Papers by David Allenotor
Grid resources pricing: A novel financial option based quality of service-profit quasi-static equilibrium model
ABSTRACT Use of grid resources has been free so far and a trend is developing to charge the users... more ABSTRACT Use of grid resources has been free so far and a trend is developing to charge the users. The challenges that characterize a grid resource pricing model include the dynamic ability of the model to provide a high satisfaction guarantee measured as quality of service (QoS) - from users perspectives, profitability constraints - from the grid operator perspectives, and the ability to orchestrate grid resources for their availability on-demand. In this study, we design, develop, and simulate a grid resources pricing model that balances these constraints. We employ financial option theory and treat the grid resources as real assets to capture the realistic value of the grid compute commodities. We then price the grid resources by solving the finance model. We discuss the results on pricing of compute cycles based on the actual data of grid usage pattern obtained from the WestGrid and the SHARCNET. We extend and generalize our study to any computational grid.
A Discrete Time Financial Option Pricing Model for Cloud Services
Option pricing is one of the most challenging problems in computational finance and derivative mo... more Option pricing is one of the most challenging problems in computational finance and derivative modeling. As a result, one has to resort to computational approaches since it is difficult to obtain closed form solution for options other than simple options such as European style options. Also, due to the complex nature of the governing mathematics, several numerical approaches have been proposed in the past to price American style options as well as complex options. In the current study, we apply trinomial lattice which has been used in many scientific and engineering applications to model option pricing for assets with high volatility. The three novelties of this paper include, the formulation of cloud asset price using stochastic process, the improvement of the American style option pricing algorithm by integrating our option pricing factor (pf) into the algorithm, and the presentation of the computed option values for various strike price. With carefully select strike-price spacing, we guarantee a fine-grain integration of pf into the trinomial lattice.
Message from the ScalCom 2016 General Chairs
Springer eBooks, May 12, 2008
A computational grid ensures the on-demand delivery of computing resources, in a security-aware, ... more A computational grid ensures the on-demand delivery of computing resources, in a security-aware, shared, scalable, and standards-based computing environment. A major concern is how to evolve a general and an encompassing framework that guarantees users' satisfaction measured as Quality of Services (QoS). To obtain a higher QoS, effective QoS perceived by subscribers (users) must conform to specified QoS agreements in the Service Level Agreements (SLAs) documenta legal contract between the Grid Services Provider (GSP) and users. Sometimes the effective user QoS does not conform to the specifications in the SLA because of the vagueness in linguistic definitions in the SLA. Existing approaches overcommitted resources to meet QoS. In this paper, we propose a fuzzy logic framework for calibrating a grid resources user-QoS that addresses the vagueness in linguistic definitions of the SLA document without overcommitting grid resources.
Integrating a financial option based model with GridSim for pricing Grid resources
ABSTRACT Analysis of grid resources utilization from real grid trace data shows the feasibility o... more ABSTRACT Analysis of grid resources utilization from real grid trace data shows the feasibility of a financial option based model for pricing grid resources to attract more users for profitability for the grid provider while providing high Quality of Service (QoS) to users. However, in the absence of grid resource pricing benchmarks, we simulate grid resources usage in order to justify our pricing model using GridSim toolkit. In this work we integrate a financial option based pricing model with GridSim framework and use it as a grid simulation tool to price grid compute resources.
A Fuzzy Real Option Model to Price Grid Compute Resources
IGI Global eBooks, Jan 18, 2011
A computational grid is a geographically disperssed heterogeneous computing facility owned by dis... more A computational grid is a geographically disperssed heterogeneous computing facility owned by dissimilar organizations with diverse usage policies. As a result, guaranteeing grid resources availability as well as pricing them raises a number of challenging issues varying from security to management of the grid resources. In this chapter we design and develop a grid resources pricing model using a fuzzy real option approach and show that finance models can be effectively used to price grid resources.
Option Pricing in a GARCH Framework
There is a compelling need to accurately and efficiently compute option values. Existing literatu... more There is a compelling need to accurately and efficiently compute option values. Existing literature shows that models based on constant stock volatilities have been widely used in option valuation. However, stock volatilities change constantly in real life situations. The introduction of the Auto Regressive Conditional Heteroskedasticity (ARCH) model and subsequently, the Generalized Auto Regressive Conditional Heteroskedasticity (GARCH) model provides a framework for valuing options using time-varying volatilities. In this paper, we explore the pricing of European styled call options using an analytical approximation of the GARCH option pricing model that is developed in existing literatures. Keyword – option pricing, financial option, volatility, GARCH.
