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.     

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.     

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.     

DRP: An energy‐efficient routing protocol for underwater sensor networks

The features of transmissions in underwater sensor networks (UWSNs) include lower transmission rate, longer delay time, and higher power consumption when compared with terrestrial radio transmissions. The negative effects of transmission collisions deteriorate in such environments. Existing UWSN routing protocols do not consider the transmission collision probability differences resulting from different transmission distances. In this paper, we show that collision probability plays an important role in route selection and propose an energy‐efficient routing protocol (DRP), which considers the distance‐varied collision probability as well as each node's residual energy. Considering these 2 issues, DRP can find a path with high successful transmission rate and high‐residual energy. In fact, DRP can find the path producing the longest network lifetime, which we have confirmed through theoretical analysis. To the best of our knowledge, DRP is the first UWSN routing protocol that uses transmission collision probability as a factor in route selection. Simulation results verify that DRP extends network lifetime, increases network throughput, and reduces end‐to‐end delay when compared with solutions without considering distance‐varied collision probability or residual energy.     

Lifetime evaluation in energy‐efficient rectangular ad hoc wireless networks

Ad hoc wireless network nodes are typically battery‐powered, therefore energy limit is one of the critical constraints of ad hoc wireless networks' development. This paper evaluates the network lifetime of a rectangular network model that achieves energy efficiency by optimizing the node radio range based on the geographical adaptive fidelity (GAF) topology management protocol (Proceedings of ACMMobil'01, July 2001; 70–84). We derive the optimal transmission range of nodes and analyze both static and dynamic traffic scenarios in both equal‐grid and adjustable‐grid rectangular GAF models, where the results show that the adjustable‐grid model saves 78.1% energy in comparison with the minimum energy consumption of equal‐grid model. The impact of node density on both equal‐grid and adjustable‐grid models is investigated to achieve grid‐lifetime balance among all grids to optimize the entire network lifetime. The lifetime estimation results show that without node density control the adjustable‐grid model prolongs the entire network lifetime by a factor of 4.2 compared with the equal‐grid model. Furthermore, the adjustable‐grid model with node density control is able to prolong the entire network lifetime by a factor of 6 compared with the equal‐grid model. Copyright © 2010 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.     

On the eNB‐based energy‐saving cooperation techniques for LTE access networks

Energy efficiency is one of the top priorities for future cellular networks, which could be accomplished by implementing cooperative mechanisms. In this paper, we propose three evolved node B (eNB)‐centric energy‐saving cooperation techniques for long‐term evolution (LTE) systems. These techniques, named as intra‐network, inter‐network, and joint cooperation, involve traffic‐aware intelligent cooperation among eNBs belonging to the same or different networks. Our proposed techniques dynamically reconfigure LTE access networks in real time utilizing less number of active eNBs and thus, achieve energy savings. In addition, these techniques are distributed and self‐organizing in nature. Analytical models for evaluating switching dynamics of eNBs under these cooperation mechanisms are also formulated. We thoroughly investigate the proposed system under different numbers of cooperating networks, traffic scenarios, eNB power profiles, and their switching thresholds. Optimal energy savings while maintaining quality of service is also evaluated. Results indicate a significant reduction in network energy consumption. System performance in terms of network capacity utilization, switching statistics, additional transmit power, and eNB sleeping patterns is also investigated. Finally, a comprehensive comparison with other works is provided for further validation. Copyright © 2013 John Wiley & Sons, Ltd.     

Link optimization for energy‐constrained wireless networks with packet retransmissions

With the objective to minimize the energy consumption for packet based communications in energy‐constrained wireless networks, this paper establishes a theoretical model for the joint optimization of the parameters at the physical layer and data link layer. Multilevel quadrature amplitude modulation (MQAM) and automatic repeat request (ARQ) techniques are considered in the system model. The optimization problem is formulated into a three dimensional nonlinear integer programming (NIP) problem with the modulation order, packet size, and retransmission limit as variables. For the retransmission limit, a simple search method is applied to degenerate the three dimensional problem into a two dimensional NIP problem, for which two optimization algorithms are proposed. One is the successive quadratic programming (SQP) algorithm, combining with the continuous relaxation based branch‐and‐bound method, which can obtain the global optimal solution since the continuous relaxation problem is proved to be hidden convex. The other is a low‐complexity sub‐optimal iterative algorithm, combining with the nearest‐neighboring method, which can be implemented with a polynomial complexity. Numerical examples are given to illustrate the optimization solution, which suggests that the joint optimization of the physical/data link layer parameters contributes noticeably to the energy saving in energy‐constrained wireless networks. Copyright © 2010 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.     

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.     

