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Journal articles on the topic 'Distributed Selection Schemes'

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Published: 6 September 2023

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1

WEI, DAVID S. L., SANGUTHEVAR RAJASEKARAN, KSHIRASAGAR NAIK, and SY-YEN KUO. "EFFICIENT ALGORITHMS FOR SELECTION AND SORTING OF LARGE DISTRIBUTED FILES ON DE BRUIJN AND HYPERCUBE STRUCTURES." International Journal of Foundations of Computer Science 14, no. 06 (December 2003): 1129–46. http://dx.doi.org/10.1142/s0129054103002229.

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In this paper we show the power of sampling techniques in designing efficient distributed algorithms. In particular, we apply sampling techniques in the design of selection algorithms on the hypercube and de Bruijn networks, and show that the message complexity of selecting an item from a set (file) is less sensitive to the cardinality of the set (file). Given a file with n keys, our algorithm performs a selection on a p-node de Bruijn network or hypercube using only O(p log log n) messages and suffering a delay of O(τ log p log log n), with high probability. Our selection scheme outperforms the existing approaches in terms of both message complexity and communication delay. Because of the lesser sensitivity of message complexity and communication delay of our algorithms to the file size, our distributed selection schemes are very attractive in applications where very large database systems are involved. Using our selection algorithms, we also show that both quicksort-based sorting scheme and enumeration sorting scheme can be developed for sorting large distributed files on the hypercube and de Bruijn networks. Both of our sorting algorithms outperform the existing distributed sorting schemes in terms of both message complexity and communication delay.
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Zhang, Yang, Wei Wang, Xiangmo Zhao, and Jun Hou. "Distributed Antenna-and-Relay Selection Schemes for MIMO Cooperative Relay Network." Wireless Communications and Mobile Computing 2022 (July 13, 2022): 1–12. http://dx.doi.org/10.1155/2022/8729079.

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Relay selection, antenna selection, and link selection are three potent means to enrich network capacity in MIMO relaying networks. To reduce feedback overhead, in this paper, three distributed antenna-and-relay selection schemes are proposed for AF multiple-relay network, which is equipped with multiple antennas at nodes. Closed-form formulations of system outage probability are derived for these schemes, as well as the lower bounds and upper bounds. Furthermore, the approximate expressions of outage probability at high SNR regime are also derived, showing that the proposed optimal strategy can achieve full diversity order. In addition, link selection scheme can improve spectral efficiency since it saves one time slot when direct link is selected.
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Wen, Yong-Kui, and Li-Min Sun. "Distributed ATMD for Buffeting Control of Cable-Stayed Bridges Under Construction." International Journal of Structural Stability and Dynamics 15, no. 03 (March 8, 2015): 1450054. http://dx.doi.org/10.1142/s0219455414500540.

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This paper is concerned with mitigating multimode buffeting of cable-stayed bridges by optimizing the placements of active tuned mass dampers (ATMDs) and sensors and developing a control model and schemes. The Third Nanjing Bridge over the Yangtze River was used to formulate a mathematical control model with distributed ATMDs under wind action. Hankel norms were combined with structural mode analysis to build placement indices of the ATMDs and sensors under a defined objective while considering the influence of exterior excitation. A selection index of modes was proposed. ATMD/sensor placement on the Third Nanjing Bridge and mode selection were simulated to determine the wind response control. A control design model with accurate mode selection was developed using modal superposition and it was used to investigate control schemes of distributed ATMDs for buffeting response control of the cable-stayed bridge. The results showed that the dynamic characteristics of the developed control design model agreed well with those of the original system model. Control scheme selection depends on the tradeoff between the control objective and actuator performance. Considering realistic engineering constraints, the distributed ATMDs are shown to perform well.
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Etezadi, Farrokh, Keyvan Zarifi, Ali Ghrayeb, and Sofiene Affes. "Decentralized Relay Selection Schemes in Uniformly Distributed Wireless Sensor Networks." IEEE Transactions on Wireless Communications 11, no. 3 (March 2012): 938–51. http://dx.doi.org/10.1109/twc.2012.010312.101314.

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Salama, Ahmed M., Islam Samy, Ahmed El Shafie, Amr Mohamed, and Tamer Khattab. "Centralized and Distributed Cognitive Relay-Selection Schemes for SWIPT Cognitive Networks." IEEE Transactions on Communications 67, no. 11 (November 2019): 7431–43. http://dx.doi.org/10.1109/tcomm.2019.2936562.

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Lee, Jaehwan, Hyeonseong Choi, Hyeonwoo Jeong, Baekhyeon Noh, and Ji Sun Shin. "Communication Optimization Schemes for Accelerating Distributed Deep Learning Systems." Applied Sciences 10, no. 24 (December 10, 2020): 8846. http://dx.doi.org/10.3390/app10248846.

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In a distributed deep learning system, a parameter server and workers must communicate to exchange gradients and parameters, and the communication cost increases as the number of workers increases. This paper presents a communication data optimization scheme to mitigate the decrease in throughput due to communication performance bottlenecks in distributed deep learning. To optimize communication, we propose two methods. The first is a layer dropping scheme to reduce communication data. The layer dropping scheme we propose compares the representative values of each hidden layer with a threshold value. Furthermore, to guarantee the training accuracy, we store the gradients that are not transmitted to the parameter server in the worker’s local cache. When the value of gradients stored in the worker’s local cache is greater than the threshold, the gradients stored in the worker’s local cache are transmitted to the parameter server. The second is an efficient threshold selection method. Our threshold selection method computes the threshold by replacing the gradients with the L1 norm of each hidden layer. Our data optimization scheme reduces the communication time by about 81% and the total training time by about 70% in a 56 Gbit network environment.
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Park, Jinho, and Kwangsue Chung. "Distributed DRL-Based Computation Offloading Scheme for Improving QoE in Edge Computing Environments." Sensors 23, no. 8 (April 21, 2023): 4166. http://dx.doi.org/10.3390/s23084166.

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Various edge collaboration schemes that rely on reinforcement learning (RL) have been proposed to improve the quality of experience (QoE). Deep RL (DRL) maximizes cumulative rewards through large-scale exploration and exploitation. However, the existing DRL schemes do not consider the temporal states using a fully connected layer. Moreover, they learn the offloading policy regardless of the importance of experience. They also do not learn enough because of their limited experiences in distributed environments. To solve these problems, we proposed a distributed DRL-based computation offloading scheme for improving the QoE in edge computing environments. The proposed scheme selects the offloading target by modeling the task service time and load balance. We implemented three methods to improve the learning performance. Firstly, the DRL scheme used the least absolute shrinkage and selection operator (LASSO) regression and attention layer to consider the temporal states. Secondly, we learned the optimal policy based on the importance of experience using the TD error and loss of the critic network. Finally, we adaptively shared the experience between agents, based on the strategy gradient, to solve the data sparsity problem. The simulation results showed that the proposed scheme achieved lower variation and higher rewards than the existing schemes.
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Ge, L., G. J. Chen, and J. A. Chambers. "Relay Selection in Distributed Transmission Based on the Golden Code Using ML and Sphere Decoding in Wireless Networks." International Journal of Information Technology and Web Engineering 6, no. 4 (October 2011): 63–75. http://dx.doi.org/10.4018/jitwe.2011100105.

