Unbalanced Energy Research Articles

Dynamic Cluster Head Selection Method for Wireless Sensor Network

In view of the wireless sensor network clustering algorithm at home and abroad, the dynamic cluster head selection methods for a wireless sensor network are put forward in order to solve the problem of the unreasonable cluster head selection that may lead to the overlapping coverage and unbalanced energy consumption in the cluster communication. Experimental results show that this method balances the network node energy in two phases compared with the existed algorithms. The network lifetime is increased by 50%, higher than that of low energy adaptive clustering hierarchy (LEACH), and increased by 30%, higher than that of distribute energy-efficient clustering algorithm (DEEC); also the survival time of the network is longer than that of energy-balanced deterministic clustering algorithm and adaptive energy optimized clustering algorithm, achieving the effectiveness of the network energy consumption, and it has the longest network lifetime.

The holes problem in wireless sensor netwoks by using the available energy fairly

We consider the holes problem in wireless sensor netwoks by using the available energy fairly. The holes problem occurs when the available energy of some sensors are exhausted while others have significant energy. In this circumstance, ehile the total available energy of the network is high, the network is no longer working. Such a problem mainly happen due to unbalanced energy consumpsion in clustering and communication protocols. In this paper, we deal with this problem and propose an data aggregation algorithm based on the well-known clustering algorithm LEACH and tree construction mechanisms. In proposed method we consider the available energy of each sensor node as a weigthing parameter in clustering phase and tree-construction phase. Experimental results show the ability of the proposed method to increase the life time of the network and to distribute the energy uniformly along the network.

무선 에너지 전송 센서망에서의 공평성을 고려한 라우팅, 스케줄링, 전력 제어

최근들어 무선 센서망에서 센서 노드에 대한 전력 공급을 위한 무선 에너지 전송(radio frequency energy transfer: RFET)에 대한 관심이 높아지고 있다. 기존의 센서망에서는 센서 노드들의 에너지 소비를 줄이는 것이 중요한 연구주제 중의 하나였지만 무선 에너지 전송 센서망에서는 센서 노드들이 계속해서 에너지를 공급받을 수 있기 때문에 에너지 소모를 줄이는 것이 상대적으로 그리 중요한 이슈는 아니다. 하지만 센서 노드들 사이에 가용 에너지양의 차가 발생하게 되기 때문에 무선 에너지 전송 센서망의 성능 향상을 위해서는 이와 같은 성질을 고려하여 프로토콜을 설계하는 것이 중요하게 된다. 이에 본 논문에서는 이를 고려하여 무선 에너지 전송 무선 센서망에서 라우팅, 스케줄링, 전력제어 기법을 'Max-min'과 'Max-min fairness' 두가지의 관점에서 제안을 한다. 또한 본 논문에서 제안한 기법들이 무선 에너지 전송 센서망의 성능을 크게 향상시킴을 보이며 이와 더불어 'Max-min'과 'Max-min fairness' 사이의 차이에 대해서도 논의를 한다. Recently, radio frequency energy transfer (RFET) attracts more and more interests for powering sensor nodes in the wireless sensor network (WSN). In the conventional WSN, reducing energy consumption of sensor nodes is of primary importance. On the contrary, in the WSN with RFET, reducing energy consumption is not an important issue. However, in the WSN with RFET, the energy harvesting rate of each sensor node depends on its location, which causes the unbalanced available energy among sensor nodes. Hence, to improve the performance of the WSN with RFET, it is important to develop network protocols considering this property. In this paper, we study this issue with jointly considering routing, scheduling, and power control in the WSN with RFET. In addition, we study this issue with considering two different objectives: 'Max-min' with which we tries to maximize the performance of a sensor node having the minimum performance and 'Max-min fairness' with which we tries to achieve max-min fairness among sensor nodes. We show that our solutions can improve network performance significantly and we also discuss the differences between 'Max-min' and 'Max-min fairness'.

