A Feature-Based Bayesian Method for Content Popularity Prediction in Edge-Caching Networks

Edge-caching is recognized as an efficient technique for future wireless cellular networks to improve network capacity and user-perceived quality of experience. Due to the random content requests and the limited cache memory, designing an efficient caching policy is a challenge. To enhance the performance of caching systems, an accurate content request prediction algorithm is essential. Here, we introduce a flexible model, a Poisson regressor based on a Gaussian process, for the content request distribution in stationary environments. Our proposed model can incorporate the content features as side information for prediction enhancement. In order to learn the model parameters, which yield the Poisson rates or alternatively content popularities, we invoke the Bayesian approach which is very robust against over-fitting. However, the posterior distribution in the Bayes formula is analytically intractable to compute. To tackle this issue, we apply a Monte Carlo Markov Chain (MCMC) method to approximate the posterior distribution. Two types of predictive distributions are formulated for the requests of existing contents and for the requests of a newly-added content. Finally, simulation results are provided to confirm the accuracy of the developed content popularity learning approach.Comment: arXiv admin note: substantial text overlap with arXiv:1903.0306

A Bayesian Poisson-Gaussian Process Model for Popularity Learning in Edge-Caching Networks

Edge-caching is recognized as an efficient technique for future cellular networks to improve network capacity and user-perceived quality of experience. To enhance the performance of caching systems, designing an accurate content request prediction algorithm plays an important role. In this paper, we develop a flexible model, a Poisson regressor based on a Gaussian process, for the content request distribution. The first important advantage of the proposed model is that it encourages the already existing or seen contents with similar features to be correlated in the feature space and therefore it acts as a regularizer for the estimation. Second, it allows to predict the popularities of newly-added or unseen contents whose statistical data is not available in advance. In order to learn the model parameters, which yield the Poisson arrival rates or alternatively the content \textit{popularities}, we invoke the Bayesian approach which is robust against over-fitting. However, the resulting posterior distribution is analytically intractable to compute. To tackle this, we apply a Markov Chain Monte Carlo (MCMC) method to approximate this distribution which is also asymptotically exact. Nevertheless, the MCMC is computationally demanding especially when the number of contents is large. Thus, we employ the Variational Bayes (VB) method as an alternative low complexity solution. More specifically, the VB method addresses the approximation of the posterior distribution through an optimization problem. Subsequently, we present a fast block-coordinate descent algorithm to solve this optimization problem. Finally, extensive simulation results both on synthetic and real-world datasets are provided to show the accuracy of our prediction algorithm and the cache hit ratio (CHR) gain compared to existing methods from the literature

Strategies for a centralized single product multiclass M/G/1 make-to-stock queue

Make-to-stock queues are typically investigated in the M/M/1 settings. For centralized single-item systems with backlogs, the multilevel rationing (MR) policy is established as optimal and the strict priority (SP) policy is a practical compromise, balancing cost and ease of implementation. However, the optimal policy is unknown when service time is general, i.e., for M/G/1 queues. Dynamic programming, the tool commonly used to investigate the MR policy in make-to-stock queues, is less practical when service time is general. In this paper we focus on customer composition: the proportion of customers of each class to the total number of customers in the queue. We do so because the number of customers in M/G/1 queues is invariant for any nonidling and nonanticipating policy. To characterize customer composition, we consider a series of two-priority M/G/1 queues where the first service time in each busy period is different from standard service times, i.e., this first service time is exceptional. We characterize the required exceptional first service times and the exact solution of such queues. From our results, we derive the optimal cost and control for the MR and SP policies for M/G/1 make-to-stock queues

A Temperature Total Fourier Series Solution For a Hollow Sphere

In the following pages, we exhibit an analytical solution of a two-dimensional temperature field in a hollow sphere under total periodic boundary condition. The material is assumed to be homogeneous and isotropic with time-independent thermal properties. Till now periodic boundary condition was derived with a harmonic vibration, whereas there is a noticeable difference in the practical conditions with harmonic vibration. In this essay, by means of Fourier analysis, we imagine the outside total periodic boundary condition, as aggregate of harmonic vibrations . To solve the problem, first we imagine the boundary condition as constant values and with separation of variables; we can obtain temperature distribution in the  sphere. Then Duhamel's theorem is used to calculate temperature field under fully periodic boundary condition. For confirmation of accurate solution, we can compare the result for a harmonic vibration and those reported by others. Also, solutions for a hollow sphere were compared with other present references. At last we can obtain thermal stresses which is caused by temperature field in the hollow sphere

