Lightweight,latency‐aware routing for data compression in wireless sensor networks with heterogeneous traffics

In many applications and scenarios, sensors have to regularly report what they monitor from the environment and quickly notify the sink node of event occurrence in the sensing field. An in‐network data reduction technique, such as data aggregation and data compression, can help diminish the amount of data sent from sensors, which not only saves the network bandwidth but also preserves sensors' energy. However, such technique does not consider packet latency because of the aggregation or compression operation. When some sensors generate regular reports in lower data rates, their packets have to spend longer time to be aggregated or compressed, resulting in higher packet delays. Besides, when events occur, the network could suffer from instant congestion due to the generation of numerous event notifications. Motivated with the aforementioned observations, the paper develops a lightweight, latency‐aware routing for data compression (L2DC) scheme to reduce packet latency when applying the compression technique, to reduce the amount of data generated from sensors. L2DC gives event notifications a higher priority over regular reports and eliminates unnecessary notifications to avoid bursty network congestion. In addition, L2DC facilitates the data compression process by allowing each sensor to determine whether to keep packets for compression locally or to send them to a neighbor to be compressed in a distributed manner. Our L2DC scheme can be easily built on most ad hoc and sensor routing protocols because it provides auxiliary redundant packet elimination and relay node selection mechanisms to reduce packet latency. By using the ad hoc on‐demand distance vector protocol as the example, simulation results demonstrate the effectiveness of the L2DC scheme. Copyright © 2015 John Wiley & Sons, Ltd.     

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.     

Optimal placement and routing strategies for resilient two‐tiered sensor networks

In hierarchical sensor networks using relay nodes, sensor nodes are arranged in clusters and higher powered relay nodes can be used as cluster heads. The lifetime of such a network is determined primarily by the lifetime of the relay nodes. In this paper, we propose two new integer linear programs (ILPs) formulations for optimal data gathering, which maximize the lifetime of the upper tier relay node network. Unlike most previous approaches considered in the literature, our formulations can generate optimal solutions under the non‐flow‐splitting model. Experimental results demonstrate that our approach can significantly extend network lifetime, compared to traditional routing schemes, for the non‐flow‐splitting model. The lifetime can be further enhanced by periodic updates of the routing strategy based on the residual energy at each relay node. The proposed rescheduling scheme can be used to handle single or multiple relay node failures. We have also presented a very simple and straightforward algorithm for the placement of relay nodes. The placement algorithm guarantees that all the sensor nodes can communicate with at least one relay node and that the relay node network is at least 2‐connected. This means that failure of a single relay node will not disconnect the network, and data may be routed around the failed node. The worst case performance of the placement algorithm is bounded by a constant with respect to any optimum placement algorithm. Copyright © 2008 John Wiley & Sons, Ltd.     

On energy‐efficient aggregation routing and scheduling in IEEE 802.15.4‐based wireless sensor networks

In wireless sensor networks, continued operation of battery‐powered devices plays a crucial role particularly in remote deployment. The lifetime of a wireless sensor is primarily dependent upon battery capacity and energy efficiency. In this paper, reduction of the energy consumption of heterogeneous devices with different power and range characteristics is introduced in the context of duty scheduling, dynamic adjustment of transmission ranges, and the effects of IEEE 802.15.4‐based data aggregation routing. Energy consumption in cluster‐based networks is modeled as a mixed‐integer linear and nonlinear programming problem, an NP‐hard problem. The objective function provides a basis by which total energy consumption is reduced. Heuristics are proposed for cluster construction (Average Energy Consumption and the Maximum Number of Source Nodes) and data aggregation routing (Cluster‐based Data Aggregation Routing) such that total energy consumption is minimized. The simulation results demonstrate the effectiveness of balancing cluster size with dynamic transmission range. The heuristics outperform other modified existing algorithms by an average of 15.65% for cluster head assignment, by an average of 22.1% for duty cycle scheduling, and by up to 18.6% for data aggregation routing heuristics. A comparison of dynamic and fixed transmission ranges for IEEE 802.15.4‐based wireless sensor networks is also provided. Copyright © 2012 John Wiley & Sons, Ltd.     

