Unbalanced Energy Research Articles

Balance the Energy Consumption of Geographic Hashing Location Service in Wireless Sensor and Actor Networks

Location service is an efficient solution to handle actor mobility in wireless sensor and actor networks. Geographic hashing location service (GHLS) is a flat hashing-based protocol which has better energy efficiency than other location service protocols. Nevertheless, GHLS suffers from unbalanced energy consumption due to the fixed hashed region. In this paper, we propose a new protocol termed as GHLS-R2 to achieve load balance in two aspects: location server rotation and energy-aware geographic routing. Simulation results show that GHLS-R2 protocol can effectively balance the energy consumption, and hence prolong the network lifetime significantly.

EELCM: An Energy Efficient Load-Based Clustering Method for Wireless Mobile Sensor Networks

Clustering techniques are employed to optimize energy consumption corresponding to different node activities and thus to conserve the limited energy of the sensor nodes. Different locations and different loads cause unbalanced energy consumption in the network nodes, consequently, the network lifetime is shortened. In this paper, a clustering method to improve energy conserving and to balance the energy consumption of cluster head is proposed. The area and the dimensions of the clusters are calculated by the algorithm in such a way that the rates of energy consumption of all the cluster heads be equalized. Also, all the intra-cluster communications are performed in single hop manner. The proposed approach presents a solution for the challenge of short lifetime of heavy burdened cluster heads around the base station. A straightforward routing scheme is proposed corresponding to the proposed clustering model to deliver the data sensed by cluster members to the base station. The performance evaluations indicate that the proposed method not only prolongs more effectively the lifetime of both cluster heads and cluster members than the other works, but also, outperforms them in balancing the energy level of the cluster heads. Consequently, the duration of activity of the cluster members in different clusters is also balanced and prolonged. Moreover, the proposed method improves the network throughput, comparing with the other works.

Deep Brain Stimulation for Obesity: A Review and Future Directions.

The global prevalence of obesity has been steadily increasing. Although pharmacotherapy and bariatric surgeries can be useful adjuvants in the treatment of morbid obesity, they may lose long-term effectiveness. Obesity result largely from unbalanced energy homeostasis. Palatable and densely caloric foods may affect the brain overlapped circuits involved with homeostatic hypothalamus and hedonic feeding. Deep brain stimulation (DBS) consists of delivering electrical impulses to specific brain targets to modulate a disturbed neuronal network. In selected patients, DBS has been shown to be safe and effective for movement disorders. We review all the cases reports and series of patients treated with DBS for obesity using a PubMed search and will address the following obesity-related issues: (i) the hypothalamic regulation of homeostatic feeding; (ii) the reward mesolimbic circuit and hedonic feeding; (iii) basic concepts of DBS as well as the rationale for obesity treatment; (iv) perspectives and challenges in obesity DBS. The small number of cases provides preliminary evidence for the safety and the tolerability of a potential DBS approach. The ventromedial (n = 2) and lateral (n = 8) hypothalamic nuclei targets have shown mixed and disappointing outcomes. Although nucleus accumbens (n = 7) targets were more encouraging for the outcomes of body weight reduction and behavioral control for eating, there was one suicide reported after 27 months of follow-up. The authors did not attribute the suicide to DBS therapy. The identification of optimal brain targets, appropriate programming strategies and the development of novel technologies will be important as next steps to move DBS closer to a clinical application. The identification of electrical control signals may provide an opportunity for closed-loop adaptive DBS systems to address obesity. Metabolic and hormonal sensors such as glycemic levels, leptin, and ghrelin levels are candidate control signals for DBS. Focused excitation or alternatively inhibition of regions of the hypothalamus may provide better outcomes compared to non-selective DBS. Utilization of the NA delta oscillation or other physiological markers from one or multiple regions in obesity-related brain network is a promising approach. Experienced multidisciplinary team will be critical to improve the risk-benefit ratio for this approach.

A PSO-Based Uneven Dynamic Clustering Multi-Hop Routing Protocol for Wireless Sensor Networks.