An Optimized Parallel Hybrid Architecture for Cryptocurrency Mining
Advances in Multidisciplinary and scientific Research Journal Publication
One of the requirements for mining cryptocurrency (Crypto) is that the secured ledger of the bloc... more One of the requirements for mining cryptocurrency (Crypto) is that the secured ledger of the blockchain must be updated. However, updating the secured ledger requires that the miner develop and solve complex mathematical equations in higher orders hexadecimal 64-digit solution called a hash. In addition to this challenge, the mining processes of cryptocurrency are both resource and cost-intensive. The resources required include, but not limited to mining software, hardware, power (energy usage), CPU or compute cycles, and NP-hard problem. Apart from these numerous challenges that are associated with mining cryptocurrency, the amount of speed that is required to mine a single block is core. Cryptocurrency mining speed requirement is significantly important because only miners that can have the fastest mining device are most likely to get the reward (profit) from competing for a block. In this paper, we designed and implemented a model to speed up mining process which is capable of gi...
A client trusted security framework for dependable cloud computing
Scientia Africana, 2017
Cloud computing is a relatively new technology that is in wide use because of the benefits it off... more Cloud computing is a relatively new technology that is in wide use because of the benefits it offers, but is still confronted with security issues. The residence of the client’s sensitive or proprietary data in the cloud service provider’s server and premises expose the data to the possibility of manipulation, modification, inspection, deletion or theft. This possibility creates fear in the mind of the data owner and reduces the user’s trust level in cloud computing. We propose a client trusted security framework to increase users trust level in cloud computing to make it more dependable. The proposed framework includes a user focused software process model for cloud computing security. A formal analysis of the proposed framework shows that it is capable of increasing the trust level of cloud computing by about 67 % when implemented by cloud service providers. Keywords: cloud computing, users trust, framework, model, cloud
A Classification Model Based on Machine Learning for Detecting Racist Comments on Social Media Platforms
Advances in Multidisciplinary and Scientific Research Journal, Jun 30, 2021
Advances in Multidisciplinary and Scientific Research Journal, Jun 30, 2022
A grid-computing paradigm delivers the processing power of massively parallel computation to all ... more A grid-computing paradigm delivers the processing power of massively parallel computation to all subscribed users. Current trends, research, and developments in grid computing show that the available grid resources exist as non-storable compute commodities and are distributed geographically-the grid problem. To solve the grid problem, several initiatives have developed frameworks for grid economy and have proposed several algorithms towards an optimized resources scheduling in a grid environment. However, since the grid resources availability depends on the time of usage and are transient, such generic approaches lack the ability to capture the realistic valuation of the resources and fail to guarantee the certainty in their availability measured as Quality of Service (QoS). Uncertainties in grid resource availability do not guarantee a user expected QoS without over committing (e.g., storing the non-storable resources) resources to the users. To guarantee QoS (satisfy a users' computing needs), we propose a price-based and quality-aware model that captures the realistic value of the grid compute commodities. We use the financial option theory from a real option perspective to value grid resources by treating them as real assets. We discuss a set of results on pricing grid compute cycles. Our results are based on the compute cycle usage obtained from the WestGrid node at the University of Manitoba. We extend and generalize our study to any grid in general but with specific reference to the WestGrid.
advances in multidisciplinary & scientific research journal publication, 2021
The emotional stress and uncertainties associated with foreign exchange (forex) trading due to th... more The emotional stress and uncertainties associated with foreign exchange (forex) trading due to the high risk of losing the investment capital has left most forex traders in a state of indecision on the best methodology to apply for achieving long term profit. The provision of lot sizes, leverages, take profits and stop losses in forex trading implies that very high profit can be made within a very short time with the same capital, but at the same time, very high losses can be incurred. On one hand, this provision often prompts a set of traders to become greedy by increasing their take profit levels, lot sizes and leverages, which in turn increases their probability of losing out. On the other hand, the provision creates doubts and induces the fear of losses in some other set of traders. Consequently, these set of conservative traders employ the use of relatively small lot sizes, low leverages and low values of take profit and high stop loss levels. This in turn often results in a de...
Evaluation of a Financial Option Based Pricing Model for Grid Resources Management: Simulation vs. Real Data
2010 IEEE 12th International Conference on High Performance Computing and Communications (HPCC), 2010
... the number of up and down moves required to reach (i, j) from root node (0, 0) and is given b... more ... the number of up and down moves required to reach (i, j) from root node (0, 0) and is given by S[i, j] = S[0, 0](uidj). ... The novelty of the extension from binomial to trinomial in our model is in the application of our compensation function which con-ceptually is similar to an airline ...
