A review on solar forecasting and power management approaches for energy‐harvesting wireless sensor networks

For rechargeable wireless sensor nodes, effective power management is of prime importance because of the stochastic behaviour of the environmental resources. A key issue in integrating solar resources with wireless sensor networks (WSNs) is the need of precise irradiance measurements and power to resource modelling. WSNs are employed in an adhoc manner comprises of numerous sensing nodes and organised as a network for the sake of checking and balancing the environmental factors. Each node has sensing, computation, communication, and locomotion capabilities but operates with limited battery life. Energy harvesting is a way of powering these WSNs by harvesting energy from the environment. By considering harvested energy as an energy source, certain considerations are different from that of battery‐operated networks. Nondeterministic energy availability with respect to time is the reason behind these differences, which put a limit on the maximum rate at which energy can be used. Thus, reliable knowledge of solar radiation is essential for informed design, deployment planning, and optimal management of energy in rechargeable WSNs. Further, power management is essential in self‐powerssed networks to efficiently utilize the available energy. In this paper, a detailed survey on different solar forecasting techniques has been presented for precise energy estimates. A detailed study on energy efficient power management techniques is also proposed to address the feasibility of energy‐harvesting approach in WSNs.     

WCDS‐DCR: an energy‐efficient data‐centric routing scheme for wireless sensor networks

Wireless sensor networks (WSNs) typically consist of a large number of battery‐constrained sensors often deployed in harsh environments with little to no human control, thereby necessitating scalable and energy‐efficient techniques. This paper proposes a scalable and energy‐efficient routing scheme, called WCDS‐DCR, suitable for these WSNs. WCDS‐DCR is a fully distributed, data‐centric, routing technique that makes use of an underlying clustering structure induced by the construction of WCDS (Weakly Connected Dominating Set) to prolong network lifetime. It aims at extending network lifetime through the use of data aggregation (based on the elimination of redundant data packets) by some particular nodes. It also utilizes both the energy availability information and the distances (in number of hops) from sensors to the sink in order to make hop‐by‐hop, energy‐aware, routing decisions. Simulation results show that our solution is scalable, and outperforms existing schemes in terms of network lifetime. Copyright © 2010 John Wiley & Sons, Ltd.     

Achieving energy‐neutral data transmission by adjusting transmission power for energy‐harvesting wireless sensor networks

Recently, benefiting from rapid development of energy harvesting technologies, the research trend of wireless sensor networks has shifted from the battery‐powered network to the one that can harvest energy from ambient environments. In such networks, a proper use of harvested energy poses plenty of challenges caused by numerous influence factors and complex application environments. Although numerous works have been based on the energy status of sensor nodes, no work refers to the issue of minimizing the overall data transmission cost by adjusting transmission power of nodes in energy‐harvesting wireless sensor networks. In this paper, we consider the optimization problem of deriving the energy‐neutral minimum cost paths between the source nodes and the sink node. By introducing the concept of energy‐neutral operation, we first propose a polynomial‐time optimal algorithm for finding the optimal path from a single source to the sink by adjusting the transmission powers. Based on the work earlier, another polynomial‐time algorithm is further proposed for finding the approximated optimal paths from multiple sources to the sink node. Also, we analyze the network capacity and present a near‐optimal algorithm based on the Ford–Fulkerson algorithm for approaching the maximum flow in the given network. We have validated our algorithms by various numerical results in terms of path capacity, least energy of nodes, energy ratio, and path cost. Simulation results show that the proposed algorithms achieve significant performance enhancements over existing schemes. Copyright © 2016 John Wiley & Sons, Ltd.     

