Deployment Options Research Articles

Link Quality Improvement of Long-Term Evolution and 802.11ax in High-Density Areas

The 802.11ax high-efficiency wireless (HEW) particularly designed for high-density areas. However, dense areas have specific requirements that demand precise deployment strategies by network developers. In dense networks, a large number of users are simultaneously connected to the same channel; hence, the available bandwidth is divided among the users in such a way that joining more users can eventually saturate the network. Furthermore, in dense areas, a large number of closely spaced users are transmitting data at the same time. In such a heavily frequency interfered environment, the wireless link quality extremely degrades, which can practically render the network unavailable. Thereby, it is essential to determine the appropriate deployment options regarding the specific networks’ settings and configurations. Hence, this work proposes a network architecture model to determine the dual-band HEW performance in dense deployments. The model additionally includes long-term evolution (LTE) as the cellular alternative for high-density areas which is utilized by the model as the reference point for corresponding comparison purposes with HEW. The model is implemented, and link quality parameters are measured based on different aspects of the deployment options. To further validate the model and determine the optimization levels provided by the options, the simulation and analytical results are compared.

Virtualization in CyberGIS instruction: lessons learned constructing a private cloud to support development and delivery of a WebGIS course

ABSTRACT Students in geographic information systems and science (GIS) require significant experience outside of spatial analysis, cartography, and other traditional geographic topics. Computer science knowledge, skills, and practices exist as essential components of GIS practice, but coursework in this area is not universally offered in geography or GIS degrees. To support those interested in developing such courses, this paper describes the design and implementation of a server-focused course in WebGIS at Texas A&M University. We provide an in-depth discussion of the equipment and resources required to build and operate an on-premise CyberGIS server infrastructure suitable for supporting such classes, providing comparisons with an equivalent solution built on Amazon Web Services (AWS). We consider the comparative costs of these systems, including benefits and drawbacks of each. In comparing these deployment options, we outline the technical expertise, monetary investments, operational expenses, and organizational strategies necessary to run server-based CyberGIS courses. Finally, we reflect on assignments and feedback from students and consider their experiences in a course of this nature. This article provides a resource for GIS instructors, academic departments, or other academic units to consider during infrastructure investment, curriculum redesign, the addition of courses in degree plans, or for the development of CyberGIS components.

Hover or Perch: Comparing Capacity of Airborne and Landed Millimeter-Wave UAV Cells

On-demand deployments of millimeter-wave (mmWave) access points (APs) carried by unmanned aerial vehicles (UAVs) are considered today as a potential solution to enhance the performance of 5G+ networks. The battery lifetime of modern UAVs, though, limits the flight times in such systems. In this letter, we evaluate a feasible deployment alternative for temporary capacity boosting in the areas with highly fluctuating user demands. The approach is to land UAV-based mmWave APs on the nearby buildings instead of hovering over the area. Within the developed mathematical framework, we compare the system-level performance of airborne and landed deployments by taking into account the full operation cycle of the employed drones. Our numerical results demonstrate that the choice of the UAV deployment option is determined by an interplay of the separation distance between the service area and the UAV charging station, drone battery lifetime, and the number of aerial APs in use. The presented methodology and results can support efficient on-demand deployments of UAV-based mmWave APs in prospective 5G+ networks.

A Service-Based Architecture for Enabling UAV Enhanced Network Services

This article provides an overview of enhanced network services, while emphasizing the role of UAVs as core network equipment with radio and backhaul capabilities. Initially, we elaborate the various deployment options, focusing on UAVs as airborne radio, backhaul and core network equipment, pointing out the benefits and limitations. We then analyze the required enhancements in the SBA to support UAV services including UAV navigation and air traffic management, weather forecasting and UAV connectivity management. The use of airborne UAVs network services is assessed via qualitative means, considering the impact on vehicular applications. Finally, an evaluation has been conducted via a testbed implementation, to explore the performance of UAVs as edge cloud nodes, hosting an ACS function responsible for the control and orchestration of a UAV fleet.