Self‐adaptive routing protocols for integrating cellular networks,WLANs, and MANETs

A growing need to have ubiquitous connectivity has motivated our research to provide continuous connection between various wireless platforms such as cellular networks, wireless local area networks (WLANs), and mobile ad hoc networks (MANETs). In this paper, we consider integration at the routing layer and propose two adaptable routing protocols (IRP‐RD and IRP‐PD) that exploit topology information stored at the fixed network components (cellular base stations and WLAN access points) for the route discovery and maintenance processes. Our proposed protocols can provide connectivity to the cellular network and/or WLAN hotspots through multihop routing, while differ in the gateway discovery approach used. In IRP‐RD, multihop routes to gateways to the cellular network or WLAN hot spots are discovered on demand, while in IRP‐PD out of coverage users proactively maintain routes to the gateways. Furthermore, proposed protocols can be used in any heterogeneous scenario, combining a cellular network and WLANs operating in infrastructure or ad hoc (MANET) mode. We provide simulation results that demonstrate the effectiveness of the proposed integrated routing protocols and show the advantages and drawbacks of each gateway discovery approach in different heterogeneous scenarios. Copyright © 2006 John Wiley & Sons, Ltd.     

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.     

PRDA: polynomial regression‐based privacy‐preserving data aggregation for wireless sensor networks

In wireless sensor networks, data aggregation protocols are used to prolong the network lifetime. However, the problem of how to perform data aggregation while preserving data privacy is challenging. This paper presents a polynomial regression‐based data aggregation protocol that preserves the privacy of sensor data. In the proposed protocol, sensor nodes represent their data as polynomial functions to reduce the amount of data transmission. In order to protect data privacy, sensor nodes secretly send coefficients of the polynomial functions to data aggregators instead of their original data. Data aggregation is performed on the basis of the concealed polynomial coefficients, and the base station is able to extract a good approximation of the network data from the aggregation result. The security analysis and simulation results show that the proposed scheme is able to reduce the amount of data transmission in the network while preserving data privacy. Copyright © 2013 John Wiley & Sons, Ltd.     

多基站数据聚合无线传感器网络中的最大生命期路由

研究了多基站数据聚合无线传感器网络中的最大生命期路由问题.首先证明该类问题具有NP-hard性质,然后提出一种基于最小生成森林的启发式算法,并采用次梯度方法设计了分布式算法,最后通过大量的仿真实验分析所提路由算法性能,并给出分布式算法的收敛性能.     

MDPA: multidimensional privacy‐preserving aggregation scheme for wireless sensor networks

In this paper, we propose a novel multidimensional privacy‐preserving data aggregation scheme for improving security and saving energy consumption in wireless sensor networks (WSNs). The proposed scheme integrates the super‐increasing sequence and perturbation techniques into compressed data aggregation, and has the ability to combine more than one aggregated data into one. Compared with the traditional data aggregation schemes, the proposed scheme not only enhances the privacy preservation in data aggregation, but also is more efficient in terms of energy costs due to its unique multidimensional aggregation. Extensive analyses and experiments are given to demonstrate its energy efficiency and practicability. Copyright © 2009 John Wiley & Sons, Ltd.     

无线传感器网络中数据汇聚方案的研究

针对分簇网络拓扑结构中簇头节点能量消耗过快,综合考虑了节点的密集程度和剩余能量,采用节点自适应的簇头选择算法,选择部署越集中和剩余能量越大的节点作为簇头节点。同时节点引入了新鲜性信息熵模型,通过比较前后两次接收到的数据的差别程度,设置一个参考阈值来判断是否转发数据。这种数据汇聚算法有效地降低了数据的冗余,减少了能量消耗,增加了带宽利用率,延长了网络的生存期。     

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.     

