Coexistence and interference mitigation for WPANs and WLANs from traditional approaches to deep learning: a review

More and more devices, such as Bluetooth and IEEE 802.15.4 devices forming Wireless Personal Area Networks (WPANs) and IEEE 802.11 devices constituting Wireless Local Area Networks (WLANs), share the 2.4 GHz Industrial, Scientific and Medical (ISM) band in the realm of the Internet of Things (IoT) and Smart Cities. However, the coexistence of these devices could pose a real challenge—co-channel interference that would severely compromise network performances. Although the coexistence issues has been partially discussed elsewhere in some articles, there is no single review that fully summarises and compares recent research outcomes and challenges of IEEE 802.15.4 networks, Bluetooth and WLANs together. In this work, we revisit and provide a comprehensive review on the coexistence and interference mitigation for those three types of networks. We summarize the strengths and weaknesses of the current methodologies, analysis and simulation models in terms of numerous important metrics such as the packet reception ratio, latency, scalability and energy efficiency. We discover that although Bluetooth and IEEE 802.15.4 networks are both WPANs, they show quite different performances in the presence of WLANs. IEEE 802.15.4 networks are adversely impacted by WLANs, whereas WLANs are interfered by Bluetooth. When IEEE 802.15.4 networks and Bluetooth co-locate, they are unlikely to harm each other. Finally, we also discuss the future research trends and challenges especially Deep-Learning and Reinforcement-Learning-based approaches to detecting and mitigating the co-channel interference caused by WPANs and WLANs

LINK ADAPTATION IN WIRELESS NETWORKS: A CROSS-LAYER APPROACH

Conventional Link Adaptation Techniques in wireless networks aim to overcome harsh link conditions caused by physical environmental properties, by adaptively regulating modulation, coding and other signal and protocol specific parameters. These techniques are essential for the overall performance of the networks, especially for environments where the ambient noise level is high or the noise level changes rapidly. Link adaptation techniques answer the questions of What to change? and When to change? in order to improve the present layer performance. Once these decisions are made, other layers are expected to function perfectly with the new communication channel conditions. In our work, we have shown that this assumption does not always hold; and provide two mechanisms that lessen the negative outcomes caused by these decisions. Our first solution, MORAL, is a MAC layer link adaptation technique which utilizes the physical transmission information in order to create differentiation between wireless users with different communication capabilities. MORAL passively collects information from its neighbors and re-aligns the MAC layer parameters according to the observed conditions. MORAL improves the fairness and total throughput of the system through distributing the mutually shared network assets to the wireless users in a fairer manner, according to their capabilities. Our second solution, Data Rate and Fragmentation Aware Ad-hoc Routing protocol, is a network layer link adaptation technique which utilizes the physical transmission information in order to differentiate the wireless links according to their communication capabilities. The proposed mechanism takes the physical transmission parameters into account during the path creation process and produces energy-efficient network paths. The research demonstrated in this dissertation contributes to our understanding of link adaptation techniques and broadens the scope of such techniques beyond simple, one-step physical parameter adjustments. We have designed and implemented two cross-layer mechanisms that utilize the physical layer information to better adapt to the varying channel conditions caused by physical link adaptation mechanisms. These mechanisms has shown that even though the Link Adaptation concept starts at the physical layer, its effects are by no means restricted to this layer; and the wireless networks can benefit considerably by expanding the scope of this concept throughout the entire network stack