Multi-stage stochastic programming models for provisioning cloud computing resources

We focus on the resource provisioning problem of a cloud consumer from an Infrastructure-as-a-Service type of cloud. The cloud provider offers two deployment options, which can be mixed and matched as appropriate. Cloud instances may be reserved for a fixed time period in advance at a smaller usage cost per hour but require a full commitment and payment for the entire contract duration. In contrast, on-demand instances reflect a pay-as-you-go policy at a premium. The trade-off between these two options is rooted in the inherent uncertainty in demand and price and makes it attractive to complement a base reserved capacity with on-demand capacity to hedge against the spikes in demand. This paper provides several novel multi-stage stochastic programming formulations to enable a cloud consumer to handle the cloud resource provisioning problem at a tactical level. We first formulate the cloud resource provisioning problem as a risk-neutral multi-stage stochastic program, which serves as the base model for further modeling variants. In our second set of models, we also incorporate a certain concept of system reliability. In particular, chance constraints integrated into the base formulation require a minimum service level met from reserved capacity, provide more visibility into the future available capacity, and smooth out expensive on-demand usage by hedging against possible demand fluctuations. An extensive computational study demonstrates the value of the proposed models by discussing computational performance, gleaning practical managerial insights from the analysis of the solutions of the proposed models, and quantifying the value of the stochastic solutions.

Mobile Relay Technology for 5G

This paper summarizes the current status and future prospects of the mobile relay technology toward the direction of 5G. It discusses several key technical challenges when developing and deploying a mobile relay system in the aspects of frequency band, mobility, duplexing, and handover. It is expected that a mobile relay can be an efficient and cost effective deployment option in future 5G releases.

Breeding unicorns: Developing trustworthy and scalable randomness beacons.

Randomness beacons are services that periodically emit a random number, allowing users to base decisions on the same random value without trusting anyone: ideally, the randomness beacon does not only produce unpredictable values, but is also of low computational complexity for the users, bias-resistant and publicly verifiable. Such randomness beacons can serve as an important primitive for smart contracts in a variety of contexts. This paper first presents a structured security analysis, based on which we then design, implement, and evaluate a trustworthy and efficient randomness beacon. Our approach does not require users to register or run any computationally intensive operations. We then compare different implementation and deployment options on distributed ledgers, and report on an Ethereum smart contract-based lottery using our beacon.

Establishment of wMel Wolbachia in Aedes aegypti mosquitoes and reduction of local dengue transmission in Cairns and surrounding locations in northern Queensland, Australia.

Background: The wMel strain of Wolbachia has been successfully introduced into Aedes aegypti mosquitoes and subsequently shown in laboratory studies to reduce transmission of a range of viruses including dengue, Zika, chikungunya, yellow fever, and Mayaro viruses that cause human disease. Here we report the entomological and epidemiological outcomes of staged deployment of Wolbachia across nearly all significant dengue transmission risk areas in Australia. Methods: The wMel strain of Wolbachiawas backcrossed into the local Aedes aegyptigenotype (Cairns and Townsville backgrounds) and mosquitoes were released in the field by staff or via community assisted methods. Mosquito monitoring was undertaken and mosquitoes were screened for the presence of Wolbachia. Dengue case notifications were used to track dengue incidence in each location before and after releases. Results: Empirical analyses of the Wolbachia mosquito releases, including data on the density, frequency and duration of Wolbachia mosquito releases, indicate that Wolbachia can be readily established in local mosquito populations, using a variety of deployment options and over short release durations (mean release period 11 weeks, range 2-22 weeks). Importantly, Wolbachia frequencies have remained stable in mosquito populations since releases for up to 8 years. Analysis of dengue case notifications data demonstrates near-elimination of local dengue transmission for the past five years in locations where Wolbachia has been established. The regression model estimate of Wolbachia intervention effect from interrupted time series analyses of case notifications data prior to and after releases, indicated a 96% reduction in dengue incidence in Wolbachia treated populations (95% confidence interval: 84 - 99%). Conclusion: Deployment of the wMel strain of Wolbachia into local Ae. aegypti populations across the Australian regional cities of Cairns and most smaller regional communities with a past history of dengue has resulted in the reduction of local dengue transmission across all deployment areas.

Novel blockchain reference model for government services: Dubai government case study

Blockchain, a Distributed Ledger Technology, is a disruptive and revolutionary technology that enables transacting data in a decentralized structure without the need for trusted central authorities. Many industries have taken steps to unleash the potential of blockchain technology, including the government sector, and early adopters are exploring the use of blockchain as one of the critical capabilities needed to create new business models and to radically transform government services and functions. However, despite this interest in adopting Blockchain technology, there is a lack of Blockchain frameworks or reference models/architecture that addresses government services in literature. In this paper, we propose a novel blockchain model that can be adopted by governments to establish government-led blockchain ecosystem for government services. The blockchain model is proposed based on the outcomes of our analysis of permissioned blockchain platform, and analysis of blockchain powered housing rentals use case that is being implemented by the Dubai Government. The proposed blockchain model outcomes includes a blockchain governance structure, participants and roles definition, and network architecture design which explains the deployment options and components. We also explain the model lifecycle and blockchain services, and we shed the light on the security and performance of the model. The study also includes exploring many blockchain use cases used by governments through proofs of concept or prototypes. Our analysis of Hyperledger Fabric design features shows the platform’s relevance to government services and use cases. The Hyperledger Fabric analysis also identifies the platform’s actors, services, processes and data structure of Hyperledger Fabric.