Determination of safe operation zone for an intermediate-temperature solid oxide fuel cell and gas turbine hybrid system

This paper proposes a novel approach to determine the safe zone for an intermediate-temperature solid oxide fuel cell and gas turbine hybrid system. The approach first ensures the compressor safety and then determines the overall system safe zone by analyzing the unsafe characteristics of main components. Safe performance of the hybrid system fueled with biomass gas at all operations is analyzed. Finally, the map of safe zone is obtained to avoid component malfunctions and system performance deterioration. Results show that the hybrid system can achieve a high efficiency 60.78%, which is an interesting reference for distributed power stations. Under all operations, two unbalanced energy zones exist, which may cause the short supply of O2 or fuel for electrochemical reaction. The lower the rotational speed of gas turbine, the narrower the zone of carbon deposition takes place in the reformer or turbine inoperation caused by too low inlet temperature. However, the phenomenon of fuel cell thermal cracking due to over-temperature will be exacerbated. System layout also affects component safety especially for the fuel cell. In the safe zone, the system has a characteristic of high efficiency and low load with low rotational speed, vice versa. In other words, the powers and load adjustment ranges both decrease with decreasing rotational speed whereas the efficiency increases, which peaks at 63.43%.

Lifespan prolonging location-wise predetermined deployment strategy for visual sensor networks

Visual sensor networks are widely used for surveillance, environmental monitoring and tracking. However, due to the funneling effect, visual sensor nodes (SNs) close to the sink tend to deplete their energy sooner than SNs farther away from the sink resulting in energy hole problem. This energy hole problem significantly increases the unbalanced energy usage among SNs and leads to premature decrease in network lifetime. Initially, we analyzed network lifetime and found number of relay nodes and their location has significant influence on limiting the energy hole problem and enhancement of network lifetime. Based on the principle of energy balancing, derived from this analysis, we develop a heterogeneous SNs deployment strategy leading to an enhancement of network lifetime. Exhaustive simulation is performed, primarily to measure the extent of achieving our design goal of limiting memory and computation overheads, enhancing network lifetime while attaining energy balancing. We also measure the effect of placement errors on the performance and show that even in presence of placement error the performance is comparable with the other competing scheme. Further, the simulation results show that our scheme does not compromise with other network performance metrics such as end-to-end delay and throughput while achieving the design goal. Finally, all the results are compared with a competing scheme and the results confirm our scheme׳s supremacy in terms of both design performance metrics as well as network performance metrics.

Balancing Energy Consumption in Wireless Sensor Networks Using Biogeography Based Optimization Algorithm and Fuzzy Approach

Extending the lifetime of the energy constrained wireless sensor networks is a crucial challenge in wireless sensor networks (WSNs) research. When designing a WSN infrastructure Resource limitations have to be taken into account. The inherent problem in WSNs is unbalanced energy consumption, characterized by multi hop routing and a many-to-one traffic pattern. This uneven energy dissipation can significantly reduce network lifetime. This paper proposes a new routing method for WSNs to extend network lifetime using a combination of a fuzzy approach and Biogeography Based Optimization (BBO) algorithm. Determine an optimal routing path from the source to the destination by favoring the highest remaining battery power, and the lowest distance (minimum number of hops) to the sink. To demonstrate the effectiveness of the proposed method in terms of balancing energy consumption and maximization of network lifetime, we compare our approach with the BBO search algorithm and fuzzy approach using the same routing criteria. Simulation results demonstrate that the network lifetime is significantly increased by employing the proposed routing method.

Energy consumption model for density controlled divide-and-rule scheme for energy efficient routing in wireless sensor networks

In wireless sensor networks WSNs, sensor nodes nodes are equipped with limited energy source. Therefore, efficient energy utilisation of nodes has become a hot research area in WSNs. In this paper, we introduce a new routing technique for WSNs in which, we solve the problem of unbalanced energy utilisation, which causes energy and coverage holes in WSNs. Deployment area is divided into subareas; each subarea logically represents a static cluster. Dividing network field into subfields helps to control coverage hole problem whereas, static clustering helps to avoid energy hole problem. Mathematical formulation of the proposed work is provided to analyse and verify our technique. Simulation results show that our technique balances energy utilisation of the network.

An Improved GPSR Algorithm Based on Energy Gradient and APIT Grid

We investigate GPSR algorithms of WSN and propose an improved routing algorithm based on energy gradient and APIT grid to solve the problem of high and unbalanced energy consumption of GPSR. In GPSR, network uses greedy algorithm and right-hand rule to establish routing paths, and the path keeps running till some nodes within the path are invalid because energy is exhausted, which would lead to the high energy consumption of some nodes in the path and the low energy consumption of others nearby the nodes not in the path as well as bringing high and unbalanced energy consumption of the network. Regarding these problems, we use APIT localization algorithm and APIT grid to query and establish routing paths and establish the corresponding energy gradient when messages are transmitted along the routing paths. When some nodes are approaching the threshold status, we use right-hand rule and recursion greedy algorithm in advance to plan a new routing path towards the target area. When query messages arrive at the event area, the network uses a different method to transmit data according to the density of sensor nodes. Simulation experiments show that the improved routing algorithm is capable of reducing the energy consumption of network and extending the lifecycle of network.