Low end‐to‐end delay fuzzy networking protocol for mobile wireless sensing

Because of the practical limitations of the energy and processing capabilities, the deployment of many Wireless Sensor Networks (WSN) is facing two main challenges of increasing network lifetime and reducing End to End Delay (EED) which become critical when the nodes are mobile and use non‐rechargeable energy sources. One way to help to extend network lifetime is using fuzzy logic in a form of artificial intelligence. To this end we propose a new routing protocol for using mobile WSNs, which holds the nodes in an equal level of energy and decreases energy dissipation of the network. An optimum path is selected based on the cost of each node to increase network lifetime. In order to lessen EED, we also attempt to design a novel zoning‐scheme for the network area. In this scheme, zonation is dynamic and works based on the Data Link (DL) position. The simulation result shows a significant improvement in lifetime and EED by proposed protocol compared with existing protocols. Copyright © 2016 John Wiley & Sons, Ltd.     

Energy‐efficient multi‐level and distance‐aware clustering mechanism for WSNs

Most sensor networks are deployed at hostile environments to sense and gather specific information. As sensor nodes have battery constraints, therefore, the research community is trying to propose energy‐efficient solutions for wireless sensor networks (WSNs) to prolong the lifetime of the network. In this paper, we propose an energy‐efficient multi‐level and distance‐aware clustering (EEMDC) mechanism for WSNs. In this mechanism, the area of the network is divided into three logical layers, which depends upon the hop‐count‐based distance from the base station. The simulation outcomes show that EEMDC is more energy efficient than other existing conventional approaches. Copyright © 2013 John Wiley & Sons, Ltd.     

Fuzzy chessboard clustering and artificial bee colony routing method for energy‐efficient heterogeneous wireless sensor networks

Energy is an extremely critical resource for battery‐powered wireless sensor networks (WSNs), thus making energy‐efficient protocol design a key challenging problem. However, uneven energy consumption is an inherent problem in WSNs caused by multi‐hop routing and many‐to‐one traffic pattern among sensors. In this paper, we therefore propose a new clustering method called fuzzy chessboard clustering (FFC), which is capable to overcome the bottleneck problem and addressing the uneven energy consumption problem in heterogeneous WSNs. We also propose an energy‐efficient routing method called artificial bee colony routing method (ABCRM) to find the optimal routing path for the heterogeneous WSNs. ABCRM seeks to investigate the problems of balancing energy consumption and maximization of network lifetime. To demonstrate the effectiveness of FCC‐ABCRM in terms of lessening end‐to‐end delay, balancing energy consumption, and maximization of heterogeneous network lifetime, we compare our method with three approaches namely, chessboard clustering approach, PEGASIS, and LEACH. Simulation results show that the network lifetime achieved by FCC‐ABCRM could be increased by nearly 25%, 45%, and 60% more than that obtained by chessboard clustering, PEGASIS, and LEACH, respectively. Copyright © 2013 John Wiley & Sons, Ltd.     

Improving physical layer security via cooperative diversity in energy‐constrained cognitive radio networks with multiple eavesdroppers

In this paper, a scheme that exploits cooperative diversity of multiple relays to provide physical layer security against an eavesdropping attack is concerned. Relay‐based cognitive radio network (CRN) faces issues multiple issues other than the same as faced by conventional wireless communications. If the nodes in a CRN are able to harvest energy and then spend less energy than the total energy available, we can ensure a perpetual lifetime for the network. In this paper, an energy‐constrained CRN is considered where relay nodes are able to harvest energy. A cooperative diversity‐based relay and subchannel‐selection algorithm is proposed, which selects a relay and a subchannel to achieve the maximum secrecy rate while keeping the energy consumed under a certain limit. A transmission power factor is also selected by the algorithm, which ensures long‐term operation of the network. The power allocation problem at the selected relay and at the source also satisfies the maximum‐interference constraint with the primary user (PU). The proposed scheme is compared with a variant of the proposed scheme where the relays are assumed to have an infinite battery capacity (so maximum transmission power is available in every time slot) and is compared with a scheme that uses jamming for physical layer security. The simulation results show that the infinite battery‐capacity scheme outperforms the jamming‐based physical layer security scheme, thus validating that cooperative diversity‐based schemes are suitable to use when channel conditions are better employed, instead of jamming for physical layer security.     

