scholarly journals Design and evaluation of a biologically-inspired cloud elasticity framework

2020 ◽  
Vol 23 (4) ◽  
pp. 3095-3117
Author(s):  
Amjad Ullah ◽  
Jingpeng Li ◽  
Amir Hussain
Keyword(s):  
Fuzzy System ◽  
State Of The Art ◽  
The State ◽  
Effective Management ◽  
Biologically Inspired ◽  
Computational Overhead ◽  
Cloud Elasticity ◽  
Computational Resources ◽  
Auto Scaling ◽  
Selection Of

Abstract The elasticity in cloud is essential to the effective management of computational resources as it enables readjustment at runtime to meet application demands. Over the years, researchers and practitioners have proposed many auto-scaling solutions using versatile techniques ranging from simple if-then-else based rules to sophisticated optimisation, control theory and machine learning based methods. However, despite an extensive range of existing elasticity research, the aim of implementing an efficient scaling technique that satisfies the actual demands is still a challenge to achieve. The existing methods suffer from issues like: (1) the lack of adaptability and static scaling behaviour whilst considering completely fixed approaches; (2) the burden of additional computational overhead, the inability to cope with the sudden changes in the workload behaviour and the preference of adaptability over reliability at runtime whilst considering the fully dynamic approaches; and (3) the lack of considering uncertainty aspects while designing auto-scaling solutions. In this paper, we aim to address these issues using a holistic biologically-inspired feedback switch controller. This method utilises multiple controllers and a switching mechanism, implemented using fuzzy system, that realises the selection of suitable controller at runtime. The fuzzy system also facilitates the design of qualitative elasticity rules. Furthermore, to improve the possibility of avoiding the oscillatory behaviour (a problem commonly associated with switch methodologies), this paper integrates a biologically-inspired computational model of action selection. Lastly, we identify seven different kinds of real workload patterns and utilise them to evaluate the performance of the proposed method against the state-of-the-art approaches. The obtained computational results demonstrate that the proposed method results in achieving better performance without incurring any additional cost in comparison to the state-of-the-art approaches.

Accelerating Mobile-Cloud Computing

2015 ◽  
pp. 1933-1955
Author(s):  
Tolga Soyata ◽  
He Ba ◽  
Wendi Heinzelman ◽  
Minseok Kwon ◽  
Jiye Shi
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
High Speed ◽  
Mobile Cloud Computing ◽  
Response Times ◽  
State Of The Art ◽  
The State ◽  
Mobile Cloud ◽  
Computational Resources ◽  
Traditional Approaches

With the recent advances in cloud computing and the capabilities of mobile devices, the state-of-the-art of mobile computing is at an inflection point, where compute-intensive applications can now run on today's mobile devices with limited computational capabilities. This is achieved by using the communications capabilities of mobile devices to establish high-speed connections to vast computational resources located in the cloud. While the execution scheme based on this mobile-cloud collaboration opens the door to many applications that can tolerate response times on the order of seconds and minutes, it proves to be an inadequate platform for running applications demanding real-time response within a fraction of a second. In this chapter, the authors describe the state-of-the-art in mobile-cloud computing as well as the challenges faced by traditional approaches in terms of their latency and energy efficiency. They also introduce the use of cloudlets as an approach for extending the utility of mobile-cloud computing by providing compute and storage resources accessible at the edge of the network, both for end processing of applications as well as for managing the distribution of applications to other distributed compute resources.

scholarly journals 3D Printing in Heterogeneous Catalysis—The State of the Art

Materials ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 4534 ◽  
Author(s):  
Elżbieta Bogdan ◽  
Piotr Michorczyk
Keyword(s):  
Additive Manufacturing ◽  
Heterogeneous Catalysis ◽  
3D Printing ◽  
Chemical Synthesis ◽  
State Of The Art ◽  
Three Dimensional ◽  
Production Method ◽  
The State ◽  
Monolithic Catalysts ◽  
Selection Of

This paper describes the process of additive manufacturing and a selection of three-dimensional (3D) printing methods which have applications in chemical synthesis, specifically for the production of monolithic catalysts. A review was conducted on reference literature for 3D printing applications in the field of catalysis. It was proven that 3D printing is a promising production method for catalysts.

scholarly journals Incremental predictive clustering trees for online semi-supervised multi-target regression

2020 ◽  
Vol 109 (11) ◽  
pp. 2121-2139
Author(s):  
Aljaž Osojnik ◽  
Panče Panov ◽  
Sašo Džeroski
Keyword(s):  
State Of The Art ◽  
Predictive Performance ◽  
The State ◽  
High Frequencies ◽  
Comparable Performance ◽  
Tree Methods ◽  
Online Setting ◽  
Computational Resources ◽  
Good Predictive Performance ◽  
Predictive Clustering Trees