An Energy-Efficient Clustering Algorithm for Edge-Based Wireless Sensor Networks

To employee clustering algorithms in multi-hop data forwarding mechanism, Hot-spot problem will cause unbalanced energy dissipation among the cluster heads in the network. Unequal clustering technique promotes even energy dissipation only in inter-cluster communications not in intra-cluster communication. An Energy-efficient Clustering Algorithm (EECA) is introduced to avoid these problems in edge-based wireless sensor networks. The main aim of the presented algorithm is to avoid hot-spot problem by balancing uniform energy utilization among networked cluster heads. EECA constructs uneven size clusters in different levels to enable uniform energy expenditure among cluster heads. Data delivery is one of the important and unavoidable energy consuming operation in any sensor networks. To balance energy consumption load among data transmission routes, a multi-hop data forwarding protocol is introduced. Here, source node selects a relaying node who has minimum hop count to base station with more energy reserves and relayed less number of packets. Extensive experimental results prove that the presented algorithm overcome the congestion problem in the network by uniform distribution of energy consumption and enhances network's lifetime.

Analysis of food advertising to children on Spanish television: probing exposure to television marketing.

IntroductionWe aimed to assess longitudinal changes in television (TV) food advertising during 2013 compared to 2007, measuring children's exposure to healthy and unhealthy advertisements, after the new European and Spanish Public Health laws published in 2011.Material and methodsTwo thematic channels for children (TC), and 2 generalist channels (GC) for all ages were recorded, between April and May 2013, on 2 week and 2 weekend days. Food advertisements were classified as core (CFA) (nutrient dense, low energy), non-core (NCFA) (unbalanced energy profile or high in energy), or others (OFA) (supermarkets and special food).ResultsOne thousand two hundred sixty-three food advertisements were recorded (TC: 579/GC: 684) in 2013. NCFA were the most shown (54.9%) in the regular full day TV programming (p < 0.001). In 2013, children watching GC had a higher relative risk of being exposed to fast food advertisements than when watching TC (RR = 2.133, 95% CI: 1.398–3.255); CFA were broadcast most frequently in 2013 (GC: 23.7%; and TC: 47.2%) vs. 2007 (TC: 22.9%) (p < 0.001). The proportion of broadcasting between NCFA/CFA and OFA food advertisements in children's peak time slots was higher on TC (203/162) during 2013 than on GC (189/140), and significantly higher than that shown on TC in 2007 (180/36, p < 0.001).ConclusionsBroadcasting of unhealthy TV food advertising on TC is lower today than six years ago; but, children's exposure to TV advertising of unhealthy food is worrying in Spain, and there is more exposure to unhealthy than healthy food by TV. Watching GC in 2013 had higher risk of being exposed to fast food advertisements than watching TC.

A routing algorithm for WSNs based on uneven clustering and entropy theory

An energy efficient routing algorithm is the major concern in wireless sensor networks(WSNs),especial-ly the hot spot,because of unbalanced energy consumption. Based on uneven clustering and entropy theory,a kindof improved routing algorithm is proposed for solving that problem. In the process of cluster head election and com-petition radius calculation,node energy,density and distance to BS are considered to effectively balance energy con-sumption and prolong the life cycle of cluster head nodes. Meanwhile the hybrid rules of single-hop and multi-hoprouting is adopted to reduce the energy consumption among clusters. Introducing fusion weight coefficient,informa-tion entropy mechanism is used for reducing the uncertainty and improving the efficiency of data fusion. Simulationresults show that compared with LEACH,EEUC and EBUCA,the new algorithm can balance energy consumptionand prolong the life cycle of wireless sensor networks.

PEGASIS : Power-Efficient Gathering in Sensor Information Systems

Sensor network consisting of nodes with limited battery power and wireless communications are deployed to collect useful information from the field. The main idea in PEGASIS is for each node to receive from and transmit to close neighbors and take turns being the leader for transmission to the BS. This approach distributes the energy load evenly among the sensor nodes in the network. Sensor nodes are randomly deployed in the sensor field, and therefore, the i th node is at a random location. The nodes will be organized to form a chain, which can either be accomplished by the sensor nodes themselves using a greedy algorithm. The algorithm to resolve the unbalanced energy consumption problem caused by long distance data transmission of some nodes in a chain formed by the greedy algorithm.