Optimal power‐aware relay placement for cooperative wireless sensor networks

We study the problem of optimizing the symbol error probability (SEP) performance of cluster‐based cooperative wireless sensor networks. Recent studies in literature show that an efficient relay selection protocol based on simple geographical information of the nodes to execute cooperative diversity can significantly improve the SEP performance at the destination of such networks. As well, similar line of research on optimal power allocation (for the source and relay nodes) can be found in literature. However, to achieve the best SEP performance at the destination of a cooperative wireless sensor network, joint optimization of power allocation and relay placement should be accomplished. To this aim, we reformulate the SEP of a multi‐hop cooperative communication in a general form and optimize transmitted power level and relay placement simultaneously. This analysis is developed for both amplify‐and‐forward and decode‐and‐forward relaying protocols. Simulation results demonstrate that the proposed joint optimization can effectively improve the SEP performance of the network. Copyright © 2013 John Wiley & Sons, Ltd.     

EFFORT: energy‐efficient opportunistic routing technology in wireless sensor networks

The utilization of limited energy in wireless sensor networks (WSNs) is the critical concern, whereas the effectiveness of routing mechanisms substantially influence energy usage. We notice that two common issues in existing specific routing schemes for WSNs are that (i) a path may traverse through a specific set of sensors, draining out their energy quickly and (ii) packet retransmissions over unreliable links may consume energy significantly. In this paper, we develop an energy‐efficient routing scheme (called EFFORT) to maximize the amount of data gathered in WSNs before the end of network lifetime. By exploiting two natural advantages of opportunistic routing, that is, the path diversity and the improvement of transmission reliability, we propose a new metric that enables each sensor to determine a suitable set of forwarders as well as their relay priorities. We then present EFFORT, a routing protocol that utilizes energy efficiently and prolongs network lifetime based on the proposed routing metric. Simulation results show that EFFORT significantly outperforms other routing protocols. Copyright © 2011 John Wiley & Sons, Ltd.     

GWO‐C: Grey wolf optimizer‐based clustering scheme for WSNs

A wireless sensor network (WSN) is a prominent technology that could assist in the fourth industrial revolution. Sensor nodes present in the WSNs are functioned by a battery. It is impossible to recharge or replace the battery, hence energy is the most important resource of WSNs. Many techniques have been devised and used over the years to conserve this scarce resource of WSNs. Clustering has turned out to be one of the most efficient methods for this purpose. This paper intends to propose an efficient technique for election of cluster heads in WSNs to increase the network lifespan. For the achievement of this task, grey wolf optimizer (GWO) has been employed. In this paper, the general GWO has been modified to cater to the specific purpose of cluster head selection in WSNs. The objective function for the proposed formulation considers average intra‐cluster distance, sink distance, residual energy, and CH balancing factor. The simulations are carried out in diverse conditions. On comparison of the proposed protocol, ie, GWO‐C protocol with some well‐known clustering protocols, the obtained results prove that the proposed protocol outperforms with respect to the consumption of the energy, throughput, and the lifespan of the network. The proposed protocol forms energy‐efficient and scalable clusters.     

Energy‐efficient and localized lossy data aggregation in asynchronous sensor networks

In wireless sensor networks, most data aggregation scheduling methods let all nodes aggregate data in every time instance. It is not energy efficient and practical because of link unreliability and data redundancy. This paper proposes a lossy data aggregation (LDA) scheme to reduce traffic and save energy. LDA selects partial child nodes to sample data at partial time slots and allows estimated aggregation at parent nodes or a root in a network. We firstly consider that all nodes sample data synchronously and find that the error between the real value of a physical parameter and that measured by LDA is bounded respectively with and without link unreliability. Detailed analysis is given on error bound when a confidence level is previously assigned to the root by a newly designed algorithm. Thus, each parent can determine the minimum number of child nodes needed to achieve its assigned confidence level. We then analyze a probability to bound the error with a confidence level previously assigned to the root when all nodes sample data asynchronously. An algorithm then is designed to implement our data aggregation under asynchronization. Finally, we implement our experiment on the basis of real test‐beds to prove that the scheme can save more energy than an existing algorithm for node selection, Distributive Online Greedy (DOG). Copyright © 2012 John Wiley & Sons, Ltd.     

