Living on the Edge: The Role of Proactive Caching in 5G Wireless Networks

This article explores one of the key enablers of beyond $4$G wireless networks leveraging small cell network deployments, namely proactive caching. Endowed with predictive capabilities and harnessing recent developments in storage, context-awareness and social networks, peak traffic demands can be substantially reduced by proactively serving predictable user demands, via caching at base stations and users' devices. In order to show the effectiveness of proactive caching, we examine two case studies which exploit the spatial and social structure of the network, where proactive caching plays a crucial role. Firstly, in order to alleviate backhaul congestion, we propose a mechanism whereby files are proactively cached during off-peak demands based on file popularity and correlations among users and files patterns. Secondly, leveraging social networks and device-to-device (D2D) communications, we propose a procedure that exploits the social structure of the network by predicting the set of influential users to (proactively) cache strategic contents and disseminate them to their social ties via D2D communications. Exploiting this proactive caching paradigm, numerical results show that important gains can be obtained for each case study, with backhaul savings and a higher ratio of satisfied users of up to $22\%$ and $26\%$, respectively. Higher gains can be further obtained by increasing the storage capability at the network edge.Comment: accepted for publication in IEEE Communications Magazin

A Transfer Learning Approach for Cache-Enabled Wireless Networks

Locally caching contents at the network edge constitutes one of the most disruptive approaches in $5$G wireless networks. Reaping the benefits of edge caching hinges on solving a myriad of challenges such as how, what and when to strategically cache contents subject to storage constraints, traffic load, unknown spatio-temporal traffic demands and data sparsity. Motivated by this, we propose a novel transfer learning-based caching procedure carried out at each small cell base station. This is done by exploiting the rich contextual information (i.e., users' content viewing history, social ties, etc.) extracted from device-to-device (D2D) interactions, referred to as source domain. This prior information is incorporated in the so-called target domain where the goal is to optimally cache strategic contents at the small cells as a function of storage, estimated content popularity, traffic load and backhaul capacity. It is shown that the proposed approach overcomes the notorious data sparsity and cold-start problems, yielding significant gains in terms of users' quality-of-experience (QoE) and backhaul offloading, with gains reaching up to $22\%$ in a setting consisting of four small cell base stations.Comment: some small fixes in notatio

On the Delay of Geographical Caching Methods in Two-Tiered Heterogeneous Networks

We consider a hierarchical network that consists of mobile users, a two-tiered cellular network (namely small cells and macro cells) and central routers, each of which follows a Poisson point process (PPP). In this scenario, small cells with limited-capacity backhaul are able to cache content under a given set of randomized caching policies and storage constraints. Moreover, we consider three different content popularity models, namely fixed content popularity, distance-dependent and load-dependent, in order to model the spatio-temporal behavior of users' content request patterns. We derive expressions for the average delay of users assuming perfect knowledge of content popularity distributions and randomized caching policies. Although the trend of the average delay for all three content popularity models is essentially identical, our results show that the overall performance of cached-enabled heterogeneous networks can be substantially improved, especially under the load-dependent content popularity model.Comment: to be presented at IEEE SPAWC'2016, Edinburgh, U

On the Benefits of Edge Caching for MIMO Interference Alignment

In this contribution, we jointly investigate the benefits of caching and interference alignment (IA) in multiple-input multiple-output (MIMO) interference channel under limited backhaul capacity. In particular, total average transmission rate is derived as a function of various system parameters such as backhaul link capacity, cache size, number of active transmitter-receiver pairs as well as the quantization bits for channel state information (CSI). Given the fact that base stations are equipped both with caching and IA capabilities and have knowledge of content popularity profile, we then characterize an operational regime where the caching is beneficial. Subsequently, we find the optimal number of transmitter-receiver pairs that maximizes the total average transmission rate. When the popularity profile of requested contents falls into the operational regime, it turns out that caching substantially improves the throughput as it mitigates the backhaul usage and allows IA methods to take benefit of such limited backhaul.Comment: 20 pages, 5 figures. A shorter version is to be presented at 16th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC'2015), Stockholm, Swede

Flexible Cache-Aided Networks with Backhauling

Caching at the edge is a promising technique to cope with the increasing data demand in wireless networks. This paper analyzes the performance of cellular networks consisting of a tier macro-cell wireless backhaul nodes overlaid with a tier of cache-aided small cells. We consider both static and dynamic association policies for content delivery to the user terminals and analyze their performance. In particular, we derive closed-form expressions for the area spectral efficiency and the energy efficiency, which are used to optimize relevant design parameters such as the density of cache-aided small cells and the storage size. By means of this approach, we are able to draw useful design insights for the deployment of highly performing cache-aided tiered networks.Comment: 5 pages, 5 figures, to be presented at 18th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC'2017), Sapporo, Japan, 201

If unnecessary computed tomography scans are performing for abdominal emergent pathologies in our radiology unit; retrospective study with comparing performed abdominal computed tomography scans with previous safer tests like ultrasound