Since wireless sensor networks (WSNs) are powered by energy-constrained batteries, many energy-efficient routing protocols have been proposed to extend the network lifetime. However, most of the protocols do not well balance the energy consumption of the WSNs. The hotspot problem caused by unbalanced energy consumption in the WSNs reduces the network lifetime. To solve the problem, this paper proposes a PSO (Particle Swarm Optimization)-based uneven dynamic clustering multi-hop routing protocol (PUDCRP). In the PUDCRP protocol, the distribution of the clusters will change dynamically when some nodes fail. The PSO algorithm is used to determine the area where the candidate CH (cluster head) nodes are located. The adaptive clustering method based on node distribution makes the cluster distribution more reasonable, which balances the energy consumption of the network more effectively. In order to improve the energy efficiency of multi-hop transmission between the BS (Base Station) and CH nodes, we also propose a connecting line aided route construction method to determine the most appropriate next hop. Compared with UCCGRA, multi-hop EEBCDA, EEMRP, CAMP, PSO-ECHS and PSO-SD, PUDCRP prolongs the network lifetime by between 7.36% and 74.21%. The protocol significantly balances the energy consumption of the network and has better scalability for various sizes of network.

Research on low energy consumption distributed fault detection mechanism in wireless sensor network

Wireless sensor network is an important technical support for ubiquitous communication. For the serious impacts of network failure caused by the unbalanced energy consumption of sensor nodes, hardware failure and attacker intrusion on data transmission, a low energy consumption distributed fault detection mechanism in wireless sensor network (LEFD) is proposed in this paper. Firstly, the time correlation information of nodes is used to detect fault nodes in LEFD, and then the spatial correlation information is adopted to detect the remaining fault nodes, so as to check the states of nodes comprehensively and improve the efficiency of data transmission. In addition, the nodes do not need to exchange information with their neighbor nodes in the initial detection process since LEFD adopts the data sensed by node itself to detect some types of faults, thus reducing the energy consumption of nodes effectively. Finally, LEFD also considers the nodes that may have transient faults. Performance analysis and simulation results show that the proposed detection mechanism can improve the transmission performance and reduce the energy consumption of network effectively.

A novel residual energy‐based distributed clustering and routing approach for performance study of wireless sensor network

SummaryNon‐uniform energy consumption during operation of a cluster‐based routing protocol for large‐scale wireless sensor networks (WSN) is major area of concern. Unbalanced energy consumption in the wireless network results in early node death and reduces the network lifetime. This is because nodes near the sink are overloaded in terms of data traffic compared with the far away nodes resulting in node deaths. In this work, a novel residual energy–based distributed clustering and routing (REDCR) protocol has been proposed, which allows multi‐hop communication based on cuckoo‐search (CS) algorithm and low‐energy adaptive‐clustering–hierarchy (LEACH) protocol. LEACH protocol allows choice of possible cluster heads by rotation at every round of data transmission by a newly developed objective function based on residual energy of the nodes. The information about the location and energy of the nodes is forwarded to the sink node where CS algorithm is implemented to choose optimal number of cluster heads and their positions in the network. This approach helps in uniform distribution of the cluster heads throughout the network and enhances the network stability. Several case studies have been performed by varying the position of the base stations and by changing the number of nodes in the area of application. The proposed REDCR protocol shows significant improvement by an average of 15% for network throughput, 25% for network scalability, 30% for network stability, 33% for residual energy conservation, and 60% for network lifetime proving this approach to be more acceptable one in near future.

Sleep Scheduling for Unbalanced Energy Harvesting in Industrial Wireless Sensor Networks

Energy harvesting from ambient energy sources has gained increased attention due to its advantage of less maintenance and for removing the dependency on batteries in IWSNs. However, due to the dynamic nature of ambient energy sources and the position of harvesting nodes, energy-harvesting is not always available, resulting in unbalanced energy-harvesting in IWSNs. Although, some battery operated nodes are used, the limited lifetime problem still exists due to the non-harvesting nodes. In this article, we propose a scheme that combines the advantages of energy-harvesting and sleep-scheduling in hybrid solar energy-harvesting IWSNs and non-harvesting nodes. We present a model of the harvesting-node using a three-state Markov chain. The proposed harvest-use-store type architecture aims to guarantee an energy-neutral condition to avoid energy harvesting nodes from early energy exhaustion. The proposed approach allows to wake up a few more non-harvesting nodes to handle network coverage and connectivity during less-energy-harvesting intervals. Similarly, non-harvesting nodes are allowed to sleep by increasing the default transmission range of the solar-harvesting nodes during higher energy harvesting intervals prolonging network lifetime.