Evaluation of Water Use Efficiency Derived from MODIS Products against Eddy Variance Measurements in China

Water use efficiency (WUE) is a useful indicator to illustrate the interaction of carbon and water cycles in terrestrial ecosystems. MODIS gross primary production (GPP) and evapotranspiration (ET) products have been used to analyze the spatial and temporal patterns of WUE and their relationships with environmental factors at regional and global scales. Although MODIS GPP and ET products have been evaluated using eddy covariance flux measurements, the accuracy of WUE estimated from MODIS products has not been well quantified. In this paper, we evaluated WUE estimated from MODIS GPP and ET products against eddy covariance measurements of GPP and ET during 2003–2008 at eight sites of the Chinese flux observation and research network (ChinaFLUX) and conducted sensitivity analysis to investigate the possible key contributors to the bias of MODIS products. Results show that MODIS products underestimate eight-day water use efficiency in four forest ecosystems and one cropland ecosystem with the bias from −0.36–−2.28 g·C·kg−1 H2O, while overestimating it in three grassland ecosystems with the bias from 0.26–1.11 g·C·kg−1 H2O. Mean annual WUE was underestimated by 14%–54% at four forest sites, 45% at one cropland site and 7% at an alpine grassland site, but overestimated by 66% and 9% at a temperate grassland site and an alpine meadow site, respectively. The underestimation of WUE by MODIS data results from underestimated GPP and overestimated ET at four forest sites, while MODIS WUE values are significantly overvalued mainly due to underestimated ET in the three grassland ecosystems. The maximum light use efficiency and fraction of photosynthetically-active radiation (FPAR) were the two most sensitive factors to the estimation of WUE derived from the MODIS GPP and ET algorithms. The error in meteorological data partly caused the overestimation of ET and accordingly underestimation in WUE in subtropical and tropical forests. The bias of MODIS-produced WUE was also derived from the uncertainties in eddy flux data due to gap-filling processes and unbalanced surface energy issue. Their contributions to the uncertainty in estimated WUE at both eight-day and annual scales still need to be further quantified.

Mobility assisted data gathering with solar irradiance awareness in heterogeneous energy replenishable wireless sensor networks

Wireless sensor networks adopting static data gathering may suffer from unbalanced energy consumption due to non-uniform packet relay. Although mobile data gathering provides a reasonable approach to solving this problem, it inevitably introduces longer data collection latency due to the use of mobile data collectors. In the meanwhile, energy harvesting has been considered as a promising solution to relieve energy limitation in wireless sensor networks. In this paper, we consider a joint design of these two schemes and propose a novel two layer heterogeneous architecture for wireless sensor networks, which consists of two types of nodes: sensor nodes which are static and powered by solar panels, and cluster heads that have limited mobility and can be wirelessly recharged by power transporters. Based on this network architecture, we present a data gathering scheme, called mobility assisted data gathering with solar irradiance awareness (MADG-SIA), where sensor nodes are clustered around cluster heads that adaptively change their positions according to solar irradiance, and the sensing data are forwarded to the data sink by these cluster heads working as data aggregation points. We evaluate the performance of the proposed scheme by extensive simulations and the results show that MADG-SIA provides significant improvement in terms of balancing energy consumption and the amount data gathered compared to previous work.

Analysis of Base Station Assisted Novel Network Design Space for Edge-based WSNs

Limited and constrained energy resources of wireless sensor network should be used wisely to prolong sensor nodes lifetime. To achieve high energy efficiency and to increase wireless sensor network lifetime, sensor nodes are grouped together to form clusters. Organizing wireless sensor networks into clusters enables the efficient utilization of limited energy resources of the deployed sensor nodes. However, the problems of unbalanced energy consumption exist in intra and inter cluster communication, and it is tightly bound to the role and the location of a sensor nodes and cluster heads in the network. Also, clustering mechanism results in an unequal load distribution in the network. This paper presents an analytical and conceptual model of Energy- efficient edge-based network partitioning scheme proposed for wireless sensor networks. Also, it analyzes different network design space proposed for wireless sensor networks and evaluates their performance. From the experimental results it is observed that, with proper network organization mechanism, sensor network resources are utilized effectively to elevate network lifetime.