Abstract In many application settings, labeling data examples is a costly endeavor, while unlabeled examples are abundant and cheap to produce. Labeling examples can be particularly problematic in an online setting, where there can be arbitrarily many examples that arrive at high frequencies. It is also problematic when we need to predict complex values (e.g., multiple real values), a task that has started receiving considerable attention, but mostly in the batch setting. In this paper, we propose a method for online semi-supervised multi-target regression. It is based on incremental trees for multi-target regression and the predictive clustering framework. Furthermore, it utilizes unlabeled examples to improve its predictive performance as compared to using just the labeled examples. We compare the proposed iSOUP-PCT method with supervised tree methods, which do not use unlabeled examples, and to an oracle method, which uses unlabeled examples as though they were labeled. Additionally, we compare the proposed method to the available state-of-the-art methods. The method achieves good predictive performance on account of increased consumption of computational resources as compared to its supervised variant. The proposed method also beats the state-of-the-art in the case of very few labeled examples in terms of performance, while achieving comparable performance when the labeled examples are more common.

scholarly journals Generating Multiple Diverse Responses with Multi-Mapping and Posterior Mapping Selection

2019 ◽  
Author(s):  
Chaotao Chen ◽  
Jinhua Peng ◽  
Fan Wang ◽  
Jun Xu ◽  
Hua Wu
Keyword(s):  
State Of The Art ◽  
The State ◽  
Target Response ◽  
Empirical Results ◽  
Art Methods ◽  
Mapping Mechanism ◽  
The One ◽  
Selection Of

In human conversation an input post is open to multiple potential responses, which is typically regarded as a one-to-many problem. Promising approaches mainly incorporate multiple latent mechanisms to build the one-to-many relationship. However, without accurate selection of the latent mechanism corresponding to the target response during training, these methods suffer from a rough optimization of latent mechanisms. In this paper, we propose a multi-mapping mechanism to better capture the one-to-many relationship, where multiple mapping modules are employed as latent mechanisms to model the semantic mappings from an input post to its diverse responses. For accurate optimization of latent mechanisms, a posterior mapping selection module is designed to select the corresponding mapping module according to the target response for further optimization. We also introduce an auxiliary matching loss to facilitate the optimization of posterior mapping selection. Empirical results demonstrate the superiority of our model in generating multiple diverse and informative responses over the state-of-the-art methods.

Ensuring Food Security in the Context of the Development of Integration Processes

2019 ◽  
Vol 9 (5) ◽  
pp. 1120
Author(s):  
Saniya SAGINOVA ◽  
Rauza ABELDINA ◽  
Valeriy BIRYUKOV ◽  
Gulnar SAPAROVA ◽  
Alken TEMIRBULATOV ◽  
...  
Keyword(s):  
Economic Policy ◽  
Food Security ◽  
Food System ◽  
Statistical Data ◽  
The State ◽  
Important Task ◽  
Effective Management ◽  
Food Market ◽  
The Republic ◽  
Selection Of

Food security is one of the main objectives of the agrarian and economic policy of the state. In its general form, it forms the vector of movement of any national food system to an ideal state. Analysis of indicators of the state of the food market and the provision of the population with food, the selection of the most optimal of them for making effective management decisions is an important task in developing a strategy for ensuring the country's food security. Therefore, the purpose of this article is to assess food security in the Republic of Kazakhstan. The article analyses the statistical data of the Republic of Kazakhstan on ensuring food security in the country.

scholarly journals Speeding Up Incomplete GDL-based Algorithms for Multi-agent Optimization with Dense Local Utilities

2020 ◽  
Author(s):  
Yanchen Deng ◽  
Bo An
Keyword(s):  
Utility Function ◽  
Branch And Bound ◽  
State Of The Art ◽  
Search Space ◽  
Computational Effort ◽  
The State ◽  
Computational Overhead ◽  
Multi Agent

Incomplete GDL-based algorithms including Max-sum and its variants are important methods for multi-agent optimization. However, they face a significant scalability challenge as the computational overhead grows exponentially with respect to the arity of each utility function. Generic Domain Pruning (GDP) technique reduces the computational effort by performing a one-shot pruning to filter out suboptimal entries. Unfortunately, GDP could perform poorly when dealing with dense local utilities and ties which widely exist in many domains. In this paper, we present several novel sorting-based acceleration algorithms by alleviating the effect of densely distributed local utilities. Specifically, instead of one-shot pruning in GDP, we propose to integrate both search and pruning to iteratively reduce the search space. Besides, we cope with the utility ties by organizing the search space of tied utilities into AND/OR trees to enable branch-and-bound. Finally, we propose a discretization mechanism to offer a tradeoff between the reconstruction overhead and the pruning efficiency. We demonstrate the superiorities of our algorithms over the state-of-the-art from both theoretical and experimental perspectives.

