A Fuzzy Approach for Reducing Power Consumption in Wireless Sensor Networks: A Testbed With IEEE 802.15.4 and WirelessHART

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E2XLRADR (Energy Efficient Cross Layer Routing Algorithm with Dynamic Retransmission for Wireless Sensor Networks)

The main focus of this article is to achieve prolonged network lifetime with overall energy efficiency in wireless sensor networks through controlled utilization of limited energy. Major percentage of energy in wireless sensor network is consumed during routing from source to destination, retransmission of data on packet loss. For improvement, cross layered algorithm is proposed for routing and retransmission scheme. Simulation and results shows that this approach can save the overall energy consumptio

Resilient Distributed Optimization Algorithms for Resource Allocation

Distributed algorithms provide flexibility over centralized algorithms for resource allocation problems, e.g., cyber-physical systems. However, the distributed nature of these algorithms often makes the systems susceptible to man-in-the-middle attacks, especially when messages are transmitted between price-taking agents and a central coordinator. We propose a resilient strategy for distributed algorithms under the framework of primal-dual distributed optimization. We formulate a robust optimization model that accounts for Byzantine attacks on the communication channels between agents and coordinator. We propose a resilient primal-dual algorithm using state-of-the-art robust statistics methods. The proposed algorithm is shown to converge to a neighborhood of the robust optimization model, where the neighborhood's radius is proportional to the fraction of attacked channels.Comment: 15 pages, 1 figure, accepted to CDC 201

Comparison of Energy Consumption of Wireless Sensor Network at Various Topology Deployment: Array, Grid, and Random

This paper is review wireless sensor network and it’s energy consumption at different deployment methods. Wireless Sensor Networks (WSN) are emerging with many applications, because of the advances in large scale wireless communications. These networks are deployed to serve single objective application, with high optimization requirements such as power saving. The WSN design problem is of high complexity, and requires robust methodologies, including simulation support. We use NS2 as simulation program for this model. In this paper, the authors compare the energy consumption on three different deployment methods of WSN. These deployment methods refer to topology deployment. In this simulation, we deploy WSN on grid, array, and random topology. We use different numbers of WSN nodes for showing the scalability. We use AODV as routing protocol and CBR as the traffic. After that, we compare the energy consumption that consume by that networks. Based on simulation result, the array topology is the best topology for deployment. This topology is the lowest on energy consumption, 0.560%.

Computing and Diagnosing Changes in Unit Test Energy Consumption

Many developers have reason to be concerned with with power consumption. For example, mobile app developers want to minimize how much power their applications draw, while still providing useful functionality. However, developers have few tools to get feedback about changes to their application\u27s power consumption behavior as they implement an application and make changes to it over time. We present a tool that, using a team\u27s existing test cases, performs repeated measurements of energy consumption based on instructions executed, objects generated, and blocking latency, generating a distribution of energy use estimates for each test run, recording these distributions in a time series of distributions over time. Then, when these distributions change substantially, we inform the developer of this change, and offer them diagnostic information about the elements of their code potentially responsible for the change and the inputs responsible. Through this information, we believe that developers will be better enabled to relate recent changes in their code to changes in energy consumption, enabling them to better incorporate changes in software energy consumption into their software evolution decisions

APPLICATION OF INTELLIGENT GAME THEORY APPROACH IN COGNITIVE RADIO AD HOC NETWORKS

Cognitive Radio (CR) technology is imagined to solve the problems in Wireless Ad-hoc NETworks (WANET) resulting from the limited available spectrum and the inefficiency in the spectrum usage by exploiting the existing wireless spectrum opportunistically. Game theory is a process to analyze multi-person decision making situation, where each decision maker tries to maximize his own utility. In this paper, we illustrates how various interactions in Cognitive Radio Ad Hoc Network (CRAHN) can be modeled as a game. It also illustrates a problem with solution approach that uses intelligent game theory technique in CRAHN

FUZZY MULTI-OBJECTIVE LINEAR PROGRAMMING APPROACH FOR SOLVING PROBLEM OF FOOD INDUSTRY

Enterprises and industrial centers need current decision for making products in fast changing market. Uncertainty and yield defined goals make decision making more difficult. In this situation fuzzy logic is used for coping surrounding environment. This paper deals with a fuzzy linear programming model for a problem of food industry. The different types of achievement function such as compensatory and weighted compensatory form&nbsp