Energy-balanced cooperative routing in multihop wireless networks

Cooperative communication (CC) allows multiple nodes to simultaneously transmit the same packet to the receiver so that the combined signal at the receiver can be correctly decoded. Since the CC can reduce the transmission power and extend the transmission coverage, it has been considered in minimum energy routing protocols to reduce the total energy consumption. However, previous research on cooperative routing only focuses on minimizing the total energy consumption from the source node to the destination node, which may lead to the unbalanced energy distribution among nodes. In this paper, we aim to study the impact of cooperative routing on balancing the energy distribution among nodes. By introducing a new routing scheme which carefully selects cooperative relay nodes and assigns their transmission power, our cooperative routing method can balance the remaining energy among neighboring nodes to maximize the lifetime of the network. Simulation results demonstrate that the proposed cooperative routing algorithm significantly balances the energy distribution and prolongs the lifetime of the network.     

一种基于LEACH协议的改进算法

作为能量有效、基于层次结构的路由协议的典型代表,LEACH协议存在的不足表现为网络中会出现极大簇和极小簇并存;当节点能量不同时簇头选择不合理;在簇头死亡后簇内节点仍会消耗能量.本文基于LEACH提出了一种改进算法,使用引入簇成员数门限和合并极小簇的方法避免极大簇和极小簇同时存在;通过对簇头能量消耗的估计,在簇头能量耗尽...     

Efficient Energy Utilization Through Optimum Number of Sensor Node Distribution in Engineered Corona-Based (ONSD-EC) Wireless Sensor Network

An optimum sensor node deployment in wireless sensor network can sense the event precisely in many real time scenarios for example forests, habitat, battlefields, and precision agriculture. Due to these applications, it is necessary to distribute the sensor node in an efficient way to monitor the event precisely and to utilize maximum energy during network lifetime. In this paper, we consider the energy hole formation due to the unbalanced energy consumption in many-to-one wireless sensor network. We propose a novel method using the optimum number of sensor node Distribution in Engineered Corona-based wireless sensor network, in which the interested area is divided into a number of coronas. A mathematical models is proposed to find out the energy consumption rate and to distribute the optimum number of sensor node in each corona according to energy consumption rate. An algorithm is proposed to distribute the optimum number of sensor nodes in corona-based networks. Simulation result shows that the proposed technique utilized 95 % of the total energy of the network during network lifetime. The proposed technique also maximizes the network lifetime, data delivery and reduce the residual energy ratio during network lifetime.     

Actor-oriented directional anycast routing in wireless sensor and actor networks with smart antennas

Current routing protocols in wireless sensor and actor networks (WSANs) shows a lack of unification for different traffic patterns because the communication for sensor to actor and that for actor to actor are designed separately. Such a design poses a challenge for interoperability between sensors and actors. With the presence of rich-resource actor nodes, we argue that to improve network lifetime, the problem transforms from reducing overall network energy consumption to reducing energy consumption of constrained sensor nodes. To reduce energy consumption of sensor nodes, especially in challenging environments with coverage holes/obstacles, we propose that actor nodes should share forwarding tasks with sensor nodes. To enable such a feature, efficient interoperability between sensors and actors is required, and thus a unified routing protocol for both sensors and actors is needed. This paper explores capabilities of directional transmission with smart antennas and rich-resource actors to design a novel unified actor-oriented directional anycast routing protocol (ADA) which supports arbitrary traffic in WSANs. The proposed routing protocol exploits actors as main routing anchors as much as possible because they have better energy and computing power compared to constraint sensor nodes. In addition, a directional anycast routing approach is also proposed to further reduce total delay and energy consumption of overall network. Through extensive experiments, we show that ADA outperforms state-of-the-art protocols in terms of packet delivery latency, network lifetime, and packet reliability. In addition, by offer fault tolerant features, ADA also performs well in challenging environments where coverage holes and obstacles are of concerns.     

Routing design avoiding energy holes in underwater acoustic sensor networks

Interest in underwater acoustic sensor networks (UW‐ASNs) has rapidly increased with the desire to control the large portion of the world covered by oceans. Energy efficiency is one of the major concerns in UW‐ASNs due to the limited energy budget of the underwater sensor nodes. In this paper, we tackle the problem of energy holes in UW‐ASNs while taking into consideration the unique characteristics of the underwater channel. We prove that we can evenly distribute the transmission load among sensor nodes provided that sensors adjust their communication range when they send or forward the periodically generated data. In particular, we propose a balanced routing strategy along with the associated deployment pattern that meticulously determines the load weight for each possible next hop that leads to fair energy consumption among all underwater sensors. Consequently, the energy holes problem is overcome, and hence, the network lifetime is improved. To the best of our knowledge, this is the first work that addresses the energy hole problem in UW‐ASNs. Copyright © 2016 John Wiley & Sons, Ltd.     

