The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper presents a method of cloud resource allocation designed to take into account both consumers and providers' interests. This comes in contrast to today's provider centered models that subject users to more restrictive terms and conditions. Both parties' interests are computed in the form of integer constraints. Costs and availability are embedded as key objectives and performance criteria...
In this paper, we address cloud VoIP scheduling strategies to provide appropriate levels of quality of service to users, and cost to VoIP service providers. This bi-objective focus is reasonable and representative for real installations and applications. We conduct comprehensive simulation on real data of twenty three on-line non-clairvoyant scheduling strategies with fixed threshold of utilization...
The demand for multi-dimensional range query over Distributed Ordered Table (DOT) has become increasingly popular, however, the DOT does not support queries very well other than the primary key. One solution to this problem is indexing. Many indexing techniques are focusing on how to improve the query ability, but do not care about the consistency between the index table and base data table. This...
RNNLM (Recurrent Neural Network Language Model) can save the historical information of the training dataset by the last hidden layer and can also as input for training. It has become an interesting topic in the field of Natural Language Processing research. However, the immense training time overhead is a big problem. The large output layer, hidden layer, last hidden layer and the connections among...
We consider the implementation of an in-situ machine learning system with the computing model promoted by Qarnot computing. Qarnot introduced an utility computing model in which servers are distributed in homes and offices where they serve as heaters. The Qarnot servers also embed several sensors for temperature, humidity, CO 2 etc. Qarnot offers an adequate platform to develop in-situ workflows for...
A major component of many advanced programming courses is an open-ended "end-of-term project" assignment. Delivering and evaluating open-ended parallel programming projects for hundreds or thousands of students brings a need for broad system reconfigurability coupled with challenges of testing and development uniformity, access to esoteric hardware and programming environments, scalability,...
Power is a primary concern for mobile, cloud, and high-performance computing applications. Approximate computing refers to running applications to obtain results with tolerable errors under resource constraints, and it can be applied to balance energy consumption with service quality. In this paper, we propose a "Good Enough (GE)" scheduling algorithm that uses approximate computing to provide...
Many of todays important applications of our everyday lives, e.g. weather forecast, design of plane and car shapes, medical analysis or even search engine queries depend on massively-parallel computer programs that are executed in data centers hosting thousands of computers. A large amount of electrical energy is used to power them, and it is of primary importance to compute more efficiently to sustain...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.