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The implementation of cooperative diversity with relays has advantages over point-to-point multiple-input multiple-output (MIMO) systems, in particular, overcoming correlated paths due to small inter-element spacing. A simple transmitter with one antenna may exploit cooperative diversity or space time coding gain through distributed relays. In this paper, similar distributed transmission is considered with the golden code, and the authors propose a new strategy for relay selection, called the maximum-mean selection policy, for distributed transmission with the full maximum-likelihood (ML) decoding and sphere decoding (SD) based on a wireless relay network. This strategy performs a channel strength tradeoff at every relay node to select the best two relays for transmission. It improves on the established one-sided selection strategy of maximum-minimum policy. Simulation results comparing the bit error rate (BER) based on different detectors and a scheme without relay selection, with the maximum-minimum and maximum-mean selection schemes confirm the performance advantage of relay selection. The proposed strategy yields the best performance of the three methods.
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9

Ma, Bo, Jianhua Ge, Weiliang Han, and Jing Li. "Auction-Based Pricing Schemes for Distributed Partner Selection in Cooperative Wireless Networks." Wireless Personal Communications 96, no. 1 (May 5, 2017): 265–90. http://dx.doi.org/10.1007/s11277-017-4166-7.

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10

Wei, David S. L., Sanguthevar Rajasekaran, Z. Cheng, K. Naik, and Sy-Yen Kuo. "Efficient Selection and Sorting Schemes Using Coteries for Processing Large Distributed Files." Journal of Parallel and Distributed Computing 62, no. 8 (August 2002): 1295–313. http://dx.doi.org/10.1006/jpdc.2002.1861.

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11

Abdulhadi, S., M. Jaseemuddin, and A. Anpalagan. "A Survey of Distributed Relay Selection Schemes in Cooperative Wireless Ad hoc Networks." Wireless Personal Communications 63, no. 4 (November 15, 2010): 917–35. http://dx.doi.org/10.1007/s11277-010-0174-6.

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12

Ding, Haiyang, Jianhua Ge, Daniel Benevides da Costa, and Zhuoqin Jiang. "Link Selection Schemes for Selection Relaying Systems With Transmit Beamforming: New and Efficient Proposals From a Distributed Concept." IEEE Transactions on Vehicular Technology 61, no. 2 (February 2012): 533–52. http://dx.doi.org/10.1109/tvt.2011.2178871.

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13

Yang, Wen, and Hongbo Shi. "Sensor selection schemes for consensus based distributed estimation over energy constrained wireless sensor networks." Neurocomputing 87 (June 2012): 132–37. http://dx.doi.org/10.1016/j.neucom.2012.02.011.

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14

Song, Xiyu, Nae Zheng, and Ting Bai. "Resource Allocation Schemes for Multiple Targets Tracking in Distributed MIMO Radar Systems." International Journal of Antennas and Propagation 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/7241281.

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Considering the demands of different location accuracy for multiple targets tracking, performance-driven resource allocation schemes in distributed MIMO radar system are proposed. Restricted by the tracking antenna number, location estimation mean-square error (MSE), and target priorities, an optimization problem of the minimal antenna subsets selection is modeled as a knapsack problem. Then, two operational schemes, modified fair multistart local search (MFMLS) algorithm and modified fair multistart local search with one antenna to all targets (MFMLS_OAT) algorithm, are presented and evaluated. Simulation results indicate that the proposed MFMLS and MFMLS_OAT algorithm outperform the existing algorithms. Moreover, the MFMLS algorithm can distinguish targets with different priorities, while the MFMLS_OAT algorithm can perform the tracking tasks with higher accuracy.
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15

Sultan, Kiran, Ijaz Mansoor Qureshi, Aqdas Naveed Malik, and Muhammad Zubair. "Performance Analysis of Relay Subset Selection for Amplify-and-Forward Cognitive Relay Networks." Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/548082.

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Cooperative communication is regarded as a key technology in wireless networks, including cognitive radio networks (CRNs), which increases the diversity order of the signal to combat the unfavorable effects of the fading channels, by allowing distributed terminals to collaborate through sophisticated signal processing. Underlay CRNs have strict interference constraints towards the secondary users (SUs) active in the frequency band of the primary users (PUs), which limits their transmit power and their coverage area. Relay selection offers a potential solution to the challenges faced by underlay networks, by selecting either single best relay or a subset of potential relay set under different design requirements and assumptions. The best relay selection schemes proposed in the literature for amplify-and-forward (AF) based underlay cognitive relay networks have been very well studied in terms of outage probability (OP) and bit error rate (BER), which is deficient in multiple relay selection schemes. The novelty of this work is to study the outage behavior of multiple relay selection in the underlay CRN and derive the closed-form expressions for the OP and BER through cumulative distribution function (CDF) of the SNR received at the destination. The effectiveness of relay subset selection is shown through simulation results.
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16

Ouyang, Yu Hua, and Xiang Dong Jia. "Study on the Nth Best Relay Selection over Nakagami-m Fading Channels." Applied Mechanics and Materials 347-350 (August 2013): 1561–65. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.1561.

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We study the Nth best relay selection schemes over independent and non-identically distributed (i.ni.d) Nakagami-m fading channels. For such opportunistic relaying schemes, we first obtain the closed-form expressions to the probability density function (PDF) and cumulative distribution function (CDF) of the instantaneous end-to-end signal-to-noise ratio (SNR). Then, with the obtained CDF and PDF, three main measurements are investigated, i.e., outage probability, average symbol error ratio (SER), and ergodic capacity. The numerical results show that the simulations match derivations exactly.
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17

Asad, Muhammad, Saima Shaukat, Dou Hu, Zekun Wang, Ehsan Javanmardi, Jin Nakazato, and Manabu Tsukada. "Limitations and Future Aspects of Communication Costs in Federated Learning: A Survey." Sensors 23, no. 17 (August 23, 2023): 7358. http://dx.doi.org/10.3390/s23177358.

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This paper explores the potential for communication-efficient federated learning (FL) in modern distributed systems. FL is an emerging distributed machine learning technique that allows for the distributed training of a single machine learning model across multiple geographically distributed clients. This paper surveys the various approaches to communication-efficient FL, including model updates, compression techniques, resource management for the edge and cloud, and client selection. We also review the various optimization techniques associated with communication-efficient FL, such as compression schemes and structured updates. Finally, we highlight the current research challenges and discuss the potential future directions for communication-efficient FL.
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18

Hussain, Arif, Chul-Hwan Kim, and Arif Mehdi. "A Comprehensive Review of Intelligent Islanding Schemes and Feature Selection Techniques for Distributed Generation System." IEEE Access 9 (2021): 146603–24. http://dx.doi.org/10.1109/access.2021.3123382.

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19

Kim, Seong-Cheol, Papia Ray, and Surender Reddy Salkuti. "Islanding detection in a distribution network with distributed generators using signal processing techniques." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 4 (December 1, 2020): 2099. http://dx.doi.org/10.11591/ijpeds.v11.i4.pp2099-2106.

