scholarly journals Nash Bargaining Solution as Negotiation Concept for Resource Allocation Problem with Groves-Ledyard Mechanism

2021 ◽  
Vol 14 ◽  
pp. 216-226
Author(s):  
Nikolay A. Korgin ◽  
◽  
Vsevolod O. Korepanov ◽  
Keyword(s):  
Experimental Data ◽  
Resource Allocation ◽  
Nash Bargaining Solution ◽  
Allocation Problem ◽  
Nash Bargaining ◽  
Bargaining Solution ◽  
Resource Allocation Problem ◽  
Proportional Allocation ◽  
Best Response ◽  
Behavior Models

Motivated by research works on Zeuthen-Hicks bargaining, which leads to the Nash bargaining solution, we analyze experimental data of resource allocation gaming with Groves-Ledyard mechanism. The games were designed in the form of negotiation to allow players to reach consensus. Behavior models based on best response, constant behavior, and Nash bargaining solution are defined. Analysis conducted over decisions made by participants shows that a significant share of all decisions leads to an increase of the Nash bargaining value. It is even higher than the share of decisions that are in agreement with the best-response concept. Consensusended games show light attraction to the Nash bargaining solution, it's less than we obtained in games with the mechanism of Yang-Hajek from another class of so-called proportional allocation mechanisms. We discuss differences of consensus-ended games from timeout-ended games, what decisions lead to the situations with the Nash bargaining value increasing and differences between balanced mechanism Groves-Ledyard and unbalanced mechanism Yang-Hajek.

scholarly journals Nash bargaining solution as negotiation concept for resource allocation problem: analysis of experimental data

2020 ◽  
Vol 13 ◽  
pp. 207-217
Author(s):  
Nikolay A. Korgin ◽  
◽  
Vsevolod O. Korepanov ◽  
Keyword(s):  
Resource Allocation ◽  
Nash Bargaining Solution ◽  
Negotiation Process ◽  
Nash Bargaining ◽  
Problem Analysis ◽  
Bargaining Solution ◽  
Proportional Allocation ◽  
Best Response ◽  
Behavior Models ◽  
Analyze Data

Motivated by research works on Zeuthen-Hicks bargaining, which leads to the Nash bargaining solution (Vetschera, 2018), we analyze data obtained during experimental resource allocation gaming with Yang-Hajek's mechanism from the class of proportional allocation mechanisms. Games were designed in the form of negotiation to allow players to reach consensus. Behavior models based on best response, constant behavior, and Nash bargaining solution are defined. Analysis conducted over decisions made by participants shows that a significant share of all decisions leads to an increase of Nash bargaining value. It is even higher than the share of decisions that are in agreement with the best-response concept. Consensus-ended games show more but subtle attraction to Nash bargaining solution behavior. We discuss how these decisions correspond with other types of behavior actively exhibited by participants of this experiments — so-called constant behavior and with the end of negotiation process in games.

Resource allocation based on overall equipment effectiveness using cooperative game

Kybernetes ◽  
2019 ◽  
Vol 49 (3) ◽  
pp. 819-834 ◽  
Author(s):  
Seyed Hadi Mousavi-Nasab ◽  
Jalal Safari ◽  
Ashkan Hafezalkotob
Keyword(s):  
Resource Allocation ◽  
Optimal Allocation ◽  
Rank Correlation ◽  
Nash Bargaining Solution ◽  
Nash Bargaining ◽  
Bargaining Solution ◽  
Content Type ◽  
Spearman’S Rank Correlation ◽  
Spearman’S Rank Correlation Coefficient ◽  
Topsis Technique

