Energy‐aware supply route data collecting methods using wireless sensor networks

In military action, marching is a common method used for supply‐troop movement. Supply routes are typically in the wilderness where the route conditions change over time. This paper proposes a power‐saving algorithm allowing supply troops to collect route information using wireless sensor network technology. Each member in the marching supply troop is equipped with a battery‐powered sensor. To save power consumption, the proposed methods schedule the sleeping period for each member according to the size of the marching supply troop and its moving velocity. Two data carrying methods are proposed to reduce the frequency of long‐distance data uploading. The first method allows the uploaded data to be carried within a single‐round data collection period, and the second method extends the data carrying period to multiple rounds. The simulation results show that scheduling a sleep period can prolong the sensing distance along the route. These two proposed methods can add an additional 18–70% in distance data over methods without scheduling a sleep period. The energy spent on long‐distance data transmissions can be improved by 7–25%. Copyright © 2015 John Wiley & Sons, Ltd.     

A lightweight,self‐adaptive lock gate designation scheme for data collection in long‐thin wireless sensor networks

Constrained by the physical environments, the long‐thin topology has recently been promoted for many practical deployments of wireless sensor networks (WSNs). In general, a long‐thin topology is composed of a number of long branches of sensor nodes, where along a branch each sensor node has only one potential parent node toward the sink node. Although data aggregation may alleviate excessive packet contention, the maximum payload size of a packet and the dynamically changing traffic loads may severely affect the amount of sensor readings that may be collected along a long branch of sensor nodes. In addition, many practical applications of long‐thin WSNs demand the exact sensor readings at each location along the deployment areas for monitoring and analysis purposes, so sensor readings may not be aggregated when they are collected. This paper proposes a lightweight, self‐adaptive scheme that designates multiple collection nodes, termed lock gates, along a long‐thin network to collect sensor readings sent from their respective upstream sensor nodes. The self‐adaptive lock gate designation scheme balances between the responsiveness and the congestion of data collection while mitigating the funneling effect. The scheme also dynamically adapts the designation of lock gates to accommodate the time‐varying sensor reading generation rates of different sensor nodes. A testbed of 100 Jennic sensor nodes is developed to demonstrate the effectiveness of the proposed lock gate designation scheme. Copyright © 2011 John Wiley & Sons, Ltd.     

Energy harvesting,cooperative spectrum sensing,and data transmission improvement in energy‐efficient multichannel cognitive sensor networks

In this paper, we investigate the energy harvesting capability in a multichannel wireless cognitive sensor networks for energy‐efficient cooperative spectrum sensing and data transmission. Spectrum sensors can cooperatively scan the spectrum for available channels, whereas data sensors transmit data to the fusion center (FC) over those channels. We select the sensing, data transmission, and harvesting sensors by setting the sensing time, data transmission time, and also harvesting time to maximize the network data transmission rate and improve the total energy consumption in the multichannel network under global probability of false alarm and global probability of detection constraints. We formulate our optimization problem and employ the convex optimization method to obtain the optimal times and nodes for spectrum sensing, data transmission, and harvesting energy in each subchannel for multiband cognitive sensor networks. Simulation results show that in our proposed algorithm, the network data transmission rate is improved while more energy is saved compared with the baseline methods with equal sensing time in all subchannels.     

Maximizing the lifetime of energy‐constrained cooperative spectrum sensing sensor network

Adding the cognitive capability to wireless sensor networks allows the sensors to monitor the spectrum and identify the spectrum holes to operate in different frequencies according to the radio environment which result in better spectrum utilization. Spectrum sensing is a main component in any cognitive radio network. In this paper, we propose a new cooperative sensing scheme based on energy detection for cognitive sensor networks which is constrained by the energy limitation of the wireless sensor elements. The proposed scheme minimizes the sensing energy for individual sensor and carefully selects the suitable participant sensors in each cooperative sensing process. This results in maximizing the lifetime of energy‐constrained wireless sensor networks. The proposed scheme also takes into consideration the constraints on the detection accuracy. The simulation results show that the proposed scheme prolonged the lifetime of the cognitive network, makes efficient usage of available spectrum by secondary users, and satisfy the target detection performance.     

