Self-healing in unattended wireless sensor networks

Wireless sensor networks (WSNs) appeal to a wide range of applications that involve the monitoring of various physical phenomena. However, WSNs are subject to many threats. In particular, lack of pervasive tamper-resistant hardware results in sensors being easy targets for compromise. Having compromised a sensor, the adversary learns all the sensor secrets, allowing it to later encrypt/decrypt or authenticate messages on behalf of that sensor. This threat is particularly relevant in the novel unattended wireless sensor networks (UWSNs) scenario. UWSNs operate without constant supervision by a trusted sink. UWSN?s unattended nature and increased exposure to attacks prompts the need for special techniques geared towards regaining security after being compromised. In this article, we investigate cooperative self-healing in UWSNs and propose various techniques to allow unattended sensors to recover security after compromise. Our techniques provide seamless healing rates even against a very agile and powerful adversary. The effectiveness and viability of our proposed techniques are assessed by thorough analysis and supported by simulation results. Finally, we introduce some real-world issues affecting UWSN deployment and provide some solutions for them as well as a few open problems calling for further investigation.

Real time monitoring of click chemistry self-healing in polymer composites

A photo-healable rubber composite based on effective and fast thiol-alkyne click chemistry as a selfhealing agent prestored in glass capillaries is reported. The click reaction and its effect on the mechanical properties of the composite are monitored in real time by dynamic mechanical analysis, showing that the successful bleeding of healing agents to the crack areas and the effective photoinitiated click reaction result in a 30% storage modulus increase after only 5 min of UV light exposure. X-ray tomography confirms capillary-driven bleeding of reactants to the damaged areas. The effect of storing the click chemistry reactants in separate capillaries is also studied, and results show the importance of stoichiometry in achieving a significant level of repair of the composite. No reactant degradation or premature chemical reaction is observed over time in samples stored in the absence of UV radiation; they are able to undergo the self-healing reaction even one month after preparation.

Sam Leake's letters on right thinking and self-healing.

Mode of access: Internet.

Self-healing of cracks during ductile regime machining of silicon: Insights from molecular dynamics simulation

During nanoindentation and ductile-regime machining of silicon, a phenomenon known as “self-healing” takes place in that the microcracks, microfractures, and small spallings generated during the machining are filled by the plastically flowing ductile phase of silicon. However, this phenomenon has not been observed in simulation studies. In this work, using a long-range potential function, molecular dynamics simulation was used to provide an improved explanation of this mechanism. A unique phenomenon of brittle cracking was discovered, typically inclined at an angle of 45° to 55° to the cut surface, leading to the formation of periodic arrays of nanogrooves being filled by plastically flowing silicon during cutting. This observation is supported by the direct imaging. The simulated X-ray diffraction analysis proves that in contrast to experiments, Si-I to Si-II (beta tin) transformation during ductile-regime cutting is highly unlikely and solid-state amorphisation of silicon caused solely by the machining stress rather than the cutting temperature is the key to its brittle-ductile transition observed during the MD simulations

Self-healing thermal annealing: surface morphological restructuring control of GaN nanorods

With advances in nanolithography and dry etching, top-down methods of nanostructuring have become a widely used tool for improving the efficiency of optoelectronics. These nano dimensions can offer various benefits to the device performance in terms of light extraction and efficiency, but often at the expense of emission color quality. Broadening of the target emission peak and unwanted yellow luminescence are characteristic defect-related effects due to the ion beam etching damage, particularly for III–N based materials. In this article we focus on GaN based nanorods, showing that through thermal annealing the surface roughness and deformities of the crystal structure can be “self-healed”. Correlative electron microscopy and atomic force microscopy show the change from spherical nanorods to faceted hexagonal structures, revealing the temperature-dependent surface morphology faceting evolution. The faceted nanorods were shown to be strain- and defect-free by cathodoluminescence hyperspectral imaging, micro-Raman, and transmission electron microscopy (TEM). In-situ TEM thermal annealing experiments allowed for real time observation of dislocation movements and surface restructuring observed in ex-situ annealing TEM sampling. This thermal annealing investigation gives new insight into the redistribution path of GaN material and dislocation movement post growth, allowing for improved understanding and in turn advances in optoelectronic device processing of compound semiconductors.

