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.
Content Not FoundUnfortunately we are unable to locate the content you are looking for. It is possiblethat the publisher, journal or issue is no longer hosted at Ingenta Connect, or that the link thatbrought you to this page is incorrect.Please use the browse orsearch features to find thecontent you are looking for. M.G. Avram. Author links open the author workspace. With the rapid development of processing and storage technologies and the success of the Internet, computing resources have become cheaper, more powerful and more available than ever before.
This metatrader stock charts ron trend has enabled the realization of a new computing model called cloud computing, in which resources are provided as general utilities that can be leased and released by users through the Internet in an on-demand fashion. The organizations are gaining more experience in the cloud and they start to shift more core business functions onto cloud platforms. Cite this paper as: Allenotor D., Thulasiram R.K.
(2007) A Grid Resources Valuation Model Using Fuzzy Real Option. Lecture Notes in Computer Science, vol 4742. Grid resources are non-storable compute commodities (eg., 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.
This requirement further imposes service constraints on the grid because it must provide a user-acceptable QoS guarantee to compensate for the upfront value. In order to reduce their maintenance cost of internal IT clusters, many hard- and software providers reconsider to offer these resources in grid and cloud markets. However, participants in these markets bear some uncertainties and risks which can be hedged against by resource reservation.
In this work we analyze the use of real options traded at an additional contract market, to efficiently manage economical issues arising from the realization of a flexible resource reservation scheme. We derive the necessary conditions that even risk neutral agents have incentives to participate in such a market, as it increases their expected real option valuation on grid computing model.
Dirk Neumann,TCurrent 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 capt.