scholarly journals On Constructing t -Spanner in IoT under SINR

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xiujuan Zhang ◽  
Yongcai Wang ◽  
Wenping Chen ◽  
Yuqing Zhu ◽  
Deying Li ◽  
...  
Keyword(s):  
Distributed Algorithms ◽  
Optimization Problems ◽  
Time Slot ◽  
Randomized Algorithm ◽  
Independent Set ◽  
Task Completion ◽  
Time Interval ◽  
Communication Graph ◽  
Effectiveness And Efficiency ◽  
The Internet Of Things

Following the recent advances in the Internet of Things (IoT), it is drawing lots of attention to design distributed algorithms for various network optimization problems under the SINR (Signal-to-Interference-and-Noise-Ratio) interference model, such as spanner construction. Since a spanner can maintain a linear number of links while still preserving efficient routes for any pair of nodes in wireless networks, it is important to design distributed algorithms for spanners. Given a constant t > 1 as the required stretch factor, the problem of our concern is to design an efficient distributed algorithm to construct a t -spanner of the communication graph under SINR such that the delay for the task completion is minimized, where the delay is the time interval between the time slot that the first node commences its operation to the time slot that all the nodes finish their task of constructing the t -spanner. Our main contributions include four aspects. First, we propose a proximity range and proximity independent set (PISet) to increase the number of nodes transmitting successfully at the same time in order to reduce the delay. Second, we develop a distributed randomized algorithm SINR-Spanner to construct a required t -spanner with high probability. Third, the approximation ratio of SINR-Spanner is proven to be a constant. Finally, extensive simulations are carried out to verify the effectiveness and efficiency of our proposed algorithm.

Comparison of Meta-heuristic Algorithms on Benchmark Functions

2019 ◽  
Vol 2 (3) ◽  
pp. 508-517
Author(s):  
FerdaNur Arıcı ◽  
Ersin Kaya
Keyword(s):  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Optimization Algorithms ◽  
Gravitational Search Algorithm ◽  
Differential Evolution Algorithm ◽  
Population Based ◽  
Time Interval ◽  
Bee Colony ◽  
Different Characteristics

Optimization is a process to search the most suitable solution for a problem within an acceptable time interval. The algorithms that solve the optimization problems are called as optimization algorithms. In the literature, there are many optimization algorithms with different characteristics. The optimization algorithms can exhibit different behaviors depending on the size, characteristics and complexity of the optimization problem. In this study, six well-known population based optimization algorithms (artificial algae algorithm - AAA, artificial bee colony algorithm - ABC, differential evolution algorithm - DE, genetic algorithm - GA, gravitational search algorithm - GSA and particle swarm optimization - PSO) were used. These six algorithms were performed on the CEC’17 test functions. According to the experimental results, the algorithms were compared and performances of the algorithms were evaluated.

scholarly journals Operations management of smart logistics: A literature review and future research

2021 ◽  
Author(s):  
Bo Feng ◽  
Qiwen Ye
Keyword(s):  
Operations Management ◽  
Optimization Problems ◽  
Future Research ◽  
Information Communication ◽  
Logistics Industry ◽  
Smart Logistics ◽  
Promising Solution ◽  
Future Research Directions ◽  
Offline Channels ◽  
The Internet Of Things

AbstractThe global collaboration and integration of online and offline channels have brought new challenges to the logistics industry. Thus, smart logistics has become a promising solution for handling the increasing complexity and volume of logistics operations. Technologies, such as the Internet of Things, information communication technology, and artificial intelligence, enable more efficient functions into logistics operations. However, they also change the narrative of logistics management. Scholars in the areas of engineering, logistics, transportation, and management are attracted by this revolution. Operations management research on smart logistics mainly concerns the application of underlying technologies, business logic, operation framework, related management system, and optimization problems under specific scenarios. To explore these studies, the related literature has been systematically reviewed in this work. On the basis of the research gaps and the needs of industrial practices, future research directions in this field are also proposed.

scholarly journals Gumbel-softmax-based optimization: a simple general framework for optimization problems on graphs

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yaoxin Li ◽  
Jing Liu ◽  
Guozheng Lin ◽  
Yueyuan Hou ◽  
Muyun Mou ◽  
...  
Keyword(s):  
Objective Function ◽  
Statistical Physics ◽  
Automatic Differentiation ◽  
Optimization Problems ◽  
Vertex Cover ◽  
Independent Set ◽  
Computational Social Science ◽  
Maximization Problem ◽  
Maximum Independent Set ◽  
Gradient Descent Algorithm