Self-sealing of thermal fatigue and mechanical damage in fiber-reinforced composite materials

Fiber reinforced composite tanks provide a promising method of storage for liquid oxygen and hydrogen for aerospace applications. The inherent thermal fatigue of these vessels leads to the formation of microcracks, which allow gas phase leakage across the tank walls. In this dissertation, self-healing functionality is imparted to a structural composite to effectively seal microcracks induced by both mechanical and thermal loading cycles. Two different microencapsulated healing chemistries are investigated in woven glass fiber/epoxy and uni-weave carbon fiber/epoxy composites. Self-healing of mechanically induced damage was first studied in a room temperature cured plain weave E-glass/epoxy composite with encapsulated dicyclopentadiene (DCPD) monomer and wax protected Grubbs' catalyst healing components. A controlled amount of microcracking was introduced through cyclic indentation of opposing surfaces of the composite. The resulting damage zone was proportional to the indentation load. Healing was assessed through the use of a pressure cell apparatus to detect nitrogen flow through the thickness direction of the damaged composite. Successful healing resulted in a perfect seal, with no measurable gas flow. The effect of DCPD microcapsule size (51 um and 18 um) and concentration (0 - 12.2 wt%) on the self-sealing ability was investigated. Composite specimens with 6.5 wt% 51 um capsules sealed 67% of the time, compared to 13% for the control panels without healing components. A thermally stable, dual microcapsule healing chemistry comprised of silanol terminated poly(dimethyl siloxane) plus a crosslinking agent and a tin catalyst was employed to allow higher composite processing temperatures. The microcapsules were incorporated into a satin weave E-glass fiber/epoxy composite processed at 120C to yield a glass transition temperature of 127C. Self-sealing ability after mechanical damage was assessed for different microcapsule sizes (25 um and 42 um) and concentrations (0 - 11 vol%). Incorporating 9 vol% 42 um capsules or 11 vol% 25 um capsules into the composite matrix leads to 100% of the samples sealing. The effect of microcapsule concentration on the short beam strength, storage modulus, and glass transition temperature of the composite specimens was also investigated. The thermally stable tin catalyzed poly(dimethyl siloxane) healing chemistry was then integrated into a [0/90]s uniweave carbon fiber/epoxy composite. Thermal cycling (-196C to 35C) of these specimens lead to the formation of microcracks, over time, formed a percolating crack network from one side of the composite to the other, resulting in a gas permeable specimen. Crack damage accumulation and sample permeability was monitored with number of cycles for both self-healing and traditional non-healing composites. Crack accumulation occurred at a similar rate for all sample types tested. A 63% increase in lifetime extension was achieved for the self-healing specimens over traditional non-healing composites.

Wireless Sensor Network Deployment

Wireless Sensor Networks (WSNs) are widely used for various civilian and military applications, and thus have attracted significant interest in recent years. This work investigates the important problem of optimal deployment of WSNs in terms of coverage and energy consumption. Five deployment algorithms are developed for maximal sensing range and minimal energy consumption in order to provide optimal sensing coverage and maximum lifetime. Also, all developed algorithms include self-healing capabilities in order to restore the operation of WSNs after a number of nodes have become inoperative. Two centralized optimization algorithms are developed, one based on Genetic Algorithms (GAs) and one based on Particle Swarm Optimization (PSO). Both optimization algorithms use powerful central nodes to calculate and obtain the global optimum outcomes. The GA is used to determine the optimal tradeoff between network coverage and overall distance travelled by fixed range sensors. The PSO algorithm is used to ensure 100% network coverage and minimize the energy consumed by mobile and range-adjustable sensors. Up to 30% - 90% energy savings can be provided in different scenarios by using the developed optimization algorithms thereby extending the lifetime of the sensor by 1.4 to 10 times. Three distributed optimization algorithms are also developed to relocate the sensors and optimize the coverage of networks with more stringent design and cost constraints. Each algorithm is cooperatively executed by all sensors to achieve better coverage. Two of our algorithms use the relative positions between sensors to optimize the coverage and energy savings. They provide 20% to 25% more energy savings than existing solutions. Our third algorithm is developed for networks without self-localization capabilities and supports the optimal deployment of such networks without requiring the use of expensive geolocation hardware or energy consuming localization algorithms. This is important for indoor monitoring applications since current localization algorithms cannot provide good accuracy for sensor relocation algorithms in such indoor environments. Also, no sensor redeployment algorithms, which can operate without self-localization systems, developed before our work.

Multifarious facets of sugar-derived molecular gels: molecular features, mechanisms of self-assembly and emerging applications

The remarkable capability of nature to design and create excellent self-assembled nano-structures, especially in the biological world, has motivated chemists to mimic such systems with synthetic molecular and supramolecular systems. The hierarchically organized self-assembly of low molecular weight gelators (LMWGs) based on non-covalent interactions has been proven to be a useful tool in the development of well-defined nanostructures. Among these, the self-assembly of sugar-derived LMWGs has received immense attention because of their propensity to furnish biocompatible, hierarchical, supramolecular architectures that are macroscopically expressed in gel formation. This review sheds light on various aspects of sugar-derived LMWGs, uncovering their mechanisms of gelation, structural analysis, and tailorable properties, and their diverse applications such as stimuli-responsiveness, sensing, self-healing, environmental problems, and nano and biomaterials synthesis.

