Flow-balanced routing for multi-hop clustered wireless sensor networks

Power efficiency and coverage preservation are two important performance metrics for a wireless sensor network. However, there is scarcely any protocol to consider them at the same time. In this paper, we propose a flow-balanced routing (FBR) protocol for multi-hop clustered wireless sensor networks that attempts to achieve both power efficiency and coverage preservation. The proposed protocol consists of four algorithms, one each for network clustering, multi-hop backbone construction, flow-balanced transmission, and rerouting. The proposed clustering algorithm groups several sensors into one cluster on the basis of overlapping degrees of sensors. The backbone construction algorithm constructs a novel multi-level backbone, which is not necessarily a tree, using the cluster heads and the sink. Furthermore, the flow-balanced routing algorithm assigns the transferred data over multiple paths from the sensors to the sink in order to equalize the power consumption of sensors. Lastly, the rerouting algorithm reconstructs the network topology only in a place where a head drops out from the backbone due to the head running out of its energy. Two metrics called the network lifetime and the coverage lifetime are used to evaluate the performance of FBR protocol in comparison with previous ones. The simulation results show that FBR yields both much longer lifetime and better coverage preservation than previous protocols. For example, FBR yields more than twice network lifetime and better coverage preservation than a previous efficient protocol, called the coverage-preserving clustering protocol (CPCP) [18], when the first sensor dies and the network coverage is kept at 100%, respectively.     

分簇无线传感器网络中的频谱感知方案

无线传感器网络中的节点众多,节点之间仅依靠频谱资源管理机制分配的频段进行数据传输会造成频谱资源紧张。针对这一问题,将认知无线电技术引入分簇的无线传感器网络,并且考虑分簇无线传感器网络节点的能量受限问题提出了一种节能的频谱感知方案。此方案首先让簇内的节点采取双门限能量检测的协作频谱感知方法,在满足目标检测概率和虚警概率的条件下,确定进行频谱感知的最少节点数,降低系统能耗。其次,通过选择合适的簇内节点进行频谱感知,使簇内节点的能耗均衡,簇的生命周期得到延长。     

无线传感器网络能量均衡分簇路由协议

针对LEACH协议存在的3大问题:簇头选举时未考虑节点剩余能量、频繁成簇造成了大量额外能耗以及欠缺对簇间能耗均衡的考虑,提出了能量有效分簇路由协议(LEACH-improved).该协议中,首轮成簇后网络中簇的分布和数量将保持不变,以后每轮各簇的簇头由上一轮簇头结合节点的能量水平来指定,借鉴泛洪算法的思想,在簇间建立多...     

Firework inspired load balancing approach for wireless sensor networks

Wireless Networks - In Wireless Sensor Networks (WSNs), where power consumption is a huge concern, the improvement of the network’s lifetime is an area of constant study and innovation. The...     

A game theoretic approach to balancing energy consumption in heterogeneous wireless sensor networks

Energy balancing is an effective technique in enhancing the lifetime of a wireless sensor network (WSN). Specifically, balancing the energy consumption among sensors can prevent losing some critical sensors prematurely due to energy exhaustion so that the WSN's coverage can be maintained. However, the heterogeneous hostile operating conditions—different transmission distances, varying fading environments, and distinct residual energy levels—have made energy balancing a highly challenging task. A key issue in energy balancing is to maintain a certain level of energy fairness in the whole WSN. To achieve energy fairness, the transmission load should be allocated among sensors such that, regardless of a sensor's working conditions, no sensor node should be unfairly overburdened. In this paper, we model the transmission load assignment in WSN as a game. With our novel utility function that can capture realistic sensors’ behaviors, we have derived the Nash equilibrium (NE) of the energy balancing game. Most importantly, under the NE, while each sensor can maximize its own payoff, the global objective of energy balancing can also be achieved. Moreover, by incorporating a penalty mechanism, the delivery rate and delay constraints imposed by the WSN application can be satisfied. Through extensive simulations, our game theoretic approach is shown to be effective in that adequate energy balancing is achieved and, consequently, network lifetime is significantly enhanced. Copyright © 2012 John Wiley & Sons, Ltd.     

