Extending Wireless Rechargeable Sensor Network Life without Full Knowledge

When extending the life of Wireless Rechargeable Sensor Networks (WRSN), one challenge is charging networks as they grow larger. Overcoming this limitation will render a WRSN more practical and highly adaptable to growth in the real world. Most charging algorithms require a priori full knowledge of sensor nodes’ power levels in order to determine the nodes that require charging. In this work, we present a probabilistic algorithm that extends the life of scalable WRSN without a priori power knowledge and without full network exploration. We develop a probability bound on the power level of the sensor nodes and utilize this bound to make decisions while exploring a WRSN.We verify the algorithm by simulating a wireless power transfer unmanned aerial vehicle, and charging a WRSN to extend its life. Our results show that, without knowledge, our proposed algorithm extends the life of a WRSN on average 90% of what an optimal full knowledge algorithm can achieve. This means that the charging robot does not need to explore the whole network, which enables the scaling of WRSN. We analyze the impact of network parameters on our algorithm and show that it is insensitive to a large range of parameter values

Node Discovery and Replacement Using Mobile Robot

International audienceA critical problem of wireless sensor networks is the network lifetime, due to the device's limited battery lifetime. The nodes are randomly deployed in the field and the system has no previous knowledge of their position. To tackle this problem we use a mobile robot, that discovers the nodes around it and replaces the active nodes, whose energy is drained, by fully charged inactive nodes. In this paper we propose two localized algorithms, that can run on the robot and that decide, which nodes to replace. We simulate our algorithms and our findings show that all nodes that fail are replaced in a short period of time

Energy-Aware Adaptive Weighted Grid Clustering Algorithm for Renewable Wireless Sensor Networks

Wireless sensor networks (WSNs), built from many battery-operated sensor nodes are distributed in the environment for monitoring and data acquisition. Subsequent to the deployment of sensor nodes, the most challenging and daunting task is to enhance the energy resources for the lifetime performance of the entire WSN. In this study, we have attempted an approach based on the shortest path algorithm and grid clustering to save and renew power in a way that minimizes energy consumption and prolongs the overall network lifetime of WSNs. Initially, a wireless portable charging device (WPCD) is assumed which periodically travels on our proposed routing path among the nodes of the WSN to decrease their charge cycle time and recharge them with the help of wireless power transfer (WPT). Further, a scheduling scheme is proposed which creates clusters of WSNs. These clusters elect a cluster head among them based on the residual energy, buffer size, and distance of the head from each node of the cluster. The cluster head performs all data routing duties for all its member nodes to conserve the energy supposed to be consumed by member nodes. Furthermore, we compare our technique with the available literature by simulation, and the results showed a significant increase in the vacation time of the nodes of WSNs

Recharging <i>vs</i>. Replacing Sensor Nodes Using Mobile Robots for Network Maintenance

International audienceWireless sensor networks (WSNs) have been of very high interest for the research community since years, but the quest for deploying a self-sustained network and effectively prolonging its lifetime has not found a satisfactory answer yet. Two main approaches can be identified that target this objective: either "recharging'' or "replacing'' the sensor nodes that are running out of energy. Of particular interest are solutions where mobile robots are used to execute the above mentioned tasks to automatically and autonomously maintain the WSN, thus reducing human intervention.Recently, the progress in wireless power transfer techniques has boosted research activities in the direction of battery recharging, with high expectations for its application to WSNs. Similarly, also sensor replacement techniques have been widely studied as a means to provide service continuity in the network. Objective of this paper is to investigate the limitations and the advantages of these two research directions. Key decision points must be identified for effectively supporting WSN self-maintenance: (i) which sensor nodes have to be recharged/replaced; (ii) in which order the mobile robot is serving (i.e., recharging/replacing) the nodes and by following which path; (iii) how much energy is delivered to a sensor when recharged. The influence that a set of parameters, relative to both the sensors and the mobile robot, on the decisions will be considered. Centralized and distributed solutions are compared in terms of effectiveness in prolonging the network lifetime and in allowing network self-sustainability. The performance evaluation in a variety of scenarios and network settings offers the opportunity to draw conclusions and to discuss the boundaries for one technique being preferable to the other

Energy Management in Wireless Sensor Network Operations

In this dissertation, we develop and analyze effective energy management policies for wireless sensor networks in emerging applications. Existing methods in this area have primarily focused on energy conservation through the use of various communication techniques. However, in most applications of wireless sensor networks, savings in energy come at the expense of several performance parameters. Therefore it is necessary to manage energy consumption while being conscious of its effects on performance. In most cases, such energy-performance issues are specific to the nature of the application. Our research has been motivated by new techniques and applications where efficient energy-performance trade-off decisions are required. We primarily study the following trade-off cases: energy and node replacement costs (Case I), energy and delay (Case II), and energy and availability (Case III). We consider these trade-off situations separately in three distinct problem scenarios. In the first problem (Case I), we consider minimizing energy and node replacement costs in underwater wireless sensor networks for seismic monitoring application. In this case, we introduce mixed-integer programming (MIP) formulations based on a combined routing and node replacement policy approach and develop effective policies for large problem instances where our MIP models are intractable. In the second problem (Case II), we develop a Markov decision process (MDP) model to manage energy-delay trade-off in network coding which is a new energy-saving technique for wireless networks. Here we derive properties of the optimal policy and develop in- sights into other simple policies that are later shown to be efficient in particular situations. In the third problem (Case III), we consider an autonomous energy harvesting sensor network where nodes are turned off from time to time to operate in an “energy-neutral” manner. In this case, we use stochastic fluid-flow analysis to evaluate and analyze the availability of the sensor nodes under effective energy management policies. In each of the above problem cases, we develop analytical formulations, and derive and/or analyze policies that effectively manage the considered energy-performance trade-off. Overall, our analyses and solution methods make new contributions to both operations research and communication networking literature