Energy-Efficient Data Reporting Strategy (EDRS) for Multilayer Clustering WSN

Energy consumption is one of the key issues in data reporting in wireless sensor networks (WSNs). Unbalanced energy consumption that characterized by many-to-one traffic pattern results in uneven energy dissipation among sensors which consequently reduces network lifetime significantly. In event tracking and monitoring system with direct constant data reporting of the ongoing event, energy depletion of sensors in specific region in the network where the event takes place is unavoidable. However, energy depletion can be balanced if sensors are clustered into groups and sensed data are transmitted through multi-hop towards the Based Station (BS) over Cluster Heads (CHs) with different transmission ranges capabilities. CHs should have the knowledge that enables them to know how many packets should be transmitted either in multi-hop or directly in order to avoid the fast energy drain of sensors near the BS. The knowledge can be provided by the BS based on the region where CHs are located. In this paper, we propose an energy-efficient strategy for reporting the sensed data in multilayer clustered WSN. The proposed strategy maximizes network lifetime through balancing energy consumption by using dual transmission range for forwarding pre-defined number of data packets according to the network condition. Experimental simulations have been performed to validate the proposed strategy

Energy-efficient topology control algorithm for maximizing network lifetime in wireless sensor networks with mobile sink

Uneven energy consumption is an inherent problem in wireless sensor networks characterized by multi-hop routing and many-to-one traffic pattern. Such unbalanced energy dissipation can significantly reduce network lifetime. In this paper, we study the problem of prolonging network lifetime in large-scale wireless sensor networks where a mobile sink gathers data periodically along the predefined path and each sensor node uploads its data to the mobile sink over a multi-hop communication path. By using greedy policy and dynamic programming, we propose a heuristic topology control algorithm with time complexity O(n(m+nlogn)), where n and m are the number of nodes and edges in the network, respectively, and further discuss how to refine our algorithm to satisfy practical requirements such as distributed computing and transmission timeliness. Theoretical analysis and experimental results show that our algorithm is superior to several earlier algorithms for extending network lifetime.

Morphological allometry and intersexuality in horsehair-worm-infected mantids, Hierodula formosana (Mantodea: Mantidae).

Parasitic castration is a strategy used by parasites to minimize damage to the host by consuming its reproductive system, which results in the morphological alteration of the host. We determined that the forewing shape and density of the antennal sensilla of field-collected adult male mantids (Hierodula formosana), infected by horsehair worms (Chordodes formosanus) was partially feminized (intersexuality), and both male and female mantids infected by horsehair worms exhibited allometric changes in their wings and walking legs. In addition, the testes of most infected male adults disappeared or reduced in size, whereas the number of ovarioles in infected female adults was unaffected. The infection mainly influenced the structures related to host reproduction and locomotion, suggesting unbalanced energy exploitation and the reduction of parasitic virulence. In addition, the intersexuality of infected male adults indicated that sexual differentiation in insects, which researchers have considered to be an autonomous process, was influenced by the infection. The similarity of the antennae of infected male adults with those of last-instar female nymphs suggested that parasitic juvenilization may cause such feminization, but the mechanism of parasitic influence on insect sex characteristics should be studied further.

Game Theory Based Cooperative MIMO Routing Scheme for Lifetime Enhancement of WSN

The lifetime of wireless sensor network (WSN) is reduced due to the impact caused by channel fading, interference and unbalanced energy consumption. The node’s energy is wasted due to uneven energy consumption for various processes. Communicating the data from source to sink node will consume more power compared to data sensing and processing etc. The channel fading is mitigated through spatial diversity techniques to reduce the energy required for data communication. Spatial diversity can be obtained by using multiple cooperative nodes both at the transmitter as well as the receiver. The cooperative multiple input multiple output (C-MIMO) technique is used to improve the communication performance of WSNs. An efficient cluster based routing protocol is called efficient energy consumption protocol (EECP) which involves fixed clusters and randomized weighted algorithm for cluster head selection to reduce the energy consumption efficiently. The energy consumption of the node is reduced in WSN by incorporating the CMIMO in EECP routing protocol using coalition game. In this paper the game theory based EECP routing protocol with MIMO technology is used to achieve higher energy savings. Simulation results of proposed game theory based CMIMO shows that great energy savings can be achieved and also prolong the lifetime of the network.

An adaptive MR-CT registration method for MRI-guided prostate cancer radiotherapy

Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ cm−3, and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume during the transformation between the MR and CT images and improves the accuracy of the B-spline registrations in the prostate region. The approach will be valuable for the development of high-quality MRI-guided radiation therapy.