Load balancing clustering and routing for IoT-enabled wireless sensor networks

Internet of things (IoT) devices are equipped with a number of interconnected sensor nodes that relies on ubiquitous connectivity between sensor devices to optimize information automation processes. Because of the extensive deployments in adverse areas and unsupervised nature of wireless sensor networks (WSNs), energy efficiency is a significant aim in these networks. Network survival time can be extended by optimizing its energy consumption. It has been a complex struggle for researchers to develop energy-efficient routing protocols in the field of WSNs. Energy consumption, path reliability and Quality of Service (QoS) in WSNs became important factors to be focused on enforcing an efficient routing strategy. A hybrid optimization technique presented in this paper is a combination of fuzzy c-means and Grey Wolf optimization (GWO) techniques for clustering. The proposed scheme was evaluated on different parameters such as total energy consumed, packet delivery ratio, packet drop rate, throughput, delay, remaining energy and total network lifetime. According to the results of the simulation, the proposed scheme improves energy efficiency and throughput by about 30% and packet delivery ratio and latency by about 10%, compared with existing protocols such as Chemical Reaction Approach based Cluster Formation (CHRA), Hybrid Optimal Based Cluster Formation (HOBCF), GWO-based clustering (GWO-C) and Cat Swarm Optimization based Energy-Efficient Reliable sectoring Scheme with prediction algorithms (P_CSO_EERSS). The study concludes that the protocol suitable for creating IoT monitoring system network lifetime is an important criteria.     

Load balancing techniques for lifetime maximizing in wireless sensor networks

Energy consumption has been the focus of many studies on Wireless Sensor Networks (WSN). It is well recognized that energy is a strictly limited resource in WSNs. This limitation constrains the operation of the sensor nodes and somehow compromises the long term network performance as well as network activities. Indeed, the purpose of all application scenarios is to have sensor nodes deployed, unattended, for several months or years.This paper presents the lifetime maximization problem in “many-to-one” and “mostly-off” wireless sensor networks. In such network pattern, all sensor nodes generate and send packets to a single sink via multi-hop transmissions. We noticed, in our previous experimental studies, that since the entire sensor data has to be forwarded to a base station via multi-hop routing, the traffic pattern is highly non-uniform, putting a high burden on the sensor nodes close to the base station.In this paper, we propose some strategies that balance the energy consumption of these nodes and ensure maximum network lifetime by balancing the traffic load as equally as possible. First, we formalize the network lifetime maximization problem then we derive an optimal load balancing solution. Subsequently, we propose a heuristic to approximate the optimal solution and we compare both optimal and heuristic solutions with most common strategies such as shortest-path and equiproportional routing. We conclude that through the results of this work, combining load balancing with transmission power control outperforms the traditional routing schemes in terms of network lifetime maximization.     

A new load balancing and data collection algorithm for energy saving in wireless sensor networks

Data gathering is a major function of many applications in wireless sensor networks. The most important issue in designing a data gathering algorithm is how to save energy of sensor nodes while meeting the requirements of special applications or users. Wireless sensor networks are characterized by centralized data gathering, multi-hop communication and many to one traffic pattern. These three characteristics can lead to severe packet collision, network congestion and packet loss, and even result in hot-spots of energy consumption thus causing premature death of sensor nodes and entire network. In this paper, we propose a load balance data gathering algorithm that classifies sensor nodes into different layers according to their distance to sink node and furthermore, divides the sense zone into several clusters. Routing trees are established between sensor node and sink depending on the energy metric and communication cost. For saving energy consumption, the target of data aggregation scheme is adopted as well. Analysis and simulation results show that the algorithm we proposed provides more uniform energy consumption among sensor nodes and can prolong the lifetime of sensor networks.     

Prediction-based energy map for wireless sensor networks

A fundamental issue in the design of a wireless sensor network is to devise mechanisms to make efficient use of its energy, and thus, extend its lifetime. The information about the amount of available energy in each part of the network is called the energy map and can be useful to increase the lifetime of the network. In this paper, we address the problem of constructing the energy map of a wireless sensor network using prediction-based approach. Simulation results compare the performance of a prediction-based approach with a naive one in which no prediction is used. Results show that the prediction-based approach outperforms the naive in a variety of parameters. We also investigate the possibility of sampling the energy information in some nodes in the network in order to diminish the number of energy information packets. Results show that the use of sampling techniques produce more constant error curves.     

An adaptive-weighted two-dimensional data aggregation algorithm for clustered wireless sensor networks

In this paper, an Adaptive-Weighted Time-Dimensional and Space-Dimensional （AWTDSD） data aggregation algorithm for a clustered sensor network is proposed for prolonging the lifetime of the network as well as improving the accuracy of the data gathered in the network. AWTDSD contains three phases： （1） the time-dimensional aggregation phase for eliminating the data redundancy; （2） the adaptive-weighted aggregation phase for further aggregating the data as well as improving the accuracy of the aggregated data; and （3） the space-dimensional aggregation phase for reducing the size and the amount of the data transmission to the base station. AWTDSD utilizes the correlations between the sensed data for reducing the data transmission and increasing the data accuracy as well. Experimental result shows that AWTDSD can not only save almost a half of the total energy consumption but also greatly increase the accuracy of the data monitored by the sensors in the clustered network.     