The Physical Origin of Diffusion Induced Grain Boundary Migration Explored by Atomistic Simulations

Diffusion-induced grain boundary motion (DIGM) is the phenomenon of normal grain boundary migration caused by the lateral diffusion of solutes along it. Despite its technological importance and the fact that DIGM has been firstly observed and studied since 1970, the physical origin of DIGM still remains largely hypothetical. In this work, a comprehensive approach by combining two atomistic simulation techniques, i.e., the synthetic driving force method and the interface random walk method is developed to quantify the driving forces that operate during DIGM. It is found that the driving force that initiates DIGM is quantitatively consistent with that arising from coherency strain energy, which proves that a major driving force of DIGM originates from unbalanced coherency strain energy across the boundary due to the non-uniform distribution of solute atoms. The simulation results also show that segregation plays an important role in promoting DIGM once GB is in close contact with the solute atoms. All observations made during the simulations are supported by the atomic configurations and graphical analysis at different stages of the process. It is hoped that this study sheds some light and provides a clearer picture of DIGM after more than a decade’s stagnation in this field.

A New Technology Applied to Power System Stability Control: Phase Sequence Exchange Technology

AC transmission systems are often affected by stability issues. During the design phase of such systems, their ability to cope with the various kinds of disturbance is taken into consideration, however, sudden large disturbances may still result in power angle instability, which can greatly increase the risk of an overarching power system break down. Therefore, the development of a safety protection system is a priority in the field of power system construction. In response to this problem, we propose a new exploratory solution strategy - Phase Sequence Exchange Technology (PSET). The PSET can be summarized as follows: when the power angle of an equivalent dual power supply system swings to a suitable angle between 90° and 180°, disconnect the primary side phase of the communication line by power electronic equipment and causing the swift misalignment of the connection. The A, B, C three-phase sequence then, connects to the three-phase C, A, B sequence. The PSET instantaneously realizes this change and reduces the power angle by 120°, pulling the formerly increasing power angle back to a smaller angle and preventing the system from becoming imbalanced. In this paper, the mechanism which improves the stability of the PSET is explained by using the equal area rule. The threshold of the PSET work angle is determined by the energy function and the unbalanced potential energy in the system that can be effectively reduced by the PSET. Based on these findings, the phase trajectory method is used to determine the evaluation criteria for the PSET. This allows us to establish whether the PSET is effective by examining the state of the system after the fault is removed. Finally, an example is given in order to verify the effectiveness of the PSET and to prove that PSET is able to prevent the system from becoming imbalanced while still maintaining its structural integrity.

Influence of stiffness gradient on friction between graphene layers

According to the molecular dynamics simulations and the mechanism of energy dissipation of nanofriction, we construct a model system with a flake sliding in commensurate configuration on a monolayer suspended graphene anchored on a bed of springs. The system is to analyze the contributions of different regions (T1-T7) of the graphene flake to friction force, with the substrate characterized by different stiffness gradients and midpoint stiffness.</br>The results indicate that the soft region of contact (T1) always contributes to the driving force, whereas the hard region (T7) leads to the biggest friction force on all column atoms of the flake. Moreover, as the support stiffness increases, when the stiffness gradient and the midpoint stiffness are equal to 1.34 nN/nm<sup>2</sup> and 12 nN/nm, respectively, the contribution ratio of T7 to the total friction increases from 33% to 47%, which is approximately 4-15 times greater than those of each column atoms in T3-T6. The results also indicate that the energy barrier decreases with the increase of support stiffness along the stiffness gradient direction of the substrate, which induces the resistance forces on the relative motion to decrease. Meanwhile, the amplitude of the thermal atomic fluctuation is higher in the softer region while lower in the harder one. This difference in amplitude leads to the considerable potential gradient that ultimately causes the driving force. Finally, for a given point at the end of the flake (T1 or T7), the intensity of the van der Waals potential field is mainly determined by the nearest substrate atoms at that point. Part of these nearest atoms lie inside the contact region while the others do not. Consequently, the thermal vibration of the atoms inside the contact region is different from that of the atoms outside the confinement. The different thermal vibrations induce the greater edge barriers. In addition, T1 lies in the soft edge region and T7 in the hard one. As a result, the normal deformations of these two regions are always different, and therefore they also generate the driving force.</br>At these points, the results reported here suggest that the friction force in each contact region is caused by the coupling of the energy barrier and the elastic deformation between the graphene surfaces. The former contribution, i.e.the energy barrier, includes the interfacial potential barrier in commensurate state which is against the sliding of the surfaces with respect to each other, and the potential gradient caused by the different vibration magnitudes of the substrate atoms against the different spring stiffness in the direction of stiffness gradient. The latter contribution, i.e. the elastic deformation, is the unbalanced edge energy barrier resulting from the asymmetrical deformation and the different degrees of freedom between the edge atoms of the slider and atoms inside and outside the contact area of the substrate. Results of this paper are expected to be able to provide theoretical guidance in considering the influence of stiffness gradient on friction between commensurate surfaces and in designing the nanodevices.

