IEEHR: Improved Energy Efficient Honeycomb based Routing in MANET for Improving Network Performance and Longevity

In present scenario, efficient energy conservation has been the greatest focus in Mobile Adhoc Networks (MANETs). Typically, the energy consumption rate of dense networks is to be reduced by proper topological management. Honeycomb based model is an efficient parallel computing technique, which can manage the topological structures in a promising manner.  Moreover, discovering optimal routes in MANET is the most significant task, to be considered with energy efficiency. With that motive, this paper presents a model called Improved Energy Efficient Honeycomb based Routing (IEEHR) in MANET. The model combines the Honeycomb based area coverage with Location-Aided Routing (LAR), thereby reducing the broadcasting range during the process of path finding. In addition to optimal routing, energy has to be effectively utilized in MANET, since the mobile nodes have energy constraints. When the energy is effectively consumed in a network, the network performance and the network longevity will be increased in respective manner. Here, more amount of energy is preserved during the sleeping state of the mobile nodes, which are further consumed during the process of optimal routing. The designed model has been implemented and analyzed with NS-2 Network Simulator based on the performance factors such as Energy Efficiency, Transmission Delay, Packet Delivery Ratio and Network Lifetime

JSSDR: Joint-Sparse Sensory Data Recovery in Wireless Sensor Networks

Abstract-Data loss is ubiquitous in wireless sensor networks (WSNs) mainly due to the unreliable wireless transmission, which results in incomplete sensory data sets. However, the completeness of a data set directly determines its availability and usefulness. Thus, sensory data recovery is an indispensable operation against the data loss problem. However, existing solutions cannot achieve satisfactory accuracy due to special loss patterns and high loss rates in WSNs. In this work, we propose a novel sensory data recovery algorithm which exploits the spatial and temporal jointsparse feature. Firstly, by mining two real datasets, namely the Intel Indoor project and the GreenOrbs project, we find that: (1) for one attribute, sensory readings at nearby nodes exhibit inter-node correlation; (2) for two attributes, sensory readings at the same node exhibit inter-attribute correlation; (3) these inter-node and inter-attribute correlations can be modeled as the spatial and temporal joint-sparse features, respectively. Secondly, motivated by these observations, we propose two JointSparse Sensory Data Recovery (JSSDR) algorithms to promote the recovery accuracy. Finally, real data-based simulations show that JSSDR outperforms existing solutions. Typically, when the loss rate is less than 65%, JSSDR can estimate missing values with less than 10% error. And when the loss rate reaches as high as 80%, the missing values can be estimated by JSSDR with less than 20% error

A Holistic Approach to Functional Safety for Networked Cyber-Physical Systems

Functional safety is a significant concern in today's networked cyber-physical systems such as connected machines, autonomous vehicles, and intelligent environments. Simulation is a well-known methodology for the assessment of functional safety. Simulation models of networked cyber-physical systems are very heterogeneous relying on digital hardware, analog hardware, and network domains. Current functional safety assessment is mainly focused on digital hardware failures while minor attention is devoted to analog hardware and not at all to the interconnecting network. In this work we believe that in networked cyber-physical systems, the dependability must be verified not only for the nodes in isolation but also by taking into account their interaction through the communication channel. For this reason, this work proposes a holistic methodology for simulation-based safety assessment in which safety mechanisms are tested in a simulation environment reproducing the high-level behavior of digital hardware, analog hardware, and network communication. The methodology relies on three main automatic processes: 1) abstraction of analog models to transform them into system-level descriptions, 2) synthesis of network infrastructures to combine multiple cyber-physical systems, and 3) multi-domain fault injection in digital, analog, and network. Ultimately, the flow produces a homogeneous optimized description written in C++ for fast and reliable simulation which can have many applications. The focus of this thesis is performing extensive fault simulation and evaluating different functional safety metrics, \eg, fault and diagnostic coverage of all the safety mechanisms

