state-of-the-art solutions are then analyzed. Performance is related to the assessment of the performance footprint of containers and comparison with the footprint of virtual machines and bare metal deployments, the monitoring, the performance prediction, the I/O throughput improvement. Orchestration is related to the selection, the deployment, and the dynamic control of the configuration of multi-container packaged applications on distributed platforms. The focus of this work is on run-time adaptation. Cyber-security is about container isolation, confidentiality of containerized data, and network security. From the analysis of 97 papers, it came out that the state-of-the-art is more mature in the area of performance evaluation and run-time adaptation rather than in security solutions. However, the main unsolved challenges are I/O throughput optimization, performance prediction, multilayer monitoring, isolation, and data confidentiality (at rest and in transit). © 2020 John Wiley & Sons, Ltd.
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| 3. |
- Herskind, Lasse, et al.
(författare)
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BitFlow : Enabling Real‐time Cash‐flow Evaluations through Blockchain
- 2020
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Ingår i: Concurrency and Computation. - : John Wiley & Sons. - 1532-0626 .- 1532-0634. ; 32:12
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Tidskriftsartikel (refereegranskat)abstract
- Disbursement registration has always been a cumbersome, opaque, and inefficient process, up to the point that most businesses perform cash-flow evaluations only on a quarterly basis. We believe that automatic cash-flow evaluations can actively mitigate these issues. In this paper, we presentBitFlow, ablockchain-based architecture thatprovides complete cash-flow transparency and diminishes the probability of undetected frauds through the BitKrone, a non-volatile cryptocurrency that maps to the Danish Krone (DKK). We show that confidentiality can be effectively achieved on a permissionless blockchain using Zero-Knowledge proofs, ensuring verifiable transfers and automatic evaluations. Furthermore, we discuss several experiments to evaluate our proposal, in particular, the impact that confidential transactions have on the whole system, in terms of responsiveness and from an economical expenditure perspective.
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| 4. |
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| 5. |
- HoseinyFarahabady, MohammadReza, et al.
(författare)
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Energy efficient resource controller for Apache Storm
- 2023
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Ingår i: Concurrency and Computation. - : John Wiley & Sons. - 1532-0626 .- 1532-0634. ; 35:17
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Tidskriftsartikel (refereegranskat)abstract
- Apache Storm is a distributed processing engine that can reliably process unbounded streams of data for real-time applications. While recent research activities mostly focused on devising a resource allocation and task scheduling algorithm to satisfy high performance or low latency requirements of Storm applications across a distributed and multi-core system, finding a solution that can optimize the energy consumption of running applications remains an important research question to be further explored. In this article, we present a controlling strategy for CPU throttling that continuously optimize the level of consumed energy of a Storm platform by adjusting the voltage and frequency of the CPU cores while running the assigned tasks under latency constraints defined by the end-users. The experimental results running over a Storm cluster with 4 physical nodes (total 24 cores) validates the effectiveness of proposed solution when running multiple compute-intensive operations. In particular, the proposed controller can keep the latency of analytic tasks, in terms of 99th latency percentile, within the quality of service requirement specified by the end-user while reducing the total energy consumption by 18% on average across the entire Storm platform.
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| 6. |
- HoseinyFarahabady, MohammadReza, et al.
(författare)
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Enhancing disk input output performance in consolidated virtualized cloud platforms using a randomized approximation scheme
- 2022
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Ingår i: Concurrency and Computation. - : John Wiley & Sons. - 1532-0626 .- 1532-0634. ; 34:2
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Tidskriftsartikel (refereegranskat)abstract
- In a virtualized computer system with shared resources, consolidated virtual services (VSs) fiercely compete with each other to obtain the required capacity of resources, and this causes significant system's performance degradation. The performance of input output (I/O)-bound applications running inside their own VS is mainly determined by the total time required to schedule every read/write request, plus the actual time needed by the device driver to complete the request. To achieve a right performance isolation of shared resources (e.g., the last level cache, memory bandwidth, and the disk buffer), it is essential to limit the performance degradation level among collocated applications, as simultaneously several I/O operations are requested by VSs, perhaps with different priorities. This article proposes a resource allocation controller that uses a fully polynomial-time randomized approximation scheme to enable performance isolation of concurrent I/O requests in a shared system with multiple consolidated VSs. This controller uses a Monte Carlo sampling approach to measure and estimate the unknown attributes of operational requests originating from each VS. This is formalized as an optimization problem with the aim to minimize the degree of total quality of service (QoS) violation incidents in the entire platform. We associated a reward function to every working machine that represents the fulfillment degree of quality of service metric among all running VSs. The conducted comprehensive set of experiments showed that the proposed algorithm can reduce the QoS violation incidents by 32%, compared with the result which is obtained by employing the default resource allocation policy embedded in the existing Linux container layer.