Mobile Multi-Sink Nodes Path Planning Algorithm Concerned With Energy Balance in Wireless Sensor Networks

In order to relieve the problem of unbalanced energy consumption of sensor nodes near the base station in the wireless sensor network, this paper proposes a mobile multi-sink nodes path planning algorithm with energy balance (hexHPSO). An optimization model is established by considering the energy consumption of each group, network lifetime, and movement path of the mobile sink nodes. Meanwhile, a hybrid positive and negative particle swarm optimization algorithm (HPNPSOA) is proposed to solve the optimization model to obtain a path with optimal grid traversal order and optimal parking position. Compared with the DOSM algorithm, GLRM algorithm, and RWM algorithm, the hexHPSO algorithm improves the network lifetime by 68%. The experimental results show that the hexHPSO algorithm can effectively balance the energy consumption, alleviate hotspot phenomenon, and extend the network lifetime.

Two-Hop Neighborhood Information Joint Double Broadcast Radius for Effective Code Dissemination in WSNs

With the development of software-defined network (SDN) technology, sensor nodes can update soft codes to enable themselves to have new functions so as to make wireless sensor network (WSN) full of new vitality. However, how to spread the new code to every node in the network quickly and energy-efficient is a challengeable issue. In this paper, a Two-hop Neighborhood Information joint Double Broadcast Radius (TNI-DBR) scheme is proposed to disseminate the codes in duty cycle-based WSNs in a fast and energy-efficient style. The main innovations of this paper are as follows. The TNI-DBR scheme makes full use of the unbalanced energy consumption of the sensor network in the process of data collection and doubles the broadcast radius in the area with redundant energy so that more nodes can receive the new code in one broadcast and the broadcast range is further, which can reduce the delay of code dissemination effectively. Different from the conventional code dissemination schemes that select broadcasting nodes according to the information of the one-hop neighbors, in the TNI-DBR scheme, an $O(n)$ two-hop neighbor information exchange algorithm is proposed to obtain the duty cycle information of the two-hop neighbors. The TNI-DBR scheme selects the best broadcasting nodes based on information in the range of two-hop neighbors to enlarge the number of active nodes and reduce the time required for code dissemination. Sufficient theoretical analysis and experimental results show that the TNI-DBR scheme can significantly optimize the performance of code dissemination. Compared to previous schemes, the delay of code dissemination can be reduced by 43.09%~78.69%, the number of broadcasts can be reduced by 44.51%~86.18%, and the energy utilization ratio is improved by about 24.5%.

An Energy-Optimization Clustering Routing Protocol Based on Dynamic Hierarchical Clustering in 3D WSNs

An important issue in the three-dimensional (3D) wireless sensor networks (WSNs) is sensor energy optimization. To alleviate this issue, we introduce a new 3D spherical network structure model, and by combining the original energy consumption model to construct a new method to determine the optimal number of clusters and balance the total energy consumption. Since the different sizes of the clusters are generated by traditional hierarchical clustering, it causes unbalanced energy consumption in the network. To alleviate this problem, we adopt an improved dynamic hierarchical clustering method and implement two strategies that include the following three contributions: the introduction of the distance similarity index to get a better clustering, a double cluster head (CH) strategy to reduce the load of a cluster head in a large cluster, and a node dormancy mechanism to balance the energy consumption of the network. In addition, we also propose the optimal cluster-head function to select the CH of each cluster in each round, and the optimal cluster-head function is constructed based on the residual energy and positions of the nodes. Finally, to optimize the CH election strategy, several parameters of the optimal cluster-head function are determined according to the network structure. The simulation results show that our routing protocol is more robust compared with four other protocols, which is of great significance for the application in 3D environment monitoring.

