Mixed-signal CNN array chips for image processing

Due to their local connectivity and wide functional capabilities, cellular nonlinear networks (CNN) are excellent candidates for the implementation of image processing algorithms using VLSI analog parallel arrays. However, the design of general purpose, programmable CNN chips with dimensions required for practical applications raises many challenging problems to analog designers. This is basically due to the fact that large silicon area means large development cost, large spatial deviations of design parameters and low production yield. CNN designers must face different issues to keep reasonable enough accuracy level and production yield together with reasonably low development cost in their design of large CNN chips. This paper outlines some of these major issues and their solutions

Agile-SD: A Linux-based TCP Congestion Control Algorithm for Supporting High-speed and Short-distance Networks

Recently, high-speed and short-distance networks are widely deployed and their necessity is rapidly increasing everyday. This type of networks is used in several network applications; such as Local Area Networks (LAN) and Data Center Networks (DCN). In LANs and DCNs, high-speed and short-distance networks are commonly deployed to connect between computing and storage elements in order to provide rapid services. Indeed, the overall performance of such networks is significantly influenced by the Congestion Control Algorithm (CCA) which suffers from the problem of bandwidth under-utilization, especially if the applied buffer regime is very small. In this paper, a novel loss-based CCA tailored for high-speed and Short-Distance (SD) networks, namely Agile-SD, has been proposed. The main contribution of the proposed CCA is to implement the mechanism of agility factor. Further, intensive simulation experiments have been carried out to evaluate the performance of Agile-SD compared to Compound and Cubic which are the default CCAs of the most commonly used operating systems. The results of the simulation experiments show that the proposed CCA outperforms the compared CCAs in terms of average throughput, loss ratio and fairness, especially when a small buffer is applied. Moreover, Agile-SD shows lower sensitivity to the buffer size change and packet error rate variation which increases its efficiency.Comment: 12 Page

Autonomous QoS Management and Policing in Unmanaged Local Area Networks

The high increase of bandwidth-intensive applications like high definition video streaming in home and small office environments leads to QoS challenges in hybrid wired/wireless local area networks. These networks are often not QoS aware and may contain bottlenecks in their topology. In addition, they often have a hybrid nature due to the used access technology consisting of, for example, Ethernet, wireless, and PowerLAN links. In this paper, we present the research work on a novel autonomous system for hybrid QoS in local area networks, called QoSiLAN, which does not rely on network infrastructure support but on host cooperation and works independently of the access technology. We present a new QoS Signalling Protocol, policing and admission control algorithms, and a new lightweight statistical bandwidth prediction algorithm for autonomous resource management in LANs. This new QoS framework enables link based, access-medium independent bandwidth management without network support. We provide evaluation results for the novel bandwidth prediction algorithm as well as for the QoSiLAN framework and its protocol, which highlight the features, robustness, and the effectiveness of the proposed system

Dependability in wireless networks: can we rely on WiFi?

WiFi - short for "wireless fidelity" - is the commercial name for the 802.11 products that have flooded the corporate wireless local area network (WLAN) market and are becoming rapidly ingrained in our daily lives via public hotspots and digital home networks. Authentication and confidentiality are crucial issues for corporate WiFi use, but privacy and availability tend to dominate pervasive usage. However, because a technology's dependability requirements are proportional to its pervasiveness, newer applications mandate a deeper understanding of how much we can rely on WiFi and its security promises. In this article, we present an overview of WiFi vulnerabilities and investigate their proximate and ultimate origins. The intended goal is to provide a foundation to discuss WiFi dependability and its impact on current and future usage scenarios. Although a wireless network's overall security depends on the network stack to the application layer, this article focuses on specific vulnerabilities at the physical (PHY) and data (MAC) layers of 802.11 network