DynaChannAl: dynamic channel allocation with minimal end‐to‐end delay for two‐tier wireless sensor networks

With recent advances in wireless networking and in low‐power sensor technology, wireless sensor networks (WSNs) have taken significant roles in various applications. Whereas some WSNs only require minimal bandwidth, newer applications operate with a noticeably larger amount of data. One way to deal with these applications is to maximize the available capacity by utilizing multiple wireless channels. We propose DynaChannAl, a distributed dynamic wireless channel allocation algorithm that effectively distributes nodes to multiple wireless channels in WSNs. Specifically, DynaChannAl targets applications where mobile nodes connect to preexisting wireless backbones and takes the expected end‐to‐end queuing delay as its core metric. We used the link quality indicator values provided by 802.15.4 radios to whitelist high‐quality links and evaluate these links with the aggregated queuing latency, making it useful for applications that require minimal end‐to‐end delay (i.e., health care). DynaChannAl is a lightweight and adoptable scheme that can be incorporated easily with predeveloped systems. As the first study to consider end‐to‐end latency as the core metric for channel allocation in WSNs, we evaluate DynaChannAl on a 45 node test bed and show that DynaChannAl successfully distributes source nodes to different channels and enables them to select channels and links that minimizes the end‐to‐end latency. Copyright © 2012 John Wiley & Sons, Ltd.     

Energy‐aware geographic routing in wireless sensor networks with anchor nodes

Energy efficiency has become an important design consideration in geographic routing protocols for wireless sensor networks because the sensor nodes are energy constrained and battery recharging is usually not feasible. However, numerous existing energy‐aware geographic routing protocols are energy‐inefficient when the detouring mode is involved in the routing. Furthermore, most of them rarely or at most implicitly take into account the energy efficiency in the advance. In this paper, we present a novel energy‐aware geographic routing (EAGR) protocol that attempts to minimize the energy consumption for end‐to‐end data delivery. EAGR adaptively uses an existing geographic routing protocol to find an anchor list based on the projection distance of nodes for guiding packet forwarding. Each node holding the message utilizes geographic information, the characteristics of energy consumption, and the metric of advanced energy cost to make forwarding decisions, and dynamically adjusts its transmission power to just reach the selected node. Simulation results demonstrate that our scheme exhibits higher energy efficiency, smaller end‐to‐end delay, and better packet delivery ratio compared to other geographic routing protocols. Copyright © 2011 John Wiley & Sons, Ltd.     

Distributed semi‐adaptive compressive sensing data collection in wireless sensor networks

Recently, many researches have been conducted to exploit the compressive sensing (CS) theory in wireless sensor networks (WSNs). One of the most important goals in CS is to prolong the lifetime of WSNs. But CS may suffer from some errors during the reconstruction phase. In addition, an adaptive version of CS named Bayesian compressive sensing has been studied to improve the reconstruction accuracy in WSNs. This paper investigates these adaptive methods and identifies their associated problems. Finally, a distributed and semi‐adaptive CS‐based data collection method is proposed. The proposed method tackles the aforementioned problems. Simulation results show that considering both lifetime and accuracy factors as a compound metric, the proposed method yields a 200% improvement compared with the Bayesian compressive sensing‐based method and outperforms other compared methods in the literature.     

