بایگانی برچسب برای: Poisson distribution

Bacteriophages.Methods.and.Protocols.Volume.[taliem.ir]

Bacteriophages

Basic mathematical descriptions are useful in phage ecology, applied phage ecology such as in the course of phage therapy, and also toward keeping track of expected phage–bacterial interactions as seen during laboratory manipulation of phages. The most basic mathematical descriptor of phages is their titer, that is, their concentration within stocks, experimental vessels, or other environments. Various phenomena can serve to modify phage titers, and indeed phage titers can vary as a function of how they are measured. An important aspect of how changes in titers can occur results from phage interactions with bacteria. These changes tend to vary in degree as a function of bacterial densities within environments, and particularly densities of those bacteria that are susceptible to or at least adsorbable by a given phage type. Using simple mathematical models one can describe phage–bacterial interactions that give rise particularly to phage adsorption events. With elaboration one can consider changes in both phage and bacterial densities as a function of both time and these interactions. In addition, phages along with their impact on bacteria can be considered as spatially constrained processes. In this chapter we consider the simpler of these concepts, providing in particular detailed verbal explanations toward facile mathematical insight. The primary goal is to stimulate a more informed use and manipulation of phages and phage populations within the laboratory as well as toward more effective phage application outside of the laboratory, such as during phage therapy. More generally, numerous issues and approaches to the quantification of phages are considered along with the quantification of individual, ecological, and applied properties of phages.
Probabilistic Modeling to Achieve Load balancing in Expert Clouds[taliem.ir]

Probabilistic Modeling to Achieve Load balancing in Expert Clouds

Expert Cloud as a new class of Cloud computing systems enables its users to request the skill, knowledge and expertise of people without any information of their location by employing Internet infrastructures and Cloud computing concepts. Effective load balancing in a heterogeneous distributed environment such as Cloud is important. Since the differences in the human resource (HRs) capabilities and the variety of users' requests causes that some HRs are overloaded and some others are idle. The task allocation to the HR based on the announced requirements by the user may cause the imbalanced load distribution among HRs as well. Hence resource management and scheduling are among the important cases to achieve load balancing. Using static and dynamic algorithms, the ant colony, and the method based on searching tree all are among the methods to achieve load balancing. This paper presents a new method in order to distribute the dynamic load based on distributed queues aware of service quality in the Cloud environment. In this method, we utilize the colorful ants as a ranking for making distinction among the HRs capabilities. In this paper, we perform the mapping among the tasks and HRs using allocating a label to each HR. We model the load balancing and mapping process based on Poisson and exponential distribution. This model allows us to allocate each task to the HR which is able to execute it with maximum power using the distributed queues aware of the service quality. Simulation results show that the expert Cloud can reduce the execution and tardiness time and improve HR utilization. The cost of using resources as an effective factor in load balancing is also observed.