AbstractIn computer science, there exist a large number of optimization problems defined on graphs, that is to find a best node state configuration or a network structure, such that the designed objective function is optimized under some constraints. However, these problems are notorious for their hardness to solve, because most of them are NP-hard or NP-complete. Although traditional general methods such as simulated annealing (SA), genetic algorithms (GA), and so forth have been devised to these hard problems, their accuracy and time consumption are not satisfying in practice. In this work, we proposed a simple, fast, and general algorithm framework based on advanced automatic differentiation technique empowered by deep learning frameworks. By introducing Gumbel-softmax technique, we can optimize the objective function directly by gradient descent algorithm regardless of the discrete nature of variables. We also introduce evolution strategy to parallel version of our algorithm. We test our algorithm on four representative optimization problems on graph including modularity optimization from network science, Sherrington–Kirkpatrick (SK) model from statistical physics, maximum independent set (MIS) and minimum vertex cover (MVC) problem from combinatorial optimization on graph, and Influence Maximization problem from computational social science. High-quality solutions can be obtained with much less time-consuming compared to the traditional approaches.

scholarly journals Data Downlink System in the Vast IOT Node Condition Assisted by UAV, Large Intelligent Surface, and Power and Data Beacon

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5748
Author(s):  
Zhibo Zhang ◽  
Qing Chang ◽  
Na Zhao ◽  
Chen Li ◽  
Tianrun Li
Keyword(s):  
Communication Systems ◽  
Optimization Problems ◽  
Minimum Energy ◽  
Numerical Algorithms ◽  
Flight Trajectory ◽  
Performance Improvements ◽  
Minimum Energy Consumption ◽  
Significant Performance ◽  
Downlink System ◽  
The Internet Of Things

The future development of communication systems will create a great demand for the internet of things (IOT), where the overall control of all IOT nodes will become an important problem. Considering the essential issues of miniaturization and energy conservation, in this study, a new data downlink system is designed in which all IOT nodes harvest energy first and then receive data. To avoid the unsolvable problem of pre-locating all positions of vast IOT nodes, a device called the power and data beacon (PDB) is proposed. This acts as a relay station for energy and data. In addition, we model future scenes in which a communication system is assisted by unmanned aerial vehicles (UAVs), large intelligent surfaces (LISs), and PDBs. In this paper, we propose and solve the problem of determining the optimal flight trajectory to reach the minimum energy consumption or minimum time consumption. Four future feasible scenes are analyzed and then the optimization problems are solved based on numerical algorithms. Simulation results show that there are significant performance improvements in energy/time with the deployment of LISs and reasonable UAV trajectory planning.

scholarly journals Identification Conditions for the Solvability of NP-complete Problems for the Class of Pre-fractal Graphs

2021 ◽  
Vol 28 (2) ◽  
pp. 126-135
Author(s):  
Aleksandr Vasil'evich Tymoshenko ◽  
Rasul Ahmatovich Kochkarov ◽  
Azret Ahmatovich Kochkarov
Keyword(s):  
Communication Networks ◽  
Hamiltonian Cycle ◽  
Optimization Problems ◽  
Independent Set ◽  
Network Systems ◽  
Logistics Networks ◽  
Complete Problems ◽  
Discrete Problems ◽  
Np Complete ◽  
Discrete Optimization Problems

Modern network systems (unmanned aerial vehicles groups, social networks, network production chains, transport and logistics networks, communication networks, cryptocurrency networks) are distinguished by their multi-element nature and the dynamics of connections between its elements. A number of discrete problems on the construction of optimal substructures of network systems described in the form of various classes of graphs are NP-complete problems. In this case, the variability and dynamism of the structures of network systems leads to an "additional" complication of the search for solutions to discrete optimization problems. At the same time, for some subclasses of dynamical graphs, which are used to model the structures of network systems, conditions for the solvability of a number of NP-complete problems can be distinguished. This subclass of dynamic graphs includes pre-fractal graphs. The article investigates NP-complete problems on pre-fractal graphs: a Hamiltonian cycle, a skeleton with the maximum number of pendant vertices, a monochromatic triangle, a clique, an independent set. The conditions under which for some problems it is possible to obtain an answer about the existence and to construct polynomial (when fixing the number of seed vertices) algorithms for finding solutions are identified.

scholarly journals Integration of biosensor to a window-based control system for user emotion detection to static and dynamic visual contents of webpages