Hybrid renewable energy systems for household ancillary services

The development of Hybrid Renewable Energy Systems (HRES) under the Distributed Generation (DG) paradigm is the support for substantial reduction of CO2 emissions and for greater penetration of renewable energy sources. The performance and reliability of HRES depend on the interaction between demand, generation, storage and the energy management strategy. In this study a comparison between two different control strategies is presented. In particular, a Rule Based Control (RBC) strategy has been compared with a more sophisticated Model Predictive Control (MPC) for the management of an HRES for residential applications.Results show that a HRES operating in a connected mode has potential to support grid balancing actions giving economic benefits for both end-users and providers. Moreover, the MPC strategy gives a potential reduction of the unbalanced energy exchange with the grid and a more efficient use of the HRES components. The MPC strategy allows thus for a more effective use of renewable sources if compared with a conventional RBC for a Microgrid of same size, thus allowing for a greater penetration of renewable sources into the energy mix, or equivalently, toward downsizing of storage and programmable source subsystems with economic benefits.

Inter- and intra-cluster movement of mobile sink algorithms for cluster-based networks to enhance the network lifetime

Due to limited resources of the sensor nodes energy efficiency is an important performance metric to evaluate the wireless sensor networks (WSN). In cluster-based WSNs, the cluster heads (CH) located around base station (BS) consume more energy and exhaust their energy supplies faster than other ones which leads to energy hole problem and premature network death. Furthermore, single-hop transmission manner is usually applied for intra-cluster communication, therefore the member nodes (MN) located farther away from CHs die sooner than other MNs, which leads to coverage holes and reduce the network performance. In this paper, we propose mobile sink (MS) based inter- and intra-cluster routing algorithms. The first algorithm aims to solve the unbalanced energy consumption of CHs, which results in enhanced network lifetime. Likewise, the goal of the second algorithm is to balance the energy consumption of MNs, which results in improved coverage time of the network. In the proposed mechanism, MSs move along clusters and stay in each cluster for a limited sojourn time calculated via first algorithm. Then, the optimal sojourn positions of MSs in the clusters are determined via second algorithm. Simulation results reveal that the proposed algorithms enhance the network performance in terms of different performance evaluation metrics.

Fault Detection Modelling and Analysis in a Wireless Sensor Network

For the serious impacts of network failure caused by the unbalanced energy consumption of sensor nodes, hardware failure, and attacker intrusion on data transmission, a low-energy-consumption distributed fault detection mechanism in a wireless sensor network (LEFD) is proposed in this paper. The time correlation information of nodes is used to detect fault nodes in LEFD firstly, and then the spatial correlation information is adopted to detect the remaining fault nodes, so as to check the states of nodes comprehensively and improve the efficiency of data transmission. In addition, the nodes do not need to exchange information with their neighbor nodes in the detection process since LEFD uses the data sensed by the node itself to detect some types of faults, thus reducing the energy consumption of nodes effectively. Performance analysis and simulation results show that the proposed detection mechanism can improve the transmission performance and reduce the energy consumption of the network effectively.

A Type of Annulus-Based Energy Balanced Data Collection Method in Wireless Rechargeable Sensor Networks.

With the increasing number of ubiquitous terminals and the continuous expansion of network scale, the problem of unbalanced energy consumption in sensor networks has become increasingly prominent in recent years. However, a node scheduling strategy or an energy consumption optimization algorithm may be not enough to meet the requirements of large-scale application. To address this problem a type of Annulus-based Energy Balanced Data Collection (AEBDC) method is proposed in this paper. The circular network is divided into several annular sectors of different sizes. Nodes in the same annulus-sector form a cluster. Based on this model, a multi-hop data forwarding strategy with the help of the candidate cluster headers is proposed to balance energy consumption during transmission and to avoid buffer overflow. Meanwhile, in each annulus, there is a Wireless Charging Vehicle (WCV) that is responsible for periodically recharging the cluster headers as well as the candidate cluster headers. By minimizing the recharging cost, the energy efficiency is enhanced. Simulation results show that AEBDC can not only alleviate the “energy hole problem” in sensor networks, but also effectively prolong the network lifetime.

