scholarly journals Agent-based Multi-tier SLA Negotiation for Intercloud

2021 ◽  
Author(s):  
Lin Li ◽  
Kaibiao Lin ◽  
Shunzhi Zhu
Keyword(s):  
Negotiation Process ◽  
Fuzzy Membership Function ◽  
Cloud Provider ◽  
Agent Based ◽  
Level Of Satisfaction ◽  
Cloud Resource ◽  
Global Consistency ◽  
Cloud Providers ◽  
Feasible Solutions ◽  
Behavior Preference

Abstract The evolving intercloud enables idle resources to be traded among cloud providers to facilitate optimizing utilization and to improve the cost-effectiveness of service for cloud consumers. However, several challenges are raised for this multi-tier dynamic market, where cloud providers not only compete for consumer requests but also cooperate with each other. To establish a healthier and more efficient intercloud ecosystem, this paper proposed a multi-tier agent-based fuzzy constraint-directed negotiation (AFCN) model for a fully distributed negotiation environment without a broker to coordinate the negotiation process. The novelty of AFCN is the use of a fuzzy membership function to represent imprecise preferences of the agent, which not only reveals the opponent’s behavior preference but can also specify the possibilities prescribing the extent to which the feasible solutions are suitable for the agent’s behavior. Moreover, this information can pass and guide each tier of negotiation to generate a more favorable proposal. Thus, the multi-tier AFCN can not only improve the performance of negotiation, but also enforce global consistency to improve the integrated solution capacity in the intercloud. The experimental results demonstrate that the proposed multi-tier AFCN model outperforms other agent negotiation models and gives full play to the efficiency and scalability of the intercloud in terms of the level of satisfaction, the ratio of successful negotiation, the average revenue of the cloud provider, and the buying price of the unit cloud resource.

scholarly journals Agent-based Multi-tier SLA Negotiation for Intercloud

2021 ◽  
Author(s):  
Lin Li ◽  
Kaibiao Lin ◽  
Shunzhi Zhu
Keyword(s):  
Negotiation Process ◽  
Fuzzy Membership Function ◽  
Cloud Provider ◽  
Agent Based ◽  
Level Of Satisfaction ◽  
Cloud Resource ◽  
Global Consistency ◽  
Cloud Providers ◽  
Feasible Solutions ◽  
Behavior Preference

Abstract The evolving intercloud enables idle resources to be traded among cloud providers to facilitate optimizing utilization and to improve the cost-effectiveness of service for cloud consumers. However, several challenges are raised for this multi-tier dynamic market, where cloud providers not only compete for consumer requests but also cooperate with each other. To establish a healthier and more efficient intercloud ecosystem, this paper proposed a multi-tier agent-based fuzzy constraint-directed negotiation (AFCN) model for a fully distributed negotiation environment without a broker to coordinate the negotiation process. The novelty of AFCN is the use of a fuzzy membership function to represent imprecise preferences of the agent, which not only reveals the opponent’s behavior preference but can also specify the possibilities prescribing the extent to which the feasible solutions are suitable for the agent’s behavior. Moreover, this information can pass and guide each tier of negotiation to generate a more favorable proposal. Thus, the multi-tier AFCN can not only improve the performance of negotiation, but also enforce global consistency to improve the integrated solution capacity in the intercloud. The experimental results demonstrate that the proposed multi-tier AFCN model outperforms other agent negotiation models and gives full play to the efficiency and scalability of the intercloud in terms of the level of satisfaction, the ratio of successful negotiation, the average revenue of the cloud provider, and the buying price of the unit cloud resource.

scholarly journals The Complexity and Simulation of Revenue Sharing Negotiation Based on Construction Stakeholders

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Qingfeng Meng ◽  
Jingxian Chen ◽  
Kun Qian
Keyword(s):  
Success Rate ◽  
Construction Projects ◽  
Revenue Sharing ◽  
Negotiation Process ◽  
Inequity Aversion ◽  
Obvious Effect ◽  
Agent Based ◽  
Time Compression ◽  
Life Cycle Perspective ◽  
Moderate Range

