Information reuse in dynamic spectrum access

Dynamic spectrum access (DSA), where the permission to use slices of radio spectrum is dynamically shifted (in time an in different geographical areas) across various communications services and applications, has been an area of interest from technical and public policy perspectives over the last decade. The underlying belief is that this will increase spectrum utilization, especially since many spectrum bands are relatively unused, ultimately leading to the creation of new and innovative services that exploit the increase in spectrum availability. Determining whether a slice of spectrum, allocated or licensed to a primary user, is available for use by a secondary user at a certain time and in a certain geographic area is a challenging task. This requires 'context information' which is critical to the operation of DSA. Such context information can be obtained in several ways, with different costs, and different quality/usefulness of the information. In this paper, we describe the challenges in obtaining this context information, the potential for the integration of various sources of context information, and the potential for reuse of such information for related and unrelated purposes such as localization and enforcement of spectrum sharing. Since some of the infrastructure for obtaining finegrained context information is likely to be expensive, the reuse of this infrastructure/information and integration of information from less expensive sources are likely to be essential for the economical and technological viability of DSA. © 2013 IEEE

Building a green connected future: smart (Internet of) Things for smart networks

The vision of Internet of Things (IoT) promises to reshape society by creating a future where we will be surrounded by a smart environment that is constantly aware of the users and has the ability to adapt to any changes. In the IoT, a huge variety of smart devices is interconnected to form a network of distributed agents that continuously share and process information. This communication paradigm has been recognized as one of the key enablers of the rapidly emerging applications that make up the fabric of the IoT. These networks, often called wireless sensor networks (WSNs), are characterized by the low cost of their components, their pervasive connectivity, and their self-organization features, which allow them to cooperate with other IoT elements to create large-scale heterogeneous information systems. However, a number of considerable challenges is arising when considering the design of large-scale WSNs. In particular, these networks are made up by embedded devices that suffer from severe power constraints and limited resources. The advent of low-power sensor nodes coupled with intelligent software and hardware technologies has led to the era of green wireless networks. From the hardware perspective, green sensor nodes are endowed with energy scavenging capabilities to overcome energy-related limitations. They are also endowed with low-power triggering techniques, i.e., wake-up radios, to eliminate idle listening-induced communication costs. Green wireless networks are considered a fundamental vehicle for enabling all those critical IoT applications where devices, for different reasons, do not carry batteries, and that therefore only harvest energy and store it for future use. These networks are considered to have the potential of infinite lifetime since they do not depend on batteries, or on any other limited power sources. Wake-up radios, coupled with energy provisioning techniques, further assist on overcoming the physical constraints of traditional WSNs. In addition, they are particularly important in green WSNs scenarios in which it is difficult to achieve energy neutrality due to limited harvesting rates. In this PhD thesis we set to investigate how different data forwarding mechanisms can make the most of these green wireless networks-enabling technologies, namely, energy harvesting and wake-up radios. Specifically, we present a number of cross-layer routing approaches with different forwarding design choices and study their consequences on network performance. Among the most promising protocol design techniques, the past decade has shown the increasingly intensive adoption of techniques based on various forms of machine learning to increase and optimize the performance of WSNs. However, learning techniques can suffer from high computational costs as nodes drain a considerable percentage of their energy budget to run sophisticated software procedures, predict accurate information and determine optimal decision. This thesis addresses also the problem of local computational requirements of learning-based data forwarding strategies by investigating their impact on the performance of the network. Results indicate that local computation can be a major source of energy consumption; it’s impact on network performance should not be neglected

