On the vulnerabilities of voronoi-based approaches to mobile sensor deployment

Mobile sensor networks are the most promising solution to cover an Area of Interest (AoI) in safety critical scenarios. Mobile devices can coordinate with each other according to a distributed deployment algorithm, without resorting to human supervision for device positioning and network configuration. In this paper, we focus on the vulnerabilities of the deployment algorithms based on Voronoi diagrams to coordinate mobile sensors and guide their movements. We give a geometric characterization of possible attack configurations, proving that a simple attack consisting of a barrier of few compromised sensors can severely reduce network coverage. On the basis of the above characterization, we propose two new secure deployment algorithms, named SecureVor and Secure Swap Deployment (SSD). These algorithms allow a sensor to detect compromised nodes by analyzing their movements, under different and complementary operative settings. We show that the proposed algorithms are effective in defeating a barrier attack, and both have guaranteed termination. We perform extensive simulations to study the performance of the two algorithms and compare them with the original approach. Results show that SecureVor and SSD have better robustness and flexibility and excellent coverage capabilities and deployment time, even in the presence of an attac

Progressive damage assessment and network recovery after massive failures

After a massive scale failure, the assessment of damages to communication networks requires local interventions and remote monitoring. While previous works on network recovery require complete knowledge of damage extent, we address the problem of damage assessment and critical service restoration in a joint manner. We propose a polynomial algorithm called Centrality based Damage Assessment and Recovery (CeDAR) which performs a joint activity of failure monitoring and restoration of network components. CeDAR works under limited availability of recovery resources and optimizes service recovery over time. We modified two existing approaches to the problem of network recovery to make them also able to exploit incremental knowledge of the failure extent. Through simulations we show that CeDAR outperforms the previous approaches in terms of recovery resource utilization and accumulative flow over time of the critical service

Network recovery after massive failures

This paper addresses the problem of efficiently restoring sufficient resources in a communications network to support the demand of mission critical services after a large scale disruption. We give a formulation of the problem as an MILP and show that it is NP-hard. We propose a polynomial time heuristic, called Iterative Split and Prune (ISP) that decomposes the original problem recursively into smaller problems, until it determines the set of network components to be restored. We performed extensive simulations by varying the topologies, the demand intensity, the number of critical services, and the disruption model. Compared to several greedy approaches ISP performs better in terms of number of repaired components, and does not result in any demand loss. It performs very close to the optimal when the demand is low with respect to the supply network capacities, thanks to the ability of the algorithm to maximize sharing of repaired resources

On critical service recovery after massive network failures

This paper addresses the problem of efficiently restoring sufficient resources in a communications network to support the demand of mission critical services after a large-scale disruption. We give a formulation of the problem as a mixed integer linear programming and show that it is NP-hard. We propose a polynomial time heuristic, called iterative split and prune (ISP) that decomposes the original problem recursively into smaller problems, until it determines the set of network components to be restored. ISP's decisions are guided by the use of a new notion of demand-based centrality of nodes. We performed extensive simulations by varying the topologies, the demand intensity, the number of critical services, and the disruption model. Compared with several greedy approaches, ISP performs better in terms of total cost of repaired components, and does not result in any demand loss. It performs very close to the optimal when the demand is low with respect to the supply network capacities, thanks to the ability of the algorithm to maximize sharing of repaired resources

Network analysis and algorithm solutions in critical emergency scenarios

Critical emergency scenarios in network communication, mobile wireless sensor networks and Smart Grids. Network recovery after massive disruption, algorithms for damaged networks, protocols for damaged networks, progressive monitoring of a damaged network, progressive flow restoration of a damaged network. Analysis of the vulnerabilities of the deployment algorithm for Mobile Wireless Sensor Netowkrs in human hostile environment, Algorithms for Mobile Wireless Sensor Networks under attack. Analysis of the cascading failures phenomenon in the Smart Grids, Prevents Large Blackout in the Smart Grids, Reduce the energy demand on the Smart Grids using the Internet of Things

Network recovery from massive failures under uncertain knowledge of damages

This paper addresses progressive network recovery under uncertain knowledge of damages. We formulate the problem as a mixed integer linear programming (MILP), and show that it is NP-Hard. We propose an iterative stochastic recovery algorithm (ISR) to recover the network in a progressive manner to satisfy the critical services. At each optimization step, we make a decision to repair a part of the network and gather more information iteratively, until critical services are completely restored. Three different algorithms are used to find a feasible set and determine which node to repair, namely, 1) an iterative shortest path algorithm (ISR-SRT), 2) an approximate branch and bound (ISR-BB) and 3) an iterative multi-commodity LP relaxation (ISR-MULT). Further, we have modified the state-of-the-Art iterative split and prune (ISP) algorithm to incorporate the uncertain failures. Our results show that ISR-BB and ISR- MULT outperform the state-of-the-Art 'progressive ISP' algorithm while we can configure our choice of trade-off between the execution time, number of repairs (cost) and the demand loss. We show that our recovery algorithm, on average, can reduce the total number of repairs by a factor of about 3 with respect to ISP, while satisfying all critical deman