This paper focuses on the complexity characteristics of a stakeholder’s revenue sharing for time compression in construction projects, such as adopting a life cycle perspective, the preferences of stakeholders, and the adaptability behaviors in the negotiation process. We build an agent-based model on revenue sharing negotiation. Considering that the agents who are in a weak position not only care about their own benefits but also compare their benefits to others, we design an experimental scenario where a contractor has fairness preference based on China’s reality. According to different sympathy and envy coefficients, we can divide the inequity aversion preference into three typical types, and we research how a contractor’s different types of inequity aversion preferences impact revenue sharing coefficient of agreements, results of successful negotiations, and efficiency in negotiations. Results are as follows: it is advantageous for a contractor to maintain a modest inequity aversion for their own earnings and the degree of sympathy preference in inequity aversion has an important impact on the time to reach consensus while the degree of jealousy preference has no obvious effect. If contractors’ sympathy preference is maintained within a moderate range, it will achieve a higher success rate of negotiations in the negotiation process; the success rate of negotiation is affected largely by the agents’ sympathy preference, though it is also influenced by the jealousy preference, but it is not very sensitive.

Agen Based Modeling for Corn Supply Chain Risks Identification and Sales Negotiation in PTPN VIII

Jurnal METRIS ◽  
2020 ◽  
Vol 21 (01) ◽  
pp. 1-12
Author(s):  
Syarif Hidayat ◽  
Dyah Ayu Suliandar
Keyword(s):  
Fuzzy Reasoning ◽  
Negotiation Process ◽  
Corn Yield ◽  
Selling Price ◽  
Total Size ◽  
Agent Based ◽  
Business Goals ◽  
Risk Appetite ◽  
Owned Company ◽  
Supply Chain Risks

PTPN VIII is a state-owned company in West Java cultivating several kinds of commodities, and still have three marginal farmlands with a total size of 3000 hectares open for investment for corn. The type of corn that would be produced is corn feed for poultry needs. Three agents are involved in this agent-based model: the farmers (or cooperatives), PTPN VIII, and the buyers of the corn yields. All agents face risks in doing their businesses which hamper or reduce their probability of achieving their business goals. The potential risks are identified using fuzzy reasoning method. The three blocks of farmland have different levels of fertility. Farmers are expected to compete for the hunt of farmland to rent for cultivating corns, until their funds run out. They must prepare the land, procure their best corn seeds, plant and maintain the crops, and eventually harvest, dry and sell their corn yield. The dryness of the corn grains dictates the selling price. The buyers will buy the corns until their demands are fulfilled for the particular season. There will be a negotiation process between agents to reach an agreement. Each agent seeks to achieve its goal. This is why agent-based modelling is employed. Netlogo software is used to develop the model. Based on fuzzy reasoning method the obtained result shows that the most potential risk is quality risk. The negotiation results show that when both buyer and seller experience heightened degree of risk appetite, the shortest negotiations are achieved.

scholarly journals Learning Resource Allocation and Pricing for Cloud Profit Maximization

2019 ◽  
Vol 33 ◽  
pp. 7570-7577 ◽  
Author(s):  
Bingqian Du ◽  
Chuan Wu ◽  
Zhiyi Huang
Keyword(s):  
Resource Allocation ◽  
Optimal Allocation ◽  
Short Term Memory ◽  
Fundamental Problem ◽  
Cloud Provider ◽  
Resource Usage ◽  
Performance Models ◽  
Model Free ◽  
Cloud Resource ◽  
Real World Datasets

Cloud computing has been widely adopted to support various computation services. A fundamental problem faced by cloud providers is how to efficiently allocate resources upon user requests and price the resource usage, in order to maximize resource efficiency and hence provider profit. Existing studies establish detailed performance models of cloud resource usage, and propose offline or online algorithms to decide allocation and pricing. Differently, we adopt a blackbox approach, and leverage model-free Deep Reinforcement Learning (DRL) to capture dynamics of cloud users and better characterize inherent connections between an optimal allocation/pricing policy and the states of the dynamic cloud system. The goal is to learn a policy that maximizes net profit of the cloud provider through trial and error, which is better than decisions made on explicit performance models. We combine long short-term memory (LSTM) units with fully-connected neural networks in our DRL to deal with online user arrivals, and adjust the output and update methods of basic DRL algorithms to address both resource allocation and pricing. Evaluation based on real-world datasets shows that our DRL approach outperforms basic DRL algorithms and state-of-theart white-box online cloud resource allocation/pricing algorithms significantly, in terms of both profit and the number of accepted users.

scholarly journals Cloud services as the ultimate gate(keeper)