A novel energy‐aware routing mechanism for SDN‐enabled WSAN

Energy consumption is one of the most important design constraints when building a wireless sensor and actuator network since each device in the network has a limited battery capacity, and prolonging the lifetime of the network depends on saving energy. Overcoming this challenge requires a smart and reconfigurable network energy management strategy. The Software‐Defined Networking (SDN) paradigm aims at building a flexible and dynamic network structure, especially in wireless sensor networks. In this study, we propose an SDN‐enabled wireless sensor and actuator network architecture that has a new routing discovery mechanism. To build a flexible and energy‐efficient network structure, a new routing decision approach that uses a fuzzy‐based Dijkstra's algorithm is developed in the study. The proposed architecture can change the existing path during data transmission, which is the key property of our model and is achieved through the adoption of the SDN approach. All the components and algorithms of the proposed system are modeled and simulated using the Riverbed Modeler software for more realistic performance evaluation. The results indicate that the proposed SDN‐enabled structure with fuzzy‐based Dijkstra's algorithm outperforms the one using the regular Dijkstra's and the ZigBee‐based counterpart, in terms of the energy consumption ratio, and the proposed architecture can provide an effective cluster routing while prolonging the network lifetime.     

Improving MANET performance by a hop‐aware and energy‐based buffer management scheme

A hop‐aware and energy‐based buffer management scheme (HEB) is proposed in this paper. HEB can provide better quality of service to packets with real‐time requirements and improve MANET power efficiency. In our algorithm, the buffer is divided into real‐time and non‐real‐time partitions. We consider the number of hops passed, the power levels of the transmitting node, the predicted number of remaining hops, and waiting time in the buffer to determine packet transmission priority. In addition, specialized queue management and a probabilistic scheduling algorithm are proposed to decrease retransmissions caused by packet losses. Mathematical derivations of loss rates and end‐to‐end delays are also proposed. Coincidence between mathematical and simulation results is also shown. Finally, the HEB is compared with first in first out, random early detection, and hop‐aware buffering scheme. Simulation results show that the proposed algorithm reduces loss rates, power consumption, and end‐to‐end delays for real‐time traffic, considerably improving the efficiency of queue management in MANET. Copyright © 2012 John Wiley & Sons, Ltd.     

A distributed,multi‐hop,adaptive, tree‐based energy‐balanced routing approach

To accomplish the primary objective of data sensing and collection of wireless sensor networks (WSN), the design of an energy efficient routing algorithm is very important. However, the energy constrained sensing nodes along with the intrinsic properties of the (WSN) environment makes the routing a challenging task. To overcome this routing dilemma, an improved distributed, multi‐hop, adaptive, tree‐based energy‐balanced (DMATEB) routing scheme is proposed in this paper. In this scheme, a relay node is selected in view of minimum distance and high energy from a current sensing node. Further, the parent node is chosen among the selected relay nodes on the basis of high residual energy and less power consumption with due consideration of its associated child nodes. As each sensing node itself selects its parent among the available alternatives, the proposed scheme offers a distributive and adaptive approach. Moreover, the proposed system does not overload any selected parent of a particular branch as it starts acting as a child whenever its energy lowers among the other available relay nodes. This leads to uniform energy utilization of nodes that offers a better energy balance mechanism and improves the network lifespan by 20% to 30% as compared with its predecessors.     

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.     

An energy‐aware transmission mechanism for WiFi‐based mobile devices handling upload TCP traffic

This paper presents an energy‐aware transmission mechanism that improves the throughput and reduces the energy consumption of mobile devices in wired‐cum‐wireless TCP networks. The proposed mechanism places an agent at the base station, which identifies the cause of packet losses in the underlying network. When the mobile device acts as a TCP source, it adjusts the size of the congestion window adaptively according to the cause of packet losses with the aids of the agent in order to improve the transmission performance. In addition, the proposed mechanism lets the communication device to stay in sleep mode after completing the transmission in order to reduce the energy consumption. As a result, the cooperation between the mobile device and the agent improves the transmission performance as well as the energy efficiency greatly. To evaluate the performance of the proposed mechanism, we analyzed the effect of TCP on the communication device for mobile devices and present a power model. With extensive simulations based on the power model, we demonstrate that the proposed mechanism significantly improves the transmission performance, and reduces the energy consumption over a wide range of both wired and wireless packet losses. Copyright © 2008 John Wiley & Sons, Ltd.     