Tree‐based channel assignment schemes for multi‐channel wireless sensor networks

Many sensor node platforms used for establishing wireless sensor networks (WSNs) can support multiple radio channels for wireless communication. Therefore, rather than using a single radio channel for whole network, multiple channels can be utilized in a sensor network simultaneously to decrease overall network interference, which may help increase the aggregate network throughput and decrease packet collisions and delays. This method, however, requires appropriate schemes to be used for assigning channels to nodes for multi‐channel communication in the network. Because data generated by sensor nodes are usually delivered to the sink node using routing trees, a tree‐based channel assignment scheme is a natural approach for assigning channels in a WSN. We present two fast tree‐based channel assignment schemes (called bottom up channel assignment and neighbor count‐based channel assignment) for multi‐channel WSNs. We also propose a new interference metric that is used by our algorithms in making decisions. We validated and evaluated our proposed schemes via extensive simulation experiments. Our simulation results show that our algorithms can decrease interference in a network, thereby increasing performance, and that our algorithms are good alternatives for static channel assignment in WSNs. Copyright © 2015 John Wiley & Sons, Ltd.     

Multi‐hop medium access control protocol for low energy critical infrastructure monitoring networks using wake‐up radio

The IEEE 802.15.4K Task Group was formed recently to address the low energy critical infrastructure monitoring networks. The aim is to collect scheduled and event data from a large number of non‐mains powered endpoints that are widely dispersed. The application requirements include reliable data transfer, energy efficiency, and long deployment lifetime. To meet the low energy critical infrastructure monitoring network requirements, we propose a multihop medium access control protocol where the scheduled or event data are routed to the coordinator through the cluster heads. The power consumption of the cluster heads is critical as they use more power than the normal endpoints. Our protocol uses the wake‐up radio approach from cluster head to cluster head communication and an efficient guaranteed time slots allocation scheme to minimize the power consumption of the cluster heads. We derive analytical expressions for the average power consumption of cluster heads as well as ordinary endpoints. The results show that our proposed protocol outperforms the IEEE 802.15.4 MAC and SCP MAC in terms of power consumption. High power efficiency is achieved in both the cluster heads and normal endpoints. Copyright © 2012 John Wiley & Sons, Ltd.     

Energy-efficient data sensing and routing in unreliable energy-harvesting wireless sensor network

Energy-harvesting wireless sensor network (WSN) is composed of unreliable wireless channels and resource-constrained nodes which are powered by solar panels and solar cells. Energy-harvesting WSNs can provide perpetual data service by harvesting energy from surrounding environments. Due to the random characteristics of harvested energy and unreliability of wireless channel, energy efficiency is one of the main challenging issues. In this paper, we are concerned with how to decide the energy used for data sensing and transmission adaptively to maximize network utility, and how to route all the collected data to the sink along energy-efficient paths to maximize the residual battery energy of nodes. To solve this problem, we first formulate a heuristic energy-efficient data sensing and routing problem. Then, unlike the most existing work that focuses on energy-efficient data sensing and energy-efficient routing respectively, energy-efficient data sensing and routing scheme (EEDSRS) in unreliable energy-harvesting wireless sensor network is developed. EEDSRS takes account of not only the energy-efficient data sensing but also the energy-efficient routing. EEDSRS is divided into three steps: (1) an adaptive exponentially weighted moving average algorithm to estimate link quality. (2) an distributed energetic-sustainable data sensing rate allocation algorithm to allocate the energy for data sensing and routing. According to the allocated energy, the optimal data sensing rate to maximize the network utility is obtained. (3) a geographic routing with unreliable link protocol to route all the collected data to the sink along energy-efficient paths. Finally, extensive simulations to evaluate the performance of the proposed EEDSRS are performed. The experimental results demonstrate that the proposed EEDSRS is very promising and efficient.     