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This paper proposes quick & accurate islanding detection technique for a distribution system with distributed generators (DGs). Here two schemes of islanding detection based on signal processing is proposed of which one is based on discrete wavelet transform (DWT) with artificial neural network (ANN), and another one is based on S-transform with ANN. The negative sequence current/voltage signals are retrieved at targeted DG location which are used for islanding detection in the distribution system. Here, the wavelet and S-transforms are used for fault location and classification applications. Further, the feature extraction is used for reducing the size of data matrix by transforming it into set of features. In this work, particle swarm optimization (PSO) based feature selection scheme is applied. Simulation results on test system indicate the efficacy of proposed islanding detection techniques.
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Xie, Xueqing, and Ming He. "Smart City Facility Location Recommendation Algorithm Using Multimedia Data and Improved Generative Adversarial Networks." International Journal of Intelligent Systems 2023 (July 15, 2023): 1–13. http://dx.doi.org/10.1155/2023/6664219.

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Internet of Things, low energy consumption, and intelligent and functionally integrated urban infrastructure construction are crucial elements in the development of smart cities. Distributed generation (DG) and electric vehicle charging infrastructure play a vital role in the planning and construction of smart cities. However, the uncertainty associated with the power output of distributed generation significantly impacts the planning of distribution networks. To address this issue, this paper proposes a site-selection recommendation algorithm that leverages urban multimedia data and improved generative adversarial networks. The proposed algorithm begins by modeling the uncertainty of wind power and photovoltaic (PV) generation using an enhanced conditional generative adversarial network model. To generate multimedia datasets with time-series characteristics for wind power and PV generation scenarios, monthly multimedia data labels are incorporated into the model. These multimedia datasets, representing a wide range of scenarios, are then clustered using the K-means clustering method. Furthermore, a distributed generation planning model is established, aiming to minimize the annual integrated cost. The planning problem is efficiently solved using CPLEX, a mathematical programming solver. In the simulation experiments, the proposed scheme is compared with alternative schemes. The results demonstrate that the proposed scheme achieves a significant total cost saving of 21.95% compared to the comparison scheme. Moreover, the experimental comparison reveals that the proposed scheme exhibits higher stability. Additionally, in terms of algorithm efficiency, the proposed algorithm outperforms the other three algorithms tested in terms of the number of iterations and speed. The experimental results highlight the effectiveness of the proposed planning model in improving the economy and stability of the distribution network. Furthermore, it enhances the computational efficiency of the planning problem associated with distributed power supply and electric vehicle charging stations. The findings of this research hold substantial research significance for the site selection planning of distributed power supply.
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KIRKPATRICK, MARK, and THOMAS BATAILLON. "Artificial selection on phenotypically plastic traits." Genetical Research 74, no. 3 (December 1999): 265–70. http://dx.doi.org/10.1017/s0016672399004115.

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Many phenotypes respond physiologically or developmentally to continuously distributed environmental variables such as temperature and nutritional quality. Information about phenotypic plasticity can be used to improve the efficiency of artificial selection. Here we show that the quantitative genetic theory for ‘infinite-dimensional’ traits such as reaction norms provides a natural framework to accomplish this goal. It is expected to improve selection responses by making more efficient use of information about environmental effects than do conventional methods. The approach is illustrated by deriving an index for mass selection of a phenotypically plastic trait. We suggest that the same approach could be extended directly to more general and efficient breeding schemes, such as those based on general best linear unbiased prediction. Methods for estimating genetic covariance functions are reviewed.
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Hu, Zhuhua, Yong Bai, Mengxing Huang, Mingshan Xie, and Yaochi Zhao. "A Self-Adaptive Progressive Support Selection Scheme for Collaborative Wideband Spectrum Sensing." Sensors 18, no. 9 (September 8, 2018): 3011. http://dx.doi.org/10.3390/s18093011.

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The sampling rate of wideband spectrum sensing for sparse signals can be reduced by sub-Nyquist sampling with a Modulated Wideband Converter (MWC). In collaborative spectrum sensing, the fusion center recovers the spectral support from observation and measurement matrices reported by a network of CRs, to improve the precision of spectrum sensing. However, the MWC has a very high hardware complexity due to its parallel structure; it sets a fixed threshold for a decision without considering the impact of noise intensity, and needs a priori information of signal sparsity order for signal support recovery. To address these shortcomings, we propose a progressive support selection based self-adaptive distributed MWC sensing scheme (PSS-SaDMWC). In the proposed scheme, the parallel hardware sensing channels are scattered on secondary users (SUs), and the PSS-SaDMWC scheme takes sparsity order estimation, noise intensity, and transmission loss into account in the fusion center. More importantly, the proposed scheme uses a support selection strategy based on a progressive operation to reduce missed detection probability under low SNR levels. Numerical simulations demonstrate that, compared with the traditional support selection schemes, our proposed scheme can achieve a higher support recovery success rate, lower sampling rate, and stronger time-varying support recovery ability without increasing hardware complexity.
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Yang, Ping, Weichao Kuang, and Shanjin Wang. "Relay Selection for Dual-Hop Cooperative Ambient Backscatter Communication Systems." Sensors 23, no. 13 (June 21, 2023): 5791. http://dx.doi.org/10.3390/s23135791.

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Previous works only focus on the optimization design for the dual-hop cooperative ambient backscatter communication (AmBC) system with single-relay selection. The impact of relay selection on the outage performance of dual-hop cooperative AmBC systems is still missing. Motivated by this, in this paper, we investigate the outage performance of a dual-hop cooperative AmBC system with single-relay selection, where the backscatter link shares the receiver with the cellular link and the harmful direct-link interference (DLI) is mitigated by using successive interference cancellation (SIC). In the system considered, the selected relay has dual functions. One is to forward message for the cellular link, and the other is to act as the radio-frequency (RF) source for the backscatter device (BD). Specifically, after proposing two novel single-relay selection schemes (RSSs), namely reactive RSS and proactive RSS, we derive the closed-form outage probability (OP) expressions for both RSSs, which can be performed in a distributed manner. To gain more insights, the asymptotic OPs at high signal-to-noise ratio (SNR) are explored and the outage performance comparison between the reactive RSS and proactive RSS are also provided. Results show that the proposed reactive RSS is outage-optimal among all possible single-relay selection schemes. The theoretical analysis is validated by Monte Carlo simulations. The results also show that the relay selection scheme, the number of relays, the location of BD, and the reflection coefficient of BD have great impact on the outage performance of cooperative AmBC systems.
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Mingaleeva, Guzel, Olga Afanaseva, Duc Toan Nguen, Dang Nayt Pham, and Pietro Zunino. "The Integration of Hybrid Mini Thermal Power Plants into the Energy Complex of the Republic of Vietnam." Energies 13, no. 21 (November 9, 2020): 5848. http://dx.doi.org/10.3390/en13215848.

