An Efficient Edge Servers Selection in Content Delivery Network Using Voronoi Diagram

Handle on demand network popularity of the Content Delivery Network and solve the flash crowd problem, caching web content at the internet’s edge server has been emerged. To provide faster service of the web users, content come from nearby edge servers. Therefore nearest edge server finding of a particular web user is an open research problem and it ensures a faster response time and download time of the requested content due to reduced latency. Our simulation study and application to a real set of geographical coordinates of the edge servers which are geographically dispersed and a well-known geometric device, Voronoi diagram is used for decomposing the earth surface around each location of a particular edge server and closest edge servers of the requested web user is searched by the nearest neighbor queries using Delaunay triangulation property over the aforesaid decomposed earth surface

Organic Molecular Thin Films on Device-Relevant Substrates

Organic thin films are central to many cutting-edge electronic devices. Improving our understanding of the characteristics of thin films is important not only to the development of condensed matter physics but also to our ability to engineer specialized devices that we demand be ever smaller, less expensive, and more efficient. This thesis applies the experimental techniques of scanning tunneling microscopy and spectroscopy to the task of characterizing submonolayer thin films of two types: the organic semiconductor C60 on silicon oxide, and self-assembling porous networks of trimesic acid on graphite. Capture zone analysis of the initial nucleation regime for C60 on ultrathin silicon oxide is reported. The critical nucleus size, reflecting the largest unstable cluster of particles on a surface, is found to have a parabolic dependence on temperature rather than a monotonically increasing one. Between stages of stable monomers (i=0$) at 480 K, a peak corresponding to i=1 is found at 386±3 K. This unique temperature dependence is attributed to defect-like variation in the silicon oxide surface. The first successful room-temperature UHV STM of trimesic acid on graphite is also presented here. These exploratory studies indicate the potential for a variety of porous hexagonal networks of trimesic acid to exist on a graphitic surface at room temperature. Significant electronic effects on graphite from trimesic acid lattices are shown via scanning tunneling spectroscopy, including an electronic state at -0.14 V that appears in networks whose pores are filled with excess TMA guest molecules. Ultimately, if the growth of TMA films could be extended to graphene, then the periodicity of electronegative oxygen atoms in molecules physisorbed on the graphene surface is predicted to provide a slight energy shift between the degenerate sublattices, opening a band gap. Promising directions for future research in these areas are also discussed

Tutorial on LTE/LTE-A Cellular Network Dimensioning Using Iterative Statistical Analysis

LTE is the fastest growing cellular technology and is expected to increase its footprint in the coming years, as well as progress toward LTE-A. The race among operators to deliver the expected quality of experience to their users is tight and demands sophisticated skills in network planning. Radio network dimensioning (RND) is an essential step in the process of network planning and has been used as a fast, but indicative, approximation of radio site count. RND is a prerequisite to the lengthy process of thorough planning. Moreover, results from RND are used by players in the industry to estimate preplanning costs of deploying and running a network; thus, RND is, as well, a key tool in cellular business modelling. In this work, we present a tutorial on radio network dimensioning, focused on LTE/LTE-A, using an iterative approach to find a balanced design that mediates among the three design requirements: coverage, capacity, and quality. This approach uses a statistical link budget analysis methodology, which jointly accounts for small and large scale fading in the channel, as well as loading due to traffic demand, in the interference calculation. A complete RND manual is thus presented, which is of key importance to operators deploying or upgrading LTE/LTE-A networks for two reasons. It is purely analytical, hence it enables fast results, a prime factor in the race undertaken. Moreover, it captures essential variables affecting network dimensions and manages conflicting targets to ensure user quality of experience, another major criterion in the competition. The described approach is compared to the traditional RND using a commercial LTE network planning tool. The outcome further dismisses the traditional RND for LTE due to unjustified increase in number of radio sites and related cost, and motivates further research in developing more effective and novel RND procedures

A Unified Line-of-Sight Probability Model for Commercial 5G Mobile Network Deployments

In this paper we present a novel analytical approach used to derive a new multi-scenario line-of-sight (LOS) probability model for cellular network deployments in the UK. The approach considers the use of lamp post databases as statistically representative geo-spatial data points for evaluation of LOS likelihood from macro cellular base stations. Crucially, the proposed model is built on a high resolution (0.25-1 m) 3D digital surface model underpinned by real network and environmental datasets and validated with supporting field measurements. This work unifies all common cell site classification types; urban, suburban and rural into a single 3D LOS statistical probability model whilst also addressing the influence of endpoint height properties up to 10 m. The contributions outlined in this paper have applications in statistical path loss modelling and coverage/outage probability. They also have direct application in deployment modelling of mmWave (millimeter wave) mobile access networks (24.25-52.6 GHz) and wireless x-haul transport networks (71-174.8 GHz)

