scholarly journals PRICE DEMAND MODEL FOR A CLOUD CACHE

2010 ◽  
pp. 246-249
Author(s):  
SHAIK MOHAMMED GOUSE ◽  
G. PRAKASH BABU
Keyword(s):  
User Satisfaction ◽  
Dynamic Pricing ◽  
Optimal Pricing ◽  
Demand Model ◽  
Efficient Manner ◽  
Cloud Data ◽  
Pricing Scheme ◽  
Novel Method ◽  
Time Changes ◽  
Price Demand

Cloud applications that offer data management services are emerging. Such clouds support caching of data in order to provide quality query services. The users can query the cloud data, paying the price for the infrastructure they use. Cloud management necessitates an economy that manages the service of multiple users in an efficient, but also, resource economic way that allows for cloud profit. Naturally, the maximization of cloud profit given some guarantees for user satisfaction presumes an appropriate price-demand model that enables optimal pricing of query services. The model should be plausible in that it reflects the correlation of cache structures involved in the queries. Optimal pricing is achieved based on a dynamic pricing scheme that adapts to time changes. This paper proposes a novel price-demand model designed for a cloud cache and a dynamic pricing scheme for queries executed in the cloud cache. The pricing solution employs a novel method that estimates the correlations of the cache services in an time-efficient manner. The experimental study shows the efficiency of the solution.

scholarly journals ENHANCING JOB ALLOCATION USING NBST IN CLOUD ENVIRONMENT: A REVIEW

2017 ◽  
Vol 16 (3) ◽  
pp. 6247-6253
Author(s):  
Ashima Ashima ◽  
Mrs Navjot Jyoti
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
User Satisfaction ◽  
Data Centers ◽  
Virtual Machines ◽  
Efficient Manner ◽  
Equal Distribution ◽  
Cloud Data ◽  
Cloud Data Centers ◽  
Load Balancing Algorithm

Cloud computing is a vigorous technology by which a user can get software, application, operating system and hardware as a service without actually possessing it and paying only according to the usage. Cloud Computing is a hot topic of research for the researchers these days. With the rapid growth of Interne technology cloud computing have become main source of computing for small as well big IT companies. In the cloud computing milieu the cloud data centers and the users of the cloud-computing are globally situated, therefore it is a big challenge for cloud data centers to efficiently handle the requests which are coming from millions of users and service them in an efficient manner. Load balancing is a critical aspect that ensures that all the resources and entities are well balanced such that no resource or entity neither is under loaded nor overloaded. The load balancing algorithms can be static or dynamic.  Load balancing in this environment means equal distribution of workload across all the nodes. Load balancing provides a way of achieving the proper utilization of resources and better user satisfaction. Hence, use of an appropriate load balancing algorithm is necessary for selecting the virtual machines or servers. This paper focuses on the load balancing algorithm which distributes the incoming jobs among VMs optimally in cloud data centers. In this paper, we have reviewed several existing load balancing mechanisms and we have tried to address the problems associated with them.

scholarly journals Pricing Strategies of Logistics Distribution Services for Perishable Commodities

Algorithms ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 186
Author(s):  
Tao Li ◽  
Yan Chen ◽  
Taoying Li
Keyword(s):  
Dynamic Pricing ◽  
Consumer Satisfaction ◽  
Service Providers ◽  
Time Constraints ◽  
Optimal Pricing ◽  
Pricing Strategies ◽  
Pricing Model ◽  
Logistics Service ◽  
Distribution Services ◽  
Perishable Goods

The problem of pricing distribution services is challenging due to the loss in value of product during its distribution process. Four logistics service pricing strategies are constructed in this study, including fixed pricing model, fixed pricing model with time constraints, dynamic pricing model, and dynamic pricing model with time constraints in combination with factors, such as the distribution time, customer satisfaction, optimal pricing, etc. By analyzing the relationship between optimal pricing and key parameters (such as the value of the decay index, the satisfaction of consumers, dispatch time, and the storage cost of the commodity), it is found that the larger the value of the attenuation coefficient, the easier the perishable goods become spoilage, which leads to lower distribution prices and impacts consumer satisfaction. Moreover, the analysis of the average profit of the logistics service providers in these four pricing models shows that the average profit in the dynamic pricing model with time constraints is better. Finally, a numerical experiment is given to support the findings.