Adaptive and dual data-communication trust scheme for clustered wireless sensor networks

In wireless sensor networks, trust management schemes are designed to preserve them against misbehavior of malicious sensor nodes. These schemes observe the behavior of nodes, check their conformity to what is expected, compute and assign them trust values, and avoid any interaction with untrustworthy nodes. In this paper, we introduce Adaptive and dual Data-Communication Trust scheme (ADCT) for clustered wireless sensor networks to effectively deal with untrustworthy nodes. Unlike prior works, we propose an adaptive trust function to assess the direct trust between nodes according to the application’s requirement in terms of trust severity. We also consider data trust to cope with untrustworthy nodes during the data collection despite their communication capabilities. Moreover, we use the duality data-communication trust to deal with untrustworthy recommendations when building cluster-member’s feedback at the cluster-head level. Theoretical analysis and simulation show that the trust mechanism presented in this paper provides a better cooperation with the same or even lower communication overhead compared to the latest trust management schemes proposed for clustered wireless sensor networks.     

Relocation routing for energy balancing in mobile sensor networks

Wireless sensor networks (WSNs) have been widely investigated in the past decades because of its applicability in various extreme environments. As sensors use battery, most works on WSNs focus on energy efficiency issues (e.g., local energy balancing problems) in statically deployed WSNs. Few works have paid attention to the global energy balancing problem for the scenario that mobile sensor nodes can move freely. In this paper, we propose a new routing protocol called global energy balancing routing protocol (GEBRP) based on an active network framework and node relocation in mobile sensor networks. This protocol achieves global energy efficiency by repairing coverage holes and replacing invalid nodes dynamically. Simulation and experiment results demonstrate that the proposed GEBRP achieves superior performance over the existing scheme. In addition, we analyze the delay performance of GEBRP and study how the delay performance is affected by various system parameters.Copyright © 2013 John Wiley & Sons, Ltd.     

Trust evaluation method for clustered wireless sensor networks based on cloud model

Trust Management has been proved to be an effective method to detect malicious nodes and ensure security in Wireless Sensor Networks (WSNs). While, most existing trust management methods are not good at dealing with uncertainty of trust relationship such as randomness, fuzziness in WSNs, which leads to inaccurate trust metric. In this paper, a trust evaluation method for clustered wireless sensor networks based on cloud model is proposed and evaluated, which implements the conversion between qualitative and quantitative of sensor nodes’ trust metrics in order to achieve better trust evaluation. Firstly, the method considers multi-factors including communication factor, message factor and energy factor and builds mathematical model for each trust factor to get factor trust cloud. Secondly, immediate trust cloud is calculated by assigning adjustive weights for each factor trust cloud and combining them. Thirdly, recommendation trust cloud and immediate trust cloud are synthesized according to time sensitive factor in order to get final trust cloud. Furthermore, the final trust cloud of sensor node is converted to trust grade by trust cloud decision-making. Verification Experiments manifest that the proposed method has feasibility and accuracy in the aspect of evaluating sensor nodes’ trust. Moreover, comparison experiments under different attacks show that our method is sensitive to multiple attacks, it outperforms other trust evaluation methods not only in the accuracy of detecting malicious nodes, but also in the tolerance of abnormal conditions.     

Radio range adjustment for energy efficient wireless sensor networks

In wireless ad hoc sensor networks, energy use is in many cases the most important constraint since it corresponds directly to operational lifetime. Topology management schemes such as GAF put the redundant nodes for routing to sleep in order to save the energy. The radio range will affect the number of neighbouring nodes, which collaborate to forward data to a base station or sink. In this paper we study a simple linear network and deduce the relationship between optimal radio range and traffic. We find that half of the power can be saved if the radio range is adjusted appropriately compared with the best case where equal radio ranges are used.     

一种能耗均衡的无线传感器网络路由算法

为了延长采用电池供电的无线传感器网络的生命周期,提出了一种综合考虑单个节点能耗和节点传输信息至汇集节点所需总能耗的路由算法.该算法首先根据网络中节点到汇集节点从小到大的距离顺序选择待规划节点,然后计算各对应候选节点的评价参数,该参数由单节点能耗和节点传输信息至汇集节点所需总能耗加权得到,最后选择评价参数最小的候选节点作为待规划节点的中继节点.仿真结果表明,该算法的生命周期明显长于LEACH(Low Energy Adaptive Clustering Hier-archy)算法.     