Establishment of wMel Wolbachia in Aedes aegypti mosquitoes and reduction of local dengue transmission in Cairns and surrounding locations in northern Queensland, Australia

Background: The wMel strain of Wolbachia has been successfully introduced into Aedes aegypti mosquitoes and subsequently shown in laboratory studies to reduce transmission of a range of viruses including dengue, Zika, chikungunya, yellow fever, and Mayaro viruses that cause human disease. Here we report the entomological and epidemiological outcomes of staged deployment of Wolbachia across nearly all significant dengue transmission risk areas in Australia. Methods: The wMel strain of Wolbachia was backcrossed into the local Aedes aegypti genotype (Cairns and Townsville backgrounds) and mosquitoes were released in the field by staff or via community assisted methods. Mosquito monitoring was undertaken and mosquitoes were screened for the presence of Wolbachia. Dengue case notifications were used to track dengue incidence in each location before and after releases. Results: Empirical analyses of the Wolbachia mosquito releases, including data on the density, frequency and duration of Wolbachia mosquito releases, indicate that Wolbachia can be readily established in local mosquito populations, using a variety of deployment options and over short release durations (mean release period 11 weeks, range 2-22 weeks). Importantly, Wolbachia frequencies have remained stable in mosquito populations since releases for up to 8 years. Analysis of dengue case notifications data demonstrates near-elimination of local dengue transmission for the past five years in locations where Wolbachia has been established. The regression model estimate of Wolbachia intervention effect from interrupted time series analyses of case notifications data prior to and after releases, indicated a 96% reduction in dengue incidence in Wolbachia treated populations (95% confidence interval: 84 – 99%). Conclusion: Deployment of the wMel strain of Wolbachia into local Ae. aegypti populations across the Australian regional cities of Cairns and most smaller regional communities with a past history of dengue has resulted in the reduction of local dengue transmission across all deployment areas.

Correction to: Patient-specific simulation of transcatheter aortic valve replacement: impact of deployment options on paravalvular leakage.

This is to inform that the original article was published without the "Conflict of Interest" statement.

Evaluation of Optimized CNNs on Heterogeneous Accelerators using a Novel Benchmarking Approach

Numerous algorithmic optimization techniques have been proposed to alleviate the computational complexity of convolutional neural networks. Given the broad selection of AI accelerators, it is not obvious which approach benefits from which optimization most. The design space includes a large number of deployment settings (batch sizes, power modes, etc.) and unclear measurement methods. This research provides clarity into this design space, leveraging a novel benchmarking approach. We provide a theoretical evaluation of different CNNs and hardware platforms, focusing on understanding the impact of pruning and quantization as primary optimization techniques. We benchmark across a spectrum of FPGA, GPU, TPU, and VLIW processors for systematically pruned and quantized neural networks (ResNet50, GoogLeNetv1, MobileNetv1, a VGG derivative, a multilayer perceptron) over many deployment options, considering power, latency, and throughput at a specific accuracy. Our findings show that channel pruning is most effective and works across most hardware platforms, with speedups directly correlated to the reduction in compute load, while FPGAs benefit the most from quantization. Pruning and quantization are orthogonal, and yield optimal design points when combined. Further in-depth results can be found at our web portal, where we share all experimental data, provide data analytics, and invite the community to contribute.

On the value of corner reflectors and surface models in InSAR precise point positioning

To correctly interpret the estimated displacements in InSAR point clouds, especially in the built environment, these need to be linked to real-world structures. This requires the accurate and precise 3D positioning of each point. Artificial ground control points (GCPs), such as corner reflectors, serve this purpose, but since they require efforts and resources, there is a need for criteria to assess their usefulness. Here we evaluate the value and necessity of using GCPs for different scenarios, concerning the required efforts, and compare this to alternatives such as digital surface models (DSM) and advanced (geo) physical corrections. We consider single-epoch as well as multi-epoch GCP deployment, reflect on the number of GCPs required in relation to the number of SAR data acquisitions, and compare this with digital surface models of different quality levels. Analyzing the geolocation performance using TerraSAR-X and Sentinel-1 data, we evaluate the pros and cons of various deployment options and show that the multi-epoch deployment of a GCP yields optimal geolocalization results in terms of precision, accuracy, and reliability.