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The article describes a method of integrating small distributed generation components in the power system of the Republic of Vietnam. The features of the energy system of Vietnam and the technologies used for mini thermal power plants are considered. The classification of small distributed generation components is presented with implantation of the most used resources of Vietnam—fossil and renewable. A generalized methodology for selection and calculation of technological schemes for mini thermal power plants is considered. The schemes of steam-turbine mini thermal power plants operating with coal and gas-turbine mini thermal power plants with solar air heaters are selected. Based on the calculation of the selected mini thermal power plant schemes, their distribution in the territory of the Republic of Vietnam has been obtained. The thermoeconomic efficiency has been chosen as the criterion for the best option for placing mini thermal power plants; its value for the proposed option is of 6.77%.
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25

Kharel, Binod, Onel Luis Alcaraz López, Hirley Alves, and Matti Latva-aho. "Ultra-Reliable Communication for Critical Machine Type Communication via CRAN-Enabled Multi-Connectivity Diversity Schemes." Sensors 21, no. 23 (December 2, 2021): 8064. http://dx.doi.org/10.3390/s21238064.

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This paper focuses on edge-enabled cloud radio access network architecture to achieve ultra-reliable communication, a crucial enabler for supporting mission-critical machine-type communication networks. We propose coordinated multi-point transmission schemes taking advantage of diversity mechanisms in interference-limited downlink cellular networks. The network scenario comprises spatially distributed multiple remote radio heads (RRHs) that may cooperate through silencing, or by using more elaborated diversity strategies such as maximum ratio transmission or transmit antenna selection to serve user equipment in the ultra-reliable operation regime. We derive an exact closed-form expression for the outage probabilities and expected values of signal-to-interference ratio for silencing, transmit antenna selection and maximum ratio transmission schemes. We formulate rate control and energy efficiency under reliability constraints to test the performance and resource usage of the proposed schemes. Furthermore, we study the impact on average system sum throughput with throughput-reliability trade-off under cooperative communication. Extensive numerical analysis shows the feasibility of ultra-reliable communication by implementing diversity schemes with RRHs cooperation.
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Alexandropoulos, George C., Agisilaos Papadogiannis, and Paschalis C. Sofotasios. "A Comparative Study of Relaying Schemes with Decode and Forward over Nakagami- Fading Channels." Journal of Computer Networks and Communications 2011 (2011): 1–14. http://dx.doi.org/10.1155/2011/560528.

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Although relaying can be very beneficial for wireless systems, understanding which relaying schemes can achieve specific performance objectives under realistic fading is crucial. In this paper we present a general framework for modeling and evaluating the performance of dual-hop decode-and-forward (DF) relaying schemes over independent and not necessarily identically distributed (INID) Nakagami- fading channels. We obtain closed-form expressions for the statistics of the instantaneous output signal-to-noise ratio of repetitive transmission with selection diversity. Furthermore, we present a unified statistical overview of other three significant relaying schemes with DF, one based on repetitive transmission with maximal-ratio diversity and the other two based on relay selection (RS). To compare the considered schemes, we present closed-form and analytical expressions for the outage probability and the average symbol error probability under various modulation methods, respectively. Importantly, it is shown that when the channel state information for RS is perfect, RS-based schemes always outperform repetitive ones. Furthermore, when the direct link between the source and the destination nodes is sufficiently strong, relaying may not result in any gains, and it should be switched off.
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Zafar, Faheem, Abid Khan, Saif Ur Rehman Malik, Mansoor Ahmed, Carsten Maple, and Adeel Anjum. "MobChain: Three-Way Collusion Resistance in Witness-Oriented Location Proof Systems Using Distributed Consensus." Sensors 21, no. 15 (July 28, 2021): 5096. http://dx.doi.org/10.3390/s21155096.

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Smart devices have accentuated the importance of geolocation information. Geolocation identification using smart devices has paved the path for incentive-based location-based services (LBS). However, a user’s full control over a smart device can allow tampering of the location proof. Witness-oriented location proof systems (LPS) have emerged to resist the generation of false proofs and mitigate collusion attacks. However, witness-oriented LPS are still susceptible to three-way collusion attacks (involving the user, location authority, and the witness). To overcome the threat of three-way collusion in existing schemes, we introduce a decentralized consensus protocol called MobChain in this paper. In this scheme the selection of a witness and location authority is achieved through a distributed consensus of nodes in an underlying P2P network that establishes a private blockchain. The persistent provenance data over the blockchain provides strong security guarantees; as a result, the forging and manipulation of location becomes impractical. MobChain provides secure location provenance architecture, relying on decentralized decision making for the selection of participants of the protocol thereby addressing the three-way collusion problem. Our prototype implementation and comparison with the state-of-the-art solutions show that MobChain is computationally efficient and highly available while improving the security of LPS.
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28

Lijuan, Zhang, and Li Zhangming. "Optimal selection of design schemes for a sparse distributed pile foundation based on fuzzy optimization theory." Kybernetes 38, no. 10 (October 16, 2009): 1828–34. http://dx.doi.org/10.1108/03684920910994358.

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29

Rehman, Waheed ur, Tabinda Salam, Jin Xu, and Xiaofeng Tao. "Capacity Enhancement in 60 GHz Based D2D Networks by Relay Selection and Scheduling." International Journal of Antennas and Propagation 2015 (2015): 1–15. http://dx.doi.org/10.1155/2015/205163.

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Millimeter-wave or 60 GHz communication is a promising technology that enables data rates in multigigabits. However, its tremendous propagation loss and signal blockage may severely affect the network throughput. In current data-centric device-to-device (D2D) communication networks, the devices with intended data communications usually lay in close proximity, unlike the case in voice-centric networks. So the network can be visualized as a naturally formed groups of devices. In this paper, we jointly consider resource scheduling and relay selection to improve network capacity in 60 GHz based D2D networks. Two types of transmission scenarios are considered in wireless personal area networks (WPANs), intra and intergroup. A distributed receiver based relay selection scheme is proposed for intragroup transmission, while a distance based relay selection scheme is proposed for intergroup transmission. The outage analysis of our proposed relay selection scheme is provided along with the numerical results. We then propose a concurrent transmission scheduling algorithm based on vertex coloring technique. The proposed scheduling algorithm employs time and space division in mmWave WPANs. Using vertex multicoloring, we allow transmitter-receiver (Tx-Rx) communication pairs to span over more colors, enabling better time slot utilization. We evaluate our scheduling algorithm in single-hop and multihop scenarios and discover that it outperforms other schemes by significantly improving network throughput.
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Son, A.-Young, and Eui-Nam Huh. "Multi-Objective Service Placement Scheme Based on Fuzzy-AHP System for Distributed Cloud Computing." Applied Sciences 9, no. 17 (August 29, 2019): 3550. http://dx.doi.org/10.3390/app9173550.

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With the rapid increase in the development of the cloud data centers, it is expected that massive data will be generated, which will decrease service response time for the cloud data centers. To improve the service response time, distributed cloud computing has been designed and researched for placement and migration from mobile devices close to edge servers that have secure resource computing. However, most of the related studies did not provide sufficient service efficiency for multi-objective factors such as energy efficiency, resource efficiency, and performance improvement. In addition, most of the existing approaches did not consider various metrics. Thus, to maximize energy efficiency, maximize performance, and reduce costs, we consider multi-metric factors by combining decision methods, according to user requirements. In order to satisfy the user’s requirements based on service, we propose an efficient service placement system named fuzzy- analytical hierarchical process and then analyze the metric that enables the decision and selection of a machine in the distributed cloud environment. Lastly, using different placement schemes, we demonstrate the performance of the proposed scheme.
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Kim, Jung-Bin, and In-Ho Lee. "Outage Analysis of Partial Relay Selection Schemes with Feedback Delay and Channel Estimation Errors in Nonidentical Rayleigh Fading Channels." International Journal of Antennas and Propagation 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/1862391.