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fatima M. Isiaka ◽  
Awwal Adamu ◽  
Zainab Adamu
Keyword(s):  
Control System ◽  
Eye Movement ◽  
User Experience ◽  
Completion Time ◽  
Dynamic Control ◽  
Task Completion ◽  
Time Interval ◽  
Task Completion Time ◽  
Content Type ◽  
Dynamic Control System

Purpose Basic capturing of emotion on user experience of web applications and browsing is important in many ways. Quite often, online user experience is studied via tangible measures such as task completion time, surveys and comprehensive tests from which data attributes are generated. Prediction of users’ emotion and behaviour in some of these cases depends mostly on task completion time and number of clicks per given time interval. However, such approaches are generally subjective and rely heavily on distributional assumptions making the results prone to recording errors. This paper aims to propose a novel method – a window dynamic control system – that addresses the foregoing issues. Design/methodology/approach Primary data were obtained from laboratory experiments during which 44 volunteers had their synchronized physiological readings – skin conductance response, skin temperature, eye movement behaviour and users activity attributes taken by biosensors. The window-based dynamic control system (PHYCOB I) is integrated to the biosensor which collects secondary data attributes from these synchronized physiological readings and uses them for two purposes: for detection of both optimal emotional responses and users’ stress levels. The method’s novelty derives from its ability to integrate physiological readings and eye movement records to identify hidden correlates on a webpage. Findings The results from the analyses show that the control system detects basic emotions and outperforms other conventional models in terms of both accuracy and reliability, when subjected to model comparison – that is, the average recoverable natural structures for the three models with respect to accuracy and reliability are more consistent within the window-based control system environment than with the conventional methods. Research limitations/implications Graphical simulation and an example scenario are only provided for the control’s system design. Originality/value The novelty of the proposed model is its strained resistance to overfitting and its ability to automatically assess user emotion while dealing with specific web contents. The procedure can be used to predict which contents of webpages cause stress-induced emotions to users.

scholarly journals Algorithms for Weighted Independent Transversals and Strong Colouring

2022 ◽  
Vol 18 (1) ◽  
pp. 1-16
Author(s):  
Alessandra Graf ◽  
David G. Harris ◽  
Penny Haxell
Keyword(s):  
Existence Theorems ◽  
Sufficient Conditions ◽  
Randomized Algorithm ◽  
Independent Set ◽  
Deterministic Algorithm ◽  
Efficient Algorithms ◽  
Combinatorial Problems ◽  
Vertex Partition ◽  
Partition Class ◽  
Strong Chromatic Number

An independent transversal (IT) in a graph with a given vertex partition is an independent set consisting of one vertex in each partition class. Several sufficient conditions are known for the existence of an IT in a given graph and vertex partition, which have been used over the years to solve many combinatorial problems. Some of these IT existence theorems have algorithmic proofs, but there remains a gap between the best existential bounds and the bounds obtainable by efficient algorithms. Recently, Graf and Haxell (2018) described a new (deterministic) algorithm that asymptotically closes this gap, but there are limitations on its applicability. In this article, we develop a randomized algorithm that is much more widely applicable, and demonstrate its use by giving efficient algorithms for two problems concerning the strong chromatic number of graphs.

scholarly journals Traffic optimization in IoT networks

2021 ◽  
Vol 229 ◽  
pp. 01050
Author(s):  
Hassan Ouahi ◽  
Abdenbi Mazoul
Keyword(s):  
Internet Of Things ◽  
Optimization Problems ◽  
The Internet ◽  
Data Traffic ◽  
All Optical ◽  
Machine Communication ◽  
Tools And Techniques ◽  
Traffic Optimization ◽  
The Internet Of Things ◽  
Important Activity

Since the 2000s, the idea that the Internet could be used for machine-to-machine communication and process automation has emerged. Together with the development of electronic objects capable of communicating with IP protocols, this idea led to the concept of the Internet of Things (IoT Internet of Things). Nowadays, the evolution of networks is very intense. New networks are appearing, “all-optical” solutions in the heart of networks, “wireless” solutions to facilitate access to users or to implant sensors / actors in places difficult to access, or finally the Internet of communicating objects. In this evolution, new scientific issues and challenges are emerging. Some of the problems are related to the optimization of generated traffic as well as the improvement of the performance of tools and techniques. Often, these optimization problems lead to models using graphs. The analysis of optimization problems in networks is an important activity. IOT networks create more data traffic that is difficult to control within the operator’s network. The method given in this paper will help network operators optimize their networks and assist developers in improving hardware and software interactions to reduce data traffic in the network.

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