Mapping Algorithms Optimizing the Overall Manhattan Distance for Pre-Occupied Cluster Computers in SLA-Based Grid Environments

The problems of mapping and load balancing applications on arbitrary networks are considered. A novel diffusion algorithm is presented to solve the mapping problem. It complements the well known diffusion algorithms for load balancing which have enjoyed success on massively parallel computers (MPPs). Mapping is more difficult on interconnection networks than on MPPs because of the variations which occur in network topology. Popular mapping algorithms for MPPs which depend on recursive topologies are not applicable to irregular networks. The most celebrated of these MPP algorithms use information from the Laplacian matrix of a graph of communicating processes. The diffusion algorithm presented in this paper is also derived from this Laplacian matrix. The diffusion algorithm works on arbitrary network topologies and is dramatically faster than the celebrated MPP algorithms. It is delay and fault tolerant. Time to convergence depends on initial conditions and is insensitive to problem scale. This excellent scalability, among other features, makes the diffusion algorithm a viable candidate for dynamically mapping and load balancing not only existing MPP systems but also large distributed systems like the Internet, small cluster computers, and networks of workstations.

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Cloud-integrated wireless-optical broadband access network with survivability

International Journal of Sensors Wireless Communications and Control ◽

10.2174/2210327910666200213121623 ◽

2020 ◽

Vol 10 ◽

Author(s):

Sangita Solanki ◽

Raksha Upadhyay ◽

Uma Rathore Bhatt

Keyword(s):

Access Network ◽

Access Networks ◽

Manhattan Distance ◽

Broadband Access ◽

Optical Access Networks ◽

Component Level ◽

Backup Path ◽

Wireless Router ◽

Path Computation ◽

Broadband Access Network

Cloud-integrated wireless optical broadband (CIW) access networks inheriting advantages of cloud computing, wireless and optical access networks have a broad prospect in the future. Due to failure of components like OLT level, ONU level, link or path failure and cloud component level in CIW, survivability is becoming one of the important issues. In this paper, we have presented cloud-integrated wireless-optical broadband access network with survivability using integer linear programming (ILP) model, to minimize the number of cloud components while providing maximum backup paths. Hence, we have proposed protection through cloud-integrated wireless router to available ONUs (PCIWRAO). So, evaluated the backup path computation. We have considered ONU level failure in which the affected traffic is transferred through wireless routers and cloud component to the available ONUs using Manhattan distance algorithm. Simulation results show different configurations for different number of routers and cloud components illustrating available backup path when ONU fails.

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Hybrid Deep Neural Model for Duplicate Question Detection in Transliterated Bi-lingual Data

Recent Patents on Computer Science ◽

10.2174/2213275912666190710152709 ◽

2019 ◽

Vol 12 ◽

Author(s):

Seema Rani ◽

Avadhesh Kumar ◽

Naresh Kumar

Keyword(s):

Question Answering ◽

Neural Model ◽

Manhattan Distance ◽

Semantic Matching ◽

English Only ◽

Detection Model ◽

Proposed Model ◽

Reported Study ◽

Social Media Platforms ◽

Efficient Information

Background: Duplicate content often corrupts the filtering mechanism in online question answering. Moreover, as users are usually more comfortable conversing in their native language questions, transliteration adds to the challenges in detecting duplicate questions. This compromises with the response time and increases the answer overload. Thus, it has now become crucial to build clever, intelligent and semantic filters which semantically match linguistically disparate questions. Objective: Most of the research on duplicate question detection has been done on mono-lingual, majorly English Q&A platforms. The aim is to build a model which extends the cognitive capabilities of machines to interpret, comprehend and learn features for semantic matching in transliterated bi-lingual Hinglish (Hindi + English) data acquired from different Q&A platforms. Method: In the proposed DQDHinglish (Duplicate Question Detection) Model, firstly language transformation (transliteration & translation) is done to convert the bi-lingual transliterated question into a mono-lingual English only text. Next a hybrid of Siamese neural network containing two identical Long-term-Short-memory (LSTM) models and Multi-layer perceptron network is proposed to detect semantically similar question pairs. Manhattan distance function is used as the similarity measure. Result: A dataset was prepared by scrapping 100 question pairs from various social media platforms, such as Quora and TripAdvisor. The performance of the proposed model on the basis of accuracy and F-score. The proposed DQDHinglish achieves a validation accuracy of 82.40%. Conclusion: A deep neural model was introduced to find semantic match between English question and a Hinglish (Hindi + English) question such that similar intent questions can be combined to enable fast and efficient information processing and delivery. A dataset was created and the proposed model was evaluated on the basis of performance accuracy. To the best of our knowledge, this work is the first reported study on transliterated Hinglish semantic question matching.

