Agent Based Negotiation Using Cloud – An Approach in E-Commerce

More, Amruta; Vij, Sheetal; Mukhopadhyay, Debajyoti

doi:10.1007/978-3-319-03107-1_54

Cited by 13 publications

(4 citation statements)

References 9 publications

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“…However, the proposed multiagent-based negotiation mechanisms do not allow the clients/consumers to break the contract, once set, if the service does not satisfy the consumer needs. Contrarily, a multiagent-based cloud commerce model [24], [25] devises a complex negotiation mechanism, along with its "parallel" negotiation activities among the cloud stakeholders in interrelated cloud service markets, that is breach-able by the consumers after paying a certain penalty fee.…”

Section: Agents and Services: A Brief Overviewmentioning

confidence: 99%

An Efficient Multi-Cloud Service Composition Using a Distributed Multiagent-Based, Memory-Driven Approach

Kendrick

Baker

Maamar

et al. 2021

IEEE Trans. Sustain. Comput.

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Section: Agents and Services: A Brief Overviewmentioning

confidence: 99%

An Efficient Multi-Cloud Service Composition Using a Distributed Multiagent-Based, Memory-Driven Approach

Kendrick

Baker

Maamar

et al. 2021

IEEE Trans. Sustain. Comput.

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“…Agents in these systems share their work status with each other to avoid a single point of failure. To make cloud solutions more intelligent and adaptive, multi-agent technology has been integrated to the cloud domain [46,47,48]. To make resource discovery, brokering, and swapping effective the Cloud Resource Bartering System (CRBS) presented in this work has been implemented by means of a multi-agent technology.…”

Section: Significance Of Multi-agent Technology For Operating In High...mentioning

confidence: 99%

Cloud provider capacity augmentation through automated resource bartering

Goher

Bloodsworth

Rasool

et al. 2018

Future Generation Computer Systems

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Growing interest in Cloud Computing places a heavy workload on cloud providers which is becoming increasingly difficult for them to manage with their primary datacenter infrastructures. Resource limitations can make providers vulnerable to significant reputational damage and it often forces customers to select services from the larger, more established companies, sometimes at a higher price. Funding limitations, however, commonly prevent emerging and even established providers from making continual investment in hardware speculatively assuming a certain level of growth in demand. As an alternative, they may strive to use the current inter-cloud resource sharing platforms which mainly rely on monetary payments and thus putting pressure on already stretched cash flows. To address such issues, we have designed and implemented a new multi-agent based Cloud Resource Bartering System (CRBS) that fosters the management and bartering of pooled resources without requiring costly financial transactions between providers. Agents in CRBS not only strengthen the trading relationship among providers but also enable them to handle surges in demand with their primary setup. Unlike existing systems, CRBS assigns resources by considering resource urgency which comparatively improves customers' satisfaction and the resource utilization rate by more than 50%.The evaluation results provide evidence that our system assists providers to timely acquire the additional resources and to maintain sustainable service delivery. We conclude that the existence of such a system is economically beneficial for cloud providers and enables them to adapt to fluctuating workloads.

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“…In this section, we are presenting literature survey related to only rule based and case based reasoning. In our previous paper [4], we have referred ten papers related to automated negotiation in the literature survey.…”

Section: Literature Reviewmentioning

confidence: 99%

“…2) Negotiation process: For negotiation process [4], seller and buyer give their requirements to agent in encrypted format that is generate the hash code of that requirement and encrypt that hash code using user's public key. User's public key is known to Agents.…”

Section: Components Of the Systemmentioning

confidence: 99%

An E-Negotiation Agent Using Rule Based and Case Based Approaches: A Comparative Study with Bilateral E-Negotiation with Prediction

Vij¹,

More²,

Mukhopadhyay³

et al. 2015

JSEA

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The research in the area of automated negotiation systems is going on in many universities. This research is mainly focused on making a practically feasible, faster and reliable E-negotiation system. The ongoing work in this area is happening in the laboratories of the universities mainly for training and research purpose. There are number of negotiation systems such as Henry, Kasbaah, Bazaar, Auction Bot, Inspire, and Magnet. Our research is based on making an agent software for E-negotiation which will give faster results and also is secure and flexible. The negotiation partners and contents between the service providers change frequently. The negotiation process can be transformed into rules and cases. Using these features, a new automated negotiation model for agent integrating rule based and case based reasoning can be derived. We propose an E-negotiation system, in which all product information and multiple agent details are stored on the cloud. An E-negotiation agent acts as a negotiator. Agent has user's details and their requirements for a particular product. It will check rules based data whether any rule is matching with the user requirement. An agent will see case based data to check any similar negotiation case matching to the user requirement. If a case matches with user requirement, then agent will start the negotiation process using case based data. If any rule related requirement is found in the rule base data, then agent will start the negotiation process using rule based data. If both rules based data and cases based data are not matching with the user requirement, then agent will start the negotiation process using Bilateral Negotiation model. After completing negotiation process, agent gives feedback to the user about whether negotiation is successful or not. The product details, S. R. Vij et al. 522 rule based data, and case based data will be stored on the cloud. So that system automatically becomes flexible. We also compare E-negotiation agent automated negotiation and behavior prediction system to prove that using rule based and case based approaches system should become fast.

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Agent Based Negotiation Using Cloud – An Approach in E-Commerce

Cited by 13 publications

References 9 publications

An Efficient Multi-Cloud Service Composition Using a Distributed Multiagent-Based, Memory-Driven Approach

An Efficient Multi-Cloud Service Composition Using a Distributed Multiagent-Based, Memory-Driven Approach

Cloud provider capacity augmentation through automated resource bartering

An E-Negotiation Agent Using Rule Based and Case Based Approaches: A Comparative Study with Bilateral E-Negotiation with Prediction

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