Energy harvesting for marine based sensors

This work examines powering marine based sensors (MBSs) by harvesting energy from their local environment. MBSs intrinsically operate in remote locations, traditionally requiring expensive maintenance expeditions for battery replacement and data download. Nowadays, modern wireless communication allows real-time data access, but adds a significant energy drain, necessitating frequent battery replacement. Harvesting renewable energy to recharge the MBSs battery, introduces the possibility of autonomous MBS operation, reducing maintenance costs and increasing their applicability. The thesis seeks to answer if an unobtrusive energy harvesting device can be incorporated into the MBS deployment to generate 1 Watt of average power. Two candidate renewable energy resources are identified for investigation, ocean waves and the thermal gradient across the air/water interface. Wave energy conversion has drawn considerable research in recent years, due to the large consistent energy flux of ocean waves compared to other conventional energy sources such as solar or wind, but focussing on large scale systems permanently deployed at sites targeted for their favourable wave climates. Although a small amount of research exists on using wave energy for distributed power generation, the device sizes and power outputs of these systems are still one to two orders of magnitude larger than that targeted in this thesis. The present work aims for an unobtrusive device that is easily deployable/retrievable with a mass less than 50kg and which can function at any deployment location regardless of the local wave climate. Additionally, this research differs from previous work, by also seeking to minimise the wave induced pitch motion of the MBS buoy, which negatively affects the data transmission of the MBS due to tilting and misalignment of the RF antenna. Thermal energy harvesting has previously been investigated for terrestrial based sensors, utilising the temperature difference between the soil and ambient air. In this thesis, the temperature difference between the water and ambient air is utilised, to present the first investigation of this thermal energy harvesting concept in the marine environment. A prototype wave energy converter (WEC) was proposed, consisting of a heaving cylindrical buoy with an internal permanent magnet linear generator. A mathematical model of the prototype WEC is derived by coupling a hydrodynamic model for the motion of the buoy with a vibration energy harvester model for the generator. The wave energy resource is assessed, using established mathematical descriptions of ocean wave spectra and by analysing measured wave data from the coast of Queensland, resulting in characteristic wave spectra that are input to the mathematical model of the WEC. The parameters of the WEC system are optimised, to maximise the power output while minimising the pitch motion. A prototype thermal energy harvesting device is proposed, consisting of a thermoelectric device sandwiched between airside and waterside heat exchangers. A mathematical model is derived to assess the power output of the thermal energy harvester using different environmental datasets as input. A physical prototype is built and a number of experiments performed to assess its performance. The results indicate that the prototype WEC should target the high frequency tail of ocean wave spectra, diverging from traditional philosophy of larger scale WECs which target the peak frequency of the input wave spectrum. The analysis showed that the prototype WEC was unable to provide the required power output whilst remaining below 100kg and obeying a 40 degrees pitch angle constraint to ensure robust data transmission. However, a proposed modification to the WECs cylindrical geometry, to improve its hydrodynamic coupling to the input waves, was shown to enable the WEC to provide the required 1W output power whilst obeying the pitch constraints and having a mass below 50kg. The thermal energy harvester results reveal that the thermal gradient across the air/water interface alone is not a suitable energy resource, requiring a device with a cross-sectional area in excess of 100m² to power a MBS. However, including a solar thermal energy collector to increase the airside temperature, greatly improves the performance and enables a thermal energy harvester with a cross-sectional area on the order of 1m² to provide 1W of output power. The findings in this thesis suggest that a well hydrodynamically designed buoy can provide two major benefits for a MBS deployment: enabling efficient wave energy absorption by the MBS buoy, and minimising the wave induced pitch motion which negatively affects the data transmission

Overseas Chinese Environmental Engineers and Scientists Association (OCEESA) Report, Regular Issue, February 2020

