scholarly journals GWS—A Collaborative Load-Balancing Algorithm for Internet-of-Things

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2479 ◽  
Author(s):  
Hongyu Xiao ◽  
Zhenjiang Zhang ◽  
Zhangbing Zhou
Keyword(s):  
Load Balancing ◽  
Scheduling Algorithm ◽  
Fog Computing ◽  
Nash Bargaining Solution ◽  
Nash Bargaining ◽  
Bargaining Solution ◽  
Time Sharing ◽  
Work Stealing ◽  
The Game Theory ◽  
Load Balancing Algorithm

This paper firstly replaces the first-come-first-service (FCFS) mechanism with the time-sharing (TS) mechanism in fog computing nodes (FCNs). Then a collaborative load-balancing algorithm for the TS mechanism is proposed for FCNs. The algorithm is a variant of a work-stealing scheduling algorithm, and is based on the Nash bargaining solution (NBS) for a cooperative game between FCNs. Pareto optimality is achieved through the collaborative working of FCNs to improve the performance of every FCN. Lastly the simulation results demonstrate that the game-theory based work-stealing algorithm (GWS) outperforms the classical work-stealing algorithm (CWS).

Research on fog Resource Scheduling based on Cloud-fog Collaboration Technology in the Electric Internet of Things

2021 ◽  
Vol 14 ◽  
Author(s):  
Youchan Zhu ◽  
Yingzi Wang ◽  
Weixuan Liang
Keyword(s):  
Internet Of Things ◽  
Load Balancing ◽  
Response Time ◽  
Scheduling Algorithm ◽  
Fog Computing ◽  
Resource Scheduling ◽  
Previous Method ◽  
Collaboration Technology ◽  
Iot Devices ◽  
Load Balancing Algorithm

Background: With the further development of electric Internet of things (eIoT), IoT devices in the distributed network generate data with different frequencies and types. Objective: Fog platform is located between the smart collected terminal and cloud platform, and the resources of fog computing are limited, which affects the delay of service processing time and response time. Methods: In this paper, an algorithm of fog resource scheduling and load balancing is proposed. First, the fog devices divide the tasks into high or low priority. Then, the fog management nodes cluster the fog nodes through K-mean+ algorithm and implement the earliest deadline first dynamic (EDFD) task scheduling algorithm and De-REF neural network load balancing algorithm. Results: We use tools to simulate the environment, and the results show that this method has strong advantages in -30% response time, -50% scheduling time, delay, -50% load balancing rate and energy consumption, which provides a better guarantee for eIoT. Conclusion: Resource scheduling is important factor affecting system performance. This article mainly addresses the needs of eIoT in terminal network communication delay, connection failure, and resource shortage. And the new method of resource scheduling and load balancing is proposed, The evaluation was performed and proved that our proposed algorithm has better performance than the previous method, which brings new opportunities for the realization of eIoT.

scholarly journals Rogun – Hydropower Generating Controversy in Central Asia

2014 ◽  
Vol 62 (6) ◽  
pp. 1353-1361
Author(s):  
Lea Melnikovová ◽  
Bohumil Havrland ◽  
Radim Valenčík
Keyword(s):  
Water Resources ◽  
Water Allocation ◽  
Negative Impact ◽  
Nash Bargaining Solution ◽  
Nash Bargaining ◽  
Bargaining Solution ◽  
Transboundary Water ◽  
The Game Theory ◽  
International Water Law ◽  
International Water

The aim of this paper is to analyse the current conflict between Uzbekistan and Tajikistan over shared water resources, and propose an adequate solution. The tensions between the two countries are associated with the completion of a huge dam on a river on the Tajik territory. Such construction may have a negative impact on Uzbekistan’s irrigation needs since it may restrict inflow to the Amudarya River which is Uzbekistan’s key water resource. While Tajikistan intends to use water for hydropower, Uzbekistan needs water mainly for its cotton fields. This paper analyses the background, benefits and risks of the dam, roots of the tension, and suggests methods of resolving them. Based on the current dispute, the problem of shared water resources is generalized, discussed and two complementary approaches are presented. The international water law offers a set of guidelines applicable on transboundary water conflicts; the significance of the 1997 UN Convention concerning the law of the non-navigational uses of international watercourses is emphasized. Another instrument to grasp this problem is the game theory. The water allocation problem can be described using the Nash bargaining solution. This paper demonstrates that both approaches can contribute to resolving existing disputes over shared water resources.