e‐LiteSense: Self‐adaptive energy‐aware data sensing in WSN environments

Currently deployed in a wide variety of applicational scenarios, wireless sensor networks (WSNs) are typically a resource‐constrained infrastructure. Consequently, characteristics such as WSN adaptability, low‐overhead, and low‐energy consumption are particularly relevant in dynamic and autonomous sensing environments where the measuring requirements change and human intervention is not viable. To tackle this issue, this article proposes e‐LiteSense as an adaptive, energy‐aware sensing solution for WSNs, capable of auto‐regulate how data are sensed, adjusting it to each applicational scenario. The proposed adaptive scheme is able to maintain the sensing accuracy of the physical phenomena, while reducing the overall process overhead. In this way, the adaptive algorithm relies on low‐complexity rules to establish the sensing frequency weighting the recent drifts of the physical parameter and the levels of remaining energy in the sensor. Using datasets from WSN operational scenarios, we prove e‐LiteSense effectiveness in self‐regulating data sensing accurately through a low‐overhead process where the WSN energy levels are preserved. This constitutes a step‐forward for implementing self‐adaptive energy‐aware data sensing in dynamic WSN environments.     

A secure channel code‐based scheme for privacy preserving data aggregation in wireless sensor networks

Data aggregation is an efficient method to reduce the energy consumption in wireless sensor networks (WSNs). However, data aggregation schemes pose challenges in ensuring data privacy in WSN because traditional encryption schemes cannot support data aggregation. Homomorphic encryption schemes are promising techniques to provide end to end data privacy in WSN. Data reliability is another main issue in WSN due to the errors introduced by communication channels. In this paper, a symmetric additive homomorphic encryption scheme based on Rao‐Nam scheme is proposed to provide data confidentiality during aggregation in WSN. This scheme also possess the capability to correct errors present in the aggregated data. The required security levels can be achieved in the proposed scheme through channel decoding problem by embedding security in encoding matrix and error vector. The error vectors are carefully designed so that the randomness properties are preserved while homomorphically combining the data from different sensor nodes. Extensive cryptanalysis shows that the proposed scheme is secure against all attacks reported against private‐key encryption schemes based on error correcting codes. The performance of the encryption scheme is compared with the related schemes, and the results show that the proposed encryption scheme outperforms the existing schemes.     

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.     

A reliable and energy‐efficient routing protocol for underwater wireless sensor networks

Recently, underwater wireless sensor networks (UWSNs) have attracted much research attention to support various applications for pollution monitoring, tsunami warnings, offshore exploration, tactical surveillance, etc. However, because of the peculiar characteristics of UWSNs, designing communication protocols for UWSNs is a challenging task. Particularly, designing a routing protocol is of the most importance for successful data transmissions between sensors and the sink. In this paper, we propose a reliable and energy‐efficient routing protocol, named R‐ERP²R (Reliable Energy‐efficient Routing Protocol based on physical distance and residual energy). The main idea behind R‐ERP²R is to utilize physical distance as a routing metric and to balance energy consumption among sensors. Furthermore, during the selection of forwarding nodes, link quality towards the forwarding nodes is also considered to provide reliability and the residual energy of the forwarding nodes to prolong network lifetime. Using the NS‐2 simulator, R‐ERP²R is compared against a well‐known routing protocol (i.e. depth‐based routing) in terms of network lifetime, energy consumption, end‐to‐end delay and delivery ratio. The simulation results proved that R‐ERP²R performs better in UWSNs.Copyright © 2012 John Wiley & Sons, Ltd.     

MAX–MIN aggregation in wireless sensor networks: mechanism and modeling

In‐network aggregation is crucial in the design of a wireless sensor network (WSN) due to the potential redundancy in the data collected by sensors. Based on the characteristics of sensor data and the requirements of WSN applications, data can be aggregated by using different functions. MAX—MIN aggregation is one such aggregation function that works to extract the maximum and minimum readings among all the sensors in the network or the sensors in a concerned region. MAX—MIN aggregation is a critical operation in many WSN applications. In this paper, we propose an effective mechanism for MAX—MIN aggregation in a WSN, which is called Sensor MAX—MIN Aggregation (SMMA). SMMA aggregates data in an energy‐efficient manner and outputs the accurate aggregate result. We build an analytical model to analyze the performance of SMMA as well as to optimize its parameter settings. Simulation results are used to validate our models and also evaluate the performance of SMMA. Copyright © 2010 John Wiley & Sons, Ltd.