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| 7. |
- Kjelgaard Mikkelsen, Carl Christian, 1976-, et al.
(författare)
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Newton's method revisited : how accurate do we have to be?
- 2024
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Ingår i: Concurrency and Computation. - : John Wiley & Sons. - 1532-0626 .- 1532-0634. ; 36:10
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Tidskriftsartikel (refereegranskat)abstract
- We analyze the convergence of quasi-Newton methods in exact and finite precision arithmetic using three different techniques. We derive an upper bound for the stagnation level and we show that any sufficiently exact quasi-Newton method will converge quadratically until stagnation. In the absence of sufficient accuracy, we are likely to retain rapid linear convergence. We confirm our analysis by computing square roots and solving bond constraint equations in the context of molecular dynamics. In particular, we apply both a symmetric variant and Forsgren's variant of the simplified Newton method. This work has implications for the implementation of quasi-Newton methods regardless of the scale of the calculation or the machine.
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| 8. |
- Luan, Siyu, et al.
(författare)
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LRP-based network pruning and policy distillation of robust and non-robust DRL agents for embedded systems
- 2023
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Ingår i: Concurrency and Computation. - : John Wiley & Sons. - 1532-0626 .- 1532-0634. ; 35:19
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Tidskriftsartikel (refereegranskat)abstract
- Reinforcement learning (RL) is an effective approach to developing control policies by maximizing the agent's reward. Deep reinforcement learning uses deep neural networks (DNNs) for function approximation in RL, and has achieved tremendous success in recent years. Large DNNs often incur significant memory size and computational overheads, which may impede their deployment into resource-constrained embedded systems. For deployment of a trained RL agent on embedded systems, it is necessary to compress the policy network of the RL agent to improve its memory and computation efficiency. In this article, we perform model compression of the policy network of an RL agent by leveraging the relevance scores computed by layer-wise relevance propagation (LRP), a technique for Explainable AI (XAI), to rank and prune the convolutional filters in the policy network, combined with fine-tuning with policy distillation. Performance evaluation based on several Atari games indicates that our proposed approach is effective in reducing model size and inference time of RL agents. We also consider robust RL agents trained with RADIAL-RL versus standard RL agents, and show that a robust RL agent can achieve better performance (higher average reward) after pruning than a standard RL agent for different attack strengths and pruning rates.
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| 9. |
- Myllykoski, Mirko, 1988-, et al.
(författare)
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Task‐based, GPU‐accelerated and robust library for solving dense nonsymmetric eigenvalue problems
- 2021
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Ingår i: Concurrency and Computation. - : John Wiley & Sons. - 1532-0626 .- 1532-0634. ; 33:11
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we present the StarNEig library for solving dense nonsymmetric standard and generalized eigenvalue problems. The library is built on top of the StarPU runtime system and targets both shared and distributed memory machines. Some components of the library have support for GPU acceleration. The library currently applies to real matrices with real and complex eigenvalues and all calculations are done using real arithmetic. Support for complex matrices is planned for a future release. This paper is aimed at potential users of the library. We describe the design choices and capabilities of the library, and contrast them to existing software such as LAPACK and ScaLAPACK. StarNEig implements a ScaLAPACK compatibility layer which should assist new users in the transition to StarNEig. We demonstrate the performance of the library with a sample of computational experiments.
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| 10. |
- Shirinbab, Sogand, et al.
(författare)
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Performance evaluation of containers and virtual machines when running Cassandra workload concurrently
- 2020
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Ingår i: Concurrency and Computation. - : Wiley-Blackwell. - 1532-0626 .- 1532-0634. ; 32:17
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Tidskriftsartikel (refereegranskat)abstract
- NoSQL distributed databases are often used as Big Data platforms. To provide efficient resource sharing and cost effectiveness, such distributed databases typically run concurrently on a virtualized infrastructure that could be implemented using hypervisor-based virtualization or container-based virtualization. Hypervisor-based virtualization is a mature technology but imposes overhead on CPU, networking, and disk. Recently, by sharing the operating system resources and simplifying the deployment of applications, container-based virtualization is getting more popular. This article presents a performance comparison between multiple instances of VMware VMs and Docker containers running concurrently. Our workload models a real-world Big Data Apache Cassandra application from Ericsson. As a baseline, we evaluated the performance of Cassandra when running on the nonvirtualized physical infrastructure. Our study shows that Docker has lower overhead compared with VMware; the performance on the container-based infrastructure was as good as on the nonvirtualized. Our performance evaluations also show that running multiple instances of a Cassandra database concurrently affected the performance of read and write operations differently; for both VMware and Docker, the maximum number of read operations was reduced when we ran several instances concurrently, whereas the maximum number of write operations increased when we ran instances concurrently.
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