Analysis of millimeter wave and massive MIMO cellular networks

Millimeter wave (mmWave) communication and massive multiple-input multiple-output (MIMO) are promising techniques to increase system capacity in 5G cellular networks. The prior frameworks for conventional cellular systems do not directly apply to analyze mmWave or massive MIMO networks, as (i) mmWave cellular networks differ in the different propagation conditions and hardware constraints; and (ii) with a order of magnitude more antennas than conventional multi-user MIMO systems, massive MIMO systems will be operated in time-division duplex (TDD) mode, which renders pilot contamination a primary limiting factor. In this dissertation, I develop stochastic geometry frameworks to analyze the system-level performance of mmWave, sub-6 GHz massive MIMO, and mmWave massive MIMO cellular networks. The proposed models capture the key features of each technique, and allow for tractable signal-to-interference-plus-noise ratio (SINR) and rate analyses. In the first contribution, I develop an mmWave cellular network model that incorporates the blockage effect and directional beamforming, and analyze the SINR and rate distributions as functions of the base station density, blockage parameters, and antenna geometry. The analytical results demonstrate that with a sufficiently dense base station deployment, mmWave cellular networks are capable to achieve comparable SINR coverage and much higher rates than conventional networks. In my second contribution, I analyze the uplink SINR and rate in sub-6 GHz massive MIMO networks with the incorporation of pilot contamination and fractional power control. Based on the analysis, I show scaling laws between the number of antennas and scheduled users per cell that maintain the uplink signal-to-interference ratio (SIR) distributions are different for maximum ratio combining (MRC) and zero-forcing (ZF) receivers. In my third contribution, I extend the sub-6 GHz massive MIMO model to mmWave frequencies, by incorporating key mmWave features. I leverage the proposed model to investigate the asymptotic SINR performance, when the number of antennas goes to infinity. Numerical results show that mmWave massive MIMO outperforms its sub-6 GHz counterpart in cell throughput with a dense base station deployment, while the reverse can be true with a low base station density.Electrical and Computer Engineerin

Context-Aware Self-Healing for Small Cell Networks

These can be an invaluable source of information for the management of the network, in a way that we have denominated as context-aware SON, which is the approach proposed in this thesis. To develop this concept, the thesis follows a top-down approach. Firstly, the characteristics of the cellular deployments are assessed, especially for indoor small cell networks. In those scenarios, the need for context-aware SON is evaluated and considered indispensable. Secondly, a new cellular architecture is defined to integrate both context information and SON mechanisms in the management plane of the mobile network. Thus, the specifics of making context an integral part of cellular OAM/SON are defined. Also, the real-world implementation of the architecture is proposed. Thirdly, from the established general SON architecture, a logical self-healing framework is defined to support the context-aware healing mechanisms to be developed. Fourthly, different self-healing algorithms are defined depending on the failures to be managed and the conditions of the considered scenario. The mechanisms are based on probabilistic analysis, making use of both context and network data for detection and diagnosis of cellular issues. The conditions for the implementation of these methods are assessed. Their applicability is evaluated by means of simulators and testbed trials. The results show important improvements in performance and capabilities in comparison to previous methods, demonstrating the relevance of the proposed approach.The last years have seen a continuous increase in the use of mobile communications. To cope with the growing traffic, recently deployed technologies have deepened the adoption of small cells (low powered base stations) to serve areas with high demand or coverage issues, where macrocells can be both unsuccessful or inefficient. Also, new cellular and non-cellular technologies (e.g. WiFi) coexist with legacy ones, including also multiple deployment schemes (macrocell, small cells), in what is known as heterogeneous networks (HetNets). Due to the huge complexity of HetNets, their operation, administration and management (OAM) became increasingly difficult. To overcome this, the NGMN Alliance and the 3GPP defined the Self-Organizing Network (SON) paradigm, aiming to automate the OAM procedures to reduce their costs and increase the resulting performance. One key focus of SON is the self-healing of the network, covering the automatic detection of problems, the diagnosis of their causes, their compensation and their recovery. Until recently, SON mechanisms have been solely based on the analysis of alarms and performance indicators. However, on the one hand, this approach has become very limited given the complexity of the scenarios, and particularly in indoor cellular environments. Here, the deployment of small cells, their coexistence with multiple telecommunications systems and the nature of those environments (in terms of propagation, coverage overlapping, fast demand changes and users' mobility) introduce many challenges for classic SON. On the other hand, modern user equipment (e.g. smartphones), equipped with powerful processors, sensors and applications, generate a huge amount of context information. Context refers to those variables not directly associated with the telecommunication service, but with the terminals and their environment. This includes the user's position, applications, social data, etc

Inhomogeneous Double Thinning—Modeling and Analysis of Cellular Networks by Using Inhomogeneous Poisson Point Processes

In this paper, we introduce a new methodology for modeling and analyzing downlink cellular networks, where the base stations (BSs) constitute a motion-invariant point process (PP) that exhibits some degree of interactions among the points, i.e., spatial repulsion or spatial clustering. The proposed approach is based on the theory of inhomogeneous Poisson PPs (I-PPPs) and is referred to as inhomogeneous double thinning (IDT) approach. In a PP, the distribution of the distance from a randomly distributed (typical) user to its nearest BS depends on the degree of spatial repulsion or clustering exhibited by the PP. In addition, the average number of interfering BSs that lies within a given distance from the typical user is a function of the repulsion and clustering characteristics of the PP. The proposed approach consists of approximating the original motion-invariant PP with an equivalent PP that is made of the superposition of two conditionally independent I-PPPs. The inhomogeneities of both PPs are created from the point of view of the typical user (“user-centric”): the first one is based on the distribution of the user’s distance to its nearest BS and the second one is based on the distance-dependent average number of interfering BSs around the user. The inhomogeneities are mathematically modeled through two distance-dependent thinning functions and a tractable expression of the coverage probability is obtained. Sufficient conditions on the parameters of the thinning functions that guarantee better or worse coverage compared with the baseline homogeneous PPP model are identified. The accuracy of the IDT approach is substantiated with the aid of empirical data for the spatial distribution of the BSs