The (Stabilized) Nash Bargaining Solution as a Principle of Distributive Justice

Utilitas ◽  
2010 ◽  
Vol 22 (4) ◽  
pp. 447-473 ◽  
Author(s):  
MICHAEL MOEHLER
Keyword(s):  
Distributive Justice ◽  
Moral Reasoning ◽  
Bargaining Power ◽  
Nash Bargaining Solution ◽  
Nash Bargaining ◽  
Original Position ◽  
Bargaining Solution ◽  
Moral Intuitions ◽  
Instrumental Reasoning ◽  
Relative Bargaining Power

It is argued that the Nash bargaining solution cannot serve as a principle of distributive justice because (i) it cannot secure stable cooperation in repeated interactions and (ii) it cannot capture our moral intuitions concerning distributive questions. In this article, I propose a solution to the first problem by amending the Nash bargaining solution so that it can maintain stable cooperation among rational bargainers. I call the resulting principle the stabilized Nash bargaining solution. The principle defends justice in the form ‘each according to her basic needs and above this level according to her relative bargaining power’. In response to the second problem, I argue that the stabilized Nash bargaining solution can serve as a principle of distributive justice in certain situations where moral reasoning is reduced to instrumental reasoning. In particular, I argue that rational individuals would choose the stabilized Nash bargaining solution in Rawls’ original position.

Dynamic Subcarrier and Power Allocation Based on Nash Bargaining Solution in Symmetric Cooperative OFDMA Networks

2011 ◽  
Vol 187 ◽  
pp. 510-515
Author(s):  
Wei Liu ◽  
Jing Min Tang
Keyword(s):  
Power Allocation ◽  
Nash Bargaining Solution ◽  
Nash Bargaining ◽  
Bargaining Solution ◽  
Subcarrier Allocation ◽  
Allocation Scheme ◽  
Allocation Algorithm ◽  
Cooperative Scheme ◽  
Joint Resource Allocation ◽  
Adaptive Power

In this paper, subcarrier and power allocation are jointly considered in a three-node symmetric cooperation orthogonal frequency-division multiple access uplink system. With the help of Nash bargaining solution, the dynamic subcarrier allocation scheme and the adaptive power allocation scheme are proposed for joint optimization. The joint resource allocation is decomposed and solved by dynamic subcarrier allocation algorithm and adaptive power allocation algorithm. Simulation results show the effectiveness of the proposed cooperative scheme.

scholarly journals Raiffa-Kalai-Smorodinsky Bargaining Solution for Bilateral Contracts in Electricity Markets

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2397
Author(s):  
Reinaldo Crispiniano Garcia ◽  
Javier Contreras ◽  
Matheus de Lima Barbosa ◽  
Felipe Silva Toledo ◽  
Paulo Vinicius Aires da Cunha
Keyword(s):  
Electricity Markets ◽  
Price Volatility ◽  
Spot Market ◽  
Nash Bargaining Solution ◽  
Nash Bargaining ◽  
Bargaining Solution ◽  
Market Pricing ◽  
Bilateral Contracts ◽  
Generation Company

In electricity markets, bilateral contracts (BC) are used to hedge against price volatility in the spot market. Pricing these contracts requires scheduling from either the buyer or the seller aiming to achieve the highest profit possible. Since this problem includes different players, a Generation Company (GC) and an Electricity Supplier Company (ESC) are considered. The approaches to solve this problem include the Nash Bargaining Solution (NBS) equilibrium and the Raiffa–Kalai–Smorodinsky (RKS) bargaining solution. The innovation of this work is the implementation of an algorithm based on the RKS equilibrium to find a compromise strategy when determining the concessions to be made by the parties. The results are promising and show that the RKS approach can obtain better results compared to the Nash equilibrium method applied to a case study.

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