Distributed estimation over a low-cost sensor network: a review of state-of-the-art

Proliferation of low-cost, lightweight, and power efficient sensors and advances in networked systems enable the employment of multiple sensors. Distributed estimation provides a scalable and fault-robust fusion framework with a peer-to-peer communication architecture. For this reason, there seems to be a real need for a critical review of existing and, more importantly, recent advances in the domain of distributed estimation over a low-cost sensor network. This paper presents a comprehensive review of the state-of-the-art solutions in this research area, exploring their characteristics, advantages, and challenging issues. Additionally, several open problems and future avenues of research are highlighted

Investigation of efficient resource allocation schemes for WiMAX networks

This thesis was submitted for the degree of Master of Philosophy and was awarded by Brunel University on 9 July 2008.WiMax (Worldwide Interoperability for Microwave Access) is a promising wireless technology with the aim of providing the last mile wireless broadband access designed for both fixed and mobile consumers as an alternative solution to the wired DSL and cable access schemes. The purpose of this research project is to investigate efficient resource allocation algorithms for WiMax. To achieve this goal, we investigate efficient PHY layer Partial Usage of SubCarriers (PUSC) allocation as well as MAC layer piggyback bandwidth request mechanisms. At the PHY layer we proposed improvements on the Uplink and Downlink PUSC subcarrier allocation scheme. For the Uplink PUSC we suggested a method by allocating different frequencies to neighbouring cells in combination with the Integer Frequency Reuse (IFR) and Fractional Frequency Reuse (FFR) in order to reduce interferences and collisions. The simulation results exhibit that collision rates can be reduced to zero for both IFR and FFR patterns with the proposed improvement by assuming that perfect power control is used in the system. In addition, there is no collision at cell edges. The results also show that FFR patterns achieve lower inter-cell interference and higher capacities as compared to the IFR patterns. For the Downlink PUSC we introduced an offset scheme with the purpose of increasing the number of users in the system. At the MAC layer we propose an improvement on the piggyback bandwidth request mechanism by increasing the size of the piggyback bandwidth request in order to reduce the number of bandwidth requests and hence improve the resource utilisation. The simulation results demonstrate that our improved scheme achieves higher throughput, less delay and packet loss rates as compared to the standardised piggyback bandwidth request mechanism

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

Resource optimisation in a wireless sensor network with guaranteed estimator performance

New control paradigms are needed for large networks of wireless sensors and actuators in order to efficiently utilise system resources. In this study, the authors consider the problem of discrete-time state estimation over a wireless sensor network. Given a tree that represents the sensor communications with the fusion centre, the authors derive the optimal estimation algorithm at the fusion centre, and provide a closedform expression for the steady-state error covariance matrix. They then present a tree reconfiguration algorithm that produces a sensor tree that has low overall energy consumption and guarantees a desired level of estimation quality at the fusion centre. The authors further propose a sensor tree construction and scheduling algorithm that leads to a longer network lifetime than the tree reconfiguration algorithm. Examples are provided throughout the paper to demonstrate the algorithms and theory developed

WIMAX LINK PERFORMANCE ANALYSIS FOR WIRELESS AUTOMATION APPLICATIONS

Wireless broadband access technologies are rapidly growing and a corresponding growth in the demand of its applicability transcends faster internet access, high speed file download and different multimedia applications such as voice calls, video streaming, teleconferencing etc, to industrial operations and automation. Industrial and automation systems perform operations that requires the transmission of real time information from one end to another through high-performance wireless broadband communication links. WiMAX, based on IEEE 802.16 standard is one of the wireless broadband access technologies that has overcome location, speed, and access limitations of the traditional Digital Subscriber Line and Wireless Fidelity, and offers high efficient data rates. This thesis presents detailed analysis of operational WiMAX link performance parameters such as throughput, latency, jitter, and packet loss for suitable applicability in wireless automation applications. The theoretical background of components and functionalities of WiMAX physical and MAC layers as well as the network performance features are presented. The equipment deployed for this field experiment are Alvarion BreeZeMAX 3000 fixed WiMAX equipment operating in the 3.5 GHz licensed band with channel bandwidth of 3.5 MHz. The deployed equipment consisting of MBSE and CPE are installed and commissioned prior to field tests. Several measurements are made in three link quality scenarios (sufficient, good and excellent) in the University of Vaasa campus. Observations and results obtained are discussed and analyzed.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

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