Uncertainty analysis framework for trust based routing in MANET

MANET (Mobile Ad hoc Network) has distinctive characteristics like node mobility, broadcast nature of wireless communication, and peer to peer data transfer. Due to these characteristics uncertainty is an integral part of MANET behavior. Uncertainty quantification is important for performance evaluation and better decision making in MANET. Packet dropping is a serious issue in MANET which degrades the performance of the network to a great extent. The packet dropping attack increases uncertainty in the network communication and eventually of the MANET. Trust based routing mechanisms are useful for neutralizing packet dropping attack. There are many existing trust based routing protocols which uses uncertainty for precise trust calculations. Thus, trust and uncertainty are closely related to each other. The paper proposes Uncertainty Analysis Framework (UAF) for MANET, it calculates the network Belief, Disbelief, and Uncertainty (BDU) values. The UAF framework integrated into different trust variants of AODV protocol which use direct trust, indirect trust, and global trust. The research work discovers impact of different trust models on MANET BDU using various mobility models. Experimental analysis shows that, trust based routing protocols show average 3 % gain in packet delivery ratio and at least 5 % increase in the network belief.     

Distributed on-demand address assignment in wireless sensornetworks

Sensor networks consist of autonomous wireless sensor nodes that are networked together in an ad hoc fashion. The tiny nodes are equipped with substantial processing capabilities, enabling them to combine and compress their sensor data. The aim is to limit the amount of network traffic, and as such conserve the nodes' limited battery energy. However, due to the small packet payload, the MAC header is a significant, and energy-costly, overhead. To remedy this, we propose a novel scheme for a MAC address assignment. The two key features which make our approach unique are the exploitation of spatial address reuse and an encoded representation of the addresses in data packets. To assign the addresses, we develop a purely distributed algorithm that relies solely on local message exchanges. Other salient features of our approach are the ability to handle unidirectional links and the excellent scalability of both the assignment algorithm and address representation. In typical scenarios, the MAC overhead is reduced by a factor of three compared to existing approaches     

分布式实时电力监控系统的设计

提出了一种分布式实时电力监控系统的设计思路，结合电力行业的行业特色和行业要求，设计了系统的组成，分析了系统中使用的关键技术，阐述了在系统中的实现思路。     

ANN modeling of DNA sequences: new strategies using DNA shape code

Two new encoding strategies, namely, wedge and twist codes, which are based on the DNA helical parameters, are introduced to represent DNA sequences in artificial neural network (ANN)-based modeling of biological systems. The performance of the new coding strategies has been evaluated by conducting three case studies involving mapping (modeling) and classification applications of ANNs. The proposed coding schemes have been compared rigorously and shown to outperform the existing coding strategies especially in situations wherein limited data are available for building the ANN models.     

Dynamic proteome in enigmatic preeclampsia: an account of molecular mechanisms and biomarker discovery

The coevolution of genomics and proteomics has led to advancements in the field of diagnosis and molecular mechanisms of disease. Proteomics is now stepping into the field of obstetrics, where early diagnosis of pregnancy complication such as preeclampsia (PE) is imperative. PE is a multifactorial disease characterized by hypertension with proteinuria, which is a leading cause of maternal and neonatal morbidity and mortality occurring in 5-7% of pregnancies worldwide. This review discusses the probable molecular mechanisms that lead to PE and summarizes the proteomics research carried out in understanding the pathogenicity of PE, and for identifying the candidate biomarker for diagnosis of the disease.     

Probability Collectives: A multi-agent approach for solving combinatorial optimization problems

Complex systems generally have many components. It is not possible to understand such complex systems only by knowing the individual components and their behavior. This is because any move by a component affects the further decisions/moves by other components and so on. In a complex system, as the number of components grows, complexity also grows exponentially, making the entire system to be seen as a collection of subsystems or a Multi-Agent System (MAS). The major challenge is to make these agents work in a coordinated way, optimizing their local utilities and contributing the maximum towards optimization of the global objective. This paper discusses the theory of Collective Intelligence (COIN) using the modified version of Probability Collectives (PC) to achieve the global goal. The paper successfully demonstrated this approach by optimizing the Rosenbrock function in which the coupled variables are seen as autonomous agents working collectively to achieve the function optimum. To demonstrate the PC approach on combinatorial optimization problems, two test cases of the Multi-Depot Multiple Traveling Salesmen Problem (MDMTSP) with 3 depots, 3 vehicles and 15 nodes are solved. In these cases, the vehicles are considered as autonomous agents collectively searching the minimum cost path. PC is successfully accompanied with insertion, elimination and swapping heuristic techniques. The optimum results to the Rosenbrock function and both the MDMTSP test cases are obtained at reasonable computational costs.     