This OCEESA report, which is regular issue of OCEESA Journal (Overseas Chinese Environmental Engineers and Scientists Association Journal). This report is OCEESA report number: OCEESA/JL-2020/3701, February 2020, ISSN 1072 -7248. This report is also OCEESA Journal, Volume 37, Number 1, February 2020. Yung-Tse Hung, Permanent Executive Director, OCEESA, is editor of this report. This issue includes: (A) 10 OCEESA Best Papers (B) 6 OCEESA Papers; 21.Zhang-Zhi Charlie Huang 黄长志 , Implementing Compensation System for Environmental Damages: Challenges and Solutions, 22. Hanlu Yan, Kaimin Shih施凱閔 , Quantitative X-Ray Diffraction for Characterizing P Recovery Products from Wastewater, 23. Kaimin Shih 施凱閔 , Material Mineralogical Technology for Pollution Prevention and Resource Recovery材料礦物學技術於污染防治與資源回收的應用, 24. Kuo-Kunag Hsu 許國光 , Cleanup of MSW-Gasified Synthesis Gas, 25. Pao-Chiang Yuan 袁保強 , End of Useful Life Computer Recycling Program at Jackson State University, Jackson, Mississippi, USA, 26. Qin Qian钱琴, Bo Sun, Xianchang Li, Frank Sun, Che-Jen Lin, Water quality modeling with data collected by wireless sensor networks (WSNs) in an experimental pond: A case study; (C) 3 technical papers; 28. Abdulkarim Alorayfij, Yung-Tse Hung, Anaerobic digestion of agricultural waste, 29. Abdullah Alshati, Yung-Tse Hung, Methane Gas Production from Animal Waste, 30. Abdulmajeed Alshatti, Yung-Tse Hung, Treatment of Timber Industry Wastes, 31. OCEESA Constitutions By-Laws (5 November 2000 edition), 32. OCEESA Constitutions By-Laws (14 February 2006 edition), 33. OCEESA Constitutions By-Laws (27 October 2013 edition), 34. Lawrence Kong-Pu Wang letter of support Yung-Tse Hung Permanent Executive Director OCEESA 12-30-20, 35. Wen-Chi Ku letter of support Yung-Tse Hung Permanent Executive Director OCEESA 12-03-20, 36. OCEESA Member Application Form and Information, 37. Mailing Address Pag

Détection et diagnostic des fautes dans des systèmes à base de réseaux de capteurs sans fils

