A Case Study on Auction-Based Task Allocation Algorithms in Multi-Satellite Systems

2021 ◽  
Author(s):  
Sean Phillips ◽  
Fernando Parra
Keyword(s):  
Task Allocation ◽  
Satellite Systems ◽  
Allocation Algorithms

Evaluation and Comparison of Task Allocation Algorithms for Mesh Networks

2010 ◽  
Author(s):  
Rafal Kaminski ◽  
Leszek Koszalka ◽  
Iwona Pozniak-Koszalka ◽  
Andrzej Kasprzak
Keyword(s):  
Task Allocation ◽  
Mesh Networks ◽  
Allocation Algorithms

scholarly journals ER-2 High Altitude Reconnaissance: A Case Study

1990 ◽  
Vol 66 (5) ◽  
pp. 480-486 ◽  
Author(s):  
W. Moore ◽  
T. Polzin
Keyword(s):  
Information System ◽  
Natural Resources ◽  
High Altitude ◽  
National Park ◽  
Effective Means ◽  
Data Entry ◽  
Cost Effective ◽  
Earth Satellite ◽  
Satellite Systems

There is an increasing requirement for a cost-effective means of updating digital base map and natural resources information systems. The Northern Forestry Centre of Forestry Canada is cooperating with Alberta Forestry, Lands and Wildlife and United States agencies to evaluate ER-2 high altitude (i.e., about 20 km) reconnaissance in Alberta. A demonstration flight was arranged on 20 July 1988 to cover flight lines from Waterton Lakes National Park to Lesser Slave Lake, and return (i.e., about 1500 km). The ER-2 platform provides both the high altitude perspective of earth satellite systems and the flexibilities of aircraft. The demonstration flight carried a panoramic camera, two mapping cameras and a digital scanner that were operated simultaneously. This provided rapid, high resolution and stereoscopic coverage of large areas. The savings from improved efficiencies for base map revisions alone, using one mapping camera were greater than the costs of routine ER-2 operations over Alberta. The three other selectable sensors would also permit natural resources information system updates for only the costs of processing, interpretation and data entry. These high altitude capabilities are required for forestry in Canada.

scholarly journals GNSS Interference Environment in Malaysia: A Case Study

2021 ◽  
Vol 3 (1) ◽  
pp. 13-16
Author(s):  
Ooi Wei Han ◽  
Shahrizal Ide Moslin ◽  
Wan Aminullah
Keyword(s):  
Public Awareness ◽  
Essential Element ◽  
Global Navigation Satellite Systems ◽  
Space Technology ◽  
Local Study ◽  
Satellite Systems ◽  
Wide Range ◽  
Global Navigation Satellite ◽  
Significant Interference

Global Navigation Satellite Systems or GNSS is a space technology that has become an essential element nowadays for positioning, navigation & timing (PNT) with wide range of applications in many civilian sectors as well as across military. The reliability, accuracy and availability of GNSS are highly important especially for critical and precise positioning applications. However, the signals from space are weak and it can be easily blocked, disrupted or compromised by several other threats including intentional and unintentional interferences or jamming. GPS jammer is widely available off the shelf with an affordable price and capable of interfering the GPS signal, and many authorities worldwide have raised concerns and a lot of efforts and research have been put in place to reduce and mitigate the threats. In Malaysia, understanding and countering threats to GNSS/GPS based applications will be a new and unfamiliar discipline for public and organizations. This study intended to provide an overview of the GNSS interferences environment in a local study area, in terms of interference type and the number of activity pattern that were detected. A system called Detector V1 has been used in this study. The result showed that significant interference cases happened in the study area and some of the high power interferences may impact GNSS tracking and precision of the positioning output. The role objective of having this done is to create a public awareness regarding the threat of GNSS interferences to the local users. The content also includes the proposed initiative to overcome the issue.

scholarly journals SMF-GA: Optimized Multitask Allocation Algorithm in Urban Crowdsourced Transportation

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Pengfei Wang ◽  
Ruiyun Yu
Keyword(s):  
Genetic Algorithm ◽  
Greedy Algorithm ◽  
Task Allocation ◽  
Large Scale ◽  
Hard Problem ◽  
Optimal Result ◽  
Real Dataset ◽  
Np Hard Problem ◽  
Allocation Algorithms ◽  
Real Vehicle

Urban crowdsourced transportation, which can solve traffic problem within city, is a new scenario where citizens share vehicles to take passengers and packages while driving. Differing from the traditional location based crowdsourcing system (e.g., crowdsensing system), the task has to be completed with visiting two different locations (i.e., start and end points), so task allocation algorithms in crowdsensing cannot be leveraged in urban crowdsourced transportation directly. To solve this problem, we first prove that maximizing the crowdsourcing system’s profit (i.e., maximizing the total saved distance) is an NP-hard problem. We propose a heuristic greedy algorithm called Saving Most First (SMF) which is simple and effective in assigning tasks. Then, an optimized SMF based genetic algorithm (SMF-GA) is devised to jump out of the local optimal result. Finally, we demonstrate the performance of SMF and SMF-GA with extensive evaluations, based on a large scale real vehicle traces. The evaluation with large scale real dataset indicates that both SMF and SMF-GA algorithms outperform other benchmark algorithms in terms of saved distance, participant profits, etc.