Energy-efficient MAC protocol for wireless sensor networks

A Wireless Sensor Network (WSN) is a collection of tiny devices called sensor nodes which are deployed in an area to be monitored. Each node has one or more sensors with which they can measure the characteristics of their surroundings. In a typical WSN, the data gathered by each node is sent wirelessly through the network from one node to the next towards a central base station. Each node typically has a very limited energy supply. Therefore, in order for WSNs to have acceptable lifetimes, energy efficiency is a design goal that is of utmost importance and must be kept in mind at all levels of a WSN system. The main consumer of energy on a node is the wireless transceiver and therefore, the communications that occur between nodes should be carefully controlled so as not to waste energy. The Medium Access Control (MAC) protocol is directly in charge of managing the transceiver of a node. It determines when the transceiver is on/off and synchronizes the data exchanges among neighbouring nodes so as to prevent collisions etc., enabling useful communications to occur. The MAC protocol thus has a big impact on the overall energy efficiency of a node. Many WSN MAC protocols have been proposed in the literature but it was found that most were not optimized for the group of WSNs displaying very low volumes of traffic in the network. In low traffic WSNs, a major problem faced in the communications process is clock drift, which causes nodes to become unsynchronized. The MAC protocol must overcome this and other problems while expending as little energy as possible. Many useful WSN applications show low traffic characteristics and thus a new MAC protocol was developed which is aimed at this category of WSNs. The new protocol, Dynamic Preamble Sampling MAC (DPS-MAC) builds on the family of preamble sampling protocols which were found to be most suitable for low traffic WSNs. In contrast to the most energy efficient existing preamble sampling protocols, DPS-MAC does not cater for the worst case clock drift that can occur between two nodes. Rather, it dynamically learns the actual clock drift experienced between any two nodes and then adjusts its operation accordingly. By simulation it was shown that DPS-MAC requires less protocol overhead during the communication process and thus performs more energy efficiently than its predecessors under various network operating conditions. Furthermore, DPS-MAC is less prone to become overloaded or unstable in conditions of high traffic load and high contention levels respectively. These improvements cause the use of DPS-MAC to lead to longer node and network lifetimes, thus making low traffic WSNs more feasible.Dissertation (MEng)--University of Pretoria, 2008.Electrical, Electronic and Computer EngineeringMEngUnrestricte

Design Experiences on Single and Multi Radio Systems in Wireless Embedded Platforms

The progress of radio technology has made several flavors of radio available on the market.Wireless sensor network platform designers have used these radios to build a variety of platforms. Withnew applications and different types of radios on wireless sensing nodes, it is often hard to interconnectdifferent types of networks. Hence, often additional radios have to be integrated onto existingplatforms or new platforms have to be built. Additionally, the energy consumption of these nodes have to be optimized to meetlifetime requirements of years without recharging.In this thesis, we address two issues of single and multi radio platform designfor wireless sensor network applications - engineering issues and energy optimization.We present a set of guiding principles from our design experiences while building 3 real life applications,namely asset tracking, burglar tracking and finally in-situ psychophysiological stress monitoring of human subjects in behavioral studies.In the asset tracking application, we present our design of a tag node that can be hidden inside valuable personal assets such asprinters or sofas in a home. If these items are stolen, a city wide anchor node infrastructure networkwould track them throughout the city. We also present our design for the anchor node.In the burglar tracking application, we present the design of tag nodes and the issueswe faced while integrating it with a GSM radio. Finally, we discuss our experiencesin designing a bridge node, that connects body worn physiological sensorsto a Bluetooth enabled mobile smartphone. We present the software framework that acts as middleware toconnect to the bridge, parse the sensor data, and send it to higher layers of the softwareframework.We describe 2 energy optimization schemes that are used in the Asset Tracking and the Burglar Tracking applications, that enhance the lifetime of the individual applications manifold.In the asset tracking application,we design a grouping scheme that helps increase reliability of detection of the tag nodes at theanchor nodes while reducing the energy consumption of the group of tag nodes travelling together.We achieve an increase of 5 times improvement in lifetime of the entire group. In the Burglar Tracking application, weuse sensing to determine when to turn the GSM radio on and transmit data by differentiatingturns and lane changes. This helps us reduce the number of times the GSM radio is woken up, thereby increasing thelifetime of the tag node while it is being tracked. This adds 8 minutes of trackablelifetime to the burglar tracking tag node. We conclude this thesis by observing the futuretrends of platform design and radio evolution