Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks

Conventional cellular wireless networks were designed with the purpose of providing high throughput for the user and high capacity for the service provider, without any provisions of energy efficiency. As a result, these networks have an enormous Carbon footprint. In this paper, we describe the sources of the inefficiencies in such networks. First we present results of the studies on how much Carbon footprint such networks generate. We also discuss how much more mobile traffic is expected to increase so that this Carbon footprint will even increase tremendously more. We then discuss specific sources of inefficiency and potential sources of improvement at the physical layer as well as at higher layers of the communication protocol hierarchy. In particular, considering that most of the energy inefficiency in cellular wireless networks is at the base stations, we discuss multi-tier networks and point to the potential of exploiting mobility patterns in order to use base station energy judiciously. We then investigate potential methods to reduce this inefficiency and quantify their individual contributions. By a consideration of the combination of all potential gains, we conclude that an improvement in energy consumption in cellular wireless networks by two orders of magnitude, or even more, is possible.Comment: arXiv admin note: text overlap with arXiv:1210.843

Efficient Information Access in Data-Intensive Sensor Networks

Recent advances in wireless communications and microelectronics have enabled wide deployment of smart sensor networks. Such networks naturally apply to a broad range of applications that involve system monitoring and information tracking (e.g., fine-grained weather/environmental monitoring, structural health monitoring, urban-scale traffic or parking monitoring, gunshot detection, monitoring volcanic eruptions, measuring rate of melting glaciers, forest fire detection, emergency medical care, disaster response, airport security infrastructure, monitoring of children in metropolitan areas, product transition in warehouse networks etc.).Meanwhile, existing wireless sensor networks (WSNs) perform poorly when the applications have high bandwidth needs for data transmission and stringent delay constraints against the network communication. Such requirements are common for Data Intensive Sensor Networks (DISNs) implementing Mission-Critical Monitoring applications (MCM applications).We propose to enhance existing wireless network standards with flexible query optimization strategies that take into account network constraints and application-specific data delivery patterns in order to meet high performance requirements of MCM applications.In this respect, this dissertation has two major contributions: First, we have developed an algebraic framework called Data Transmission Algebra (DTA) for collision-aware concurrent data transmissions. Here, we have merged the serialization concept from the databases with the knowledge of wireless network characteristics. We have developed an optimizer that uses the DTA framework, and generates an optimal data transmission schedule with respect to latency, throughput, and energy usage. We have extended the DTA framework to handle location-based trust and sensor mobility. We improved DTA scalability with Whirlpool data delivery mechanism, which takes advantage of partitioning of the network. Second, we propose relaxed optimization strategy and develop an adaptive approach to deliver data in data-intensive wireless sensor networks. In particular, we have shown that local actions at nodes help network to adapt in worse network conditions and perform better. We show that local decisions at the nodes can converge towards desirable global network properties e.g.,high packet success ratio for the network. We have also developed a network monitoring tool to assess the state and dynamic convergence of the WSN, and force it towards better performance

A Quality of Service Based Model for Supporting Mobile Secondary Users in Cognitive Radio Technology

Current wireless networks are characterized by a static spectrum allocation policy, where governmental agencies assign wireless spectrum to license holders on a long-term basis for large geographical regions. The operators claim that the spectrum bands for mobile operation are highly occupied. Even then, a significant amount of licensed spectrum remains underutilized. Cognitive radio senses the radio environment with a twofold objective: identify those subbands of the radio spectrum that are underutilized by the primary (i.e., legacy) users and providing the means for making those bands available for employment by secondary (i.e., unlicensed) users. For unlicensed communication, the Quality of Service parameters need to be considered. Quality of Service comprises of channel availability, accessibility, and maintainability. Assessment of vacant channels of licensed band in a geographical region is termed as availability. An analysis of the collected data lead to arrive at the conclusion that more than one-eighth part of resources of each band are nearly permanently vacant, which is enough to design in-band common control signaling methods for cognitive radio. Measurement result plot of vacant channels in cities with known population will help to assess availability of vacant channels for any city and hence, measurement complexity can be avoided. The strategy to occupy the vacant channels without disturbing the primary user operation is referred as accessibility (or selection). Accessibility of a channel is dependent on blocking probability (or Quality of Service) measured in duration of minutes instead of hours. Instantaneous blocking probability has been calculated based on current minute occupancy for all available channels as reference. A comprehensive prediction model is employed in the proposed work to compute the instantaneous blocking probability both on immediate minute occupancy basis and its preceding 60 min basis from time of request by SU. Validation through actual data establishes that channelized blocking probability estimation model has lower error value compared to estimation through prediction models of other researchers. It was also observed that hourly basis prediction model has constant blocking probability value during clock hour, whereas minutewise Grade of Service (GoS) prediction model addresses the local peak demand and hence leads to a stringent GoS estimation. On secondary user request for vacant channel, the cognitive radio network needs to evaluate the expected holding time of the particular Secondary User and to ensure channel maintainability (or allocation), and it shall predict that the allotted channel shall be able to provide interruption-free service for holding time duration. Minutewise channel occupancy traffic is bumpy in nature; hence, the present work predicts call arrival rate using Holt Winter’s method. Also, at the instant of SU channel request, the channel allocation processor inputs all PU channel status minutewise, calculates actual mean residual lifetime (MRL) in minutes for each vacant channel and selects the channel with highest predicted free time. A simulation program runs on data collected from mobile switch of cellular network, which creates pseudo-live environment for channel allocation. The present work has compared the mean residual lifetime (MRL) method with the other researchers using probabilistic method of channel allocation and MRL method has been established as more accurate. The selection and allocation process with defined blocking probability model has been verified retrieving big data from data warehouse