Vibration Confinement via Optimal Eigenvector Assignment and Piezoelectric Networks

2001 ◽  
Author(s):  
J. Tang ◽  
K. W. Wang
Keyword(s):  
Design Space ◽  
State Of The Art ◽  
The State ◽  
Regions Of Interest ◽  
Control Input ◽  
Eigenstructure Assignment ◽  
Assignment Algorithm ◽  
Underlying Principle ◽  
Rayleigh Principle ◽  
Selection Of

Abstract The underlying principle for vibration confinement is to alter the structural modes so that the corresponding modal components have much smaller amplitude in concerned areas than the remaining part of the structure. In this research, the state-of-the-art in vibration confinement technique is advanced in two correlated ways. First, a new eigenstructure assignment algorithm is developed to more directly suppress vibration in regions of interest. This algorithm is featured by the optimal selection of achievable eigenvectors that minimizes the eigenvector components at concerned areas by using the Rayleigh Principle. Second, the active control input is applied through an active-passive hybrid piezoelectric network. With the introduction of circuitry elements, which is much easier to implement than changing or adding mechanical components, the state matrices can be reformed and the design space in eigenstructure assignment can be greatly enlarged. The merit of the proposed system and scheme is demonstrated and analyzed using a numerical example.

A Simplistic Approach for Lightweight Multi-Agent SLAM Algorithm

2020 ◽  
Vol 11 (3) ◽  
pp. 67-83
Author(s):  
Anton Filatov ◽  
Kirill Krinkin
Keyword(s):  
State Of The Art ◽  
Simultaneous Localization And Mapping ◽  
The State ◽  
Limited Resources ◽  
Challenging Problem ◽  
Multiple Agents ◽  
Localization And Mapping ◽  
Multi Agent ◽  
Slam Algorithm ◽  
Computational Resources

Limitation of computational resources is a challenging problem for moving agents that launch such algorithms as simultaneous localization and mapping (SLAM). To increase the accuracy on limited resources one may add more computing agents that might explore the environment quicker than one and thus to decrease the load of each agent. In this article, the state-of-the-art in multi-agent SLAM algorithms is presented, and an approach that extends laser 2D single hypothesis SLAM for multiple agents is introduced. The article contains a description of problems that are faced in front of a developer of such approach including questions about map merging, relative pose calculation, and roles of agents.

scholarly journals LEAP: A Generalization of the Landau-Vishkin Algorithm with Custom Gap Penalties

2017 ◽  
Author(s):  
Hongyi Xin ◽  
Jeremie Kim ◽  
Sunny Nahar ◽  
Can Alkan ◽  
Onur Mutlu
Keyword(s):  
State Of The Art ◽  
String Matching ◽  
The State ◽  
Levenshtein Distance ◽  
Approximate String Matching ◽  
Matching Problem ◽  
De Bruijn Sequence ◽  
Scoring Schemes ◽  
Bit Vector ◽  
Selection Of

AbstractMotivationApproximate String Matching is a pivotal problem in the field of computer science. It serves as an integral component for many string algorithms, most notably, DNA read mapping and alignment. The improved LV algorithm proposes an improved dynamic programming strategy over the banded Smith-Waterman algorithm but suffers from support of a limited selection of scoring schemes. In this paper, we propose the Leaping Toad problem, a generalization of the approximate string matching problem, as well as LEAP, a generalization of the Landau-Vishkin’s algorithm that solves the Leaping Toad problem under a broader selection of scoring schemes.ResultsWe benchmarked LEAP against 3 state-of-the-art approximate string matching implementations. We show that when using a bit-vectorized de Bruijn sequence based optimization, LEAP is up to 7.4x faster than the state-of-the-art bit-vector Levenshtein distance implementation and up to 32x faster than the state-of-the-art affine-gap-penalty parallel Needleman Wunsch Implementation.AvailabilityWe provide an implementation of LEAP in C++ at github.com/CMU-SAFARI/[email protected], [email protected] or [email protected]

Accelerating Mobile-Cloud Computing

2013 ◽  
pp. 175-197 ◽  
Author(s):  
Tolga Soyata ◽  
He Ba ◽  
Wendi Heinzelman ◽  
Minseok Kwon ◽  
Jiye Shi
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
High Speed ◽  
Mobile Cloud Computing ◽  
Response Times ◽  
State Of The Art ◽  
The State ◽  
Mobile Cloud ◽  
Computational Resources ◽  
Traditional Approaches

With the recent advances in cloud computing and the capabilities of mobile devices, the state-of-the-art of mobile computing is at an inflection point, where compute-intensive applications can now run on today’s mobile devices with limited computational capabilities. This is achieved by using the communications capabilities of mobile devices to establish high-speed connections to vast computational resources located in the cloud. While the execution scheme based on this mobile-cloud collaboration opens the door to many applications that can tolerate response times on the order of seconds and minutes, it proves to be an inadequate platform for running applications demanding real-time response within a fraction of a second. In this chapter, the authors describe the state-of-the-art in mobile-cloud computing as well as the challenges faced by traditional approaches in terms of their latency and energy efficiency. They also introduce the use of cloudlets as an approach for extending the utility of mobile-cloud computing by providing compute and storage resources accessible at the edge of the network, both for end processing of applications as well as for managing the distribution of applications to other distributed compute resources.

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