Background: Abdominal computed tomography (CT) is an imaging method that uses X-rays and may be done to look for cause of abdominal pain or swelling and fever, hernia, masses, ınfections, injury. Besides advantages, CT use ionizing radiation, which has the potential to cause cancer. So CT may still be done if the benefits greatly outweigh the risks and it is important to minimize unnecessary CT scans. While a CT scan may provide information, it is sometimes unlikely to change the treatment. This is exactly the type of scan that may be doing a patient more harm than good. So we wonder how we are performing nontraumatic emergent abdominal CT scans in our own radiology unit, if applications are more effective and least harmful.Methods: In random 232 patients were selected from 1188 nontraumatic emergent abdominal CT scans in the last one year. Findings and previous ultrasonographies were compared and if CT scans brought additional information were examined.Results: In 5 patients ileus, in 2 patients perforation, in 2 patients appendicitis and in 3 patients ureteral calculi were detected on CT that have not been detected on sonography. In 52 patients pathologies were detected on both ultrasound (US) and CT. 168 patients had not had any pathology. All these findings have been thought that only in 12 patients CT examinations were effective (3 for diagnosing and 9 for verifying secondary findings).Conclusions: Doctors should consider whether some scans are doing more harm than good because CT scans may cause a large number of new cancers every year.

If this argument is true: Hashimoto's disease causes chronic thyroid damage so in diseased elderly population the thyroid volumes must be low-retrospective US study

Background: Hashimoto thyroiditis is part of the spectrum of autoimmune thyroid diseases and is characterized by the destruction of thyroid cells by various cell and antibody-mediated immune processes. It primarily affects middle-aged women but also can occur in men and children. Hashimoto's disease typically progresses slowly over years and causes chronic thyroid damage. This has to be thought that in diseased elderly population the thyroid volumes must be low. This paper shows if this argument is true and how thyroid volumes change over years by the disease Hashimoto because of chronic thyroid damage. A review of the literature revealed several studies about thyroid volume changes by aging and by Hashimoto thyroiditis separately. But there has not been any study in literature wondering how thyroid volumes change by aging in the course of the disease Hashimoto.Methods: The study was designed as a retrospective investigation. The study group included 136 patients who admitted for sonography examination between the years 2012-2014 whom have suffered from Hashimoto’s disease. In the study, control groups were formed with 73 healthy individuals who volunteered for participation. The volume of each thyroid lobe was calculated with ellipsoid formula: (volume (ml) = Length (cm) x Width (cm) x Thickness (cm) x1/6 Л ).Results: While healthy individuals are grown older, thyroid volumes are increased. In diseased individuals while aging although disease causes chronic thyroid damage, volume measurements do not change.Conclusions: The results have suggested that while aging although disease causes chronic thyroid damage, volume measurements do not change. Because volume reduction due to chronic damage of disease is balanced by volume increase due to aging.

Examining life satisfaction level depending on physical activity in Turkish and German societies

AbstractPhysical activity is also known to make a positive change on organic systems such as respiration,circulation,skeleton and psychological situation.This study aims to examine the life satisfaction level depending on physical activity in Turkish and German societies.The research sample includes 200 people doing exercise and not doing exercise in Konya and 200 people doing exercise and not doing exercise in Munich city of Germany in 2009..Life Satisfaction With Life Scale developed by Deiner,Emmons&Larsen (1985) was used to determine the level of life satisfaction of the subjects included in the sample.To conclude,Life Satisfaction level in Turkish and German societies was examined considering with demographic information and a significant difference has been found.A significant difference has been found between life satisfaction levels of the individuals participating and not participating in physical activity

Teachers’ views about ethical leadership behaviors of primary school directors

AbstractThe aim of this study is to find out whether private and public primary schools directors show ethical behavior. In the research survey method was used. The data was collected with “Ethical Leadership Scale”. T-test was used for the analysis of data, the significance of data was found to be .05. The result of the study indicate that school and private primary school director display high ethical leadership behavior, mostly in communication dimension which is a sub-dimension of ethical leadership behaviors. Besides, it was found out that private school directors show more ethical leadership behavior than in all four sub-dimension of ethical behavior compared to public school directors

Big Data Caching for Networking: Moving from Cloud to Edge

In order to cope with the relentless data tsunami in $5G$ wireless networks, current approaches such as acquiring new spectrum, deploying more base stations (BSs) and increasing nodes in mobile packet core networks are becoming ineffective in terms of scalability, cost and flexibility. In this regard, context-aware $5$G networks with edge/cloud computing and exploitation of \emph{big data} analytics can yield significant gains to mobile operators. In this article, proactive content caching in $5$G wireless networks is investigated in which a big data-enabled architecture is proposed. In this practical architecture, vast amount of data is harnessed for content popularity estimation and strategic contents are cached at the BSs to achieve higher users' satisfaction and backhaul offloading. To validate the proposed solution, we consider a real-world case study where several hours of mobile data traffic is collected from a major telecom operator in Turkey and a big data-enabled analysis is carried out leveraging tools from machine learning. Based on the available information and storage capacity, numerical studies show that several gains are achieved both in terms of users' satisfaction and backhaul offloading. For example, in the case of $16$ BSs with $30\%$ of content ratings and $13$ Gbyte of storage size ($78\%$ of total library size), proactive caching yields $100\%$ of users' satisfaction and offloads $98\%$ of the backhaul.Comment: accepted for publication in IEEE Communications Magazine, Special Issue on Communications, Caching, and Computing for Content-Centric Mobile Network