Multi-site Resource Allocation in a QoS-Aware 5G Infrastructure

Network softwarization has paved the way for 5G technologies, and a wide-range of (radically new) verticals. As the telecommunications infrastructure evolves into a sort of distributed datacenter, multiple tenants such as vertical industries and network service providers share its aggregate pool of resources (e.g., networking, computing, etc.) in a layered \u201das-a-Service\u201d approach exposed as slice abstractions. The challenge remains in the coordination of various stakeholders\u2019 assets in realizing end-to-end network slices and supporting the multi-site deployment and chaining of the micro-service components needed to implement cloud-native vertical applications (vApps). In this context, particular care must be taken to ensure that the required resources are identified, made available and managed in a way that satisfies the vApp requirements, allows for a fair share of resources and has a reasonable impact on the overall vApp deployment time. With these challenges in mind, this paper presents the Resource Selection Optimizer (RSO)-a software-service in the MATILDA Operations Support System (OSS), whose main goal is to select the most appropriate network and computing resources (according to some criterion) among a list of options provided by the Wide-area Infrastructure Manager (WIM). It consists of three submodules that respectively handle: (i) the aggregation of vApp components based on affinities, (ii) the forecasting of (micro-) datacenter resources utilization, (iii) and the multi-site placement of the (aggregated) vApp micro-service components. The RSO\u2019s performance is mainly evaluated in terms of the execution times of its submodules while varying their respective input parameters, and additionally, three selection policies are also compared. Experimental results aim to highlight the RSO behavior in both execution times and deployment costs, as well as the RSO interactions with other OSS submodules and network platform components, not only for multi-site vApp deployment but also for other network/services management operations

The dark side of network functions virtualization: A perspective on the technological sustainability

The Network Functions Virtualization (NFV) paradigm is undoubtedly a key technological advancement in the Information and Communication Technology (ICT) community, especially for the upcoming 5G network design. While most of its promise is quite straightforward, the implied reduction of the power consumption/carbon footprint is still debatable, and not in line with the energy efficiency perspective forecasted by the ETSI NFV working group (WG). In this paper, we provide an estimate of the possible future requirements of this upcoming technology when deployed according to the virtual Evolved Packet Core (vEPC) use case specified by the ETSI NFV WG. Our estimation is based on real performance levels, certified by independent third-party laboratories, and datasheet values provided by existing commercial products for both the legacy and NFV network architectures, under different deployment scenarios. Obtained results show that a massive deployment of the current NFV technologies in the EPC may lead to a minimum increase of 106 % in the carbon footprint/energy consumption with respect to the Business As Usual (BAU) network solutions. Moreover, these values tend to increase at a very high pace when the most suitable software/hardware combination is not applied, or when packet processing latency is taken into account

Citizen to Stay or Citizen to Go? Naturalization, Security, and Mobility of Migrants in Italy

https://doi.org/10.1080/15562948.2016.1208316We analyze the relation between naturalization, mobility, and security through 50 in-depth interviews with migrants of different origins living in two Italian regions. We show how migrants pursue naturalization both to protect themselves against bureaucracy and deportation and to move to a third country. The second migration is motivated by improving one's conditions, forced by the economic crisis, or completes the original migratory project once a strong passport is obtained. We argue that citizenship is not essentially linked to either stability or mobility and that mobility should be understood as neither exceptional nor always chosen

Scientific writing: a randomized controlled trial comparing standard and on-line instruction

<p>Abstract</p> <p>Background</p> <p>Writing plays a central role in the communication of scientific ideas and is therefore a key aspect in researcher education, ultimately determining the success and long-term sustainability of their careers. Despite the growing popularity of e-learning, we are not aware of any existing study comparing on-line vs. traditional classroom-based methods for teaching scientific writing.</p> <p>Methods</p> <p>Forty eight participants from a medical, nursing and physiotherapy background from US and Brazil were randomly assigned to two groups (n = 24 per group): An on-line writing workshop group (on-line group), in which participants used virtual communication, google docs and standard writing templates, and a standard writing guidance training (standard group) where participants received standard instruction without the aid of virtual communication and writing templates. Two outcomes, manuscript quality was assessed using the scores obtained in Six subgroup analysis scale as the primary outcome measure, and satisfaction scores with Likert scale were evaluated. To control for observer variability, inter-observer reliability was assessed using Fleiss's kappa. A post-hoc analysis comparing rates of communication between mentors and participants was performed. Nonparametric tests were used to assess intervention efficacy.</p> <p>Results</p> <p>Excellent inter-observer reliability among three reviewers was found, with an Intraclass Correlation Coefficient (ICC) agreement = 0.931882 and ICC consistency = 0.932485. On-line group had better overall manuscript quality (p = 0.0017, SSQSavg score 75.3 ± 14.21, ranging from 37 to 94) compared to the standard group (47.27 ± 14.64, ranging from 20 to 72). Participant satisfaction was higher in the on-line group (4.3 ± 0.73) compared to the standard group (3.09 ± 1.11) (p = 0.001). The standard group also had fewer communication events compared to the on-line group (0.91 ± 0.81 vs. 2.05 ± 1.23; p = 0.0219).</p> <p>Conclusion</p> <p>Our protocol for on-line scientific writing instruction is better than standard face-to-face instruction in terms of writing quality and student satisfaction. Future studies should evaluate the protocol efficacy in larger longitudinal cohorts involving participants from different languages.</p

