Infective flooding in low-duty-cycle networks, properties and bounds

Flooding information is an important function in many networking applications. In some networks, as wireless sensor networks or some ad-hoc networks it is so essential as to dominate the performance of the entire system. Exploiting some recent results based on the distributed computation of the eigenvector centrality of nodes in the network graph and classical dynamic diffusion models on graphs, this paper derives a novel theoretical framework for efficient resource allocation to flood information in mesh networks with low duty-cycling without the need to build a distribution tree or any other distribution overlay. Furthermore, the method requires only local computations based on each node neighborhood. The model provides lower and upper stochastic bounds on the flooding delay averages on all possible sources with high probability. We show that the lower bound is very close to the theoretical optimum. A simulation-based implementation allows the study of specific topologies and graph models as well as scheduling heuristics and packet losses. Simulation experiments show that simple protocols based on our resource allocation strategy can easily achieve results that are very close to the theoretical minimum obtained building optimized overlays on the network

Let the Tree Bloom: Scalable Opportunistic Routing with ORPL

Routing in battery-operated wireless networks is challenging, posing a tradeoff between energy and latency. Previous work has shown that opportunistic routing can achieve low-latency data collection in duty-cycled networks. However, applications are now considered where nodes are not only periodic data sources, but rather addressable end points generating traffic with arbitrary patterns. We present ORPL, an opportunistic routing protocol that supports any-to-any, on-demand traffic. ORPL builds upon RPL, the standard protocol for low-power IPv6 networks. By combining RPL's tree-like topology with opportunistic routing, ORPL forwards data to any destination based on the mere knowledge of the nodes' sub-tree. We use bitmaps and Bloom filters to represent and propagate this information in a space-efficient way, making ORPL scale to large networks of addressable nodes. Our results in a 135-node testbed show that ORPL outperforms a number of state-of-the-art solutions including RPL and CTP, conciliating a sub-second latency and a sub-percent duty cycle. ORPL also increases robustness and scalability, addressing the whole network reliably through a 64-byte Bloom filter, where RPL needs kilobytes of routing tables for the same task

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

A Sleep-Scheduling-Based Cross-Layer Design Approach for Application-Specific Wireless Sensor Networks

The pervasiveness and operational autonomy of mesh-based wireless sensor networks (WSNs) make them an ideal candidate in offering sustained monitoring functions at reasonable cost over a wide area. To extend the functional lifetime of battery-operated sensor nodes, stringent sleep scheduling strategies with communication duty cycles running at sub-1% range are expected to be adopted. Although ultra-low communication duty cycles can cast a detrimental impact on sensing coverage and network connectivity, its effects can be mitigated with adaptive sleep scheduling, node deployment redundancy and multipath routing within the mesh WSN topology. This work proposes a cross-layer organizational approach based on sleep scheduling, called Sense-Sleep Trees (SS-Trees), that aims to harmonize the various engineering issues and provides a method to extend monitoring capabilities and operational lifetime of mesh-based WSNs engaged in wide-area surveillance applications. Various practical considerations such as sensing coverage requirements, duty cycling, transmission range assignment, data messaging, and protocol signalling are incorporated to demonstrate and evaluate the feasibility of the proposed design approach

An ultra-low duty cycle sleep scheduling protocol stack for wireless sensor networks