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This paper investigates the impact of the channel estimation error and outdated channel state information (CSI) on the outage performances of partial relay selection (PRS) and efficient partial relay selection (EPRS). Considering imperfect channel estimation and outdated CSI with decode-and-forward (DF) relaying strategy, closed-form expressions for exact outage probabilities and asymptotic outage probabilities for PRS and EPRS are provided assuming independent and nonidentically distributed Rayleigh fading channels. Numerical investigations verify the analytical expression for outage probability and show how much performance is degraded by the channel estimation errors and the feedback delay that causes the outdated CSI.
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32

Shrivastava, Aayush, Abhishek Sharma, Manjaree Pandit, Vibhu Jately, and Brian Azzopardi. "Hybrid Protection Scheme Based Optimal Overcurrent Relay Coordination Strategy for RE Integrated Power Distribution Grid." Energies 14, no. 21 (November 2, 2021): 7192. http://dx.doi.org/10.3390/en14217192.

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A directional overcurrent relay is commonly used to protect the power distribution networks of a distributed system. The selection of the appropriate settings for the relays is an important component of the protection strategies used to isolate the faulty parts of the system. The rapid growth of distributed generation (DG) systems present new challenges to these protection schemes. The effect of solar photovoltaic power plants on relay coordination is studied initially in this research work. A protection strategy was formulated to guarantee that the increased penetration of solar photovoltaic (PV) plants does not affect the relay coordination time. This paper addresses these issues associated with a high penetration of DG through the use of a hybrid protection scheme. The protection strategy is divided into two parts. The first part is based on an optimal fault current limiter value estimated with respect to constraints and the optimal time multiplier setting, and then the coordination time interval is estimated with respect to constraint in Part II. The results of these analyses show that a hybrid protection scheme can effectively handle the complexity of distributed generation (DG) and dynamic relay coordination problems. In this research, three optimization algorithms have been used for calculating the estimated value of impedance fault current limiter (Zfcl) and time multiplier setting (TMS). The response time of hybrid protection schemes is very important. If the computational time of their proposed algorithms is less than their actual computational time, then their response time to address the issue is also less. The performance in all algorithms was identified to arrive at a conclusion that the grey wolf optimized algorithm (GWO) algorithm can substantially reduce the computational time needed to implement hybrid protection algorithms. The GWO algorithm takes a computational time of 0.946 s, achieving its feasible solution in less than 1 s.
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Pan, Zhong Liang, and Ling Chen. "Test Scheduling Method Based on Cellular Genetic Algorithm for System on Chip." Materials Science Forum 663-665 (November 2010): 670–73. http://dx.doi.org/10.4028/www.scientific.net/msf.663-665.670.

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The main aspects for the test of system on chip (SoC) are designing testability architectures and solving the test scheduling. The test time of SoC can be reduced by using good test scheduling schemes. A test scheduling method based on cellular genetic algorithm is presented in this paper. In the method, the individuals are used to represent the feasible solutions of the test scheduling problem, the individuals are distributed over a grid or connected graph, the genetic operations such as selection and mutation are applied locally in some neighborhood of each individual. The test scheduling schemes are obtained by carrying out the evolutionary operations for the populations. A lot of experiments are performed for the SoC benchmark circuits, the experimental results show that the better test scheduling schemes can be obtained by the method in this paper.
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Wahid, Ishtiaq, Ata Ul Aziz Ikram, Masood Ahmad, and Fasee Ullah. "An improved supervisory protocol for automatic selection of routing protocols in environment-aware vehicular ad hoc networks." International Journal of Distributed Sensor Networks 14, no. 11 (November 2018): 155014771881505. http://dx.doi.org/10.1177/1550147718815051.

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With resource constraint’s distributed architecture and dynamic topology, network issues such as congestion, latency, power awareness, mobility, and other quality of service issues need to be addressed by optimizing the routing protocols. As a result, a number of routing protocols have been proposed. Routing protocols have trade-offs in performance parameters and their performance varies with the underlying mobility model. For designing an improved vehicular ad hoc network, three components of the network are to be focused: routing protocols, mobility models, and performance metrics. This article describes the relationship of these components, trade-offs in performance, and proposes a supervisory protocol, which monitors the scenario and detects the realistic mobility model through analysis of the microscopic features of the mobility model. An analytical model is used to determine the best protocol for a particular mobility model. The supervisory protocol then selects the best routing protocol for the mobility model of the current operational environment. For this, EstiNet 8.1 Simulator is used to validate the proposed scheme and compare its performance with existing schemes. Simulation results of the proposed scheme show the consistency in the performance of network throughout its operation.
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35

Chen, Yi, Narjol Gonzalez-Escalona, Thomas S. Hammack, Marc W. Allard, Errol A. Strain, and Eric W. Brown. "Core Genome Multilocus Sequence Typing for Identification of Globally Distributed Clonal Groups and Differentiation of Outbreak Strains of Listeria monocytogenes." Applied and Environmental Microbiology 82, no. 20 (August 12, 2016): 6258–72. http://dx.doi.org/10.1128/aem.01532-16.

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ABSTRACTMany listeriosis outbreaks are caused by a few globally distributed clonal groups, designated clonal complexes or epidemic clones, ofListeria monocytogenes, several of which have been defined by classic multilocus sequence typing (MLST) schemes targeting 6 to 8 housekeeping or virulence genes. We have developed and evaluated core genome MLST (cgMLST) schemes and applied them to isolates from multiple clonal groups, including those associated with 39 listeriosis outbreaks. The cgMLST clusters were congruent with MLST-defined clonal groups, which had various degrees of diversity at the whole-genome level. Notably, cgMLST could distinguish among outbreak strains and epidemiologically unrelated strains of the same clonal group, which could not be achieved using classic MLST schemes. The precise selection of cgMLST gene targets may not be critical for the general identification of clonal groups and outbreak strains. cgMLST analyses further identified outbreak strains, including those associated with recent outbreaks linked to contaminated French-style cheese, Hispanic-style cheese, stone fruit, caramel apple, ice cream, and packaged leafy green salad, as belonging to major clonal groups. We further developed lineage-specific cgMLST schemes, which can include accessory genes when core genomes do not possess sufficient diversity, and this provided additional resolution over species-specific cgMLST. Analyses of isolates from different common-source listeriosis outbreaks revealed various degrees of diversity, indicating that the numbers of allelic differences should always be combined with cgMLST clustering and epidemiological evidence to define a listeriosis outbreak.IMPORTANCEClassic multilocus sequence typing (MLST) schemes targeting internal fragments of 6 to 8 genes that define clonal complexes or epidemic clones have been widely employed to studyL. monocytogenesbiodiversity and its relation to pathogenicity potential and epidemiology. We demonstrated that core genome MLST schemes can be used for the simultaneous identification of clonal groups and the differentiation of individual outbreak strains and epidemiologically unrelated strains of the same clonal group. We further developed lineage-specific cgMLST schemes that targeted more genomic regions than the species-specific cgMLST schemes. Our data revealed the genome-level diversity of clonal groups defined by classic MLST schemes. Our identification of U.S. and international outbreaks caused by major clonal groups can contribute to further understanding of the global epidemiology ofL. monocytogenes.
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Cameron, N. D., and R. Thompson. "Design of multivariate selection experiments to estimate genetic parameters." Proceedings of the British Society of Animal Production (1972) 1986 (March 1986): 26. http://dx.doi.org/10.1017/s0308229600015373.