Purpose Resource allocation has always been a critical problem with significant economic relevance. Many industries allocate the resources based on classical methods such as overall equipment effectiveness (OEE) and data envelopment analysis (DEA). The lack of OEE factors’ weight, how it is defined, analyzed, interpreted and compared in OEE and selection of unrealistic weights, self-appraisal and disability of complete ranking in DEA are challenges that are possible to occur. These defects may result in unfair allocation of the resources. This study aims to overcome the mentioned weaknesses. Design/methodology/approach In this paper, an approach using a set of various DEA models and Nash bargaining solution (NBS) is designed to solve the resource allocation problem based on OEE, among a set of comparable and uniform DMUs (decision-making units) in a fair way. Findings The results show that a unique Pareto optimal allocation solution is obtained by the proposed DEA–NBS model among the DMUs. This allocation is more acceptable for players, because the allocation results are commonly determined by all DMUs rather than a specific one. Furthermore, the rankings achieved by the utilized methods and TOPSIS (technique for order preference by similarity to ideal solution) are compared by Spearman’s rank correlation coefficient to validate the resource allocation plan. The findings indicate that the DEA–NBS method has the best correlation with the TOPSIS approach. Originality/value To the best of authors’ knowledge, no research has considered the use of DEA and NBS with OEE.

scholarly journals Resource Allocation in a Generalized Framework for Virtualized Heterogeneous Wireless Network

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Bo Fan ◽  
Hui Tian ◽  
Yuan Zhang ◽  
Xiao Yan
Keyword(s):  
Resource Allocation ◽  
Wireless Network ◽  
Service Providers ◽  
Nash Bargaining Solution ◽  
Nash Bargaining ◽  
Bargaining Solution ◽  
Heterogeneous Wireless Network ◽  
Network Access ◽  
Medium Access ◽  
Resource Allocation Algorithm

As a prevailing concept in 5G, virtualization provides efficient coordination among multiple radio access technologies (RATs) and enables multiple service providers (SPs) to share different RATs’ infrastructure. This paper proposes a generic framework for virtualizing heterogeneous wireless network with different RATs. A novel “VMAC” (virtualized medium access control) concept is introduced to converge different RAT protocols and perform inter-RAT resource allocation. To suit the proposed framework, a virtualization based resource allocation scheme is devised. We formulate the problem as a mixed combinatorial optimization, which jointly considers network access and rate allocation. First, to solve the network access problem, “adaptability ratio” is developed to model the fact that different RATs possess different adaptability to different services. And a Grey Relational Analysis (GRA) method is adopted to calculate the adaptability ratio. Second, services are modeled as players, bargaining for RAT resources in a Nash bargaining game. And a closed-form Nash bargaining solution (NBS) is derived. Combining adaptability ratio with NBS, a novel resource allocation algorithm is devised. Through simulation, the superiority and feasibility of the proposed algorithm are validated.

scholarly journals A Hierarchical Resource Allocation Scheme Based on Nash Bargaining Game in VANET

Information ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 196
Author(s):  
Xiaoshuai Zhao ◽  
Xiaoyong Zhang ◽  
Yingjuan Li
Keyword(s):  
Resource Allocation ◽  
Bargaining Game ◽  
Allocation Problem ◽  
Nash Bargaining ◽  
Resource Allocation Problem ◽  
Allocation Scheme ◽  
Computational Overhead ◽  
Nash Bargaining Game ◽  
The Difference ◽  
Resource Allocation Scheme

Due to the selfishness of vehicles and the scarcity of spectrum resources, how to realize fair and effective spectrum resources allocation has become one of the primary tasks in VANET. In this paper, we propose a hierarchical resource allocation scheme based on Nash bargaining game. Firstly, we analyze the spectrum resource allocation problem between different Road Side Units (RSUs), which obtain resources from the central cloud. Thereafter, considering the difference of vehicular users (VUEs), we construct the matching degree index between VUEs and RSUs. Then, we deal with the spectrum resource allocation problem between VUEs and RSUs. To reduce computational overhead, we transform the original problem into two sub-problems: power allocation and slot allocation, according to the time division multiplexing mechanism. The simulation results show that the proposed scheme can fairly and effectively allocate resources in VANET according to VUEs’ demand.

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