Interference Aware Cognitive Femtocell Networks

Femtocells Access Points (FAP) are low power, plug and play home base stations which are designed to extend the cellular radio range in indoor environments where macrocell coverage is generally poor. They offer significant increases in data rates over a short range, enabling high speed wireless and mobile broadband services, with the femtocell network overlaid onto the macrocell in a dual-tier arrangement. In contrast to conventional cellular systems which are well planned, FAP are arbitrarily installed by the end users and this can create harmful interference to both collocated femtocell and macrocell users. The interference becomes particularly serious in high FAP density scenarios and compromises the ensuing data rate. Consequently, effective management of both cross and co-tier interference is a major design challenge in dual-tier networks. Since traditional radio resource management techniques and architectures for single-tier systems are either not applicable or operate inefficiently, innovative dual-tier approaches to intelligently manage interference are required. This thesis presents a number of original contributions to fulfill this objective including, a new hybrid cross-tier spectrum sharing model which builds upon an existing fractional frequency reuse technique to ensure minimal impact on the macro-tier resource allocation. A new flexible and adaptive virtual clustering framework is then formulated to alleviate co-tier interference in high FAP densities situations and finally, an intelligent coverage extension algorithm is developed to mitigate excessive femto-macrocell handovers, while upholding the required quality of service provision. This thesis contends that to exploit the undoubted potential of dual-tier, macro-femtocell architectures an interference awareness solution is necessary. Rigorous evidence confirms that noteworthy performance improvements can be achieved in the quality of the received signal and throughput by applying cognitive methods to manage interference

Algorithms for data-gathering in wireless sensor networks

Wireless sensor networks consist of a large number of small battery powered sensor nodes with limited energy resources which are responsible for sensing, processing, and transmitting the monitored data. Once deployed, the sensor nodes are normally inaccessible to the user, and thus replacement of the battery is generally not feasible. A major concern in designing and operating dense Wireless Sensor Networks (WSNs) is the energy-efficiency. Hierarchical clustering and cross-layer optimization are widely accepted as effective techniques to ameliorate this concern. We propose two different novel energy efficient algorithms to gather data from sensor nodes. Energy-Efficient Media Access Control (EE-MAC) protocol is the first algorithm, which has excellent scalability and performs well for both small and large sensor networks. We will also provide a theoretical analysis of the protocol and give guidelines on how to find the optimal protocol parameters such as the number of clusters. In addition, we develop and analyze a novel and scalable Spiraled Algorithm for Data-gathering (SAD) that periodically selects cluster heads according to their geographic locations and residual energy by sorting nodes on virtual spirals. Theoretical analysis and simulation results show that SAD can achieve as much as a factor of three prolonging network lifetime compared with other conventional protocols like LEACH especially when the network is large. Moreover, SAD is also able to distribute energy dissipation evenly throughout the sensors such that 80% of the nodes run out of batteries in the last 20% of the network lifetime

Telecommunications Networks

This book guides readers through the basics of rapidly emerging networks to more advanced concepts and future expectations of Telecommunications Networks. It identifies and examines the most pressing research issues in Telecommunications and it contains chapters written by leading researchers, academics and industry professionals. Telecommunications Networks - Current Status and Future Trends covers surveys of recent publications that investigate key areas of interest such as: IMS, eTOM, 3G/4G, optimization problems, modeling, simulation, quality of service, etc. This book, that is suitable for both PhD and master students, is organized into six sections: New Generation Networks, Quality of Services, Sensor Networks, Telecommunications, Traffic Engineering and Routing