“It’s Like Hating Puppies!” Employee Disengagement and Corporate Social Responsibility

Corporate social responsibility (CSR) has been linked with numerous organizational advantages, including recruitment, retention, productivity, and morale, which relate specifically to employees. However, despite specific benefits of CSR relating to employees and their importance as a stakeholder group, it is noteworthy that a lack of attention has been paid to the individual level of analysis with CSR primarily being studied at the organizational level. Both research and practice of CSR have largely treated the individual organization as a “black box,” failing to account for individual differences amongst employees and the resulting variations in antecedents to CSR engagement or disengagement. This is further exacerbated by the tendency in stakeholder theory to homogenize priorities within a single stakeholder group. In response, utilizing case study data drawn from three multinational tourism and hospitality organizations, combined with extensive interview data collected from CSR leaders, industry professionals, engaged, and disengaged employees, this exploratory research produces a finer-grained understanding of employees as a stakeholder group, identifying a number of opportunities and barriers for individual employee engagement in CSR interventions. This research proposes that employees are situated along a spectrum of engagement from actively engaged to actively disengaged. While there are some common drivers of engagement across the entire spectrum of employees, differences also exist depending on the degree to which employees, rather than senior management, support corporate responsibility within their organizations. Key antecedents to CSR engagement that vary depending on employees’ existing level of broader engagement include organizational culture, CSR intervention design, employee CSR perceptions, and the observed benefits of participation

Managing 5G network slicing and edge computing with the MATILDA telecom layer platform

The fifth generation (5G) of mobile networks is seen as a key enabler to support the introduction of digital technologies in multiple sectors, empowering different verticals and enabling new business models. Thanks to native capabilities of 5G networks, especially network slicing, edge computing and multi-tenancy, highly integrated telecom infrastructures with end-to-end flexibility will be realized to lower the barriers for creating 5G-ready applications that are able to satisfy business and user necessities. In this context, the MATILDA Project has established a holistic framework that unifies the development, deployment and operation for this new kind of applications. Since Edge Computing is not natively supported by 4G, in order to anticipate the technological improvements foreseen with the advent of 5G, as well as to smoothen the transition to the new technology, this paper describes the design of the end-point between the mobile and edge environments that has been integrated in the MATILDA telecom layer platform. Such end-point, designed in a Virtual Network Function (VNF), allows intercepting and forwarding data and control traffic towards external Data Networks. Instances of this VNF can be horizontally scaled according to a decision policy, which determines the minimum number of instances required for the current load. Results show that the latency ascribable to the VNF processing is sufficiently low to satisfy the delay budget for all 5G use-cases up to 10 ms and that a QCI-based decision policy allows scaling with the traffic load, while still fulfilling the performance requirements of each application

Modeling Performance and Energy Efficiency of Virtualized Flexible Networks

We examine some aspects of modelling and control in modern telecommunication networks, in the light of their evolution toward a completely virtualised paradigm on top of a flexible physical infrastructure. The trade-off between performance indicators related to user satisfaction of services (e.g., in terms of perceived quality, delay and ease of the interaction) and the energy consumption induced on the physical infrastructure is considered with some attention. In this respect, we provide a discussion of potential problems and ways to face them, along with a short description of the approaches taken in some European project activities

ANNs Going beyond Time Series Forecasting: An Urban Network Perspective

5G is expected to bring forth disruptive indus-trial-societal transformation by enabling a broad catalog of (radically new, highly heterogeneous) applications and services. This scenario has called for zero-touch network and service management (ZSM). With the recent advancements in artificial intelligence, key ZSM capabilities such as the runtime prediction of user demands can be facilitated by data-driven and machine learning methods. In this respect, the article proposes a runtime prediction approach that transforms time series forecasting into a simpler multivariate regression problem with artificial neural networks (ANNs), structurally optimized with a genetic algorithm (GA) metaheuristic. Leveraging on a novel set of input features that capture seasonality and calendar effects, the proposed approach removes the prediction accuracy's dependence on the temporal succession of input data and the forecast horizon. Evaluation results based on real telecommunications data show that the GA-optimized ANN regressor has better prediction performance. It achieved average improvements of 59 percent and 86 percent compared to 1-day and 1-hour ahead forecasts obtained with state-of-the-art multi-seasonal time series and long short-term memory forecasting models, respectively. Furthermore, despite its longer training times compared to the baseline models, the proposed ANN regressor relaxes the monitoring requirements in 5G dynamic management systems by allowing less frequent retraining offline