Fog Computing in IoT Smart Environments via Named Data Networking: A Study on Service Orchestration Mechanisms

By offering low-latency and context-aware services, fog computing will have a peculiar role in the deployment of Internet of Things (IoT) applications for smart environments. Unlike the conventional remote cloud, for which consolidated architectures and deployment options exist, many design and implementation aspects remain open when considering the latest fog computing paradigm. In this paper, we focus on the problems of dynamically discovering the processing and storage resources distributed among fog nodes and, accordingly, orchestrating them for the provisioning of IoT services for smart environments. In particular, we show how these functionalities can be effectively supported by the revolutionary Named Data Networking (NDN) paradigm. Originally conceived to support named content delivery, NDN can be extended to request and provide named computation services, with NDN nodes acting as both content routers and in-network service executors. To substantiate our analysis, we present an NDN fog computing framework with focus on a smart campus scenario, where the execution of IoT services is dynamically orchestrated and performed by NDN nodes in a distributed fashion. A simulation campaign in ndnSIM, the reference network simulator of the NDN research community, is also presented to assess the performance of our proposal against state-of-the-art solutions. Results confirm the superiority of the proposal in terms of service provisioning time, paid at the expenses of a slightly higher amount of traffic exchanged among fog nodes.

Establishment of wMel Wolbachia in Aedes aegypti mosquitoes and reduction of local dengue transmission in Cairns and surrounding locations in northern Queensland, Australia.

Background: The wMel strain of Wolbachia has been successfully introduced into Aedes aegypti mosquitoes and subsequently shown in laboratory studies to reduce transmission of a range of viruses including dengue, Zika, chikungunya, yellow fever, and Mayaro viruses that cause human disease. Here we report the entomological and epidemiological outcomes of staged deployment of Wolbachia across nearly all significant dengue transmission risk areas in Australia. Methods: The wMel strain of Wolbachiawas backcrossed into the local Aedes aegyptigenotype (Cairns and Townsville backgrounds) and mosquitoes were released in the field by staff or via community assisted methods. Mosquito monitoring was undertaken and mosquitoes were screened for the presence of Wolbachia. Dengue case notifications were used to track dengue incidence in each location before and after releases. Results: Empirical analyses of the Wolbachia mosquito releases, including data on the density, frequency and duration of Wolbachia mosquito releases, indicate that Wolbachia can be readily established in local mosquito populations, using a variety of deployment options and over short release durations (mean release period 11 weeks, range 2-22 weeks). Importantly, Wolbachia frequencies have remained stable in mosquito populations since releases for up to 8 years. Analysis of dengue case notifications data demonstrates near-elimination of local dengue transmission for the past five years in locations where Wolbachia has been established. The regression model estimate of Wolbachia intervention effect from interrupted time series analyses of case notifications data prior to and after releases, indicated a 96% reduction in dengue incidence in Wolbachia treated populations (95% confidence interval: 84 - 99%). Conclusion: Deployment of the wMel strain of Wolbachia into local Ae. aegypti populations across the Australian regional cities of Cairns and most smaller regional communities with a past history of dengue has resulted in the reduction of local dengue transmission across all deployment areas.

Business Models for Local 5G Micro Operators

5G will change the mobile communication business ecosystem by introducing location specific high-quality wireless networks that can be operated by different stakeholders. This development will change the traditional business models and ecosystem roles, as well as open the market for new local mobile network operators. These operators, such as recently introduced micro operators, can target specific customers in different vertical sectors with closed 5G networks, serve mobile network operator’s (MNO) customers in high-demand areas on behalf of the MNO as a neutral host with open 5G networks, or mix different types of customers and offerings through various hybrid platform business models. This paper discusses business model options for local 5G micro operators, addressing also the different network deployment options and ecosystem constellations. Three generic 5G business models and respective value ecosystems are presented: 1) vertical business model and ecosystem; 2) horizontal business model and ecosystem; and 3) oblique business model and ecosystem. These business models are compared against the opportunities they address, drivers and boundaries of value they may generate, and sources and sustainability of advantages they represent. Finally, scalability, adaptability, and sustainability of the business models and ecosystems are examined.