Mobility Management in beyond 3G-Environments

Beyond 3G-environments are typically defined as environments that integrate different wireless and fixed access network technologies. In this paper, we address IP based Mobility Management (MM) in beyond 3G-environments with a focus on wireless access networks, motivated by the current trend of WiFi, GPRS, and UMTS networks. The GPRS and UMTS networks provide countrywide network access, while the WiFi networks provide network access in local areas such as city centres and airports. As a result, mobile end-users can be always on-line and connected to their preferred network(s), these network preferences are typically stored in a user profile. For example, an end-user who wishes to be connected with highest bandwidth could be connected to a WiFi network when available and fall back to GPRS when moving outside the hotspot area.\ud In this paper, we consider a combination of MM for legacy services (like web browsing, telnet, etc.) using Mobile IP and multimedia services using SIP. We assume that the end-user makes use of multi-interface terminals with the capability of selecting one or more types of access networks\ud based on preferences. For multimedia sessions, like VoIP or streaming video, we distinguish between changes in network access when the end-user is in a session or not in a session. If the end-user is not in a session, he or she needs to be able to start new sessions and receive invitations for new sessions. If the end-user is in a session, the session needs to be handed over to the new access network as seamless as possible from the perspective of the end-user. We propose an integrated but flexible solution to these problems that facilitates MM with a customizable transparency to applications and end-users

Random matrix theory and the loss surfaces of neural networks

Neural network models are one of the most successful approaches to machine learning, enjoying an enormous amount of development and research over recent years and finding concrete real-world applications in almost any conceivable area of science, engineering and modern life in general. The theoretical understanding of neural networks trails significantly behind their practical success and the engineering heuristics that have grown up around them. Random matrix theory provides a rich framework of tools with which aspects of neural network phenomenology can be explored theoretically. In this thesis, we establish significant extensions of prior work using random matrix theory to understand and describe the loss surfaces of large neural networks, particularly generalising to different architectures. Informed by the historical applications of random matrix theory in physics and elsewhere, we establish the presence of local random matrix universality in real neural networks and then utilise this as a modeling assumption to derive powerful and novel results about the Hessians of neural network loss surfaces and their spectra. In addition to these major contributions, we make use of random matrix models for neural network loss surfaces to shed light on modern neural network training approaches and even to derive a novel and effective variant of a popular optimisation algorithm. Overall, this thesis provides important contributions to cement the place of random matrix theory in the theoretical study of modern neural networks, reveals some of the limits of existing approaches and begins the study of an entirely new role for random matrix theory in the theory of deep learning with important experimental discoveries and novel theoretical results based on local random matrix universality.Comment: 320 pages, PhD thesi

Mobile Application for Noise Pollution Monitoring through Gamification Techniques

Full data coverage of urban environments is crucial to monitor the status of the area to detect, for instance, trends and detrimental environmental changes. Collecting observations related to environmental factors such as noise pollution in urban environments through classical approaches implies the deployment of Sensor Networks. The cost of deployment and maintenance of such infrastructure might be relatively high for local and regional governments. On the other hand recent mass-market mobile devices such as smartphones are full of sensors. For instance, it is possible to perform measurements of noise through its microphone. Therefore they become low-cost measuring devices that many citizens have in their pocket. In this paper we present an approach for gathering noise pollution data by using mobile applications. The applications are designed following gamification techniques to encourage users to participate using their personal smartphones. In this way the users are involved in taking and sharing noise pollution measurements in their cities that other stakeholders can use in their analysis and decision making processes

A Novel Method of Serving Multimedia and Background Traffic in Wireless LANs.

Wireless local area networks (LANs) require the efficient integration of multimedia and traditional data traffic. This paper proposes the priority-oriented adaptive polling (POAP) protocol that could be used in place of the enhanced distributed channel access (EDCA) part of the IEEE 802.11e access scheme. EDCA seems capable of differentiating traffic; however, it exhibits great overhead that limits the available bandwidth and degrades performance. POAP is collision free, prioritizes the different kinds of traffic, and is able to provide quality of service (QoS) for all types of multimedia network applications while efficiently supporting background data traffic. POAP, compared to EDCA, provides higher channel utilization, distributes resources to the stations adapting to their real needs, and generally exhibits superior performance