Tropospheric ozone variability over the Indian coastline and adjacent land and sea

A tropospheric ozone variability study is carried out to investigate the spatial and temporal distribution over the coastline of the Indian peninsula and adjacent land and sea using NASA Langley Tropospheric Ozone Residual data set for the period 1979–2005. A strong seasonal cycle has been observed with large variation (～ 55%) over the upper eastern coast, followed by the upper and lower western coast, compared to the lower eastern coast (～ 33%). A negative gradient in ozone concentration is observed along eastern and western coasts during summer (slope ～ –0.78 and –0.65) and a positive gradient (slope ～ 0.16 and 0.21) during winter. The same is observed over the adjacent land and sea along the coastline with slight variation. This change in gradient can be attributed to the anthropogenic emission of precursor gases that reinforce localized photochemical production of ozone. In addition, topography, transport, seasonality of emission of precursor gases and the solar insolation cycle play a vital role.     

A survey of sensory data boundary estimation,covering and tracking techniques using collaborating sensors

Boundary estimation and tracking have important applications in the areas of environmental monitoring and disaster management. A boundary separates two regions of interest in a phenomenon. It can be visualized as an edge if there is a sharp change in the field value between the two regions or alternatively, as a contour with a field value $f=\tau$ separating two regions with field values $f>\tau$ and $f<\tau$. Examples include contours/boundaries of hazardous concentration in a pollutant spill, frontal boundary of a forest fire, isotherms, isohalines etc. Recent advances in the area of embedded sensor devices and robotics have led to deployments of networks of sensors capable of sensing, computing, communication and mobility. They are used to estimate the boundaries of interest in physical phenomena, monitor or track them over time and also in some cases, mitigate the spatial spread of the phenomena. Since these sensors work autonomously in the environment, minimizing the energy consumed while maximizing the accuracy of estimation or tracking is the main challenge for algorithms for boundary estimation and tracking. Several algorithms with these objectives have been proposed in the literature. In this work, we focus on the algorithms that estimate and cover boundaries found in the sensory data in a field and not the topological boundary of the sensor network per se, which is beyond the scope of this paper.Here, our objective is to provide a comprehensive survey of the algorithms for boundary estimation and tracking by providing a taxonomy based on two broad categories — (i) Boundary estimation and tracking, where the sensors estimate the boundary without physically covering the boundary and (ii) Boundary covering — where the sensors not only predict the location and estimate the entire boundary but also physically cover the boundary by surrounding and bounding it. We further classify the techniques based on (a) sensing capabilities —in situ, range or remote sensing (b) movement capabilities — static or mobile sensors and (c) boundary type — static or dynamic and (d) type of estimation — field estimation where the entire field is sampled to search for contours and localized estimation where sampling is done near the boundary and (e) different types of mobility models in the case of mobile sensors. We believe that such a survey has not been performed before. By capturing and classifying the current state-of-the-art and identifying open research problems, we hope to ignite interest and stimulate efforts towards promising solutions for real-world boundary estimation and tracking problems.     

IBM's Linux watch, the challenge of miniaturization

Nearly four years in development, the IBM Linux watch contains a complete computer system that runs Linux, displays X11 graphics, and has wireless connectivity. The system fits in a case that could pass as a slightly unusual analog timepiece with a somewhat odd shape and an extraordinarily brilliant face. The developers have created two versions of the watch, one with an organic light-emitting diode display and the other with a liquid crystal display. Still considered a research prototype, the watch already runs some personal information management applications, and it can communicate with PCs, PDAs, and other wireless-enabled devices, viewing condensed e-mail and directly receiving pager-like messages. Eventually, users will be able to access various Internet-based services, such as up-to-the-minute information about weather, traffic conditions, the stock market, and sports