scholarly journals A Cloudware Architecture for Collaboration of Multiple AGVs in Indoor Logistics: Case Study in Fabric Manufacturing Enterprises

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2023
Author(s):  
Fatih Okumuş ◽  
Emrah Dönmez ◽  
Adnan Fatih Kocamaz
Keyword(s):  
Collision Avoidance ◽  
Task Allocation ◽  
Simulation Software ◽  
Working Environment ◽  
Automated Guided Vehicles ◽  
Cloud System ◽  
Problem Model ◽  
Logistics Systems ◽  
Optimum Path

In Industry 4.0 compatible workshops, the demand for Automated Guided Vehicles (AGVs) used in indoor logistics systems has increased remarkably. In these indoor logistics systems, it may be necessary to execute multiple transport tasks simultaneously using multiple AGVs. However, some challenges require special solutions for AGVs to be used in industrial autonomous transportation. These challenges can be addressed under four main headings: positioning, optimum path planning, collision avoidance and optimum task allocation. The solutions produced for these challenges may require special studies that vary depending on the type of tasks and the working environment in which AGVs are used. This study focuses on the problem of automated indoor logistics carried out in the simultaneous production of textile finishing enterprises. In the study, a centralized cloud system that enables multiple AGVs to work in collaboration has been developed. The finishing enterprise of a denim manufacturing factory was handled as a case study and modelling of mapping-planning processes was carried out using the developed cloud system. In the cloud system, RestFul APIs, for mapping the environment, and WebSocket methods, to track the locations of AGVs, have been developed. A collaboration module in harmony with the working model has been developed for AGVs to be used for fabric transportation. The collaboration module consists of task definition, battery management-optimization, selection of the most suitable batch trolleys (provides mobility of fabrics for the finishing mills), optimum task distribution and collision avoidance stages. In the collaboration module, all the finishing processes until the product arrives the delivery point are defined as tasks. A task allocation algorithm has been developed for the optimum performance of these tasks. The multi-fitness function that optimizes the total path of the AGVs, the elapsed time and the energy spent while performing the tasks have been determined. An assignment matrix based on K nearest neighbor (k-NN) and permutation possibilities was created for the optimal task allocation, and the most appropriate row was selected according to the optimal path totals of each row in the matrix. The D* Lite algorithm has been used to calculate the optimum path between AGVs and goals by avoiding static obstacles. By developing simulation software, the problem model was adapted and the operation of the cloud system was tested. Simulation results showed that the developed cloud system was successfully implemented. Although the developed cloud system has been applied as a case study in fabric finishing workshops with a complex structure, it can be used in different sectors as its logistic processes are similar.

scholarly journals The Optimal Location of Ground-Based GNSS Augmentation Transceivers

Geosciences ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 107 ◽  
Author(s):  
Jacek Rapinski ◽  
Artur Janowski
Keyword(s):  
Wide Band ◽  
Optimal Location ◽  
Point Of View ◽  
Global Navigation Satellite Systems ◽  
Design Stage ◽  
Shift Measurement ◽  
Satellite Systems ◽  
Global Navigation Satellite ◽  
Selection Of

Modern Global Navigation Satellite Systems (GNSS) allow for positioning with accuracies ranging from tens of meters to single millimeters depending on user requirements and available equipment. A major disadvantage of these systems is their unavailability or limited availability when the sky is obstructed. One solution is to use additional range measurements from ground-based nodes located in the vicinity of the receiver. The highest accuracy of distance measurement can be achieved using ultra wide band (UWB) or ZigBee phase shift measurement. The position of the additional transmitter must be carefully selected in order to obtain the optimal improvement in the dilution of precision (DOP), which reflects the improvement in the geometry of solution. The presented case study depicts a method for selecting the optimal location of a ground-based ranging source. It is based on a search of a minimum DOP value as a transmitter location function. The parameters of objective function are the elevation and azimuth of the transceiver. The solution was based on a limited-memory Broyden–Fletcher–Goldfarb–Shanno with Box constraints (L-BFGS-B) method and a numerical optimization algorithm for parameter value estimation. The presented approach allows for the selection of the optimal location of a ground-based source of ranging signals in GNSS processing from a geometry of solution point of view. This can be useful at the design stage of an augmentation network of ground-based transceivers. This article presents a theoretical basis and a case study presenting the selection of the optimal location of a ground-based ranging source.

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