scholarly journals CHANGE DETECTION AND DEFORMATION ANALYSIS BASED ON MOBILE LASER SCANNING DATA OF URBAN AREAS

2020 ◽  
Vol V-2-2020 ◽  
pp. 703-710
Author(s):  
J. Gehrung ◽  
M. Hebel ◽  
M. Arens ◽  
U. Stilla
Keyword(s):  
Change Detection ◽  
Urban Areas ◽  
Laser Scanning ◽  
State Of The Art ◽  
Point Clouds ◽  
Deformation Analysis ◽  
Lidar Data ◽  
Efficient Manner ◽  
Incomplete Observations ◽  
Novel Method

Abstract. Change detection is an important tool for processing multiple epochs of mobile LiDAR data in an efficient manner, since it allows to cope with an otherwise time-consuming operation by focusing on regions of interest. State-of-the-art approaches usually either do not handle the case of incomplete observations or are computationally expensive. We present a novel method based on a combination of point clouds and voxels that is able to handle said case, thereby being computationally less expensive than comparable approaches. Furthermore, our method is able to identify special classes of changes such as partially moved, fully moved and deformed objects in addition to the appeared and disappeared objects recognized by conventional approaches. The performance of our method is evaluated using the publicly available TUM City Campus datasets, showing an overall accuracy of 88 %.

OPTIMAL PRICING AND PRODUCTION POLICIES OF A MAKE-TO-STOCK SYSTEM WITH FLUCTUATING DEMAND

2009 ◽  
Vol 23 (2) ◽  
pp. 205-230 ◽  
Author(s):  
Jean-Philippe Gayon ◽  
Işılay Talay-Değirmenci ◽  
Fikri Karaesmen ◽  
E. Lerzan Örmeci
Keyword(s):  
Dynamic Pricing ◽  
Numerical Study ◽  
Optimal Pricing ◽  
Pricing Strategies ◽  
Pricing Policy ◽  
Stock Level ◽  
Production Inventory ◽  
Static Pricing ◽  
Make To Stock ◽  
Production Inventory System

We study the effects of different pricing strategies available to a production–inventory system with capacitated supply, which operates in a fluctuating demand environment. The demand depends on the environment and on the offered price. For such systems, three plausible pricing strategies are investigated: static pricing, for which only one price is used at all times, environment-dependent pricing, for which price changes with the environment, and dynamic pricing, for which price depends on both the current environment and the stock level. The objective is to find an optimal replenishment and pricing policy under each of these strategies. This article presents some structural properties of optimal replenishment policies and a numerical study that compares the performances of these three pricing strategies.

Design of Autonomous Unmanned System for Aerial Operations From Underwater Platforms

2021 ◽  
Author(s):  
Vindhya Devalla ◽  
Cris Thomas ◽  
Adthithiyan Neduncheran ◽  
Shiv Capoor ◽  
Amit Kumar Mondal
Keyword(s):  
Aerial Survey ◽  
Key Factors ◽  
Efficient Manner ◽  
Military Tactics ◽  
Land Mass ◽  
Open Land ◽  
Novel Method ◽  
Unmanned System ◽  
Design Options ◽  
Mass Surveillance

Abstract Surveillance and reconnaissance play a very important role in military and civil aspects. They are the key factors in military tactics and in the event of civilian calamities. In case of naval warfare, the submarines which are operating under deep water are required to carry out open land mass surveillance in an efficient manner without reaching to the water surface nor revealing their presence and position. This research paper proposes the conceptualized design to develop an autonomous unmanned octocopter system which is capable of being launched from an underwater platform such as submarines, with the help of a tethered launching mechanism known as octopod, to carry out surveillance, reconnaissance and payload delivery. In this paper, we present a novel method for development of UAV with special application on aerial survey from underwater platforms. A variety of design options which are investigated from various trade studies to evaluate the performance along with design configuration to satisfy the specific requirements are also presented in this paper.

Scalable Intra and Inter Domain IPv6 QoS Management and Pricing Scheme

2010 ◽  
pp. 256-279
Author(s):  
El-Bahlul Fgee ◽  
Shyamala Sivakumar ◽  
William J. Phillips ◽  
William Robertson
Keyword(s):  
Traffic Flow ◽  
Dynamic Pricing ◽  
Pricing Strategy ◽  
Traffic Flows ◽  
Lower Priority ◽  
Qos Management ◽  
Management Scheme ◽  
Pricing Scheme ◽  
End To End ◽  
Pricing Schemes