A wireless sensor network is a distributed network system consisting of miniature spatially distributed autonomous devices designed for using sensors to sense the environment and cooperatively perform a specific goal. Each sensor node contains a limited power source, a sensor and a radio through which it can communicate with other sensor nodes within its communication radius. Since these sensor nodes may be deployed in inaccessible terrains, it might not be possible to replace their power sources. The radio transceiver is the hardware component that uses the most power in a sensor node and the optimisation of this element is necessary to reduce the overall energy consumption. In the data link layer there are several major sources of energy waste which should be minimised to achieve greater energy efficiency: idle listening, overhearing, over-emitting, network signalling overhead, and collisions. Sleep scheduling utilises the low-power sleep state of a transceiver and aims to reduce energy wastage caused by idle listening. Idle listening occurs when the radio is on, even though there is no data to transmit or receive. Collisions are reduced by using medium reservation and carrier sensing; collisions occur when there are simultaneous transmissions from several nodes that are within the interference range of the receiver node. The medium reservation packets include a network allocation vector field which is used for virtual carrier sensing which reduces overhearing. Overhearing occurs when a node receives and decodes packets that are not destined to it. Proper scheduling can avoid energy wastage due to over-emitting; over-emitting occurs when a transmitter node transmits a packet while the receiver node is not ready to receive packets. A protocol stack is proposed that achieves an ultra-low duty cycle sleep schedule. The protocol stack is aimed at large nodal populations, densely deployed, with periodic sampling applications. It uses the IEEE 802.15.4 Physical Layer (PHY) standard in the 2.4 GHz frequency band. A novel hybrid data-link/network cross-layer solution is proposed using the following features: a global sleep schedule, geographical data gathering tree, Time Division Multiple Access (TDMA) slotted architecture, Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA), Clear Channel Assessment (CCA) with a randomised contention window, adaptive listening using a conservative timeout activation mechanism, virtual carrier sensing, clock drift compensation, and error control. AFRIKAANS : 'n Draadlose sensor-netwerk is 'n verspreide netwerk stelsel wat bestaan uit miniatuur ruimtelik verspreide outonome toestelle wat ontwerp is om in harmonie saam die omgewing te meet. Elke sensor nodus besit 'n beperkte bron van energie, 'n sensor en 'n radio waardeur dit met ander sensor nodusse binne hulle kommunikasie radius kan kommunikeer. Aangesien hierdie sensor nodusse in ontoeganklike terreine kan ontplooi word, is dit nie moontlik om hulle kragbronne te vervang nie. Die radio is die hardeware komponent wat van die meeste krag gebruik in 'n sensor nodus en die optimalisering van hierdie element is noodsaaklik vir die verminder die totale energieverbruik. In die data-koppelvlak laag is daar verskeie bronne van energie vermorsing wat minimaliseer moet word: ydele luister, a uistering, oor-uitstraling, oorhoofse netwerk seine, en botsings. Slaap-skedulering maak gebruik van die lae-krag slaap toestand van 'n radio met die doel om energie vermorsing wat veroorsaak word deur ydele luister, te verminder. Ydele luister vind plaas wanneer die radio aan is selfs al is daar geen data om te stuur of ontvang nie. Botsings word verminder deur medium bespreking en draer deteksie; botsings vind plaas wanneer verskeie nodusse gelyktydig data stuur. Die medium bespreking pakkies sluit 'n netwerk aanwysing vektor veld in wat gebruik word vir virtuele draer deteksie om a uistering te verminder. Afluistering vind plaas wanneer 'n nodus 'n pakkie ontvang en dekodeer maar dit was vir 'n ander nodus bedoel. Behoorlike skedulering kan energie verkwisting as gevolg van oor-uistraling verminder; oor-uistraling gebeur wanneer 'n sender nodus 'n pakkie stuur terwyl die ontvang nog nie gereed is nie. 'n Protokol stapel is voorgestel wat 'n ultra-lae slaap-skedule dienssiklus het. Die protokol is gemik op draadlose sensor-netwerke wat dig ontplooi, groot hoeveelhede nodusse bevat, en met periodiese toetsing toepassings. Dit maak gebruik van die IEEE 802.15.4 Fisiese-Laag standaard in die 2.4 GHz frekwensie band. 'n Nuwe baster datakoppelvlak/netwerk laag oplossing is voorgestel met die volgende kenmerke: globale slaap-skedulering, geogra ese data rapportering, Tyd-Verdeling-Veelvuldige-Toegang (TVVT) gegleufde argitektuur, Draer-Deteksie-Veelvuldige-Toegang met Botsing-Vermyding (DDVT/BV), Skoon-Kanaal-Assessering (SKA) met 'n wisselvallige twis-tydperk, aanpasbare slaap-skedulering met 'n konserwatiewe aktiverings meganisme, virtuele draer-deteksie, klok-wegdrywing kompensasie, en fout beheer. CopyrightDissertation (MEng)--University of Pretoria, 2012.Electrical, Electronic and Computer Engineeringunrestricte

Energy-Efficient Communication in Wireless Networks

This chapter describes the evolution of, and state of the art in, energy‐efficient techniques for wirelessly communicating networks of embedded computers, such as those found in wireless sensor network (WSN), Internet of Things (IoT) and cyberphysical systems (CPS) applications. Specifically, emphasis is placed on energy efficiency as critical to ensuring the feasibility of long lifetime, low‐maintenance and increasingly autonomous monitoring and control scenarios. A comprehensive summary of link layer and routing protocols for a variety of traffic patterns is discussed, in addition to their combination and evaluation as full protocol stacks