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts

Analysis of the energy latency trade-off in wireless sensor networks

Wireless Sensor Networks (WSNs) haben im letzten Jahrzehnt eine erhebliche Aufmerksamkeit erlangt. Diese Netzwerke zeichnen sich durch begrenzte Energieressourcen der Sensorknoten aus. Daher ist Energieeffizienz ein wichtiges Thema in Systemdesign und -betrieb von WSNs. Diese Arbeit konzentriert sich auf großflächige Anwendungen von WSNs wie Umwelt- oder Lebensraumüberwachung, die in der Regel den Ad-hoc-Einsatz von Knoten in großen Anzahl erfordern. Ad-hoc-Einsatz und Budgetbeschränkungen hindern Entwickler an der Programmierung der Knoten mit zusätzlichen Informationen wie beispielsweise Routingtabellen, Positionskoordinaten, oder Netzwerkgrenzen. Um diese Informationen zu beschaffen, ist es üblich verschiedene Initialisierungsschemen mit erheblichen Auswirkungen auf den Energieverbrauch und den Programmieraufwand zu implementieren. In Anbetracht dieser Beschränkungen ist ein neues Paradigma für die Initialisierung und den Betrieb von WSNs notwendig, das sich durch einfachen Einsatz und minimalen Energieaufwand auszeichnet. In dieser Arbeit nutzen wir Sink-Mobilität, um den Initialisierungsoverhead und den operativen Overhead zu reduzieren. Unser erster großer Beitrag ist ein Boundary Identification Schema für WSNs mit dem Namen "Mobile Sink based Boundary Detection" (MoSBoD). Es nutzt die Sink-Mobilität um den Kommunikationsoverhead der Sensorknoten zu reduzieren, was zu einer Erhöhung der Laufzeit des WSN führt. Außerdem entstehen durch das Schema keine Einschränkungen in Bezug auf Nodeplacement, Kommunikationsmodell, oder Ortsinformationen der Knoten. Der zweite große Beitrag ist das Congestion avoidance low Latency and Energy efficient (CaLEe) Routingprotokoll für WSNs. CaLEe basiert auf der virtuellen Partitionierung eines Sensorsbereich in Sektoren und der diskreten Mobilität der Sink im WSN. Unsere Simulationsergebnisse zeigen, dass CaLEe, im Vergleich zum derzeitigen State-of-the-art, nicht nur eine erhebliche Reduzierung der durchschnittlichen Energy Dissipation per Node erzielt, sondern auch eine geringere durchschnittliche End-to-End Data Latency in realistischen Szenarien erreicht. Darüber hinaus haben wir festgestellt, dass kein einziges Protokoll in der Lage ist, eine Best-Case-Lösung (minimale Data Latency und minimale Energy Dissipation) für variierende Netzwerkkonfigurationen, die beispielsweise mithilfe der Parameter Kommunikationsbereich der Nodes, Nodedichte, Durchsatz des Sensorfelds definiert werden können, bieten. Daher ist der dritte Hauptbeitrag dieser Arbeit die Identifikation von (auf unterschiedlichen Netzwerkkonfigurationen basierenden) „Operational Regions“, in denen einzelne Protokolle besser arbeiten als andere. Zusammenfassend kann man sagen, dass diese Dissertation das klassische Energieeffizienzproblem der WSNs (Ressource-begrenzte Knoten) aufgreift und gleichzeitig die End-to-End Data Latency auf einen annehmbaren Rahmen eingrenzt.Wireless Sensor Networks (WSN) have gained a considerable attention over the last decade. These networks are characterized by limited amount of energy supply at sensor node. Hence, energy efficiency is an important issue in system design and operation of WSN. This thesis focuses on large-scale applications of WSN, such as environment or habitat monitoring that usually requires ad-hoc deployment of the nodes in large numbers. Ad-hoc deployment and budget constraints restrict developers from programming the nodes with information like routing tables, position coordinates of the node, boundary of the network. In order to acquire this information, state-of-the-art is to program nodes with various initialization schemes that are heavy both from WSN’s (energy consumption) and programmer’s perspectives (programming effort). In view of these particular constraints, we require a new paradigm for WSN initialization and operation, which should be easy to deploy and have minimal energy demands. In this thesis, we exploit sink mobility to reduce the WSN initialization and operational overhead. Our first major contribution is a boundary identification scheme for WSN, named “Mobile Sink based Boundary detection” (MoSBoD). It exploits the sink mobility to remove the communication overhead from the sensor nodes, which leads to an increase in the lifetime of the WSN. Furthermore, it does not impose any restrictions on node placement, communication model, or location information of the nodes. The second major contribution is Congestion avoidance low Latency and Energy efficient (CaLEe) routing protocol for WSN. CaLEe is based on virtual partitioning of a sensor field into sectors and discrete mobility of the sink in the WSN. Our simulation results showed that CaLEe not only achieve considerable reduction in average energy dissipation per node compared to current state-of-the-art routing protocols but also accomplish lesser average end-to-end data latency under realistic scenarios. Furthermore, we observe that no single protocol is capable of providing best-case solution (minium data latency and minimum energy dissipation) under varying network configurations, which can be defined using communication range of the nodes, node density, throughput of the sensor field etc. Therefore, the third major contribution of this thesis is the identification of operational regions (based on varying network configurations) where one protocol performs better than the other. In summary, this thesis revisits the classic energy efficiency problem of a WSN (that have resource-limited nodes) while keeping end-to-end data latency under acceptable bounds

Recent Advances in Wireless Communications and Networks

This book focuses on the current hottest issues from the lowest layers to the upper layers of wireless communication networks and provides "real-time" research progress on these issues. The authors have made every effort to systematically organize the information on these topics to make it easily accessible to readers of any level. This book also maintains the balance between current research results and their theoretical support. In this book, a variety of novel techniques in wireless communications and networks are investigated. The authors attempt to present these topics in detail. Insightful and reader-friendly descriptions are presented to nourish readers of any level, from practicing and knowledgeable communication engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters