As the nodes of AWSN (Aerial Wireless Sensor Networks) fly around, the network topology changes frequently with high energy consumption and high cluster head mortality, and some sensor nodes may fly away from the original cluster and interrupt network communication. To ensure the normal communication of the network, this paper proposes an improved LEACH-M protocol for aerial wireless sensor networks. The protocol is improved based on the traditional LEACH-M protocol and MCR protocol. A Cluster head selection method based on maximum energy and an efficient solution for outlier nodes is proposed to ensure that cluster heads can be replaced prior to their death and ensure outlier nodes re-home quickly and efficiently. The experiments show that, compared with the LEACH-M protocol and MCR protocol, the improved LEACH-M protocol performance is significantly optimized, increasing network data transmission efficiency, improving energy utilization, and extending network lifetime.

In an internet of things (IoT) system using an energy harvesting device and a secondary (2nd) battery, regardless of the age of the 2nd battery, the power management shortens the lifespan of the entire system. In this paper, we propose a scheme that extends the lifetime of the energy harvesting-based IoT system equipped with a Lithium 2nd battery. The proposed scheme includes several policies of using a supercapacitor as a primary energy storage, limiting the charging level according to the predicted harvesting energy, swinging the energy level around the minimum stress state of charge (SOC) level, and delaying the charge start time. Experiments with natural solar energy measurements based on a battery aging approximation model show that the proposed method can extend the operation lifetime of an existing IoT system from less than one and a half year to more than four years.

Sensor-data gathering using multi-hop connections in a wireless sensor network is being widely used, and a tree topology for data gathering is considered promising because it eases data aggregation. Therefore, many sensor-tree-creation algorithms have been proposed. The sensors in a tree, however, generally run on batteries, so long tree lifetime is one of the most important factors in collecting sensor data from a tree over a long period. It has been proven that creating the longest-lifetime tree is a non-deterministic-polynomial complete problem; thus, all previously proposed sensor-tree-creation algorithms are heuristic. To evaluate a heuristic algorithm, the time complexity of the algorithm is very important, as well as the quantitative evaluation of the lifetimes of the created trees and algorithm speed. This paper proposes an algorithm called assured switching with accurate graph optimization (ASAGAO) that can create a sensor tree with a much longer lifetime much faster than other sensor-tree-creation algorithms. In addition, it has much smaller time complexity.

In this paper, the problem of lifetime extension of wireless sensor networks (WSNs) with redundant sensor nodes deployed in 3D vegetation-covered fields is modeled, which includes building communication models, network model and energy model. Generally, such a problem cannot be solved by a conventional method directly. Here we propose an Artificial Bee Colony (ABC) based optimal grouping algorithm (ABC-OG) to solve it. The main contribution of the algorithm is to find the optimal number of feasible subsets (FSs) of WSN and assign them to work in rotation. It is verified that reasonably grouping sensors into FSs can average the network energy consumption and prolong the lifetime of the network. In order to further verify the effectiveness of ABC-OG, two other algorithms are included for comparison. The experimental results show that the proposed ABC-OG algorithm provides better optimization performance.

Clustering is known to be an effective means of reducing energy dissipation and prolonging network lifetime in wireless sensor networks (WSNs). Recently, game theory has been used to search for optimal solutions to clustering problems. The residual energy of each node is vital to balance a WSN, but was not used in the previous game-theory-based studies when calculating the final probability of being a cluster head. Furthermore, the node payoffs have also not been expressed in terms of energy consumption. To address these issues, the final probability of being a cluster head is determined by both the equilibrium probability in a game and a node residual energy-dependent exponential function. In the process of computing the equilibrium probability, new payoff definitions related to energy consumption are adopted. In order to further reduce the energy consumption, an assistant method is proposed, in which the candidate nodes with the most residual energy in the close point pairs completely covered by other neighboring sensors are firstly selected and then transmit same sensing data to the corresponding cluster heads. In this paper, we propose an efficient energy-aware clustering protocol based on game theory for WSNs. Although only game-based method can perform well in this paper, the protocol of the cooperation with both two methods exceeds previous by a big margin in terms of network lifetime in a series of experiments.

Wireless sensor networks usually deploy sensor nodes with limited energy resources in unattended environments so that people have difficulty in replacing or recharging the depleted devices. In order to balance the energy dissipation and prolong the network lifetime, this paper proposes a routing spanning tree-based clustering algorithm (RSTCA) which uses routing spanning tree to analyze clustering. In this study, the proposed scheme consists of three phases: setup phase, cluster head (CH) selection phase and steady phase. In the setup phase, several clusters are formed by adopting the K-means algorithm to balance network load on the basis of geographic location, which solves the randomness problem in traditional distributed clustering algorithm. Meanwhile, a conditional inter-cluster data traffic routing strategy is created to simplify the networks into subsystems. For the CH selection phase, a novel CH selection method, where CH is selected by a probability based on the residual energy of each node and its estimated next-time energy consumption as a function of distance, is formulated for optimizing the energy dissipation among the nodes in the same cluster. In the steady phase, an effective modification that counters the boundary node problem by adjusting the data traffic routing is designed. Additionally, by the simulation, the construction procedure of routing spanning tree (RST) and the effect of the three phases are presented. Finally, a comparison is made between the RSTCA and the current distributed clustering protocols such as LEACH and LEACH-DT. The results show that RSTCA outperforms other protocols in terms of network lifetime, energy dissipation and coverage ratio.

As devices continue to shrink, the parameter shift due to process variation and aging effects has an increasing impact on the circuit yield and reliability. However, predicting how long a circuit can maintain its design yield above the design specification is difficult because the design yield changes during the aging process. Moreover, performing Monte Carlo (MC) simulation iteratively during aging analysis is infeasible. Therefore, most existing approaches ignore the continuity during simulations to obtain high speed, which may result in accumulation of extrapolation errors with time. In this paper, an incremental simulation technique is proposed for lifetime yield analysis to improve the simulation speed while maintaining the analysis accuracy. Because aging is often a gradual process, the proposed incremental technique is effective for reducing the simulation time. For yield analysis with degraded performance, this incremental technique also reduces the simulation time because each sample is the same circuit with small parameter changes in the MC analysis. When the proposed dynamic aging sampling technique is employed, 50× speedup can be obtained with almost no decline accuracy, which considerably improves the efficiency of lifetime yield analysis.

This paper proposes a Watts and Strogatz-model based routing method for wireless sensor network along with link-exchange operation. The proposed routing achieves low data-collection delay because of hub-node existence. By applying the link exchanges, node with low remaining battery level can escape from a hub node. Therefore, the proposed routing method achieves the fair battery-power consumptions among sensor nodes. It is possible for the proposed method to prolong the network lifetime with keeping the small-world properties. Simulation results show the effectiveness of the proposed method.

Fault tolerant methods using dynamically reconfigurable devices have been studied to overcome wear-out failures. However, quantitative comparisons have not been sufficiently assessed on device lifetime enhancement with these methods, whereas they have mainly been evaluated individually from various viewpoints such as additional hardware overheads, performance, and downtime for fault recovery. This paper presents quantitative lifetime evaluations performed by simulating the fault-avoidance procedures of five representative methods under the same conditions in wear-out scenarios, applications, and device architecture. The simulation results indicated that improvements of up to 70% mean-time-to-failure (MTTF) in comparison with ideal fault avoidance could be achieved by using methods of fault avoidance with ‘row direction shift’ and ‘dynamic partial reconfiguration’. ‘Column shift’, on the other hand, attained a high degree of stability with moderate improvements in MTTF. The experimental results also revealed that spare basic elements (BEs) should be prevented from aging so that improvements in MTTF would not be adversely affected. Moreover, we found that the selection of initial mappings guided by wire utilization could increase the lifetimes of partial reconfiguration based fault avoidance.

Many studies have reported that the single-event transient (SET) width increases with temperature. However, the mechanism for this temperature dependency is not clear, especially for an N-hit SET. In this study, TCAD simulations are carried out to study the temperature dependence of N-hit SETs in detail. Several possible factors are examined, and the results show that the temperature dependence in bulk devices is due to the decrease in the carrier mobility with temperature in both the struck NMOS and the pull-up PMOS. In contrast, the temperature dependence in SOI devices is due to the decrease in the diffusion constant and carrier lifetime with temperature, which enhances the parasitic bipolar effect.

In this letter, we propose an energy-aware source routing protocol for maximizing the network lifetime in mobile ad hoc networks. We define a new routing cost by considering both transmit and receive power consumption and remaining battery level in each node simultaneously and present an efficient route discovery procedure to investigate the proposed routing cost. Intensive simulation verifies that the proposed routing protocol has similar performance to the conventional routing protocols in terms of the number of transmission hops, transmission rate, and energy consumption while significantly improving the performance with respect to network lifetime.