Implementação distribuída de auto-cura em redes inteligentes de distribuição de energia elétrica utilizando árvores de extensão mínima.

A propriedade de auto-cura, em redes inteligente de distribuição de energia elétrica, consiste em encontrar uma proposta de reconfiguração do sistema de distribuição com o objetivo de recuperar parcial ou totalmente o fornecimento de energia aos clientes da rede, na ocorrência de uma falha na rede que comprometa o fornecimento. A busca por uma solução satisfatória é um problema combinacional cuja complexidade está ligada ao tamanho da rede. Um método de busca exaustiva se torna um processo muito demorado e muitas vezes computacionalmente inviável. Para superar essa dificuldade, pode-se basear nas técnicas de geração de árvores de extensão mínima do grafo, representando a rede de distribuição. Porém, a maioria dos estudos encontrados nesta área são implementações centralizadas, onde proposta de reconfiguração é obtida por um sistema de supervisão central. Nesta dissertação, propõe-se uma implementação distribuída, onde cada chave da rede colabora na elaboração da proposta de reconfiguração. A solução descentralizada busca uma redução no tempo de reconfiguração da rede em caso de falhas simples ou múltiplas, aumentando assim a inteligência da rede. Para isso, o algoritmo distribuído GHS é utilizado como base na elaboração de uma solução de auto-cura a ser embarcada nos elementos processadores que compõem as chaves de comutação das linhas da rede inteligente de distribuição. A solução proposta é implementada utilizando robôs como unidades de processamento que se comunicam via uma mesma rede, constituindo assim um ambiente de processamento distribuído. Os diferentes estudos de casos testados mostram que, para redes inteligentes de distribuição compostas por um único alimentador, a solução proposta obteve sucesso na reconfiguração da rede, indiferentemente do número de falhas simultâneas. Na implementação proposta, o tempo de reconfiguração da rede não depende do número de linhas nela incluídas. A implementação apresentou resultados de custo de comunicação e tempo dentro dos limites teóricos estabelecidos pelo algoritmo GHS.

Explaining World Wide Web Traffic Self-Similarity

Recently the notion of self-similarity has been shown to apply to wide-area and local-area network traffic. In this paper we examine the mechanisms that give rise to self-similar network traffic. We present an explanation for traffic self-similarity by using a particular subset of wide area traffic: traffic due to the World Wide Web (WWW). Using an extensive set of traces of actual user executions of NCSA Mosaic, reflecting over half a million requests for WWW documents, we show evidence that WWW traffic is self-similar. Then we show that the self-similarity in such traffic can be explained based on the underlying distributions of WWW document sizes, the effects of caching and user preference in file transfer, the effect of user "think time", and the superimposition of many such transfers in a local area network. To do this we rely on empirically measured distributions both from our traces and from data independently collected at over thirty WWW sites.

Natural inspiration for self-adaptive systems

The emergent behaviour of autonomic systems, together with the scale of their deployment, impedes prediction of the full range of configuration and failure scenarios; thus it is not possible to devise management and recovery strategies to cover all possible outcomes. One solution to this problem is to embed self-managing and self-healing abilities into such applications. Traditional design approaches favour determinism, even when unnecessary. This can lead to conflicts between the non-functional requirements. Natural systems such as ant colonies have evolved cooperative, finely tuned emergent behaviours which allow the colonies to function at very large scale and to be very robust, although non-deterministic. Simple pheromone-exchange communication systems are highly efficient and are a major contribution to their success. This paper proposes that we look to natural systems for inspiration when designing architecture and communications strategies, and presents an election algorithm which encapsulates non-deterministic behaviour to achieve high scalability, robustness and stability.

The Forgiving Graph: a distributed data structure for low stretch under adversarial attack

We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that, over a sequence of rounds, an adversary either inserts a node with arbitrary connections or deletes an arbitrary node from the network. The network responds to each such change by quick “repairs,” which consist of adding or deleting a small number of edges. These repairs essentially preserve closeness of nodes after adversarial deletions, without increasing node degrees by too much, in the following sense. At any point in the algorithm, nodes v and w whose distance would have been l in the graph formed by considering only the adversarial insertions (not the adversarial deletions), will be at distance at most l log n in the actual graph, where n is the total number of vertices seen so far. Similarly, at any point, a node v whose degree would have been d in the graph with adversarial insertions only, will have degree at most 3d in the actual graph. Our distributed data structure, which we call the Forgiving Graph, has low latency and bandwidth requirements. The Forgiving Graph improves on the Forgiving Tree distributed data structure from Hayes et al. (2008) in the following ways: 1) it ensures low stretch over all pairs of nodes, while the Forgiving Tree only ensures low diameter increase; 2) it handles both node insertions and deletions, while the Forgiving Tree only handles deletions; 3) it requires only a very simple and minimal initialization phase, while the Forgiving Tree initially requires construction of a spanning tree of the network.