Energy‐efficient resource allocation for lifetime maximization in M2M networks

Machine‐to‐machine (M2M) communications is one of the major enabling technologies for the realization of the Internet of Things (IoT). Most machine‐type communication devices (MTCDs) are battery powered, and the battery lifetime of these devices significantly affects the overall performance of the network and the quality of service (QoS) of the M2M applications. This paper proposes a lifetime‐aware resource allocation algorithm as a convex optimization problem for M2M communications in the uplink of a single carrier frequency division multiple access (SC‐FDMA)‐based heterogeneous network. A K‐means clustering is introduced to reduce energy consumption in the network and mitigate interference from MTCDs in neighbouring clusters. The maximum number of clusters is determined using the elbow method. The lifetime maximization problem is formulated as a joint power and resource block maximization problem, which is then solved using Lagrangian dual method. Finally, numerical simulations in MATLAB are performed to evaluate the performance of the proposed algorithm, and the results are compared to existing heuristic algorithm and inbuilt MATLAB optimal algorithm. The simulation results show that the proposed algorithm outperforms the heuristic algorithm and closely model the optimal algorithm with an acceptable level of complexity. The proposed algorithm offers significant improvements in the energy efficiency and network lifetime, as well as a faster convergence and lower computational complexity.     

Quasi‐optimal power allocation based on ergodic capacity for wireless relay networks

Half‐duplex amplify‐and‐forward (AF) transmissions may result in insufficient use of degrees of freedom if they always use the cooperative mode regardless of the fading states. In this paper, we investigate the conditions under which cooperation offers better performance and the corresponding optimal power allocation during cooperation. Specifically, we first derive an expression of ergodic capacity and its upper bound for an AF cooperative communication system with n relay nodes. Secondly, we propose a novel quasi‐optimal power allocation (QOPA) scheme to maximize the upper bound of the derived ergodic capacity. For the QOPA scheme, the cooperative mode is only adopted when the channel gain of source‐to‐destination is worse than that of relay‐to‐destination. Moreover, we analyze the performance of the system with QOPA scheme when the relay moves, which is based on the random direction model, in a single‐relay wireless network. For a multi‐relay AF network, we compare the ergodic capacity and symbol error rate, corresponding to the proposed QOPA and equal power allocation schemes, respectively. Extensive simulations were conducted to validate analytical results, showing that both ergodic capacity and symbol error rate of the system with QOPA scheme are better than those of the system with equal power allocation scheme in a multi‐relay AF network. Copyright © 2011 John Wiley & Sons, Ltd.     

Fully Solar‐Powered Uninterrupted Overall Water‐Splitting Systems

Extensive research efforts have been recently devoted to the development of self‐driven electrocatalytic water‐splitting systems to generate clean hydrogen chemical fuels. Currently, self‐driven electrocatalytic water‐splitting devices are powered by solar cells, which operate intermittently, or by aqueous batteries, which deliver stored electric power, leading to high operating costs and environmental pollution. Thus, a fully solar‐powered uninterrupted overall water‐splitting system is greatly desirable. Here, the solar cells, stable output voltage of 1.75 V Ni–Zn batteries, and high efficiency zinc–nickel–cobalt phosphide electrocatalysts are successfully assembled together to create a 24 h overall water‐splitting system. Specifically, the silicon‐based solar cells enable the charging of aqueous Ni–Zn batteries for energy storage as well as providing sufficient energy for electrocatalysis throughout the day; in addition, the high‐capacity Ni–Zn batteries offer a steady output voltage for overall water‐splitting at night. Such an uninterrupted solar‐to‐hydrogen system opens up exciting opportunities for the development and applications of renewable energy.     