Cooperative scheduling and load balancing techniques in fog and edge computing

Fog and Edge Computing are two models that reached maturity in the last decade. Today, they are two solid concepts and plenty of literature tried to develop them. Also corroborated by the development of technologies, like for example 5G, they can now be considered de facto standards when building low and ultra-low latency applications, privacy-oriented solutions, industry 4.0 and smart city infrastructures. The common trait of Fog and Edge computing environments regards their inherent distributed and heterogeneous nature where the multiple (Fog or Edge) nodes are able to interact with each other with the essential purpose of pre-processing data gathered by the uncountable number of sensors to which they are connected to, even by running significant ML models and relying upon specific processors (TPU). However, nodes are often placed in a geographic domain, like a smart city, and the dynamic of the traffic during the day may cause some nodes to be overwhelmed by requests while others instead may become completely idle. To achieve the optimal usage of the system and also to guarantee the best possible QoS across all the users connected to the Fog or Edge nodes, the need to design load balancing and scheduling algorithms arises. In particular, a reasonable solution is to enable nodes to cooperate. This capability represents the main objective of this thesis, which is the design of fully distributed algorithms and solutions whose purpose is the one of balancing the load across all the nodes, also by following, if possible, QoS requirements in terms of latency or imposing constraints in terms of power consumption when the nodes are powered by green energy sources. Unfortunately, when a central orchestrator is missing, a crucial element which makes the design of such algorithms difficult is that nodes need to know the state of the others in order to make the best possible scheduling decision. However, it is not possible to retrieve the state without introducing further latency during the service of the request. Furthermore, the retrieved information about the state is always old, and as a consequence, the decision is always relying on imprecise data. In this thesis, the problem is circumvented in two main ways. The first one considers randomised algorithms which avoid probing all of the neighbour nodes in favour of at maximum two nodes picked at random. This is proven to bring an exponential improvement in performance with respect to the probe of a single node. The second approach, instead, considers Reinforcement Learning as a technique for inferring the state of the other nodes thanks to the reward received by the agents when requests are forwarded. Moreover, the thesis will also focus on the energy aspect of the Edge devices. In particular, will be analysed a scenario of Green Edge Computing, where devices are powered only by Photovoltaic Panels and a scenario of mobile offloading targeting ML image inference applications. Lastly, a final glance will be given at a series of infrastructural studies, which will give the foundations for implementing the proposed algorithms on real devices, in particular, Single Board Computers (SBCs). There will be presented a structural scheme of a testbed of Raspberry Pi boards, and a fully-fledged framework called ``P2PFaaS'' which allows the implementation of load balancing and scheduling algorithms based on the Function-as-a-Service (FaaS) paradigm

Aesthetics, Innovation, and the Politics of Film-Production at Lenfil'm, 1961-1991

This thesis examines the relationship between Lenfil´m film-studio and the Soviet Party-state apparatus in the context of successive reformist projects and shifting repertory strategies pursued by filmmakers and executives. Drawing upon archival records, cinema-historical scholarship, professional testimonies, and feature-films, it demonstrates a studio-specific approach to the institutional relations that shaped late-Soviet cinema as an artistic process, an industry, and a political sphere. In 1961, significant reorganizations of production at Lenfil´m assured an unprecedented devolution of executive responsibilities – commissioning, development, shoot-supervision – to new, cineaste-led production-units. These artistic cohorts were afforded sufficient license to shape their professional profiles around distinctive repertory policies, which reflected the artistic interests of their filmmakers, but were also compelled to adapt these proposals to the thematic categories fixed by late-Soviet cinema’s central administrative structures. This thesis asks how Lenfil´m cineastes negotiated ideological screening and pursued aesthetical innovation in filmmaking, towards which the administrative system was consistently suspicious or outright hostile. It then considers how the studio’s repertory profile changed in response to resurgent official orthodoxies in the 1970s, only to incorporate renewed privileging of art-cinema into this response by the end of that decade. In the 1980s, with perestroika, attempts at democratization and market-focused reform found these production-units to be the irreducible professional nuclei of late-Soviet cinema. Their structures, artistic identities, and decision-making prerogatives persisted beyond all practicality of adherence to an inflexible administrative system and a collapsing film-distribution network. Through production-histories, analysis of Communist Party policies, and detailed examinations of the reforms that modified studio-structures, this thesis argues that the final three decades of the USSR saw filmmakers and studio-level administrators develop heterogenous repertory innovations, despite the crudeness of official ideological oversight. Lenfil´m became the bastion of late-Soviet auteurism within an industrial system that ought, by its own measure, to have precluded this possibility

The Viet Nam Generation Big Book

An anthology of essays, narrative, poetry and graphics published in lieu of a 1993 issue of Viet Nam Generation, intended to be used as a textbook for teaching about the 1960s. Edited by Dan Duffy and Kali Tal. Contributing editors: Renny Christopher. David DeRose, Alan Farrell. Cynthia Fuchs, William M. King. Bill Shields, Tony Williams, and David Willson