Load‐balanced data gathering in Internet of Things using an energy‐aware cuckoo‐search algorithm

This paper deals with the lifetime problem in the Internet of Things. We first propose an efficient cluster‐based scheme named “Cuckoo‐search Clustering with Two‐hop Routing Tree (CC‐TRT)” to develop a two‐hop load‐balanced data aggregation routing tree in the network. CC‐TRT uses a modified energy‐aware cuckoo‐search algorithm to fairly select the best cluster head (CH) for each cluster. The applied cuckoo‐search algorithm makes the CH role to rotate between different sensors round by round. Subsequently, we extend the CC‐TRT scheme to present two methods for constructing multi‐hop data aggregation routing trees, named “Cuckoo‐search Clustering with Multi‐Hop Routing Tree (CC‐MRT)” and “Cuckoo‐search Clustering with Weighted Multi‐hop Routing Tree (CC‐WMRT).” Both CC‐MRT and CC‐WMRT rely on a two‐level structure; they not only use an energy‐aware cuckoo‐search algorithm to fairly select the best CHs but also adopt a load‐balanced high‐level routing tree to route the aggregated data of CHs to the sink node. However, CC‐WMRT slightly has a better performance thanks to its low‐level routing strategy. As an advantage, the proposed schemes balance the energy consumption among different sensors. Numerical results show the efficiency of the CC‐TRT, CC‐MRT, and CC‐WMRT algorithms in terms of the number of transmissions, remaining energy, energy consumption variance, and network lifetime.     

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.     

Genetic simulated annealing‐based coverage‐enhancing algorithm for multimedia directional sensor networks

Multimedia directional sensor network is one kind of directional sensing systems, whose coverage scheme is quite different from the omnidirectional sensing system. And it is often used in atrocious environmental surveillance, such as nuclear contaminative areas, where people can hardly arrive. In this paper, a genetic simulated annealing‐based coverage‐enhancing algorithm (GSACEA) is proposed as a coverage‐enhancing method in multimedia directional sensor networks. Firstly, GSACEA combines the genetic algorithm and simulated annealing algorithm into an algorithm with new architecture. Then, the proposed GSACEA is applied for the purpose of coverage‐enhancing in the case of directional sensor networks with rotational direction‐adjustable model. Finally, after series actions of genetic simulated annealing, the proposed method can find the approximate solution to the best area coverage rate. And according to the results of simulations, which compared the proposed method with several other classic coverage‐enhancing methods in directional sensor networks, it could be concluded that GSACEA can achieve the highest area coverage rate of directional sensor networks and reduce the iterative computing times simultaneously. Copyright © 2014 John Wiley & Sons, Ltd.     

RECA: Referenced energy‐based CDS algorithm in wireless sensor networks

Connected dominating sets (CDS) can be used to form virtual backbones for the hierarchical routing to save energy in the wireless sensor networks. The existing algorithms for CDS can only be used to the topologies that have larger vertex connective degrees. Besides, most of them do not consider the energy characteristics of the virtual backbones constructed by the dominating sets. In this paper, a referenced energy‐based CDS algorithm (RECA) is proposed, which can generate smaller CDS in random topologies without the limitation of vertex connective degrees. At the same time, the algorithm introduces Referenced Energy as a parameter for nodes when making the decision whether they are chosen to be the dominators or not. Therefore, as the experimental results show, the energy characteristic of the dominating set is improved and routing in the virtual backbones constructed by such CDSs will have a better performance. Copyright © 2009 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.     

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.     

Utility‐driven construction of balanced data routing trees in wireless sensor networks

In wireless sensor networks, achieving load balancing in an energy‐efficient manner to improve the network lifetime as much as possible is still a challenging problem because in such networks, the only energy resource for sensor nodes is their battery supplies. This paper proposes a game theoretical‐based solution in the form of a distributed algorithm for constructing load‐balanced routing trees in wireless sensor networks. In our algorithm, load balancing is realized by adjusting the number of children among parents as much as possible, where child adjustment is considered as a game between the parents and child nodes; parents are considered as cooperative players, and children are considered as selfish players. The gained utility by each node is determined by means of some utility functions defined per role, which themselves determine the behavior of nodes in each role. When the game is over, each node gains the maximum benefit on the basis of its utility function, and the balanced tree is constructed. The proposed method provides additional benefits when in‐network aggregation is applied. Analytical and simulation results are provided, demonstrating that our proposed algorithm outperform two recently proposed benchmarking algorithms [1, 2], in terms of time complexity and communication overhead required for constructing the load‐balanced routing trees. Copyright © 2012 John Wiley & Sons, Ltd.     

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.     

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.     

Time‐aware and energy‐efficient opportunistic routing with residual energy collection in wireless sensor networks

In 1‐dimensional queue wireless sensor networks, how to balance end‐to‐end latency and energy consumption is a challenging problem. However, traditional best path routing and existing opportunistic routing protocols do not address them well because relay hop counts are usually much more, and the link appears more unreliable compared with general mesh topology. In this work, we formulate these 2 problems as a multiobjective optimization problem. Specifically, we first classify network packets into types of time tolerant and time critical and introduce a residual energy collection mechanism of neighboring nodes for forwarder set selection. We then propose a time‐aware and energy‐efficient opportunistic routing protocol (TE‐OR) to optimize energy consumption and to reduce latency for time‐critical packets. We evaluate TE‐OR by different parameters and compare it with existing protocols. The performance results show that TE‐OR achieves a trade‐off between energy consumption and time delay and balances energy consumption among nodes while guaranteeing the latency of time‐critical packets is minimized.