Efficient Provisioning of Security Service Function Chaining Using Network Security Defense Patterns

Network functions virtualization intertwined with software-defined networking opens up great opportunities for flexible provisioning and composition of network functions, known as network service chaining. In the cloud, this allows providers to create service chains tuned to each application type while optimizing resources’ utilization. This is particularly useful to accommodate different tenants’ applications with different security needs. However, considering security provisioning from the single perspective of resources optimization may lead to deployment solutions that do not comply with well-known security-related best practices and recommendations. In this paper, we propose network security defense patterns (NSDP) aimed at leveraging the best practice and know-how from the security experts and at capturing various security constraints to efficiently select compliant security functions’ deployment options. The placement problem being a NP-Hard problem to solve, we also propose a scalable networking and computing resources aware optimization framework to efficiently provision different NSDPs. We further show the feasibility of implementing NSDPs in the cloud infrastructure through the integration of our approach into an open source cloud framework, namely OpenStack, in our test laboratory. The simulation results show the effectiveness of our approach in selecting an optimal placement of the security functions for large data centers with hundreds of thousands of computing nodes, while complying with the predefined security constraints and improving the scalability compared to the current placement algorithms.

Transparency in Decision Modelling: What, Why, Who and How?

Transparency in decision modelling is an evolving concept. Recently, discussion has moved from reporting standards to open-source implementation of decision analytic models. However, in the debate about the supposed advantages and disadvantages of greater transparency, there is a lack of definition. The purpose of this article is not to present a case for or against transparency, but rather to provide a more nuanced understanding of what transparency means in the context of decision modelling and how it could be addressed. To this end, we review and summarise the discourse to date, drawing on our collective experience. We outline a taxonomy of the different manifestations of transparency, including reporting standards, reference models, collaboration, model registration, peer review and open-source modelling. Further, we map out the role and incentives for the various stakeholders, including industry, research organisations, publishers and decision makers. We outline the anticipated advantages and disadvantages of greater transparency with respect to each manifestation, as well as the perceived barriers and facilitators to greater transparency. These are considered with respect to the different stakeholders and with reference to issues including intellectual property, legality, standards, quality assurance, code integrity, health technology assessment processes, incentives, funding, software, access and deployment options, data protection and stakeholder engagement. For each manifestation of transparency, we discuss the 'what', 'why', 'who' and 'how'. Specifically, their meaning, why the community might (or might not) wish to embrace them, whose engagement as stakeholders is required and how relevant objectives might be realised. We identify current initiatives aimed to improve transparency to exemplify efforts in current practice and for the future.

Optical Transport Network Design for 5G Fixed Wireless Access

The fifth generation (5G) of mobile technology, 5G is anticipated to be a significant leap in the evolution of mobile communication. 5G will be designed to attain 1000 times higher data volumes, 10 times lower latency, and 100 times more connected devices than its predecessor, 4G. Due to 5Gs ability to sustain high bandwidth per unit area, 5G is considered to be a cost-efficient solution to provide fixed wireless access (FWA) to households on a large scale. FWA is seen as an attractive alternative for fixed broadband access in scenarios where last mile access based on wired technologies is not economically viable. While approaches for enhancing user experience in a 5G FWA environment are investigated in the research community, the problem of providing cost-effective high capacity transport for FWA deployments still remains a major challenge. This is particularly challenging due to diverse transport network architectures and requirements imposed by different 5G deployment models. This paper addresses this problem by formulating a generalized joint-optimization framework to simultaneously plan wireless access and optical transport for 5G FWA networks in order to minimize the deployment cost while meeting various network requirements. We demonstrate the applicability of the proposed framework by applying it to a real scenario with a range of deployment options and where different types of optical x-haul solutions are considered. The results provide a cornerstone for deployment strategies that will be imperative for realizing a future-proof and cost-effective broadband access network.

EMPATIA

Participatory budgeting (PB) is currently one of the most widely adopted democratic innovations. ICT platforms are key enablers of PB processes, by supporting citizen engagement. They support the establishment of diverse participation channels to build candidate proposals, for the voting process, and for monitoring proposals' implementation. PB platforms differ from electronic voting systems, reflecting the intrinsic nature of PB processes. While vote secrecy and trustworthiness of voting results is still a major requirement, other factors weight in, such as the focus on the whole process and the need for engaging several citizens by providing multiple participation channels. PB processes take place at multiple scales (municipal, national) requiring flexible deployment and dimensioning approaches. EMPATIA is an ICT platform for PB, based on multiple dimensioning and deployment options that reflect the scenarios where PB tools are expected to operate. The evaluation results provide relevant inputs to the design and implementation of similar participatory and/or voting platforms.