How has the notion of home been shaped by the uptake of interconnected mobile devices and online platforms? This chapter addresses this inquiry by opening the discussion through mapping the motivations behind the formation of a digital and transnational arrangement among dispersed family members. To begin with, it illustrates the journey of migration among transnational families in Melbourne, Australia. By analysing the mobilization of familial interactions via mobile devices and online platforms, it coins the conceptual term ‘zones of reterritorialized domesticity’, highlighting the liminal, networked, hybridized, and contradictory aspect of a transnational and digital home. This conception builds on unravelling how family norms and values, mobile platforms, and technological infrastructures shape the performance, embodiment, and negotiation of a home from afar. Ultimately, the chapter lays bare the foundation of interrogating the production of transnational homemaking in uneven mobile environments.
To what extent do digital communication technologies reconfigure the enactment of everyday family rituals in a transnational arrangement? This chapter maps the diverse impacts of digital media use on transnational family members in the performance, embodiment, and negotiation of intimate family rituals. It particularly shows how the personalized use of both broadband-based or visual-based platforms and regular calls facilitate interactions and mediated co-presence as well as the maintenance of familial bonds beyond borders. Notably, it examines the underlying tensions experienced in mobilizing family rituals as reflected in contradictory experiences and affective surveillance. Communicative issues are typically shaped by the lack of access to a stable connectivity, a certain level of technological competency, as well as differing familial expectations and living conditions. In sum, the chapter outlines the benefits and ruptures of mediating ritualized domestic interactions in digital spaces.
How do digital communication technologies mobilize the enactment of family celebrations in a transnational setting? This chapter unwraps the bittersweet moments of digital media use by migrants and their left-behind family members to enact intimate interactions during special family occasions. In the first instance, it showcases the joyful, creative, and customized moments embodied by transnational family members through the circulation of personalized messages and material gifts. However, it also exposes the frustrating experiences encountered by dispersed family members, as shaped by asymmetrical familial dynamics, economic status, uneven access, digital literacy, and technological parameters. Ultimately, this chapter opens a critical conversation on the paradoxical outcomes of the reliance of transnational family members on smartphones, social media, and mobile applications to reclaim and revive traditional and household celebrations in their efforts to sustain ties at a distance.
In what ways digital communication technologies shape the experiences of navigating multiple crises among transnational family members? This chapter investigates the diverse and personalized digital practices of transnational families in handling the consequences of natural calamities and family-based crises. As a start, it illustrates how dispersed family members use digital media technologies to enact different phases of addressing a typhoon in the Philippines—preparation, constant monitoring, and recovery. It also presents their digital practices in managing family-related personal and health issues. Importantly, it foregrounds the digital disruptions that exacerbate critical and anxiety-inducing conditions while examining the diverse tactics deployed by transnational families to cope with multiple crises and gain a sense of assurance. In short, the chapter illuminates the benefits and tensions produced through connective practices for crisis management in a transnational household.
The detection of of Heavy Hitter (HH) flows in a network device is a critical building block in many control and management tasks. A flow is considered a Heavy Hitter flow if its portion from the total traffic surpasses a given threshold. One of the most important aspect of this detection is its practicality; i.e., being able to work in line rate using the available scarce local memory in the device. In this paper, we present a practical heavy hitters detection algorithm that requires a constant amount of memory (not related to the number of flows or the number of packets) and performs at most O(1) operation per packet to keep with line rate. We present an analysis of errors for our algorithm and compare it to state-of-the-art monitoring solutions, showing a superior performance where the allocated memory is less than 1 MB. In particular, we are able to detect more HH flows with less false positive without increasing the per-packet processing time.
Self-Organizing Networks (SON) concept is a technology that aims to improve the management and operation of mobile networks, through automatic configuration of network parameters. Even though SON functions are able to change network parameters automatically, the algorithms that run inside these functions still rely on parameters and rules that are manually defined by the operator, depending on its objectives. Thus, in order to realize a network that is self-organized as a whole, there is a clear need for a higher-level management entity that automatically translates operator objectives into SON configurations. In previous works, we have already studied and proposed an intelligent integrated management solution empowered with Reinforcement Learning (RL), namely the Cognitive Policy Based SON Management (C-PBSM).The C-PBSM is able to learn optimal SON configurations through direct interaction with the network. In this paper, we address crucial aspects of the mentioned approach, namely adaptability with different and varying network environments, transferability of the knowledge and the speed of convergence. We argue that the C-PBSM has major limitations with respect to these aspects. We consequently propose a context aware C-PBSM show that it is able to overcome the limitations of the C-PBSM.
With the development of deep learning methods, adopting CNN-based detectors has become a trend to handle the detection task. The proposal of Intelligent Transportation Systems (ITS) has once again brought autonomous vehicles into the public eye. Pedestrian detection can ensure pedestrians’ safety, and it is considered one of the most challenging problems that urgently need to be solved. We have noticed that researchers use various environments when publishing experimental results, leading to unfair comparisons of experimental results. Under different computing resources, the performance of the detector may be weakened or enhanced. In this paper, we will compare two representative detectors with the same computing power for a fair comparison study, aiming to find out how experimental settings affect the detector’s accuracy.
Tanja Evers beleuchtet in ihrem Beitrag die Darstellung der Unterbringung von Geflüchteten in lokalen Öffentlichkeiten. Im Rahmen einer quantitativen Inhaltsanalyse von Regionalzeitungen analysiert sie Themen, Akteur*innen, Bewertungen und Forderungen im massenmedialen Diskurs über Ankereinrichtungen in Bayern und Sachsen. Journalistische Berichterstattung wird dabei als Faktor der (Im-)Mobilisierung und öffentliche Kommunikation als eigene Dimension der Mobilität konzeptualisiert. Im Ergebnis bewertet der mediale Diskurs die Unterbringungssituation zwar insgesamt durchaus kritisch, jedoch weniger differenziert denn polarisiert. Die Artikel vermitteln in der Regel einen engen Kanon von überwiegend problemzentrierten Narrativen. Geflüchtete werden in ihnen zwar sichtbar, allerdings treten sie kaum selbst als Sprecher*innen auf.
To improve bandwidth sharing in IP networks, load balancing and rate control are key traffic engineering ingredients. In this context, we propose a fully distributed load balancing and rate allocation mechanism that operates only from the edge. Each access router is able to determine target rates over multiple paths for different traffic aggregates based on already available link state information and, some small and optional, information received from other edge devices. Our distributed utility maximization solution provides a feasible rate allocation at each iteration with diminishing returns. Through numerical results on a variety of instances, we show that it converges to near optimal solutions after a few iterations. Thanks to packet-level simulations on an SD-WAN scenario, we also show that it can well prioritize traffic over centralized and legacy solutions.
