Introductory methods of numerical analysis / S.S. Sastry

In recent years, floods have often occurred in Indonesia. The impact of floods must be mapped and informed to reduce the impact of flood victims. The technology used to obtain flood information is a wireless sensor. Uneven wireless sensor distribution and wireless sensor resource conditions make the information obtained sometimes inaccurate. Several studies have conducted research on wireless sensors in uneven distribution. This study develops information on potential flooding in flood-prone areas. This study uses wireless sensors that are scattered along potential flood rivers as data senders. Data sent in the form of rainfall data, river water discharge, and river water level. These data are processed using the hybrid Artificial Intelligence algorithm, namely the k-NN algorithm and the Naive Bayes algorithm. The results of this data processing are in the form of three prediction conditions, namely floods, early warnings, and not floods. The results of the implementation of the system with the hybrid algorithm obtained prediction accuracy rate of 93,4%. This system has an error of 6,6% when the system cannot predict wireless sensor data.

New Method of Artificial Intelligence for Disaster Information Floods use Distributed Wireless Sensors

Abstract Sensor technology is developing rapidly and up to date. The lifetime of the Wireless Sensor Network (WSN) has also attracted many researchers, and the location of the Base Station (BS) plays a crucial role in prolonging the lifetime. The energy consumption in the WSN occurs during transmission of data and selection of cluster-head nodes. A reasonable location of the BS prolongs the lifetime of the WSN. This study proposes a Levy Flight Edge Regeneration Black Hole algorithm (LEBH) to speed up convergence and enhance optimization capabilities. The performance of LEBH and other heuristic algorithms are compared on CEC 2013. The result shows that the LEBH outperforms other heuristics in most cases. In this study, the energy consumption and WSN models are simulated. Subsequently, the proposed LEBH is combined with relocation technology to change the location of the BS to prolong the lifetime. Simulation results show LEBH-BS prolongs the lifetime of the WSN better than random-base and static-base stations and other heuristic algorithms in most cases. 

/pdf/application-of-improved-black-hole-algorithm-in-prolonging-1qqi61p2.pdf

Application of improved black hole algorithm in prolonging the lifetime of wireless sensor network

A novel predictive approach for mobility activeness in mobile wireless networks

Nowadays, mobile computing has become a key component of telecommunication systems, and the Open Systems Interconnection (OSI) layer operations are affected by the effects of node movements along the roads, from the physical to the routing/transport layers. In particular, routing approaches have been investigated from many years, trying to optimize the performance of the whole considered system, under different points of view. In this paper we are focusing the attention on the analysis of the mobility grade trend for a mobile ad-hoc network environment, as well as on the way it can be a-priori known, in order to have the possibility to study how the dynamics of mobile nodes can be described and in-advance known, with a predicted knowledge of nodes stability (in terms of mobility). Our simulations considered mobility in real geographical maps, and the obtained results confirmed the goodness of our proposed study. 

A main advantage of Mobile Ad-hoc Network(MANET) is providing mobility to the users. The erratic mobility of the nodes may cause route failures very continuously. The continuous routes square measures to interrupt cause Quality of Service have an effect on within the mobile wireless network and therefore bearing the challenge. In this paper, we've got planned a way of best signal strength primarily based link prediction utilized in AODV routing and finding the shortest path and searches for all possible paths of source to destination, and the path having best signal strength will be considered as best path to routing. Since the routing is performed through the path having best signal strength so Packet Delivery Ratio (PDR) in this case will drastically increase. As we know very well that the major concern in communication network are to deliver packets of minimum losses. So minimization in losses will drastically improve the Quality of Service (QoS). Link failure occurs due to mobility of nodes which are pure probabilistic in nature. Therefore, it is very difficult to route a packet in such a way to minimize the link failures because when we route a packet then our prime objective is to minimize packet losses in the network. That's why no research is interested in routing a packet in such a way of minimize the link failures. Then our prime objective is to minimize packet losses in the network. That's why no research is interested in routing a packet in such a way of minimize the link failures.

Advanced routing on AODV using link prediction in Mobile Ad-Hoc Network

In Wireless Sensor Network, while determining the continuance of the network, the chief issue is the energy consumed by the individual nodes. Routing based on hierarchical clusters does ameliorate the utilization of energy in the network rather than other techniques used for routing. This paper is based on a new algorithm for the multi-level cluster in which an Ant Colony Optimization based improved routing algorithm is used for choosing cluster heads. By using the improved ant colony optimization technique in the hierarchical multi-level clustering and while considering its transmission distance, node energy and direction of the transmission, an optimal way can be received from the leaf node towards the sink node This reduces the energy consumed by the network and prolonged lifetime of the network. Time Division Multiple Access (TDMA) technique is used within clusters, it helps in creating an organized cluster and avoid data collision and also improves energy efficiency.

An efficient multi-level clustering approach using improved ant colony optimization

Modern improvement in micro manufacturing technology authorized wireless communication to evolution of low power, low cost and multitasking sensor nodes. Multiple sensing applications take place sincerity as an outcome. It include environmental monitoring, disaster management, object tracking, battlefield surveillance, intrusion detection, etc. In a wireless sensor network (WSN) when data sensed and passed from one sensor to another, there arise a problem of limited battery power. Sink relocation is a method for extend the network lifetime of a WSN. In this paper a new approach of adaptive sink transmission and relocation (AST-EASR) introduces to extend the network lifetime of WSN. Our proposed method categorized in two way, sink transmission and relocation. Sink transmission operation performed by checking the receive signal strength using of heterogeneous lower energy consumption. Other side the task of sink relocation performed by grid based sensing (prior for advance node). Simulation results show that our proposed AST-EASR maximized the network lifetime of WSN as compare to conventional approaches like, energy aware sink relocation (EASR) and one-step moving scheme.

Adaptive sink transmission and relocation to extend the network lifetime of wireless sensor network

An outbreak of Rabbit Haemorrhagic Disease among meat type rabbits at the Institutional demonstration rabbit farm has been described. The clinical signs, post mortem lesions and treatment / control procedure undertaken were discussed.

Case Study INCIDENCE OF RABBIT HEMORRHAGIC DISEASE (RHD) IN MEAT TYPE RABBITS

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Advanced routing on AODV using link prediction in Mobile Ad-Hoc Network

An efficient multi-level clustering approach using improved ant colony optimization

Adaptive sink transmission and relocation to extend the network lifetime of wireless sensor network

Case Study INCIDENCE OF RABBIT HEMORRHAGIC DISEASE (RHD) IN MEAT TYPE RABBITS