2019 ◽  
Vol 7 (2) ◽  
pp. 220-248
Author(s):  
Björn Lundqvist
Keyword(s):  
Service Providers ◽  
Cloud Services ◽  
Business Strategies ◽  
Cloud Provider ◽  
Goods And Services ◽  
Use Of Data ◽  
Cloud Providers ◽  
And Storage ◽  
The Internet Of Things ◽  
Gain Access

Abstract In the Internet of Things (IoT), the amount and smart use of data will determine whether or not a firm can compete successfully. Manufacturing firms will collect data through sensors in their devices and, at least in the cases of SMEs, likely store the collected data in the cloud, purchasing cloud services and storage from the large e-platform providers doubling as cloud providers. The e-platform providers will also collect data from users of their other services. These data are often generated by the same firms that purchase cloud services when they use the e-platforms to sell goods and services. Access to the data and to data analytics on fair business terms, and the possibility to switch cloud and service providers are vital for the SMEs and, in general, to create a competitive and vibrant IoT. However, cloud and e-platform customers seem to be facing difficulties. According to the EU Commission, SMEs are finding it particularly hard to engage cloud and e-platform providers, and to gain access to cloud services on reasonable, transparent terms. The contracts are skewed in favour of the cloud providers. The customers get locked in and may be obliged to agree not to assert any of their intellectual property rights vis-à-vis the cloud provider or the cloud provider’s network. Moreover, the cloud and e-platform providers may under certain circumstances access and make use of the users’ data, and that may give them a competitive advantage vis-à-vis the users, since the providers may have access to much more data, even data originating from the users’ competitors, suppliers, customers, etc. They can thus use all the data available to them to obtain a fuller picture of whole industries, and they may use that advantage in data to leverage and enter users’ markets. Indeed, they may use the data in the cloud for data-driven business strategies to enter the core market of the firms that have provided them with data in the first place. This article discusses whether competition law can address the conduct of the cloud and e-platform providers, so that firms may access and make use of all the possibilities that the IoT harbours.

scholarly journals Teleworking and collaborative work environments in translation training

Babel ◽  
2009 ◽  
Vol 55 (2) ◽  
pp. 165-180 ◽  
Author(s):  
María Dolores Olvera-Lobo ◽  
Bryan Robinson ◽  
José A. Senso ◽  
Ricardo Muñoz-Martín ◽  
Eva Muñoz-Raya ◽  
...  
Keyword(s):  
Collaborative Work ◽  
Work Environments ◽  
Evaluation Tools ◽  
Self Confidence ◽  
Level Of Satisfaction ◽  
Global Consistency ◽  
Translator Training ◽  
Before And After ◽  
E Learning ◽  
Collaborative Platform

The professional translation work is highly influenced by new communication opportunities, reason why teleworking must occupy its rightful place in translator training at tertiary level. In addition, the ideal translation process should be divided into different stages (as already occurs in major translation agencies), each task being assigned to a different team member with a different role. This paper presents the results of a research study on translation students’ disposition towards and level of satisfaction with the use of a collaborative work environment. We propose a “Professional Approach to Translator Training”, our didactic model combines elements of roleplay, team-based task learning, simulation and case study in an innovative e-learning environment that functions via a collaborative platform (BSCW). Questionnaires were designed and used as evaluation tools before and after the experience of working in a collaborative environment. The aim of these evaluation tools was to measure students’ knowledge of the following skills: computing, tele- and teamwork, and translation tasks. The internal global consistency was adequate (Cronbach’s alpha in the pre-course questionnaire is 0.902 and the value for the post-course questionnaire is 0.802).
 Results show that collaborative work environments make the learning process easier, maintain students’ pre-existing positive disposition towards teamwork, and improve students’ self-confidence with regard to computers and translation tasks. The data obtained from this study suggest that using a collaborative work platform in translation course is beneficial, enabling students to gain confidence and feel satisfied with their work. 


INFLUENCE OF COLLABORATIVE BEHAVIOR ON CLAIM NEGOTIATION

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Rita Awwad ◽  
Stephanie Atallah ◽  
Carol Menassa
Keyword(s):  
Dispute Resolution ◽  
Construction Projects ◽  
Opinion Dynamics ◽  
Negotiation Process ◽  
Project Delivery ◽  
Integrated Project Delivery ◽  
Agent Based ◽  
Construction Disputes ◽  
Collaborative Behavior ◽  
Integrated Project