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Precise, unbiased estimates of genetic parameters, such as heritability and genetic covariance, are necessary to optimise breeding programs and to predict rates of change for various selection schemes. A classical method of estimation is to use high and low selection experiments. We consider two generation selection experiments when observations in the parental generation are only taken on one sex, resulting in half-sib family information. We consider cases of two standardised traits, with zero mean and unit variance, and assume that the traits are normally distributed. The genetic and phenotypic variance-covariance matrices for the traits are denoted by G and P respectively. The genetic variances and covariances of the standardised traits are then heritabilities and co-heritabilities.The construction of other designs is examined, assuming the phenotypic correlation of rp between traits is known. For simplicity, comparisons of designs are developed by considering the variance of the genetic variances when the traits are uncorrelated both phenotypically and genetically.
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LÓPEZ-JAMAR, JUAN, FABIÁN CASAS, MARIO DÍAZ, and MANUEL B. MORALES. "Local differences in habitat selection by Great Bustards Otis tarda in changing agricultural landscapes: implications for farmland bird conservation." Bird Conservation International 21, no. 3 (November 3, 2010): 328–41. http://dx.doi.org/10.1017/s0959270910000535.

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SummaryLocal changes in land use can influence patterns of habitat selection by farmland birds, thus biasing predictions of population responses to land use changes based on wildlife-habitat or niche modelling. This study, based in arable farmland in south-central Spain, determined whether habitat selection (use of agricultural habitats and the distance to roads, tracks and buildings) by Great Bustards Otis tarda varied between two nearby areas with differing land uses. The western sector has experienced a process of land abandonment and infrastructure development linked to an airport project that started in 1998 and finished in 2009, while the eastern sector maintains extensive dry farmland systems. Great Bustards avoided ploughed fields and selected short- and long-term fallows. Selection of fallows was more intensive in the sector suffering recent land-use changes, where these substrates were more abundant. Great Bustards were distributed further from roads, paths and buildings than would be expected if individual birds selected habitats at random. Avoidance of infrastructure was strongest in the area suffering recent land-use changes. Local patterns of habitat selection seemed to change in relation to agricultural abandonment and infrastructure development. Consequently, conservation measures based on knowledge of broad patterns of habitat use and selection such as agri-environmental schemes may fail to ensure steppe bird conservation locally if such local effects are overlooked. Specifically, schemes should include landscape-scale restrictions on the development and use of infrastructure (roads, tracks and buildings). Analyses of the patterns and causes of local and regional changes in habitat selection are essential to conserve populations of endangered farmland birds.
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38

Taneja, Ashu, Ali Alqahtani, Nitin Saluja, and Nayef Alqahtani. "Robust Resource Control Based on AP Selection in 6G-Enabled IoT Networks." Sensors 23, no. 15 (July 29, 2023): 6788. http://dx.doi.org/10.3390/s23156788.

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The diverse application vertices of internet-of-things (IoT) including internet of vehicles (IoV), industrial IoT (IIoT) and internet of drones things (IoDT) involve intelligent communication between the massive number of objects around us. This digital transformation strives for seamless data flow, uninterrupted communication capabilities, low latency and ultra-high reliability. The limited capabilities of fifth generation (5G) technology have given way to sixth generation (6G) wireless technology. This paper presents a dynamic cell-free framework for a 6G-enabled IoT network. A number of access points (APs) are distributed over a given geographical area to serve a large number of user nodes. A pilot-based AP selection (PBAS) algorithm is proposed, which offers robust resource control through AP selection based on pilots. Selecting a subset of APs against all APs for each user node results in improved performance. In this paper, the performance of the proposed transmission model is evaluated for the achieved data rate and spectral efficiency using the proposed algorithm. It is shown that the proposed PBAS algorithm improves the spectral efficiency by 22% at the cell-edge and 1.5% at the cell-center. A comparison of the different combining techniques used at different user locations is also provided, along with the mathematical formulations. Finally, the proposed model is compared with two other transmission models for performance evaluation. It is observed that the spectral efficiency achieved by an edge node with the proposed scheme is 5.3676 bits/s/Hz, compared to 0.756 bits/s/Hz and 1.0501 bits/s/Hz, attained with transmission schemes 1 and 2, respectively.
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39

Afolabi, Adedeji Olushola, Adedapo Oluwatayo, Opeyemi Oyeyipo, Rapheal Ojelabi, and Olabosipo Fagbenle. "Assessment of Designers’ Perception of Post Conflict Housing Schemes for Internally Displaced Persons." Construction Economics and Building 18, no. 1 (March 28, 2018): 27–47. http://dx.doi.org/10.5130/ajceb.v18i1.5780.

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With millions of internally displaced persons (IDPs) around the world, there is need to implement durable housing solutions post-conflict, that involves sustainable integration and sustainable reintegration using long term shelter programmes in the rural and urban areas. The study aims to assess designers’ assessment of post conflict housing schemes (PCHS) for internally displaced persons. Using a cross-sectional survey, the study utilized a questionnaire instrument distributed to one hundred (100) design professionals that have cognate field experience in the design, construction and management of post-conflict housing schemes. Statistical tools of bar chart, principal component analysis, categorical regression and one-way analysis of variance by SPSS v.21 was utilized. The study revealed that designers considered features such as external design and services, socio-cultural and space and maintenance features in the design of PCHS. Generalized factors considered in the selection of these features include demands of the household, choice/selection of building materials and population of IDPs. The study revealed that the failure of PCHS could be because of politics/partisanship, lack of international assistance/aid, need to make profit and non-involvement of IDPs in the rebuilding process, while the success of the scheme could be engendered by adequate participation of IDPs, effective monitoring mechanisms and increased government and non-governmental organizations’ (NGOs) participation. In conclusion, the study developed a framework for the design of PCHS for IDPs. The study recommended that professional designers should objectively consider the contributions and characteristics of IDPs in the design of PCHS. In addition, international bodies should increase pressure on government to increase commitment in re-settling IDPs. NGOs should not relent in their efforts.
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40

Yeo, Sangho, Ye Naing, Taeha Kim, and Sangyoon Oh. "Achieving Balanced Load Distribution with Reinforcement Learning-Based Switch Migration in Distributed SDN Controllers." Electronics 10, no. 2 (January 13, 2021): 162. http://dx.doi.org/10.3390/electronics10020162.