SPEECH‐MAC: Special purpose energy‐efficient contention‐based hybrid MAC protocol for WSN and Zigbee network

Energy‐efficient Zigbee‐based wireless sensor network (WSN) occupies a major role in emergency‐based applications. The foremost drawback of such applications is maintaining the battery power because frequent changing is not possible in those conditions. In the earlier days, several researches created new model MAC protocols in terms of increase the lifetime of the WSN. But still, there is a research gap particularly in emergency applications. In order to improve the lifetime of such applications, we introduced a novel hybrid MAC protocol, namely, special purpose energy‐efficient contention‐based hybrid MAC (SPEECH‐MAC) protocol. This protocol includes dual hop concept considerably to save the energy. Both the single hop network and the dual hop networks are developed, and the results are analyzed. Prioritization mechanism for SPEECH‐MAC protocol is introduced to analyze the emergency conditions in detail. In summary, according to the simulation, the calculated parameters are total residual energy, end‐to‐end delay, packet drop, packet delivery ratio, and network throughput.     

A frequency‐aware data‐centric mechanism for wireless sensor networks

Wireless sensor networks (WSNs) are characterized by their low bandwidth, limited energy, and largely distributed deployment. To reduce the flooding overhead raised by transmitting query and data information, several data‐centric storage (DCS) mechanisms are proposed. However, the locations of these data‐centric nodes significantly impact the power consumption and efficiency for information queries and storage capabilities, especially in a multi‐sink environment. This paper proposes a novel dissemination approach, which is namely the dynamic data‐centric routing and storage mechanism (DDCRS), to dynamically determine locations of data‐centric nodes according to sink nodes' location and data collecting rate and automatically construct shared paths from data‐centric nodes to multiple sinks. To save the power consumption, the data‐centric node is changed when new sink nodes participate when the WSNs or some queries change their frequencies. The simulation results reveal that the proposed protocol outperforms existing protocols in terms of power conservation and power balancing. Copyright © 2009 John Wiley & Sons, Ltd.     

基于位置感知和代理的WSN多径路由方案

针对无线传感器网络(WSN)中多径路由的可靠性和能量效率问题,提出了一种基于代理和位置感知的多径路由发现方案(LABMR).事件节点根据位置信息,动态寻找其到Sink节点之间的特殊中间节点,来构建多径路由.利用移动代理来收集多径路由的局部拓扑结构信息,Sink节点根据代理收集的路由参数来计算路径权值,以此选择最优不相交路径.同时,对于信息的重要性差异,Sink节点选择单条或多条路径来传输数据,在保证传输可靠性的同时减少能耗.与现有的基于代理的多径路由(ABMR)方法相比,LABMP在数据包投递率、能量消耗、额外开销和延迟方面具有更好的性能.     

RAPS: a precision‐adaptive protocol towards improved data fidelity in wireless sensor networks

Achieving high data quality and efficient network resource utilization is two major design objectives of wireless sensor networks (WSNs). However, these two objectives are often conflictive. By allowing sensors to report sampled data at high rates, fine‐grained data quality can be obtained. However, the limited resources of a WSN make it difficult to support very high traffic rate. Therefore, the capability of adaptively adjusting sensor nodes' traffic‐generating rates on the basis of the availability of network resources and application requirements is critical. This issue has attracted much attention recently, and some work has been carried out. To achieve high data quality and improved utilization of network resources, in this paper, we propose rate‐based adaptive precision setting (RAPS) protocol, which works in a way that each sensor can adaptively adjust its traffic‐generating rate on the basis of the current network resources availability and application requirements. RAPS introduces the following two key factors into its design: application's precision requirement and packet arrival rate. Analytical and simulation results show that RAPS can achieve improved data quality while reducing packet delivery latency. Copyright © 2012 John Wiley & Sons, Ltd.     