ScalCom 2014 Program Committee UIC-ATC-ScalCom 2014
Track: New Design in Multi-core Architectures for Scalability Andres Marquez, Pacific Northwest N... more Track: New Design in Multi-core Architectures for Scalability Andres Marquez, Pacific Northwest National Laboratory, Richland, USA (Chair) Ulrich Bruening, Heidelberg University, Germany Rong Ge, Marquette University, USA Eric Van Hensbergen, ARM Research Labs, USA Tom St. John, Intel Corporation, USA Karen Karavanic, Portland State University, USA Christos Kartsaklis, Oak Ridge National Laboratory, USA Rishi Khan, Extreme Scale Solutions, USA Joseph Manzano, Pacific Northwest National Laboratory, USA Benoit Meister, Reservoir Labs Inc., USA Juan Piernas, University of Murcia, Spain Bronis R de Supinski, Lawrence Livermore National Laboratory, USA Vinod Tipparaju, Advanced Micro Devices Inc. (AMD), USA
Message from the ScalCom 2014 General Chairs
Grid resources valuation with fuzzy real option
International Journal of High Performance Computing and Networking, 2011
ABSTRACT In this study, we model pricing of grid/distributed computing resources as a problem of ... more ABSTRACT In this study, we model pricing of grid/distributed computing resources as a problem of real option pricing. Grid resources are non-storable compute commodities (e.g., CPU cycles, memory, etc.). The non-storable characteristic feature of the grid resources hinders it from fitting into a risk-adjusted spot price model for pricing financial options. Grid resources users pay upfront to acquire and use grid compute cycles in the future, for example, six months. The user expects a high and acceptable degree of satisfaction expressed as the quality of service (QoS) assurance. This requirement further imposes service constraints on the grid because it must provide a user-acceptable QoS guarantee to compensate for the upfront value. This study integrates three threads of our research; pricing the grid compute cycles as a problem of real option pricing, modelling grid resources spot price using a discrete time approach, and addressing uncertainty constraints in the provision of QoS using fuzzy logic. We have proved the feasibility of this model through experiments and we have presented some of our pricing results and discussed them.
A Trade Gap Scalability Model for the Forex Market
2014 IEEE 11th Intl Conf on Ubiquitous Intelligence and Computing and 2014 IEEE 11th Intl Conf on Autonomic and Trusted Computing and 2014 IEEE 14th Intl Conf on Scalable Computing and Communications and Its Associated Workshops, 2014
A Financial Option Based Grid Resources Pricing Model: Towards an Equilibrium between Service Quality for User and Profitability for Service Providers
Lecture Notes in Computer Science, 2009
... In another related study, Sulistio et al., [18] evaluate the effectiveness of grid revenue ma... more ... In another related study, Sulistio et al., [18] evaluate the effectiveness of grid revenue management using resource reservations as a focus. ... References 1. Ian, F., Kesselman, C., Tuecke, S.: The Anatomy of The Grid: Enabling Scalable Virtual Organizations. Intl. ...
G-FRoM: Grid Resources Pricing A Fuzzy Real Option Model
Third IEEE International Conference on e-Science and Grid Computing (e-Science 2007), 2007
ABSTRACT Current research efforts in grid computing show that the available grid resources exist ... more ABSTRACT Current research efforts in grid computing show that the available grid resources exist as non-storable compute cycles (grid compute commodities) and distributed geographically across dissimilar organizations with diverse resources usage polices. Therefore, guaranteeing grid resources availability as well as pricing them raises a number of challenging issues in several areas of computer applications. To guarantee QoS we propose a price-based, quality-aware model. We design and develop our model using the financial option theory from a real option perspective and value the grid resources by treating them as real assets. Our hybridized model combines both advantages of fuzzy logic reasoning and real options of a decision-based system. We have taken into account the fact that the grid resources availability depend on the time of use and are transient, and hence solutions from our model captures the realistic value of the grid resources and guarantees the certainty in the resources availability.
Grid resources pricing: A novel financial option based quality of service-profit quasi-static equilibrium model
2008 9th IEEE/ACM International Conference on Grid Computing, 2008
ABSTRACT Use of grid resources has been free so far and a trend is developing to charge the users... more ABSTRACT Use of grid resources has been free so far and a trend is developing to charge the users. The challenges that characterize a grid resource pricing model include the dynamic ability of the model to provide a high satisfaction guarantee measured as quality of service (QoS) - from users perspectives, profitability constraints - from the grid operator perspectives, and the ability to orchestrate grid resources for their availability on-demand. In this study, we design, develop, and simulate a grid resources pricing model that balances these constraints. We employ financial option theory and treat the grid resources as real assets to capture the realistic value of the grid compute commodities. We then price the grid resources by solving the finance model. We discuss the results on pricing of compute cycles based on the actual data of grid usage pattern obtained from the WestGrid and the SHARCNET. We extend and generalize our study to any computational grid.
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Papers by David Allenotor