Optimizing lifetime of a wireless sensor network has received considerable attention in recent years. In this paper, using the feasibility and simplicity of grid-based clustering and routing schemes, we investigate optimizing lifetime of a two-dimensional wireless sensor network. Thus how to determine the optimal grid sizes in order to prolong network lifetime becomes an important problem. At first, we propose a model for lifetime of a grid in equal-grid model. We also consider that nodes can transfer packets to a grid which is two or more grids away in order to investigate the trade-off between traffic and transmission energy consumption. After developing the model for an adjustable-grid scenario, in order to optimize lifetime of the network, we derive the optimal values for dimensions of the grids. The results show that if radio ranges are adjusted appropriately, the network lifetime in adjustable-grid model is prolonged compared with the best case where an equal-grid model is used.

In this paper, we present Greedy Routing for Maximum Lifetime (GRMax) [1],[2] which can use the limited energy available to nodes in a Wireless Sensor Network (WSN) in order to delay the dropping of packets, thus extend the network lifetime. We define network lifetime as the time period until a source node starts to drop packets because it has no more paths to the destination [3]. We introduce the new concept of Network Connectivity Aiming (NCA) node. The primary goal of NCA nodes is to maintain network connectivity and avoid network partition. To evaluate GRMax, we compare its performance with Geographic and Energy Aware Routing (GEAR) [4], which is an energy efficient geographic routing protocol and Greedy Perimeter Stateless Routing (GPSR) [5], which is a milestone among geographic routing protocol. We evaluate and compare the performance of GPSR, GEAR, and GRMax using OPNET Modeler version 15. The results show that GRMax performs better than GEAR and GPSR with respect to the number of successfully delivered packets and the time period before the nodes begin to drop packets. Moreover, with GRMax, there are fewer dead nodes in the system and less energy is required to deliver packets to destination node (sink).

The authors have been investigating degradation process of Au plated slip ring and Ag-Pd-Cu brush system. In almost all cases the lifetime of the sliding system ends, when Au plating layer is worn out, the ring surface is oxidized to be black in color and contact resistance becomes very high. Further, the lifetime is very short without lubricant. So, the lubricant is very effective to make the lifetime longer. However, even with lubricant the lifetime is varied from about 1000 hours to almost 7000 hours in the past experiments. It is an important issue how the lubricant works on the lifetime of the system. In this paper the effect of lubricant on the degradation process of contact resistance is focused on. In the past tests the lubricant is supplied only once before the test. In this test the lubricant is regularly supplied almost every 900 operation hours. Consequently, the operation more than 8000 hours is realized, which is the longest among tests so far. In addition the contact voltage drop increase gradually until 2600 hours and after that it stays almost constant around 70 mV. According to the Element Analysis after the test the Ni base plating layer is totally exposed in many tracks. It means that the Au plating layer is gradually worn out probably at the stage of increasing voltage drop. In the previous tests the lifetime ended even when the Ni plating layer remained. So, the reason of long operation in this test is guessed to be that the lubricant not only decreases wear of ring and brush, but also suppresses oxidation of the Ni layer.

Battery-powered wireless sensor networks are prone to premature failures because some nodes deplete their batteries more rapidly than others due to workload variations, the many-to-one traffic pattern, and heterogeneous hardware. Most previous sensor network lifetime enhancement techniques focused on balancing the power distribution, assuming the usage of the identical battery. This paper proposes a novel fine-grained cost-constrained lifetime-aware battery allocation solution for sensor networks with arbitrary topologies and heterogeneous power distributions. Based on an energy–cost battery pack model and optimal node partitioning algorithm, a rapid battery pack selection heuristic is developed and its deviation from optimality is quantified. Furthermore, we investigate the impacts of the power variations on the lifetime extension by battery allocation. We prove a theorem to show that power variations of nodes are more likely to reduce the lifetime than to increase it. Experimental results indicate that the proposed technique achieves network lifetime improvements ranging from 4–13 over the uniform battery allocation, with no more than 10 battery pack levels and 2-5 orders of magnitudes speedup compared with a standard integer nonlinear program solver (INLP).