基于改进LEACH的多簇头分簇路由算法

为了降低无线传感器网络(WSN)的能耗,延长网络的生存周期,提出一种多簇头双工作模式的分簇路由算法.算法对低功耗自适应集簇分层(LEACH)协议作了以下改进:采用多簇头双工作模式来分担单簇头的负荷,以解决单簇头因能耗较大而过早消亡的问题;选举簇头时充分考虑节点位置和节点剩余能量,并应用粒子群优化(PSO)算法优化簇头的选举,以均衡网络内各节点的能耗;建立簇与簇之间的数据传输路由,以减少簇间通信的能耗.仿真结果表明,算法有效降低了网络的能耗,延长了网络的生存周期.     

Sleep scheduling with expected common coverage in wireless sensor networks

Sleep scheduling, which is putting some sensor nodes into sleep mode without harming network functionality, is a common method to reduce energy consumption in dense wireless sensor networks. This paper proposes a distributed and energy efficient sleep scheduling and routing scheme that can be used to extend the lifetime of a sensor network while maintaining a user defined coverage and connectivity. The scheme can activate and deactivate the three basic units of a sensor node (sensing, processing, and communication units) independently. The paper also provides a probabilistic method to estimate how much the sensing area of a node is covered by other active nodes in its neighborhood. The method is utilized by the proposed scheduling and routing scheme to reduce the control message overhead while deciding the next modes (full-active, semi-active, inactive/sleeping) of sensor nodes. We evaluated our estimation method and scheduling scheme via simulation experiments and compared our scheme also with another scheme. The results validate our probabilistic method for coverage estimation and show that our sleep scheduling and routing scheme can significantly increase the network lifetime while keeping the message complexity low and preserving both connectivity and coverage.     

Optimal load balanced clustering in homogeneous wireless sensor networks

Balancing the load among sensor nodes is a major challenge for the long run operation of wireless sensor networks. When a sensor node becomes overloaded, the likelihood of higher latency, energy loss, and congestion becomes high. In this paper, we propose an optimal load balanced clustering for hierarchical cluster‐based wireless sensor networks. We formulate the network design problem as mixed‐integer linear programming. Our contribution is 3‐fold: First, we propose an energy aware cluster head selection model for optimal cluster head selection. Then we propose a delay and energy‐aware routing model for optimal inter‐cluster communication. Finally, we propose an equal traffic for energy efficient clustering for optimal load balanced clustering. We consider the worst case scenario, where all nodes have the same capability and where there are no ways to use mobile sinks or add some powerful nodes as gateways. Thus, our models perform load balancing and maximize network lifetime with no need for special node capabilities such as mobility or heterogeneity or pre‐deployment, which would greatly simplify the problem. We show that the proposed models not only increase network lifetime but also minimize latency between sensor nodes. Numerical results show that energy consumption can be effectively balanced among sensor nodes, and stability period can be greatly extended using our models.     

非均匀数据产生率的传感器网络的节能算法

无线传感器网络中的能量洞问题是影响网络寿命的关键因素之一.在基于环模型的多跳传感器网络中,通过优化所有环的传输距离可以有效地延长网络寿命.针对非均匀数据产生率的传感器网络,用建立环关系表的方式以搜索近似最优的传输距离从而延长网络寿命,在降低搜索(算法)复杂度的同时得到与最优解近似的结果.模拟实验证明了采用此节能算法的网...     

Looking for network functionalities’ extension by avoiding energy-compromised hotspots in wireless sensor networks

The vast literature on the wireless sensor research community contains many valuable proposals for managing energy consumption, the most important factor that determines sensors’ lifetime. Interesting researches have been facing this requirement by focusing on the extension of the entire network lifetime: either by switching between node states (active, sleep) or by using energy-efficient routing. We argue that a better extension of the network lifetime can be obtained if an efficient combination of management mechanisms can be performed at the energy of each single sensor and at the load distribution over the network. Considering these two accuracy levels (i.e., node and network), this paper presents a new approach that uses cost functions to choose energy-efficient routes. In particular, by making different energy considerations at a node level, our approach distributes routing load, avoiding, thus, energy-compromised hotspots that may cause network disconnections. The proposed cost functions have completely decentralized and adaptive behavior and take into consideration the end-to-end energy consumption, the remaining energy of nodes, and the number of transmissions a node can make before its energy depletion. Our simulation results show that, though slightly increasing path lengths from sensor to sink nodes, some proposed cost functions (1) improve significantly the network lifetime for different neighborhood density degrees, while (2) preserving network connectivity for a longer period of time.     

