Research on Optimized Online Allocation of Scope Spatial Crowdsourcing Tasks

2020 ◽  
Vol 29 (03) ◽  
pp. 2050003
Author(s):  
Liping Gao ◽  
Kun Dai ◽  
Chao Lu
Keyword(s):  
Greedy Algorithm ◽  
Task Allocation ◽  
Specific Task ◽  
Spatial Crowdsourcing ◽  
Two Phase ◽  
Allocation Algorithm ◽  
Sensing Data ◽  
Important Branch ◽  
The Greedy Algorithm

Task allocation of spatial crowdsourcing tasks is an important branch of crowdsourcing. Spatial crowdsourcing tasks not only require workers to complete a specific task at a specified time, but also require users to go to the designated location to complete the corresponding tasks. In this paper, Scope spatial crowdsourcing task whose work position is a region rather than a location is a kind of spatial crowdsourcing task. Mobile crowdsourced sensing (MCS) is one of the most important platforms to publish spatial crowdsourcing tasks, based on which MCS workers can use smartphones to complete the collections of related sensing data. When assigning tasks for scoped crowdsourcing tasks, there is a scope overlap between tasks and one or more tasks due to the association of task scope between tasks, which causes a waste of manpower. The focus of this paper is to study the redundancy of the task scope that occurs when using MCS to collect scoping data in the case of fewer workers and more tasks. Optimizing scope spatial crowdsourcing tasks allocation algorithm (OSSA) can eliminate the redundancy of the task area by integrating and decomposing tasks and achieve the improvement of the assignable number of tasks. In the Windows platform, experiments are made to compare the efficiency of the OSSA algorithm with the greedy algorithm and the two-phase-based global online allocation (TGOA) algorithm to further prove the correctness and feasibility of the algorithm for task scope optimization.

Adaptive Bit Allocation Algorithm for OFDM System

2014 ◽  
Vol 989-994 ◽  
pp. 2161-2164
Author(s):  
Wei Wei ◽  
Wen Dong An
Keyword(s):  
Greedy Algorithm ◽  
Bit Error Rate ◽  
Data Transmission ◽  
Transmission Rate ◽  
Bit Allocation ◽  
Total Power ◽  
Ofdm System ◽  
Allocation Algorithm ◽  
The Greedy Algorithm ◽  
Number Of Iterations

For the greedy algorithm required a large number of iterations, this paper proposed one adaptive bit allocation algorithm based on Hughes-Hartogs algorithm which was improved greedy algorithm .Under the constraint of bit error rate and data transmission rate, the algorithm first used the Chow algorithm to allocate some of the bits, and then used the greedy algorithm to allocate the remaining bits. When minimize the total power by this algorithm, the iterations of this algorithm were significantly less than the greedy algorithm. By computer simulation, the results showed that performance of this algorithm was very close to the greedy algorithm, and the number of this algorithm’s iterations was 7.4%~34% of the greedy algorithm.

Implementasi Algoritma Dijkstra Pada Game Pacman

CCIT Journal ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 170-176
Author(s):  
Anggit Dwi Hartanto ◽  
Aji Surya Mandala ◽  
Dimas Rio P.L. ◽  
Sidiq Aminudin ◽  
Andika Yudirianto
Keyword(s):  
Artificial Intelligence ◽  
Greedy Algorithm ◽  
Dijkstra Algorithm ◽  
Testing Phase ◽  
A Value ◽  
Route Problem ◽  
Starting Point ◽  
The Greedy Algorithm

Pacman is one of the labyrinth-shaped games where this game has used artificial intelligence, artificial intelligence is composed of several algorithms that are inserted in the program and Implementation of the dijkstra algorithm as a method of solving problems that is a minimum route problem on ghost pacman, where ghost plays a role chase player. The dijkstra algorithm uses a principle similar to the greedy algorithm where it starts from the first point and the next point is connected to get to the destination, how to compare numbers starting from the starting point and then see the next node if connected then matches one path with the path). From the results of the testing phase, it was found that the dijkstra algorithm is quite good at solving the minimum route solution to pursue the player, namely by getting a value of 13 according to manual calculations

scholarly journals An Optimized Algorithm and Test Bed for Improvement of Efficiency of ESS and Energy Use

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 388 ◽  
Author(s):  
Seung-Mo Je ◽  
Jun-Ho Huh
Keyword(s):  
Greedy Algorithm ◽  
Energy Use ◽  
Storage System ◽  
Lithium Ion ◽  
Energy Storage System ◽  
Test Bed ◽  
C Language ◽  
Improvement Plan ◽  
The Republic ◽  
The Greedy Algorithm

The Republic of Korea (ROK) has four distinct seasons. Such an environment provides many benefits, but also brings some major problems when using new and renewable energies. The rainy season or typhoons in summer become the main causes of inconsistent production rates of these energies, and this would become a fatal weakness in supplying stable power to the industries running continuously, such as the aquaculture industry. This study proposed an improvement plan for the efficiency of Energy Storage System (ESS) and energy use. Use of sodium-ion batteries is suggested to overcome the disadvantages of lithium-ion batteries, which are dominant in the current market; a greedy algorithm and the Floyd–Warshall algorithm were also proposed as a method of scheduling energy use considering the elements that could affect communication output and energy use. Some significant correlations between communication output and energy efficiency have been identified through the OPNET-based simulations. The simulation results showed that the greedy algorithm was more efficient. This algorithm was then implemented with C-language to apply it to the Test Bed developed in the previous study. The results of the Test Bed experiment supported the proposals.

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