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Distributed controllers in software-defined networking (SDN) become a promising approach because of their scalable and reliable deployments in current SDN environments. Since the network traffic varies with time and space, a static mapping between switches and controllers causes uneven load distribution among controllers. Dynamic migration of switches methods can provide a balanced load distribution between SDN controllers. Recently, existing reinforcement learning (RL) methods for dynamic switch migration such as MARVEL are modeling the load balancing of each controller as linear optimization. Even if it is widely used for network flow modeling, this type of linear optimization is not well fitted to the real-world workload of SDN controllers because correlations between resource types are unexpectedly and continuously changed. Consequently, using the linear model for resource utilization makes it difficult to distinguish which resource types are currently overloaded. In addition, this yields a high time cost. In this paper, we propose a reinforcement learning-based switch and controller selection scheme for switch migration, switch-aware reinforcement learning load balancing (SAR-LB). SAR-LB uses the utilization ratio of various resource types in both controllers and switches as the inputs of the neural network. It also considers switches as RL agents to reduce the action space of learning, while it considers all cases of migrations. Our experimental results show that SAR-LB achieved better (close to the even) load distribution among SDN controllers because of the accurate decision-making of switch migration. The proposed scheme achieves better normalized standard deviation among distributed SDN controllers than existing schemes by up to 34%.
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Ustun, Taha Selim, and Saqib Ayyubi. "Automated Network Topology Extraction Based on Graph Theory for Distributed Microgrid Protection in Dynamic Power Systems." Electronics 8, no. 6 (June 10, 2019): 655. http://dx.doi.org/10.3390/electronics8060655.

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Unlike conventional grids, microgrids may utilize different connections and the overall topology can be variable. Considering this, it is required to develop a new protection concept/scheme for safe operation. Maintaining proper selective operation of the relays in these dynamic microgrid structures is a challenge itself. This requires monitoring the connections and updating time delays of the relays which will ensure the desired hierarchy in the system. In this paper, a novel approach has been taken where electrical networks are modeled according to graph theory. Smart algorithms, such as network graph discovery, local manager selection, and protection coordination strategy, are run to automatically detect topology changes and ensure proper protection operation. Furthermore, distributed nature of this method mitigates the risks associated with central controller-based schemes. The developed method is applicable to all power system operations, and it poses a unique implementation in postdisaster recovery. After a disaster or terror attack, this self-diagnosis, self-healing system can identify healthy sections and run them as a standalone system until the relief arrives. The ability of the protection system to be run as a distributed control makes sure that any healthy part of the system can be restructured and utilized, without the dependency, on any central controller or connection.
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42

Castro-Jul, Fátima, Rebeca Díaz-Redondo, Ana Fernández-Vilas, Sophie Chabridon, and Denis Conan. "Fog Architectures and Sensor Location Certification in Distributed Event-Based Systems." Sensors 19, no. 1 (December 29, 2018): 104. http://dx.doi.org/10.3390/s19010104.

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Since smart cities aim at becoming self-monitoring and self-response systems, their deployment relies on close resource monitoring through large-scale urban sensing. The subsequent gathering of massive amounts of data makes essential the development of event-filtering mechanisms that enable the selection of what is relevant and trustworthy. Due to the rise of mobile event producers, location information has become a valuable filtering criterion, as it not only offers extra information on the described event, but also enhances trust in the producer. Implementing mechanisms that validate the quality of location information becomes then imperative. The lack of such strategies in cloud architectures compels the adoption of new communication schemes for Internet of Things (IoT)-based urban services. To serve the demand for location verification in urban event-based systems (DEBS), we have designed three different fog architectures that combine proximity and cloud communication. We have used network simulations with realistic urban traces to prove that the three of them can correctly identify between 73% and 100% of false location claims.
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43

Yu, Liang, Qixin Guo, Rui Wang, Minyan Shi, Fucheng Yan, and Ran Wang. "Dynamic Offloading Loading Optimization in Distributed Fault Diagnosis System with Deep Reinforcement Learning Approach." Applied Sciences 13, no. 7 (March 23, 2023): 4096. http://dx.doi.org/10.3390/app13074096.

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Artificial intelligence and distributed algorithms have been widely used in mechanical fault diagnosis with the explosive growth of diagnostic data. A novel intelligent fault diagnosis system framework that allows intelligent terminals to offload computational tasks to Mobile edge computing (MEC) servers is provided in this paper, which can effectively address the problems of task processing delays and enhanced computational complexity. As the resources at the MEC and intelligent terminals are limited, performing reasonable resource allocation optimization can improve the performance, especially for a multi-terminals offloading system. In this study, to minimize the task computation delay, we jointly optimize the local content splitting ratio, the transmission/computation power allocation, and the MEC server selection under a dynamic environment with stochastic task arrivals. The challenging dynamic joint optimization problem is formulated as a reinforcement learning (RL) problem, which is designed as the computational offloading policies to minimize the long-term average delay cost. Two deep RL strategies, deep Q-learning network (DQN) and deep deterministic policy gradient (DDPG), are adopted to learn the computational offloading policies adaptively and efficiently. The proposed DQN strategy takes the MEC selection as a unique action while using the convex optimization approach to obtain the local content splitting ratio and the transmission/computation power allocation. Simultaneously, the actions of the DDPG strategy are selected as all dynamic variables, including the local content splitting ratio, the transmission/computation power allocation, and the MEC server selection. Numerical results demonstrate that both proposed strategies perform better than the traditional non-learning schemes. The DDPG strategy outperforms the DQN strategy in all simulation cases exhibiting minimal task computation delay due to its ability to learn all variables online.
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44

Mollahasani, Shahram, Turgay Pamuklu, Rodney Wilson, and Melike Erol-Kantarci. "Energy-Aware Dynamic DU Selection and NF Relocation in O-RAN Using Actor–Critic Learning." Sensors 22, no. 13 (July 3, 2022): 5029. http://dx.doi.org/10.3390/s22135029.

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Open radio access network (O-RAN) is one of the promising candidates for fulfilling flexible and cost-effective goals by considering openness and intelligence in its architecture. In the O-RAN architecture, a central unit (O-CU) and a distributed unit (O-DU) are virtualized and executed on processing pools of general-purpose processors that can be placed at different locations. Therefore, it is challenging to choose a proper location for executing network functions (NFs) over these entities by considering propagation delay and computational capacity. In this paper, we propose a Soft Actor–Critic Energy-Aware Dynamic DU Selection algorithm (SA2C-EADDUS) by integrating two nested actor–critic agents in the O-RAN architecture. In addition, we formulate an optimization model that minimizes delay and energy consumption. Then, we solve that problem with an MILP solver and use that solution as a lower bound comparison for our SA2C-EADDUS algorithm. Moreover, we compare that algorithm with recent works, including RL- and DRL-based resource allocation algorithms and a heuristic method. We show that by collaborating A2C agents in different layers and by dynamic relocation of NFs, based on service requirements, our schemes improve the energy efficiency by 50% with respect to other schemes. Moreover, we reduce the mean delay by a significant amount with our novel SA2C-EADDUS approach.
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45

Bhargavi, K., and Sajjan G. Shiva. "Fuzzy Neutrosophic Soft Set Based Transfer-Q-Learning Scheme for Load Balancing in Uncertain Grid Computing Environments." Cybernetics and Information Technologies 22, no. 4 (November 1, 2022): 35–55. http://dx.doi.org/10.2478/cait-2022-0038.