The high cost incurred by the resolution of conflicts is largely affected by the existing adversarial nature of the construction industry along with the use of non-efficient dispute resolution methods in construction projects. This paper studies opinion dynamics in the negotiation of construction disputes while trying to understand the behavior and extremism of each contractual party. The developed model uses an agent-based approach to show how each agent’s attitude can influence the negotiation process when solving a dispute. It can also be used to highlight the importance of alternative dispute resolution (ADR) methods and the use of a mediator in helping parties initiate negotiation and decrease the number of negotiation cycles needed to converge. The results showed that negotiation is not only affected by the attitude and character of the agents involved but it is also influenced by the delivery method of the project and the level of intensity of each agent. It was found that when the project is delivered through an Integrated Project Delivery (IPD) method, parties are more flexible and cooperative and will reach agreement within few negotiation cycles.

scholarly journals Secure Server Key Management Designs for the Public Cloud

2020 ◽  
Author(s):  
Kevin Foltz ◽  
William R. Simpson
Keyword(s):  
Key Management ◽  
Web Server ◽  
Free Access ◽  
Cloud Provider ◽  
Public Cloud ◽  
Web Based ◽  
The Public ◽  
Cloud Providers ◽  
Enterprise Level ◽  
Secure Server

The Enterprise Level Security (ELS) model focuses on designing secure, distributed web-based systems starting from basic principles. One area of ELS that poses significant design challenges is protection of web server private keys in a public cloud. Web server private keys are of critical importance because they control who can act as the server to represent the enterprise. This includes responding to requests as well as making requests within the enterprise and to its partners. The cloud provider is not part of this trusted network of servers, so the cloud provider should not have access to server private keys. However, current cloud systems are designed to allow cloud providers free access to server private keys. This paper proposes design solutions to securely manage private keys in a public cloud. An examination of commonly used approaches demonstrates the ease with which cloud providers can currently control server private keys. Two designs are proposed to prevent cloud provider access to keys, and their implementation issues are discussed.

scholarly journals A New Genetic Algorithm with Agent-Based Crossover for Generalized Assignment Problem

2019 ◽  
Vol 48 (3) ◽  
pp. 389-400 ◽  
Author(s):  
Murat DÖRTERLER
Keyword(s):  
Genetic Algorithm ◽  
Assignment Problem ◽  
Dominant Gene ◽  
Minimum Cost ◽  
Fertility Rate ◽  
Generalized Assignment Problem ◽  
Agent Based ◽  
Local Searches ◽  
Generalized Assignment ◽  
Feasible Solutions

Generalized assignment problem (GAP) considers finding minimum cost assignment of n tasks to m agents provided each task should be assigned to one agent only. In this study, a new Genetic Algorithm (GA) with some new methods is proposed to solve GAPs. The agent-based crossover is based on the concept of dominant gene in genotype science and increases fertility rate of feasible solutions. The solutions are classified as infeasible, feasible and mature with reference to their conditions. The new local searches provide not only feasibility in high diversity but high profitability for the solutions. A solution is not given up through maturation-based replacement until it reaches its best.  Computational results show that the agent-based crossover has much higher fertility rate compared to classical crossover. Also, the proposed GA creates either optimal or approximately optimal solutions.

scholarly journals Pricing strategies of an oligopolist in federated cloud markets

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Yash Khandelwal ◽  
Arushi Dogra ◽  
Karthik Ganti ◽  
Suresh Purini ◽  
Puduru V. Reddy
Keyword(s):  
Game Theory ◽  
Cooperative Game Theory ◽  
Adaptive Strategy ◽  
Coalition Structure ◽  
Cloud Provider ◽  
Pricing Strategies ◽  
Cloud Federation ◽  
Cloud Providers ◽  
Total Price ◽  
Price Offer

AbstractIn this paper, we study how an oligopolist influences the coalition structure in federated cloud markets. Specifically, we use cooperative game theory to model the circumstances under which a cloud provider prefers to join a cloud federation vis-a-vis consider taking a price offer made by an oligopolist. We consider two price offering strategies for an oligopolist: non-adaptive and adaptive. In non-adaptive strategy, an oligopolist makes a price offer to all the cloud providers simultaneously. It can be noted that the oligopolist can buy-out all the cloud providers by making a price offer which is equal to a core allocation and the total price offer made by the oligopolist is equal to the value of the grand coalition. In adaptive strategy, the oligopolist approaches the cloud providers one after another in a sequential manner. We show that by using the adaptive strategy, the oligopolist can buy-out all the cloud providers at a total price offer which is less than that of the non-adaptive strategy.

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