An energy‐efficient utility‐based distributed data routing scheme for heterogenous sensor networks

A utility‐based distributed data routing algorithm is proposed and evaluated for heterogeneous wireless sensor networks. It is energy efficient and is based on a game‐theoretic heuristic load‐balancing approach. It runs on a hierarchical graph arranged as a tree with parents and children. Sensor nodes are considered heterogeneous in terms of their generated traffic, residual energy and data transmission rate and the bandwidth they provide to their children for communication. The proposed method generates a data routing tree in which child nodes are joined to parent nodes in an energy‐efficient way. The principles of the Stackelberg game, in which parents as leaders and children as followers, are used to support the distributive nature of sensor networks. In this context, parents behave cooperatively and help other parents to adjust their loads, while children act selfishly. Simulation results indicate the proposed method can produce on average more load‐balanced trees, resulting in over 30% longer network lifetime compared with the cumulative algorithm proposed in the literature. Copyright © 2014 John Wiley & Sons, Ltd.     

High energy‐efficient and privacy‐preserving secure data aggregation for wireless sensor networks

An efficient data process technology is needed for wireless sensor networks composed of many sensors with constrained communication, computational, and memory resources. Data aggregation is presented as an efficient and significant method to reduce transmitted data and prolong lifetime for wireless sensor networks. Meanwhile, many applications require preserving privacy for secure data aggregation. In this paper, we propose a high energy‐efficient and privacy‐preserving scheme for secure data aggregation. Because of the importance of communication overhead and accuracy, our scheme achieves less communication overhead and higher data accuracy besides providing for privacy preservation. For extensive simulations, we evaluate and conclude the performance of our high energy‐efficient and privacy‐preserving scheme. The conclusion shows that the high energy‐efficient and privacy‐preserving scheme provides better privacy preservation and is more efficient than existing schemes. Copyright © 2012 John Wiley & Sons, Ltd.     

An adaptive energy‐efficient framework for time‐constrained optical backbone networks

Power management has emerged as a challenge of paramount importance having strong social and financial impact in the community. The rapid growth of information and communication technologies made backbone networks a serious energy consumer. Concurrently, backbone networking is deemed as one of the most promising areas to apply energy efficient frameworks. One of the most popular energy efficient techniques, in the context of backbone networks, is to intentionally switch off nodes and links that are monitored underutilized. Having in mind that optical technology has thoroughly dominated modern backbone networks, the function of switching off techniques entails fast operation and rigorous decision‐making because of the tremendous speed of the underlying optical media. This paper addresses this challenge by introducing a novel, adaptive, and efficient power management scheme for large‐scale backbone networks. The proposed framework exploits traffic patterns and dynamics in order to effectively switch off the set of network entities in a periodic fashion. An adaptive decision‐making algorithm is presented to maximize the network energy gains with respect to time constraints as well as QoS guarantees. The conducted simulation results reveal considerable improvements when applying the proposed framework compared with other inflexible energy efficient schemes. Copyright © 2015 John Wiley & Sons, Ltd.     

Distributed fuzzy logic based energy‐aware and coverage preserving unequal clustering algorithm for wireless sensor networks

In an energy‐constrained wireless sensor networks (WSNs), clustering is found to be an effective strategy to minimize the energy depletion of sensor nodes. In clustered WSNs, network is partitioned into set of clusters, each having a coordinator called cluster head (CH), which collects data from its cluster members and forwards it to the base station (BS) via other CHs. Clustered WSNs often suffer from the hot spot problem where CHs closer to the BS die much early because of high energy consumption contributed by the data forwarding load. Such death of nodes results coverage holes in the network very early. In most applications of WSNs, coverage preservation of the target area is a primary measure of quality of service. Considering the energy limitation of sensors, most of the clustering algorithms designed for WSNs focus on energy efficiency while ignoring the coverage requirement. In this paper, we propose a distributed clustering algorithm that uses fuzzy logic to establish a trade‐off between the energy efficiency and coverage requirement. This algorithm considers both energy and coverage parameters during cluster formation to maximize the coverage preservation of target area. Further, to deal with hot spot problem, it forms unequal sized clusters such that more CHs are available closer to BS to share the high data forwarding load. The performance of the proposed clustering algorithm is compared with some of the well‐known existing algorithms under different network scenarios. The simulation results validate the superiority of our algorithm in network lifetime, coverage preservation, and energy efficiency.