Les pannes sont la règle et non l'exception dans les réseaux de capteurs sans fil. Un nœud capteur est fragile et il peut échouer en raison de l'épuisement de la batterie ou de la destruction par un événement externe. En outre, le nœud peut capter et transmettre des valeurs incorrectes en raison de l'influence de l'environnement sur son fonctionnement. Les liens sont également vulnérables et leur panne peut provoquer un partitionnement du réseau et un changement dans la topologie du réseau, ce qui conduit à une perte ou à un retard des données. Dans le cas où les nœuds sont portés par des objets mobiles, ils peuvent être mis hors de portée de la communication. Les réseaux de capteurs sont également sujets à des attaques malveillantes, telles que le déni de service, l'injection de paquets défectueux, entraînant un comportement inattendu du système et ainsi de suite. En plus de ces défaillances prédéfinies (c'est-à-dire avec des types et symptômes connus), les réseaux de capteurs présentent aussi des défaillances silencieuses qui ne sont pas connues à l'avance, et qui sont très liées au système. En revanche, les applications de RCSF, en particulier les applications de sécurité critiques, telles que la détection d'incendie ou les systèmes d'alarme, nécessitent un fonctionnement continu et fiable du système. Cependant, la garantie d'un fonctionnement correct d'un système pendant l'exécution est une tâche difficile. Cela est dû aux nombreux types de pannes que l'on peut rencontrer dans un tel système vulnérable et non fiable. Une approche holistique de la gestion des fautes qui aborde tous les types de fautes n'existe pas. En effet, les travaux existants se focalisent sur certains états d'incohérence du système. La raison en est simple : la consommation d'énergie augmente en fonction du nombre d'éléments à surveiller, de la quantité d'informations à collecter et parfois à échanger. Dans cette thèse, nous proposons un Framework global pour la gestion des fautes dans un réseau de capteurs. Ce framework, appelé IFTF , fournit une vision complète de l'état du système avec la possibilité de diagnostiquer des phénomènes anormaux. IFTF détecte les anomalies au niveau des données, diagnostique les défaillances de réseau, détecte les défaillances d'applications, et identifie les zones affectées du réseau. Ces objectifs sont atteints grâce à la combinaison efficace d'un service de diagnostic réseau (surveillance au niveau des composants), un service de test d'applications (surveillance au niveau du système) et un système de validation des données. Les deux premiers services résident sur chaque nœud du réseau et le système de validation des données réside sur chaque chef de groupe. Grâce à IFTF, les opérations de maintenance et de reconfiguration seront plus efficaces, menant à un système WSN (Wireless Sensor Network) plus fiable. Du point de vue conception, IFTF fournit de nombreux paramètres ajustables qui le rendent approprié aux divers types d'applications. Les résultats de simulation montrent que la solution présentée est efficace en termes de coût mémoire et d'énergie. En effet, le système de validation des données n'induit pas un surcoût de communication. De plus, le fonctionnement des deux services test et diagnostic augmente la consommation d'énergie de 4% en moyenne, par rapport au fonctionnement du service de diagnostic uniquement.Sensor faults are the rule and not the exception in every Wireless Sensor Network (WSN) deployment. Sensor nodes are fragile, and they may fail due to depletion of batteries or destruction by an external event. In addition, nodes may capture and communicate incorrect readings because of environmental influence on their sensing components. Links are also failure-prone, causing network partitions and dynamic changes in network topology, leading to delays in data communications. Links may fail when permanently or temporarily blocked by an external or environmental condition. Packets may be corrupted due to the erroneous nature of communications. When nodes are embedded or carried by mobile objects, nodes can be taken out of the range of communications. WSNs are also prone to malicious attacks, such as denial of service, injection of faulty packets, leading to unexpected behavior of the system and so on. In addition to these predefined faults or failures (i.e., with known types and symptoms), many times the sensor networks exhibits silent failures that are unknown beforehand and highly system-related. Applications over WSNs, in particular safety critical applications, such as fire detection or burglar alarm systems, require continuous and reliable operation of the system. However, validating that a WSN system will function correctly at run time is a hard problem. This is due to the numerous faults that can be encountered in the resource constrained nature of sensor platforms together with the unreliability of the wireless links networks. A holistic fault management approach that addresses all fault issues does not exist. Existing work most likely misses some potential causes of system failures. The reason is simple : the more elements to monitor, the more information to be collected and sometimes to be exchanged, then the more the energy consumption becomes higher. In this thesis, we propose an Integrated Fault Tolerance Framework (IFTF) that provides a complete picture of the system health with possibility to zoom in on the fault reasons of abnormal phenomena. IFTF detects data anomalies, diagnoses network failures, detects application level failures, identifies affected areas of the network and may determine the root causes of application malfunctioning. These goals are achieved efficiently through combining a network diagnosis service (component/element level monitoring) with an application testing service (system level monitoring) and a data validation system. The first two services reside on each node in the network and the data validation system resides on each cluster head. Thanks to IFTF, the maintenance and reconfiguration operations will be more efficient leading to a more dependable WSN. From the design view, IFTF offers to the application many tunable parameters that make it suitable for various application needs. Simulation results show that the presented solution is efficient both in terms of memory use and power consumption. Data validation system does not incur power consumption (communication overhead). Using testing service combined to diagnosis service incurs a 4 %, on average, increase in power consumption compared to using solely network diagnosis solutions.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF

Sea Depth Measurement with Restricted Floating Sensors

Sea depth monitoring is a critical task to ensure the safe operation of harbors. Traditional schemes largely rely on labor-intensive work and expensive hardware. This study explores the possibility of deploying networked sensors on the surface of sea, measuring and reporting sea depth of given areas. We propose a Restricted Floating Sensors (RFS) model, in which sensor nodes are anchored to the sea bottom, floating within a restricted area. Distinguished from traditional stationary or mobile sensor networks, the RFS network consists of sensor nodes with restricted mobility. We construct the network model and elaborate the corresponding localization problem. We show that by locating such RFS sensors, the sea depth can be estimated without the help of any extra ranging devices. A prototype system with 25 Telos sensor nodes is deployed to validate this design. We also examine the efficiency and scalability of this design through large-scale simulations