Managing Contingencies in Smart Grids via the Internet of Things

This paper proposes a framework for contingency management using smart loads, which are realized through the emerging paradigm of the Internet of things. The framework involves the system operator, the load serving entities (LSEs), and the end-users with smart home management systems that automatically control adjustable loads. The system operator uses an efficient linear equation solver to quickly calculate the load curtailment needed at each bus to relieve congested lines after a contingency. Given this curtailment request, an LSE calculates a power allowance for each of its end-use customers to maximize the aggregate user utility. This large-scale NP-hard problem is approximated to a convex optimization for efficient computation. A smart home management system determines the appliances allowed to be used in order to maximize the user's utility within the power allowance given by the LSE. Since the user's utility depends on the near-future usage of the appliances, the framework provides the Welch-based reactive appliance prediction (WRAP) algorithm to predict the user behavior and maximize utility. The proposed framework is validated using the New England 39-bus test system. The results show that power system components at risk can be quickly alleviated by adjusting a large number of small smart loads. Additionally, WRAP accurately predicts the users' future behavior, minimizing the impact on the aggregate users' utility

Effects of Cord Blood Serum (CBS) on viability of retinal Müller glial cells under in vitro injury

Oxidative stress and inflammation determine retinal ganglion cell degeneration, leading to retinal impairment and vision loss. Muller glial cells regulate retinal repair under injury, through gliosis. Meanwhile, reactive gliosis can turn in pathological effects, contributing to neurodegeneration. In the present study, we tested whether Cord Blood Serum (CBS), rich of growth factors, might improve the viability of Muller cells under in vitro damage. BDNF, NGF, TGF-alpha, GDNF and EGF levels were measured in CBS samples by Human Magnetic Luminex Assay. CBS effects were evaluated on rat (rMC-1) and human (MIO-M1) Muller cells, under H2O2 and IL-1 beta damage. Cells grown with FBS or CBS both at 5% were exposed to stress and analyzed in terms of cell viability, GFAP, IL-6 and TNF-alpha expression. CBS was also administrated after treatment with K252a, inhibitor of the neurotrophin receptor Trk. Cell viability of rMC-1 and MIO-M1 resulted significantly improved when pretreated with CBS and exposed to H2O2 and IL-1 beta, in comparison to the standard culture with FBS. Accordingly, the gliosis marker GFAP resulted down-regulated following CBS priming. In parallel, we observed a lower expression of the inflammatory mediators in rMC-1 (TNF-alpha) and MIO-M1 (IL-6, TNF- alpha), especially in presence of inflammatory damage. Trk inhibition through K252a administration impaired the effects of CBS under stress conditions on MIO-M1 and rMC-1 viability, not significantly different from FBS condition. CBS is enriched with neurotrophins and its administration to rMC-1 and MIO-M1 attenuates the cytotoxic effects of H2O2 and IL-1 beta. Moreover, the decrease of the main markers of gliosis and inflammation suggests a promising use of CBS for neuroprotection aims. This study is a preliminary basis that prompts future investigations to deeply explore and confirm the CBS potential

Report of a case of discoid lupus erythematosus localised to the oral cavity: immunofluorescence findings.

Discoid Lupus Erythematosus (DLE) is a chronic disease with a typical cutaneous involvement. This pathology rarely involves mucosa: oral cavity is interested in 20% of DLE patients. We describe a case of oral DLE in a 50-year-old woman with an anamnesis for autoimmune disorders. This study shows the helpful role of immunofluorescence in the diagnosis of autoimmune diseases. The first diagnostic step was the clinical observation of the oral mucosa: the lesion area was erythematous, athrophic and hyperkeratotic. The patient then underwent laboratory examination. We utilized human epithelial cells (Hep-2010) for Indirect Immuno-Fluorescence (IIF). Moreover, the biopsy site for Direct Immuno-Fluorescence (DIF) and histopathological analysis was the untreated oral lesion. IIF detected an increase of Anti-Nuclear Antibody (ANA) and positivity for SSA-RO. By DIF, we observed IgG/IgA/fibrinogen along basal layer. Multiple biopsies reported signs of chronic basal damage. Steroid systemic therapy induced a considerable lesion regression. We suggest the use of immunofluorescence with the integration of further data to improve diagnosis of rare diseases and to establish a suitable therapy