Mobile sink based data collection for energy efficient coordination in wireless sensor network using cooperative game model

Multi-hop communication in a wireless sensor network leads to unbalanced energy consumption, creating “hot spots” around the sensor nodes. Selection of paths for the mobile sinks for hot-spot mitigation is a challenging task. In this work, we propose two multiple mobile sinks based data collection schemes, namely Direct Send and Via Static Gateway. The mobile sinks move throughout the network following two mobility patterns alternatively to reduce energy consumption and data loss and maximize network life and data collection. We formulate the problem as cooperative game with non-transferable utility, where the mobile sinks are the players. Payoff that the players receive is a function of goodness factor and energy consumption. Goodness factor is assigned to each player by the base station depending on how varied the collected data is. On the basis of received goodness factor, the players select their strategies cooperatively in order to increase their individual payoffs. The proposed algorithms are validated through simulation experiments using C programming language. Hardware test bed studies are done using Arduino sensor motes equipped with XBee antenna to validate our proposed methodology.

An area coverage algorithm for wireless sensor networks based on differential evolution

Lifetime requirements and coverage demands are emphasized in wireless sensor networks. An area coverage algorithm based on differential evolution is developed in this study to obtain a given coverage ratio [Formula: see text]. The proposed algorithm maximizes the lifetime of wireless sensor networks to monitor the area of interest. To this end, we translate continuous area coverage into classical discrete point coverage, so that the optimization process can be realized by wireless sensor networks. Based on maintaining the ε-coverage performance, area coverage algorithm based on differential evolution takes the minimal energy as optimization objective. In area coverage algorithm based on differential evolution, binary differential evolution is redeveloped to search for an improved node subset and thus meet the coverage demand. Taking into account that the results of binary differential evolution are depended on the initial value, the resulting individual is not an absolutely perfect node subset. A compensation strategy is provided to avoid unbalanced energy consumption for the obtained node subset by introducing the positive and negative utility ratios. Under the helps of those ratios and compensation strategy, the resulting node subset can be added additional nodes to remedy insufficient coverage, and redundancy active nodes can be pushed into sleep state. Furthermore, balance and residual energy are considered in area coverage algorithm based on differential evolution, which can expand the scope of population exploration and accelerate convergence. Experimental results show that area coverage algorithm based on differential evolution possesses high energy and computation efficiencies and provides 90% network coverage.

Spontaneous imbalance in the non-hydrostatic Boussinesq equations

Whereas high-frequency waves are valid solutions to the Boussinesq equations in certain limits, their amplitudes are generally observed to be small in large-scale atmospheric and oceanic data. Traditionally, this has led to the development of balance models, reducing the dynamics to only the slow subset. Their solutions, however, can spontaneously generate imbalance in the context of the full equations. To quantify this, we calculate how much energy is transferred from the balanced to the unbalanced part of a turbulent rotating stratified flow that has been initialised to remove high frequencies. We lay out an approach to derive the time evolution of the balanced modes in which their interactions with unbalanced modes are taken into account. This enables us to calculate the budget of balanced (and unbalanced) energy. Our results show that imbalance generation occurs at scales where the Froude and Rossby numbers are still small and the energy spectrum is steep. We find that the scale at which maximum imbalance is generated depends on the peak of the energy spectrum and is invariant to the strength of rotation over the range examined. The unbalanced energy, after being transferred from the balanced component of the flow at larger scales, is cascaded forward and forms a shallow energy spectrum. The steep balanced subrange of the energy spectrum and the shallow subrange cross and form a kink in the total energy spectrum consistent with observed atmospheric and oceanic data. A frequency analysis at different wavenumbers shows that the separation of time scales breaks down at wavenumbers larger than those of maximum imbalance generation, but smaller than the kink of the energy spectrum. Below these scales, there is a single turbulent distribution of frequencies.