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Parallel Network Mapping Algorithms

Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures ◽

10.1145/3409964.3461822 ◽

2021 ◽

Author(s):

Ramtin Afshar ◽

Michael T. Goodrich ◽

Pedro Matias ◽

Martha C. Osegueda

Keyword(s):

Mapping Algorithms ◽

Parallel Network ◽

Network Mapping

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An Energy Efficient Authentication Scheme based on Chebyshev Chaotic Map for Smart Grid Environments

IEEE Internet of Things Journal ◽

10.1109/jiot.2021.3078175 ◽

2021 ◽

pp. 1-1

Author(s):

Liping Zhang ◽

Yue Zhu ◽

Wei Ren ◽

Yinghan Wang ◽

Kim-Kwang Raymond Choo ◽

...

Keyword(s):

Smart Grid ◽

Energy Efficient ◽

Chaotic Map ◽

Authentication Scheme ◽

Chebyshev Chaotic Map ◽

Grid Environments

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An Automatic Aggregator of Power Flexibility in Smart Buildings Using Software Based Orchestration

Sensors ◽

10.3390/s21030867 ◽

2021 ◽

Vol 21 (3) ◽

pp. 867

Author(s):

Dharmendra Sharma ◽

Jari Rehu ◽

Klaus Känsälä ◽

Heikki Ailisto

Keyword(s):

Control Signal ◽

External Control ◽

Data Logging ◽

Building Energy Management ◽

Hardware System ◽

Temperature Thresholds ◽

Grid Environments ◽

End Use ◽

Maintenance Requirements ◽

Control And Management

This paper presents a software-based modular and hierarchical building energy management system (BEMS) to control the power consumption in sensor-equipped buildings. In addition, the need of this type of solution is also highlighted by presenting the worldwide trends of thermal energy end use in buildings and peak power problems. Buildings are critical component of smart grid environments and bottom-up BEMS solutions are need of the hour to optimize the consumption and to provide consumption side flexibility. This system is able to aggregate the controls of the all-controllable resources in building to realize its flexible power capacity. This system provides a solution for consumer to aggregate the controls of ‘behind-the-meter’ small loads in short response and provide ‘deep’ demand-side flexibility. This system is capable of discovery, status check, control and management of networked loads. The main novelty of this solution is that it can handle the heterogeneity of the installed hardware system along with time bound changes in the load device network and its scalability; resulting in low maintenance requirements after deployment. The control execution latency (including data logging) of this BEMS system for an external control signal is less than one second per connected load. In addition, the system is capable of overriding the external control signal in order to maintain consumer coziness within the comfort temperature thresholds. This system provides a way forward in future for the estimation of the energy stored in the buildings in the form of heat/temperature and use buildings as temporary batteries when electricity supply is constrained or abundant.

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Using cluster computers in bioinformatics research

Journal of Shanghai University (English Edition) ◽

10.1007/s11741-003-0012-0 ◽

2003 ◽

Vol 7 (4) ◽

pp. 370-374

Author(s):

Ckeng Zhou ◽

Song-Nian Yu

Keyword(s):

Cluster Computers

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A Numerical Study of Fluid Structure Interaction of a Flexible Submerged Cylinder Mounted on an Experimental Rig

Volume 7: Ocean Engineering ◽

10.1115/omae2015-42219 ◽

2015 ◽

Author(s):

Erkan Cakir ◽

Ayhan Akinturk ◽

Alejandro Allievi

Keyword(s):

Numerical Study ◽

Coupled Analysis ◽

Mapping Algorithms ◽

Automatic Mapping ◽

Structural Responses ◽

Submerged Cylinder ◽

Physics Model ◽

System Coupling ◽

Force Data ◽

Experimental Rig

The aim of the study is to investigate VIV effects, not only on a test cylinder but also on the experimental rig being towed under water at a prescribed depth and operating speeds. For this purpose, a numerical Multi-Physics model was created using one way coupled analysis simultaneously between the Mechanical and Fluent solvers of ANSYS software package. A system coupling was developed in order to communicate force data alternately between the solvers with the help of automatic mapping algorithms within millesimal time periods of a second. Numerical investigation into the dynamic characteristics of pressure and velocity fields for turbulent viscous fluid flow along with structural responses of the system, stressed the significance of time and space scales for convergence and accuracy of our Finite Volume (FV) CFD calculations.

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