A distributed algorithm for semantic collectors election in wireless sensors networks

Semantic clustering is a recent technique for saving energy in wireless sensor networks. Its mechanism of action consists in dividing the network into groups (clusters) formed by semantically related nodes and at least one semantic collector, which acts as a bridge between its internal nodes and the sink node. Since semantic collector nodes need to perform more tasks than normal nodes, they deplete their energy budget faster, so it is necessary to use efficient mechanisms for electing semantic collectors to prolong the network lifetime. Our hypothesis is that an effective choice of semantic collectors allows a longer network lifetime. To test it, we start from a previous work of the authors of this article and we propose an algorithm for electing semantic collectors in a distributed way based on a fuzzy inference engine. The inputs of the inference engine are the residual energy of nodes and their received signal strength indicator (RSSI). Simulation results confirm our hypothesis, since the algorithm provides (i) an improvement of 17.4% in relation to another proposal of the related literature, and (ii) a gain of 68.8% over the time life of the network’s original work.Keywords: Wireless Sensors Networks, Semantic Cluster, Semantic Collector Election

LEVERAGING PEER-TO-PEER ENERGY SHARING FOR RESOURCE OPTIMIZATION IN MOBILE SOCIAL NETWORKS

Mobile Opportunistic Networks (MSNs) enable the interaction of mobile users in the vicinity through various short-range wireless communication technologies (e.g., Bluetooth, WiFi) and let them discover and exchange information directly or in ad hoc manner. Despite their promise to enable many exciting applications, limited battery capacity of mobile devices has become the biggest impediment to these appli- cations. The recent breakthroughs in the areas of wireless power transfer (WPT) and rechargeable lithium batteries promise the use of peer-to-peer (P2P) energy sharing (i.e., the transfer of energy from the battery of one member of the mobile network to the battery of the another member) for the efficient utilization of scarce energy resources in the network. However, due to uncertain mobility and communication opportunities in the network, resource optimization in these opportunistic networks is very challenging. In this dissertation, we study energy utilization in three different applications in Mobile Social Networks and target to improve the energy efficiency in the network by benefiting from P2P energy sharing among the nodes. More specifi- xi cally, we look at the problems of (i) optimal energy usage and sharing between friendly nodes in order to reduce the burden of wall-based charging, (ii) optimal content and energy sharing when energy is considered as an incentive for carrying the content for other nodes, and (iii) energy balancing among nodes for prolonging the network lifetime. We have proposed various novel protocols for the corresponding applications and have shown that they outperform the state-of-the-art solutions and improve the energy efficiency in MSNs while the application requirements are satisfied

USCID water management conference

Presented at Meeting irrigation demands in a water-challenged environment: SCADA and technology: tools to improve production: a USCID water management conference held on September 28 - October 1, 2010 in Fort Collins, Colorado.Includes bibliographical references.The Colorado Satellite-Linked Water Resources Monitoring System: 25 years later -- Using state water law for efficient water use in the West -- On-farm strategies for deficit or limited irrigation to maximize operational profit potential in Colorado's South Platte Basin -- Economics of groundwater management alternatives in the Republican Basin -- Effects of policies governing water reuse on agricultural crops -- Flow calibration of the Bryan Canal radial gate at the United Irrigation District -- Considering canal pool resonance in controller design -- Synthetic canal lining evaluation project -- South Platte Ditch Company: demonstration flow monitoring and data collection project -- The case for ditch-wide water rights analysis in Colorado -- Bore wells: a boon for tail end users -- Irrigation efficiency and water users' performance in water management: a case study on the Heran distributary, Sanghar, Sindh, Pakistan -- Initiating SCADA projects in irrigation districts -- Use of GIS as a real time decision support system for irrigation districts -- Interaction of Advanced Scientific Irrigation Management (ASIM) with I-SCADA system for efficient and sustainable production of fiber on 10,360 hectares -- Improving irrigation system performance in the Middle Rio Grande through scheduled water delivery -- Cost-effective SCADA development for irrigation districts: a Nebraska case study -- Accomplishments from a decade of SCADA implementation in Idaho's Payette Valley -- Critical success factors for large scale automation experiences from 10,000 gates -- Mapping ET in southeastern Colorado using a surface aerodynamic temperature model -- Alfalfa crop coefficients developed using a weighing lysimeter in southeast Colorado -- Turfgrass ET from small lysimeters in northeast Colorado -- Monitoring turf water status with infrared thermometry -- Training tool for on-farm water management using heuristic simulation software -- Water production functions for high plains crops -- Assessment of economic and hydrologic impacts of reduced surface water supply for irrigation via remote sensing -- Developing corn regional crop coefficients using a satellite-based energy balance model (ReSET) in the South Platte River area of Colorado