Application of the multiple resources questionnaire (MRQ) to a complex gaming environment

2004 ◽  
Author(s):  
David B. Boles ◽  
Jeffrey B. Phillips ◽  
Jason R. Perdelwitz ◽  
Jonathan H. Bursk
Keyword(s):  
Multiple Resources ◽  
Gaming Environment

Application of the Multiple Resources Questionnaire (MRQ) to a Complex Gaming Environment

2004 ◽  
Vol 48 (16) ◽  
pp. 1968-1972 ◽  
Author(s):  
David B. Boles ◽  
Jeffrey B. Phillips ◽  
Jason R. Perdelwitz ◽  
Jonathan H. Bursk
Keyword(s):  
Multiple Resources ◽  
Gaming Environment

scholarly journals Multiple Resources Planning in Microgrid Based on Modeling Demand Response of User Side

2021 ◽  
Vol 634 (1) ◽  
pp. 012048
Author(s):  
Si-cong Wang ◽  
Qi-xin Wang ◽  
Zi-xia Sang ◽  
Ji-feng He ◽  
Jia-qi Huang ◽  
...  
Keyword(s):  
Demand Response ◽  
Multiple Resources ◽  
Resources Planning

scholarly journals IoT Resource Allocation and Optimization Based on Heuristic Algorithm

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 539 ◽  
Author(s):  
Arun Kumar Sangaiah ◽  
Ali Asghar Rahmani Hosseinabadi ◽  
Morteza Babazadeh Shareh ◽  
Seyed Yaser Bozorgi Rad ◽  
Atekeh Zolfagharian ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Distributed System ◽  
Communication Cost ◽  
The Internet ◽  
Multiple Resources ◽  
Whale Optimization ◽  
Total Communication ◽  
The Internet Of Things ◽  
Proper Performance ◽  
Better Than

The Internet of Things (IoT) is a distributed system that connects everything via internet. IoT infrastructure contains multiple resources and gateways. In such a system, the problem of optimizing IoT resource allocation and scheduling (IRAS) is vital, because resource allocation (RA) and scheduling deals with the mapping between recourses and gateways and is also responsible for optimally allocating resources to available gateways. In the IoT environment, a gateway may face hundreds of resources to connect. Therefore, manual resource allocation and scheduling is not possible. In this paper, the whale optimization algorithm (WOA) is used to solve the RA problem in IoT with the aim of optimal RA and reducing the total communication cost between resources and gateways. The proposed algorithm has been compared to the other existing algorithms. Results indicate the proper performance of the proposed algorithm. Based on various benchmarks, the proposed method, in terms of “total communication cost”, is better than other ones.

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