Network multimedia applications constitute a large part of Internet traffic and guaranteed delivery of such traffic is a challenge because of their sensitivity to delay, packet loss and higher bandwidth requirement. The need for guaranteed traffic delivery is exacerbated by the increasing delay experienced by traffic propagating through more than one QoS domain. Hence, there is a need for a flexible and a scalable QoS manager that handles and manages the needs of traffic flows throughout multiple IPv6 domains. The IPv6 QoS manager, presented in this paper, uses a combination of the packets’ flow ID and the source address (Domain Global Identifier (DGI)), to process and reserve resources inside an IPv6 domain. To ensure inter-domain QoS management, the QoS domain manager should also communicate with other QoS domains’ managers to ensure that traffic flows are guaranteed delivery. In this scheme, the IPv6 QoS manager handles QoS requests by either processing them locally if the intended destination is located locally or forwards the request to the neighboring domain’s QoS manager. End-to-end QoS is achieved with an integrated admission and management unit. The feasibility of the proposed QoS management scheme is illustrated for both intra- and inter-domain QoS management. The scalability of the QoS management scheme for inter-domain scenarios is illustrated with simulations for traffic flows propagating through two and three domains. Excellent average end-to-end delay results have been achieved when traffic flow propagates through more than one domain. Simulations show that packets belonging to non-conformant flows experience increased delay, and such packets are degraded to lower priority if they exceed their negotiated traffic flow rates. Many pricing schemes have been proposed for QoS-enabled networks. However, integrated pricing and admission control has not been studied in detail. A dynamic pricing model is integrated with the IPv6 QoS manager to study the effects of increasing traffic flows rates on the increased cost of delivering high priority traffic flows. The pricing agent assigns prices dynamically for each traffic flow accepted by the domain manager. Combining the pricing strategy with the QoS manager allows only higher priority traffic packets that are willing to pay more to be processed during congestion. This approach is flexible and scalable as end-to-end pricing is decoupled from packet forwarding and resource reservation decisions. Simulations show that additional revenue is generated as prices change dynamically according to the network congestion status.

scholarly journals Fuzzy based QoS prediction using bayesian network in cloud computing environment

2017 ◽  
Vol 7 (1.5) ◽  
pp. 170 ◽  
Author(s):  
Saravanan Chandrasekaran ◽  
Vijay Bhanu Srinivasan ◽  
Latha Parthiban
Keyword(s):  
Bayesian Network ◽  
User Satisfaction ◽  
Fuzzy Inference ◽  
User Preference ◽  
Inference Rules ◽  
Cloud Infrastructure ◽  
Qos Prediction ◽  
Prediction Probability ◽  
Service Capability ◽  
Novel Method

The Quality of Service (QoS) is enforced in discovering an optimal web service (WS).The QoS is uncertain due to the fluctuating performance of WS in the dynamic cloud environment. We propose a Fuzzy based Bayesian Network (FBN) system for Efficient QoS prediction. The novel method comprises three processes namely Semantic QoS Annotation, QoS Prediction, and Adaptive QoS using cloud infrastructure. The FBN employs the compliance factor to measure the performance of QoS attributes and fuzzy inference rules to infer the service capability. The inference rules are defined according to the user preference which assists to achieve the user satisfaction. The FBN returns the optimal WSs from a set of functionally equivalent WS. The unpredictable and extreme access of the selected WS is handled using cloud infrastructure. The results show that the FBN approach achieves nearly 95% of QoS prediction accuracy when providing an adequate number of past QoS data, and improves the prediction probability by 2.6% more than that of the existing approach.  

scholarly journals Mathematical modeling of optimal product supply strategies for manufacturer-to-group customers based on semi-real demand patterns

2020 ◽  
Vol 12 ◽  
pp. 184797902094148
Author(s):  
Zhiyi Zhuo ◽  
Ka Yin Chau ◽  
Shizheng Huang ◽  
Yun Kit Ip
Keyword(s):  
Optimal Pricing ◽  
Production Volume ◽  
Demand Model ◽  
Optimal Production ◽  
Numerical Examples ◽  
The Core ◽  
Demand Pattern ◽  
Optimization Principle ◽  
Optimal Value ◽  
Demand Patterns

Customer demand is the core of the vendor’s implementation of product supply strategies. There are three different patterns of demand: real demand, false demand, and semi-real demand. For this article, we study the product supply strategy formulated for manufacturer-to-group customers based on a semi-real demand pattern. Firstly, we construct two mathematical models in which the manufacturer obtains the best profit based on the two supply modes in the semi-real demand pattern. Secondly, we solve the optimal production volume and optimal pricing. Finally, numerical examples are used to verify the validity of the model. In accordance with the optimization principle, results of the analysis are extended to the range of optimal value of product profit in the demand model, so as to explore the mechanism of manufacturers for maximizing group customers’ product profits under the semi-real demand model.

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