Solar‐powered ZigBee‐based wireless motion surveillance: a prototype development and experimental results

This paper describes the design and implementation of a solar‐powered wireless motion sensor surveillance network. Commercially available systems with similar functionality which exist today have several disadvantages including single points of failure and requires (semi) constant personnel attention as well as an elaborate power system. These systems require a lot of time to set up, they cannot be used in remote areas where a main power supply is unavailable, and are quite costly. Therefore, there is a need to develop a system which is portable, easy to set up, and is energy efficient. The wireless motion surveillance network described in this paper is designed to be portable, economically inexpensive, and energy efficient. The network is created using the IEEE 802.15.4 ZigBee wireless standard by implementing multiple Microchip PICDEM Z nodes. Each node in the network is equipped with a Direction Sensing Infrared Motion Detector (DSIMD) and a solar power unit (SPU). The DSIMD allows for detection of humans and animals alike moving into or out of the network. The system is powered by solar energy that makes it quite adaptable for remote applications. The network is able to cover an area of radius 30 m. By developing a low‐cost system, which is portable, easy to set up, and has an unlimited power supply, this technology is made accessible to a wider range of applications. The implementation of a CMOS camera is discussed at the end which can be used to take a snapshot of the detected object. Copyright © 2007 John Wiley & Sons, Ltd.     

A joint resource allocation‐channel coding design based on distributed source coding

Wireless sensor networks (WSNs) have found a wide variety of applications recently. However, the challenges in WSNs still remain in improving the sensor energy efficiency and information quality (distortion reduction) of the sensing data transmissions. In this paper, we propose a novel cross‐layer design of resource allocation and channel coding to protect distributed source coding (DSC)‐based data transmission. Resource allocation strategies include rate adaptation and automatic repeat‐request retransmissions. Our proposed joint design of resource allocation, channel coding, and DSC can improve the network energy efficiency and information quality while meeting the data transmission latency requirements. Further, we investigate how the resource allocation enables the network to achieve unequal error protection among correlated DSC streams. Our simulation studies demonstrate that the proposed joint design significantly improves the DSC‐based data transmission quality and the network energy efficiency. Copyright © 2013 John Wiley & Sons, Ltd.     

An efficient actor‐critic reinforcement learning for device‐to‐device communication underlaying sectored cellular network

In this paper, a novel reinforcement learning (RL) approach with cell sectoring is proposed to solve the channel and power allocation issue for a device‐to‐device (D2D)‐enabled cellular network when the prior traffic information is not known to the base station (BS). Further, this paper explores an optimal policy for resource and power allocation between users intending to maximize the sum‐rate of the overall system. Since the behavior of wireless channel and traffic request of users in the system is stochastic in nature, the dynamic property of the environment allows us to employ an actor‐critic RL technique to learn the best policy through continuous interaction with the surrounding. The proposed work comprises of four phases: cell splitting, clustering, queuing model, and channel allocation and power allocation simultaneously using an actor‐critic RL. The implementation of cell splitting with novel clustering technique increases the network coverage, reduces co‐channel cell interference, and minimizes the transmission power of nodes, whereas the queuing model solves the issue of waiting time for users in a priority‐based data transmission. With the help of continuous state‐action space, the actor‐critic RL algorithm based on policy gradient improves the overall system sum‐rate as well as the D2D throughput. The actor adopts a parameter‐based stochastic policy for giving continuous action while the critic estimates the policy and criticizes the actor for the action. This reduces the high variance of the policy gradient. Through numerical simulations, the benefit of our resource sharing scheme over other existing traditional scheme is verified.     

An asynchronous low‐power medium access control protocol for wireless sensor networks

Duty cycling is a fundamental approach used in contention‐based medium access control (MAC) protocols for wireless sensor networks (WSNs) to reduce power consumption in sensor nodes. Existing duty cycle‐based MAC protocols use either scheduling or low‐power listening (LPL) to reduce unnecessary energy lost caused by idle listening and overhearing. This paper presents a new asynchronous duty‐cycled MAC protocol for WSN. It introduces a novel dual preamble sampling (DPS) approach to efficiently coordinate channel access among nodes. DPS combines LPL with a short‐strobed preamble approach to significantly reduce the idle‐listening issue in existing asynchronous protocols. We provide detailed analysis of the energy consumption by using well‐known energy models and compare our work with B‐MAC and X‐MAC, two most popular asynchronous duty cycle‐based MAC protocols for WSNs. We also present experimental results based on NS‐2 simulations. We show that depending on the traffic load and preamble length, the proposed MAC protocol improves energy consumption significantly without degrading network performances in terms of delivery ratio and latency. For example, for a traffic rate of 0.1 packets/s and a preamble length of 0.1 s, the average improvement in energy consumption is about 154%. Copyright © 2011 John Wiley & Sons, Ltd.     