Rendezvous-based data dissemination for supporting mobile sinks in multi-hop clustered wireless sensor networks

In wireless sensor networks, a clustering-based technique is considered as an efficient approach for supporting mobile sinks without using position information. It exploits a Backbone-based Virtual Infrastructure (BVI) which uses only cluster heads (CHs) to construct routing structures. Since sensor nodes have constrained energy and are failure-prone, the effective design of both a clustering structure to construct a BVI and a routing protocol in the BVI is an important issue to achieve energy-efficient and reliable data delivery. However, since previous studies use one-hop clustering for a BVI, they are not robust against node and link failures and thus leading low data delivery ratio. They also use flooding-based routing protocols in a BVI and thus leading high energy consumption. Thus, in this paper, we propose a rendezvous-based data dissemination protocol based on multi-hop clustering (RDDM). Since RDDM uses a multi-hop clustering to provide enough backup sensor nodes to substitute a CH and enough backup paths between neighbor CHs, it can provide high robustness against node and link failures. By using a rendezvous CH, RDDM constructs routing paths from source nodes to mobile sinks without flooding in our BVI and thus can save energy of sensor nodes. By considering movement types of sinks, RDDM finds out a shorter path between a source node and a mobile sink through signaling only between neighbor CHs and thus can reduce the energy consumption. Analysis and simulation results show that RDDM provides better performance than previous protocols in terms of energy consumption and data delivery ratio.     

Game of energy consumption balancing in heterogeneous sensor networks

In a multi‐hop sensor network, sensors largely rely on other nodes as a traffic relay to communicate with targets that are not reachable by one hop. Depending on the topology and position of nodes, some sensors receive more relaying traffic and lose their energy faster. Such imbalanced energy consumption may lead to server problems like network partitioning. In this paper, we study the problem of energy consumption balancing (ECB) in heterogeneous sensor networks by assuming general any‐to‐any traffic pattern. We consider both factors of transmission power and forwarding load in measuring energy consumption. To find a solution, we formulate the problem as a strategic network formation game with a new utility function. We show that this game is guaranteed to converge to strongly connected topologies which have better ECB and bounded inefficiency. We propose a localized algorithm in which every node knows only about its k‐hop neighbourhood. Through simulations on uniform and clustered networks with various densities, we show that the performance of our algorithm is comparable with global and centralized algorithms. Copyright © 2015 John Wiley & Sons, Ltd.     

SCE-PSO based clustering approach for load balancing of gateways in wireless sensor networks

Wireless Networks - Wireless sensor networks (WSNs) consist of spatially distributed low power sensor nodes and gateways along with sink to monitor physical or environmental conditions. In...     

An energy efficient clustering routing algorithm for wireless sensor networks

~~An energy efficient clustering routing algorithm for wireless sensor networks1. Mainwaring A, Polastre J, Szewczyk R, et al. Wireless sensor networks for habitat monitoring. Proceedings of the ACM International Workshop on Wireless Sensor Networks and A…     

A stable energy efficient clustering protocol for wireless sensor networks

Sensor networks comprise of sensor nodes with limited battery power that are deployed at different geographical locations to monitor physical events. Information gathering is a typical but an important operation in many applications of wireless sensor networks (WSNs). It is necessary to operate the sensor network for longer period of time in an energy efficient manner for gathering information. One of the popular WSN protocol, named low energy adaptive clustering hierarchy (LEACH) and its variants, aim to prolong the network lifetime using energy efficient clustering approach. These protocols increase the network lifetime at the expense of reduced stability period (the time span before the first node dies). The reduction in stability period is because of the high energy variance of nodes. Stability period is an essential aspect to preserve coverage properties of the network. Higher is the stability period, more reliable is the network. Higher energy variance of nodes leads to load unbalancing among nodes and therefore lowers the stability period. Hence, it is perpetually attractive to design clustering algorithms that provides higher stability, lower energy variance and are energy efficient. In this paper to overcome the shortcomings of existing clustering protocols, a protocol named stable energy efficient clustering protocol is proposed. It balances the load among nodes using energy-aware heuristics and hence ensures higher stability period. The results demonstrate that the proposed protocol significantly outperforms LEACH and its variants in terms of energy variance and stability period.