The future wireless mobile communication networks are expected to provide seamless wireless access and data exchange to mobile users. In particular, it is expected that the demand for ubiquitous data exchange between mobile users will increase with the widespread use of various wireless applications of the intelligent transportation system (ITS) and intelligent vehicles. Mobile ad hoc networks (MANETs) are one of the representative research areas pursuing the technology needed to satisfy the increasing mobile communication requirements. However, most of the works on MANET systems do not take into account the continuous and dynamic changes of nodal mobility to accommodate system design and performance evaluation. The mobility of nodes limits the reliability of communication between the source and the destination node since a link between two continuously moving nodes is established only when one node enters the transmission range of the other. To alleviate this problem, mobile relay has been studied. In particular, it is shown that relay selection is an efficient way to support nodal mobility in MANET systems. In this paper, we propose a mobility-based relay selection algorithm for the MANET environment. Firstly, we define the lifetime as the maximum link duration for which the link between two nodes remains active. Therefore, the lifetime indicates the reliability of the relay link which measures its capability to successfully support relayed communication when requested by the source node. Furthermore, we consider a series of realistic scenarios according to the randomness of nodal mobility. Thus, the proposed algorithm can be easily applied in practical MANET systems by choosing the appropriate node mobility behavior. The numerical results show that the improved reliability of the proposed algorithm's relayed communication is achieved with a proper number of mobile relay nodes rather than with the conventional selection algorithm. Lastly, we show that random mobility of the individual nodes enhances reliability of the network in a sparse network environment.

A key challenge in developing energy-efficient sensor networks is to extend network lifetime in resource-limited environments. As sensors are often densely distributed, they can be scheduled on alternative duty cycles to conserve energy while satisfying the system requirements. Directional sensor networks composed of a large number of directional sensors equipped with a limited battery and with a limited angle of sensing have recently attracted attention. Many types of directional sensors can rotate to face a given direction. Maximizing network lifetime while covering all of the targets in a given area and forwarding sensor data to the sink is a challenge in developing such rotatable directional sensor networks. In this paper, we address the maximum directional cover tree (MDCT) problem of organizing directional sensors into a group of non-disjoint subsets to extend network lifetime. One subset, in which the directional sensors cover all of the targets and forward the data to the sink, is activated at a time, while the others sleep to conserve energy. For the MDCT problem, we first present an energy-consumption model that mainly takes into account the energy expenditure for sensor rotation as well as for the sensing and relaying of data. We also develop a heuristic scheduling algorithm called directional coverage and connectivity (DCC)-greedy to solve the MDCT problem. To verify and evaluate the algorithm, we conduct extensive simulations and show that it extends network lifetime to a reasonable degree.

This letter investigates the cluster lifetime of single-hop wireless sensor networks with cooperative Multi-Input Single-Output (MISO) scheme. The energy consumptions of both intra-cluster and out-cluster communications are considered. Moreover, uniform and linear data aggregations are discussed. It is found the optimal transmission scheme varies with the distance from the cluster to the base station. More interestingly and novelly, the effect of cluster size on the cluster lifetime has been clarified.

In practical settings of wireless sensor networks, it is often feasible to consider heterogeneous deployments of devices with different capabilities. Under prescribed cost constraints, we analyze such heterogenous deployments and present how they impact the coverage of a sensor network including spatial correlation effect. We derive expressions for the heterogeneous mixture of devices that maximizes the lifetime coverage in both single-hop direct and multi-hop communication models. Our results show that using an optimal mixture of many inexpensive low-capability devices and some expensive high-capability devices can significantly extend the duration of a network's sensing performance, especially in a network with low spatial correlation.

In this letter, we discuss a forwarding method for maximizing network lifetime, which combines multi-hop forwarding and direct forwarding with a direct/multi-hop forwarding ratio of each sensor node. The direct forwarding ratio refers to the forwarding amount ratio of sensor nodes' own data directly towards a sink node in one packet/instance data generation rate. We tackle an optimization problem to determine the direct forwarding ratio of each sensor node, maximizing network lifetime, as well as nearly guaranteeing energy consumption balancing characteristics. The optimization problem is tackled through the Lagrange multiplier approach. We found that the direct forwarding ratio is overall inversely proportional to the increase of node index in h < i ≤ N case. Finally, we compare energy consumption and network lifetime of the proposed forwarding method with other existing forwarding methods. The numerical results show that the proposed forwarding method balances energy consumption in most of the sensor nodes, comparing with other existing forwarding methods, such as multi-hop forwarding and direct forwarding. The proposed forwarding method also maximizes network lifetime.