Comparative Analysis of Sectoral Innovation System and Diamond Model: The Case of Telecom Sector of Iran

Porter’s model of Competitive advantage of nations (named as Diamond Model) has been widely used and criticized as well, over recent two decades. On the other hand, non-mainstream economists have tried to propose new frameworks for industrial analysis, that among them, Sectoral Innovation System (SIS) is one of the most influential ones. After proposing an assessment framework, we use this framework to compare SIS and Porter’s models and apply them to the case of second mobile operator in Iran. Briefly, SIS model sheds light on the innovation process and competence building and focuses on system failures that are of special importance in the context of developing countries, while Diamond model has the advantage of brining the production process and the influential role of government into focus, but each one has its own shortcomings for analyzing industrial development in developing countries and both of them fail to pay enough attention to foreign relations and international linkages.Porter’s model of Competitive advantage of nations (named as Diamond Model) has been widely used and criticized as well, over recent two decades. On the other hand, non-mainstream economists have tried to propose new frameworks for industrial analysis, that among them, Sectoral Innovation System (SIS) is one of the most influential ones. After proposing an assessment framework, we use this framework to compare SIS and Porter’s models and apply them to the case of second mobile operator in Iran. Briefly, SIS model sheds light on the innovation process and competence building and focuses on system failures that are of special importance in the context of developing countries, while Diamond model has the advantage of brining the production process and the influential role of government into focus, but each one has its own shortcomings for analyzing industrial development in developing countries and both of them fail to pay enough attention to foreign relations and international linkages.Porter’s model of Competitive advantage of nations (named as Diamond Model) has been widely used and criticized as well, over recent two decades. On the other hand, non-mainstream economists have tried to propose new frameworks for industrial analysis, that among them, Sectoral Innovation System (SIS) is one of the most influential ones. After proposing an assessment framework, we use this framework to compare SIS and Porter’s models and apply them to the case of second mobile operator in Iran. Briefly, SIS model sheds light on the innovation process and competence building and focuses on system failures that are of special importance in the context of developing countries, while Diamond model has the advantage of brining the production process and the influential role of government into focus, but each one has its own shortcomings for analyzing industrial development in developing countries and both of them fail to pay enough attention to foreign relations and international linkages

Enterprise architecture evaluation using architecture framework and UML stereotypes

There is an increasing need for enterprise architecture in numerous organizations with complicated systems with various processes. Support for information technology, organizational units whose elements maintain complex relationships increases. Enterprise architecture is so effective that its non-use in organizations is regarded as their institutional inability in efficient information technology management. The enterprise architecture process generally consists of three phases including strategic programing of information technology, enterprise architecture programing and enterprise architecture implementation. Each phase must be implemented sequentially and one single flaw in each phase may result in a flaw in the whole architecture and, consequently, in extra costs and time. If a model is mapped for the issue and then it is evaluated before enterprise architecture implementation in the second phase, the possible flaws in implementation process are prevented. In this study, the processes of enterprise architecture are illustrated through UML diagrams, and the architecture is evaluated in programming phase through transforming the UML diagrams to Petri nets. The results indicate that the high costs of the implementation phase will be reduced

The Effect of Social Status and Gender on Realization of Refusal of Suggestion among Iranian EFL Intermediate Learners

The current study aimed at exploring the dependence of realized and applied strategies in refusal of suggestion on the people of different levels of social status (i.e., equal, low and high) and the gender differences. Teaching communicative rules, social conventions and values of the target nation can help EFL learners to avoid pragmatic failures. One of the important factors in realization of refusal strategies is the speaker's knowledge of the refusals usage to save the interlocutor's face and to be polite. The participants of this study consisted of 60 (30 females and 30 males) intermediate English Foreign Language (EFL) learners in Tehran, Iran. Discourse-completion test (DCT) with 18 situations was used. Chi- square indicated that learners employed more indirect strategies to people of equal social status. They used more direct strategies to people of low social status, and we can claim that they applied the same types of direct and indirect strategies to people of high social status. Learners utilized more adjunct strategies to people of equal social status and the frequency of realized and applied strategies in refusal of suggestion was not statistically different between the female and male participants in each of three levels of social status.