Dynamic Pricing Strategy and Optimal Resource Selection Strategy Based on Credibility Model

2014 ◽  
Vol 668-669 ◽  
pp. 1615-1620
Author(s):  
Yu Yang ◽  
Hua Zhou ◽  
Jun Hui Liu ◽  
Yun Feng
Keyword(s):  
Cloud Computing ◽  
Dynamic Pricing ◽  
Resource Selection ◽  
Supply And Demand ◽  
Market Price ◽  
Pricing Strategy ◽  
Selection Strategy ◽  
Fixed Rate ◽  
Gradual Development ◽  
Optimal Resource

With the gradual development of Cloud Computing, the model of work and business will fundamentally change in the future. Current market trading mechanism under the cloud computing environment is lacking in flexibility and most of companies adopt a fixed-rate pricing model, which is difficult to meet the different needs of users. Based on cloud bank model, this paper introduces economic theory to provide a theoretical basis for the development of resource prices and propose a dynamic pricing strategy and maximize utility resource selection strategy based on market supply and demand and credit for cloud bank. In the last part of this paper, we use simulation platform to do a simple experiment to test this dynamic pricing strategy. Experiment result shows the pricing strategy could adjust computing resource prices automatically under the general market price rule conditions and maximize utility resource selection strategy could get the max utility for resource consumers.

Auction-Based Pricing in Cloud Environment

2021 ◽  
pp. 86-97
Author(s):  
Branka Mikavica ◽  
Aleksandra Kostic-Ljubisavljevic
Keyword(s):  
Cloud Computing ◽  
Dynamic Pricing ◽  
Rapid Development ◽  
Supply And Demand ◽  
Bidding Strategy ◽  
Cloud Environment ◽  
Allocation Mechanism ◽  
Bidding Strategies ◽  
Selection Of ◽  
Cloud Resources

The rapid development of cloud computing requires improvement of pricing and allocation mechanisms of cloud resources. Dynamic pricing and allocation mechanisms are considered convenient, due to characteristics of cloud resources and the fact that demand for cloud resources is not uniform. The aims of such a mechanism are to optimize the utilization of cloud resources, to maximize cloud providers' revenues, and to minimize prices for cloud customers. Auction-based pricing and allocation mechanisms are often used since resources are allocated to the customers that value them the most, and prices are determined depending on the supply and demand conditions. Selection of an appropriate bidding strategy is a very important issue and requires the comprehensive approach. This chapter analyses the benefits of auction-based pricing and allocation mechanism in the cloud environment. In addition, the effects of different bidding strategies application are addressed.

Managerial Economics – Family Medicine Care

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Ecler Jaqua ◽  
Terry Jaqua ◽  
Van Nguyen
Keyword(s):  
Family Medicine ◽  
Service Providers ◽  
Supply And Demand ◽  
Pricing Strategy ◽  
Demand And Supply ◽  
Business Opportunity ◽  
Is Research ◽  
The Us ◽  
Managerial Economics

Supply and demand are amongst the essential requirements before starting up a business. Understanding the quantity of a commodity wished to be sold by producers based on different prices and the item needed by consumers wish purchasing is essential in coming up with ideas. Based on the understanding of this and background research on costs in healthcare, specifically family medicine, it is found that healthcare is amongst the essential requirements, and thus the critical focus of the business idea in a physician’s practice focusing on family medicine care in the US. Starting up the business is based on healthcare demands in the market and further the pricing strategy utilized by most family medicine clinics. Through a connection to the business based on visits in hospitals and the quality offered by these service providers, it is noted that the demand is high and is the most expensive sector in the world, but care is ineffective (The Peterson Center on Healthcare, n.d.) thus leading to searching for effective alternatives by consumers. This creates a potential for offering the most effective services to cater to the demands, and as noted by the Peterson Center on Healthcare (n.d.), the US healthcare system is the most expensive, and costs are projected to grow dramatically in the coming years thus creating the most significant business opportunity to entrepreneurs. By adjusting the resources and trying to cater to the demand in various locations, the key idea is to cater to the need and profit from the sector. The concern of gaining information in the market is research on different healthcare websites and the prices offered and the quality of their services. This will aid in adjusting the prices effectively and thus retaining the demand and supply chain.

scholarly journals A Quantitative and Qualitative Study of Food Loss in Glasshouse-Grown Tomatoes

Horticulturae ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 39
Author(s):  
Margaret Thorsen ◽  
Miranda Mirosa ◽  
Sheila Skeaff
Keyword(s):  
Supply Chain ◽  
New Zealand ◽  
Supply And Demand ◽  
Qualitative Interviews ◽  
Market Price ◽  
Food Loss ◽  
Greenhouse Tomato ◽  
Total Food ◽  
Food Losses ◽  
Key Industry

Reducing food loss and waste (FLW) is one strategy to limit the environmental impact of the food supply chain. Australian data suggest that primary production accounts for 31% of national FLW, but there are no comparable data in New Zealand. This study aimed to measure food loss and explore food loss drivers for one of New Zealand’s largest tomato growers by weighing and visually assessing tomato losses at the glasshouse, packhouse and sales warehouse. Qualitative interviews were also held with the grower (n = 3), employees (n = 10), and key industry stakeholders (n = 8). Total food loss for this greenhouse tomato grower was 16.9% of marketed yield, consisting of 13.9% unharvested tomatoes, 2.8% rejected at the glasshouse and 0.3% rejected at the packhouse. The grower’s tomato loss predominantly resulted from commercial factors such as market price, competitor activity and supply and demand. Similar issues were recognized throughout the New Zealand horticulture sector. Commercial factors, in particular, are challenging to address, and collaboration throughout the supply chain will be required to help growers reduce food losses.

scholarly journals Modified Flower Pollination based Task Scheduling in Cloud Environment using Virtual Machine Migration

2019 ◽  
Vol 8 (9) ◽  
pp. 1856-1860
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Resource Selection ◽  
Heuristic Algorithms ◽  
Past History ◽  
Fitness Function ◽  
Task Type ◽  
Flower Pollination Algorithm ◽  
Flower Pollination ◽  
Selection Of

Cloud computing allows users to use resources pay per use model by the help of internet. Users are able to do computation dynamically from different location by using internet resources. The major challenging task in cloud computing is efficient selection of resources for the tasks submitted by users. A number of heuristics and meta-heuristics algorithms are designed by different researchers. The most critical phase is the selection of appropriate resource and its management. The selection of resource include to identify list of authenticated available resources in the cloud for job submission and to choose the best resource. The best resource selection is done by the analysis of several factors like expected time to execute a task by user, access restriction to resources, and expected cost to use resources. In this paper, cloud architecture for resource selection is proposed which combines these factors and make the effective resource selection. In this paper a modified flower pollination algorithm is proposed to migrate the task on efficient virtual machine. The selection of the efficient virtual machine is calculated by the fitness function. By calculating the fitness function, the modified FPA algorithm is used to take the decision regarding VM migration is required to improve the resource efficiency or not. In this paper Virtual machine mapper maps the task as per knowledge base i.e. past history of the virtual machine, task type whether computational or communicational based. The results are compared with the existing meta-heuristic algorithms.

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