32 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

    Get PDF
    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Bowdoin College Catalogue and Academic Handbook (2023-2024)

    Get PDF
    https://digitalcommons.bowdoin.edu/course-catalogues/1321/thumbnail.jp

    LIPIcs, Volume 244, ESA 2022, Complete Volume

    Get PDF
    LIPIcs, Volume 244, ESA 2022, Complete Volum

    Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking

    Get PDF
    The emerging massive density of human-held and machine-type nodes implies larger traffic deviatiolns in the future than we are facing today. In the future, the network will be characterized by a high degree of flexibility, allowing it to adapt smoothly, autonomously, and efficiently to the quickly changing traffic demands both in time and space. This flexibility cannot be achieved when the network’s infrastructure remains static. To this end, the topic of UAVs (unmanned aerial vehicles) have enabled wireless communications, and networking has received increased attention. As mentioned above, the network must serve a massive density of nodes that can be either human-held (user devices) or machine-type nodes (sensors). If we wish to properly serve these nodes and optimize their data, a proper wireless connection is fundamental. This can be achieved by using UAV-enabled communication and networks. This Special Issue addresses the many existing issues that still exist to allow UAV-enabled wireless communications and networking to be properly rolled out

    Bowdoin College Catalogue and Academic Handbook (2022-2023)

    Get PDF
    https://digitalcommons.bowdoin.edu/course-catalogues/1320/thumbnail.jp

    Pervasive AI for IoT applications: A Survey on Resource-efficient Distributed Artificial Intelligence

    Get PDF
    Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of Things (IoT) applications and services, spanning from recommendation systems and speech processing applications to robotics control and military surveillance. This is driven by the easier access to sensory data and the enormous scale of pervasive/ubiquitous devices that generate zettabytes of real-time data streams. Designing accurate models using such data streams, to revolutionize the decision-taking process, inaugurates pervasive computing as a worthy paradigm for a better quality-of-life (e.g., smart homes and self-driving cars.). The confluence of pervasive computing and artificial intelligence, namely Pervasive AI, expanded the role of ubiquitous IoT systems from mainly data collection to executing distributed computations with a promising alternative to centralized learning, presenting various challenges, including privacy and latency requirements. In this context, an intelligent resource scheduling should be envisaged among IoT devices (e.g., smartphones, smart vehicles) and infrastructure (e.g., edge nodes and base stations) to avoid communication and computation overheads and ensure maximum performance. In this paper, we conduct a comprehensive survey of the recent techniques and strategies developed to overcome these resource challenges in pervasive AI systems. Specifically, we first present an overview of the pervasive computing, its architecture, and its intersection with artificial intelligence. We then review the background, applications and performance metrics of AI, particularly Deep Learning (DL) and reinforcement learning, running in a ubiquitous system. Next, we provide a deep literature review of communication-efficient techniques, from both algorithmic and system perspectives, of distributed training and inference across the combination of IoT devices, edge devices and cloud servers. Finally, we discuss our future vision and research challenges

    INSPIRE: Distributed Bayesian Optimization for ImproviNg SPatIal REuse in Dense WLANs

    Full text link
    WLANs, which have overtaken wired networks to become the primary means of connecting devices to the Internet, are prone to performance issues due to the scarcity of space in the radio spectrum. As a response, IEEE 802.11ax and subsequent amendments aim at increasing the spatial reuse of a radio channel by allowing the dynamic update of two key parameters in wireless transmission: the transmission power (TX_POWER) and the sensitivity threshold (OBSS_PD). In this paper, we present INSPIRE, a distributed solution performing local Bayesian optimizations based on Gaussian processes to improve the spatial reuse in WLANs. INSPIRE makes no explicit assumptions about the topology of WLANs and favors altruistic behaviors of the access points, leading them to find adequate configurations of their TX_POWER and OBSS_PD parameters for the "greater good" of the WLANs. We demonstrate the superiority of INSPIRE over other state-of-the-art strategies using the ns-3 simulator and two examples inspired by real-life deployments of dense WLANs. Our results show that, in only a few seconds, INSPIRE is able to drastically increase the quality of service of operational WLANs by improving their fairness and throughput

    YALJOD Full Issue 3.1

    Get PDF
    The Young African Leaders Journal of Development (YALJOD) is a biennial journal and an official publication of the Young African Leaders Forum (YALF). It was established in 2015 to host scholarly analysis and competing viewpoints about the development of Africa; and it’s multidisciplinary approach makes it more formidable. YALJOD accepts papers from varied disciplinary areas — including Social Sciences, Physical Sciences and Humanities — that show direct relevance to the development of Africa. It publishes researches understood as the social, economic, political, cultural and technological processes of change in Africa. The intended audience of the journal remains the entire African people. Howbeit, for effectiveness, special emphasis is given to African leadership operators, development academics, researchers and youths — who appear to be the next African leaders

    Triple Helix as a Strategic Tool to Fast-Track Climate Change Adaptation in Rural Kenya: Case Study of Marsabit County

    Get PDF
    AbstractThe lack of affordable, clean, and reliable energy in Africa's rural areas forces people to resort to poor quality energy source, which is detrimental to the people's health and prevents the economic development of communities. Moreover, access to safe water and food security are concerns closely linked to health issues and children malnourishment. Recent climate change due to global warming has worsened the already critical situation.Electricity is well known to be an enabler of development as it allows the use of modern devices thus enabling the development of not only income-generating activities but also water pumping and food processing and conservation that can promote socioeconomic growth. However, all of this is difficult to achieve due to the lack of investors, local skills, awareness by the community, and often also government regulations.All the above mentioned barriers to the uptake of electricity in rural Kenya could be solved by the coordinated effort of government, private sector, and academia, also referred to as Triple Helix, in which each entity may partially take the other's role. This chapter discretizes the above and shows how a specific county (Marsabit) has benefited from this triple intervention. Existing government policies and actions and programs led by nongovernmental organizations (NGOs) and international agencies are reviewed, highlighting the current interconnection and gaps in promoting integrated actions toward climate change adaptation and energy access

    Bowdoin College Catalogue and Academic Handbook (2021-2022)

    Get PDF
    https://digitalcommons.bowdoin.edu/course-catalogues/1319/thumbnail.jp
    corecore