Energy consumption optimization for self‐powered IoT networks with non‐orthogonal multiple access

Energy harvesting (EH) has been considered as one of the promising technologies to power Internet of Things (IoT) devices in self‐powered IoT networks. By adopting a typical harvest‐then‐transmit mode, IoT devices with the EH technology first harvest energy by using wireless power transfer (WPT) and then carry out wireless information transmission (WIT), which leads to the coordination between WPT and WIT. In this paper, we consider optimizing energy consumption of periodical data collection in a self‐powered IoT network with non‐orthogonal multiple access (NOMA). Particularly, we take into account time allocation for the WPT and WIT stages, node deployment, and constraints for data transmission. Moreover, to thoroughly explore the impact of different multiple access methods, we theoretically analyse and compare the performance achieved by employing NOMA, frequency division multiple access (FDMA), and time division multiple access (TDMA) in the considered IoT network. To validate the performance of the proposed method, we conduct extensive simulations and show that the NOMA outperforms the FDMA and TDMA in terms of energy consumption and transmission power.     

An efficient online‐battery aware geographic routing algorithm for wireless sensor networks

Wireless sensor networks (WSNs) are being used in a wide variety of critical applications such as military and health‐care applications. Such networks, which are composed of sensor nodes with limited memory capacity, limited processing capabilities, and most importantly limited energy supply, require routing protocols that take into consideration these constraints. The aim of this paper is to provide an efficient power aware routing algorithm for WSNs that guarantees QOS and at the same time minimizes energy consumption by calculating the remaining battery capacity of nodes and taking advantage of the battery recovery process. We present an online‐battery aware geographic routing algorithm. To show the effectiveness of our approach, we simulated our algorithm in ns2 and compared it with greedy perimeter stateless routing for wireless networks and battery‐aware routing for streaming data transmissions in WSNs. Copyright © 2009 John Wiley & Sons, Ltd.     

Software‐defined network‐enabled opportunistic offloading and charging scheme in multi‐unmanned aerial vehicle ecosystem

Unmanned aerial vehicles (UAVs) are autonomous fliers, which can play different roles in modern day applications. In one of the important role, UAVs can act as aerial data forwarding nodes for communication range enhancement in remote areas. UAVs form a web of drones, which can be geo‐distributed across a large area to serve various applications. However, the two major contradicting challenges with respect to multi‐UAV networks are channel congestion and flight time enhancement. The use of effective data transmission techniques to handle congestion can lead to higher battery dissipation, which in turn end up in the reduction in flight time. However, it is utmost necessity to provide an effective framework, which can provide a viable solution for handling congestion in multi‐UAV networks while enhancing the flight time of UAVs. To handle these issues, software‐defined network (SDN)–enabled opportunistic offloading and charging scheme (SOOCS) in multi‐UAV ecosystem is designed in this paper. In this scheme, an opportunistic offloading scheme is proposed, which uses an SDN‐based control model to handle congestion issues. Apart from this, an opportunistic energy‐charging scheme is designed, wherein the UAVS can either replenish their batteries using solar plates or they can wirelessly charge energy from charging points deployed at various geo‐distributed locations. The proposed scheme is evaluated using a simulation‐based study over the realistic deployment of charging points in Chandigarh City, India. The results obtained show the superiority of SOOCS over other variants of its category in terms of end‐to‐end delay, throughput, and hand‐over latency.