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Abstract Effective load balancing is tougher in grid computing compared to other conventional distributed computing platforms due to its heterogeneity, autonomy, scalability, and adaptability characteristics, resource selection and distribution mechanisms, and data separation. Hence, it is necessary to identify and handle the uncertainty of the tasks and grid resources before making load balancing decisions. Using two potential forms of Hidden Markov Models (HMM), i.e., Profile Hidden Markov Model (PF_HMM) and Pair Hidden Markov Model (PR_HMM), the uncertainties in the task and system parameters are identified. Load balancing is then carried out using our novel Fuzzy Neutrosophic Soft Set theory (FNSS) based transfer Q-learning with pre-trained knowledge. The transfer Q-learning enabled with FNSS solves large scale load balancing problems efficiently as the models are already trained and do not need pre-training. Our expected value analysis and simulation results confirm that the proposed scheme is 90 percent better than three of the recent load balancing schemes.
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46

Ramasamy, Bhairavi, and Gnanou Florence Sudha. "Instantaneous channel characteristics and progression factor based collaborative routing." Indonesian Journal of Electrical Engineering and Computer Science 28, no. 2 (November 1, 2022): 918. http://dx.doi.org/10.11591/ijeecs.v28.i2.pp918-925.

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Underwater acoustic sensor networks (UWASN) have enormous applications like investigating oceanographic environment, data gathering, scrutiny, calamity avoidance etc. Cooperative communication becomes mandatory when nodes are distributed far apart especially in the ocean environment. The existing relay selection techniques do not consider the instantaneous channel characteristics while selecting the relay nodes. The relays selected based on the outdated channel state information aggravates or worsens the performance of the rapidly changing or dynamic UWASN. Hence, this paper proposes an instantaneous channel characteristics and progression factor (ICPF) based collaborative routing for underwater acoustic sensor networks. It considers numerous indexes such as propagation delay, residual energy, progression factor, spreading, transmission and absorption loss in the forwarding relay node selection. These indexes are averaged and updated periodically to overcome the difficulties caused by the inconsistency and aggressive nature of underwater channel. The progression factor proposed in this work is a prime metric that facilitates efficient data forwarding. Simulation results show that the proposed technique outperforms the existing schemes in terms of packet delivery ratio (PDR), average end to end delay and energy consumption and is capable of achieving PDR of 90.1% for network comprising of 100 acoustic nodes.
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47

Blasiak, Pawel, Ewa Borsuk, and Marcin Markiewicz. "On safe post-selection for Bell tests with ideal detectors: Causal diagram approach." Quantum 5 (November 11, 2021): 575. http://dx.doi.org/10.22331/q-2021-11-11-575.

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Reasoning about Bell nonlocality from the correlations observed in post-selected data is always a matter of concern. This is because conditioning on the outcomes is a source of non-causal correlations, known as a selection bias, rising doubts whether the conclusion concerns the actual causal process or maybe it is just an effect of processing the data. Yet, even in the idealised case without detection inefficiencies, post-selection is an integral part of experimental designs, not least because it is a part of the entanglement generation process itself. In this paper we discuss a broad class of scenarios with post-selection on multiple spatially distributed outcomes. A simple criterion is worked out, called the all-but-one principle, showing when the conclusions about nonlocality from breaking Bell inequalities with post-selected data remain in force. Generality of this result, attained by adopting the high-level diagrammatic tools of causal inference, provides safe grounds for systematic reasoning based on the standard form of multipartite Bell inequalities in a wide array of entanglement generation schemes, without worrying about the dangers of selection bias. In particular, it can be applied to post-selection defined by single-particle events in each detection chanel when the number of particles in the system is conserved.
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48

Wang, Jingyan, Carmel Baharav, Nihar B. Shah, Anita Williams Woolley, and R. Ravi. "Allocation Schemes in Analytic Evaluation: Applicant-Centric Holistic or Attribute-Centric Segmented?" Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 10, no. 1 (October 14, 2022): 207–18. http://dx.doi.org/10.1609/hcomp.v10i1.22000.

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Many applications such as hiring and university admissions involve evaluation and selection of applicants. These tasks are fundamentally difficult, and require combining evidence from multiple different aspects (what we term "attributes"). In these applications, the number of applicants is often large, and a common practice is to assign the task to multiple evaluators in a distributed fashion. Specifically, in the often-used holistic allocation, each evaluator is assigned a subset of the applicants, and is asked to assess all relevant information for their assigned applicants. However, such an evaluation process is subject to issues such as miscalibration (evaluators see only a small fraction of the applicants and may not get a good sense of relative quality), and discrimination (evaluators are influenced by irrelevant information about the applicants). We identify that such attribute-based evaluation allows alternative allocation schemes. Specifically, we consider assigning each evaluator more applicants but fewer attributes per applicant, termed segmented allocation. We compare segmented allocation to holistic allocation on several dimensions via theoretical and experimental methods. We establish various tradeoffs between these two approaches, and identify conditions under which one approach results in more accurate evaluation than the other.
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Ngo, Mao V., Tie Luo, and Tony Q. S. Quek. "Adaptive Anomaly Detection for Internet of Things in Hierarchical Edge Computing: A Contextual-Bandit Approach." ACM Transactions on Internet of Things 3, no. 1 (February 28, 2022): 1–23. http://dx.doi.org/10.1145/3480172.

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The advances in deep neural networks (DNN) have significantly enhanced real-time detection of anomalous data in IoT applications. However, the complexity-accuracy-delay dilemma persists: Complex DNN models offer higher accuracy, but typical IoT devices can barely afford the computation load, and the remedy of offloading the load to the cloud incurs long delay. In this article, we address this challenge by proposing an adaptive anomaly detection scheme with hierarchical edge computing (HEC). Specifically, we first construct multiple anomaly detection DNN models with increasing complexity and associate each of them to a corresponding HEC layer. Then, we design an adaptive model selection scheme that is formulated as a contextual-bandit problem and solved by using a reinforcement learning policy network . We also incorporate a parallelism policy training method to accelerate the training process by taking advantage of distributed models. We build an HEC testbed using real IoT devices and implement and evaluate our contextual-bandit approach with both univariate and multivariate IoT datasets. In comparison with both baseline and state-of-the-art schemes, our adaptive approach strikes the best accuracy-delay tradeoff on the univariate dataset and achieves the best accuracy and F1-score on the multivariate dataset with only negligibly longer delay than the best (but inflexible) scheme.
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50

Potirakis, Stelios M., Bilel Nefzi, Nikolas Alexander Tatlas, Gurkan Tuna, and Maria Rangoussi. "A Wireless Network of Acoustic Sensors for Environmental Monitoring." Key Engineering Materials 605 (April 2014): 43–46. http://dx.doi.org/10.4028/www.scientific.net/kem.605.43.

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A distributed microelectronic system for the sound/acoustic monitoring of areas of environmental interest, based on a wireless network of acoustic sensors (microphones), and the automated generation of multi-level sound maps for environmental assessment has been recently proposed. This contribution focuses on the relation between the density of the wireless nodes and node operational parameters, like the required communication rate, data compression and power autonomy, in each one of the proposed area coverage schemes/ network architectures. The results provide the grounds both for the selection of the hardware architecture on network and on node level, but also for the decision on the distribution of the processing effort between the local and the central processing units.
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