Adaptive energy aware cluster-based routing protocol for wireless sensor networks

Wireless sensor networks (WSNs) have grown excessively due to their various applications and low installation cost. In WSN, the main concern is to reduce energy consumption among nodes while maintaining timely and reliable data forwarding. However, most of the existing energy aware routing protocols incur unbalanced energy consumption, which results in inefficient load balancing and compromised network lifetime. Therefore, the main target of this research paper is to present adaptive energy aware cluster-based routing (AECR) protocol for improving energy conservation and data delivery performance. Our proposed AECR protocol differs from other energy efficient routing schemes in some aspects. Firstly, it generates balance sized clusters based on nodes distribution and avoids random clusters formation. Secondly, it optimizes both intra-cluster and inter-cluster routing paths for improving data delivery performance while balancing data traffic on constructed forwarding routes and at the end, in order to reduce the excessive energy consumption and improving load distribution, the role of Cluster Head (CH) is shifted dynamically among nodes by exploit of network conditions. Simulation results demonstrate that AECR protocol outperforms state of the art in terms of various performance metrics.

     

Traffic-Aware Density-Based Sleep Scheduling and Energy Modeling for Two Dimensional Gaussian Distributed Wireless Sensor Network

Sleep scheduling of sensors in network domain is considered to be the most fundamental way of achieving higher life expectancy of wireless sensor networks. In this paper we have proposed density-based sleep scheduling strategy with traffic awareness in Gaussian distributed sensor network for minimizing energy consumption. In uniform distributed sensor network, it has been found that nodes in the nearest belt around the sink consume more energy. The reason behind is that the nodes near the sink involve more packet relaying load than the distant nodes. Consequently, the energy of these sensors get exhausted rapidly, thereby creating connectivity breaks known as energy hole. For this purpose, Gaussian distribution is used by densely deploying nodes around the sink which well-balances the relaying load. In addition, we have developed the analytical model for computing the energy consumption and coverage analysis in the sensor network. The performance of our sleep scheduling method is evaluated with respect to the Randomized Scheduling and Linear Distance-based Scheduling protocols. The simulation results of our proposed work show commendable improvement in network lifetime.     

Controllably mobile infrastructure for low energy embedded networks

We discuss the use of mobility to enhance network performance for a certain class of applications in sensor networks. A major performance bottleneck in sensor networks is energy since it is impractical to replace the batteries in embedded sensor nodes post-deployment. A significant portion of the energy expenditure is attributed to communications and, in particular, the nodes close to the sensor network gateways used for data collection typically suffer a large overhead as these nodes must relay data from the remaining network. Even with compression and in-network processing to reduce the amount of communicated data, all the processed data must still traverse these nodes to reach the gateway. We discuss a network infrastructure based on the use of controllably mobile elements to reduce the communication energy consumption at the energy constrained nodes and, thus, increase useful network lifetime. In addition, our approach yields advantages in delay-tolerant networks and sparsely deployed networks. We first show how our approach helps reduce energy consumption at battery constrained nodes. Second, we describe our system prototype, which utilizes our proposed approach to improve the energy performance. As part of the prototyping effort, we experienced several interesting design choices and trade-offs that affect system capabilities and performance. We describe many of these design challenges and discuss the algorithms developed for addressing these. In particular, we focus on network protocols and motion control strategies. Our methods are tested using a practical system and do not assume idealistic radio range models or operation in unobstructed environments.     

Low-Energy Adaptive Unequal Clustering Protocol Using Fuzzy c-Means in Wireless Sensor Networks

Clustering technique in wireless sensor networks incorporate proper utilization of the limited energy resources of the deployed sensor nodes with the highest residual energy that can be used to gather data and send the information. However, the problem of unbalanced energy consumption exists in a particular cluster node in the network. Some more powerful nodes act as cluster head to control sensor network operation when the network is organized into heterogeneous clusters. It is important to assume that energy consumption of these cluster head nodes is balanced. Often the network is organized into clusters of equal size where cluster head nodes bear unequal loads. Instead in this paper, we proposed a new protocol low-energy adaptive unequal clustering protocol using Fuzzy c-means in wireless sensor networks (LAUCF), an unequal clustering size model for the organization of network based on Fuzzy c-means (FCM) clustering algorithm, which can lead to more uniform energy dissipation among the cluster head nodes, thus increasing network lifetime. A heuristic comparison between our proposed protocol LAUCF and other different energy-aware protocol including low energy adaptive clustering hierarchy (LEACH) has been carried out. Simulation result shows that our proposed heterogeneous clustering approach using FCM protocol is more effective in prolonging the network lifetime compared with LEACH and other protocol for long run.     

A green cluster‐based routing scheme for large‐scale wireless sensor networks

In wireless sensor networks (WSNs), clustering has been shown to be an efficient technique to improve scalability and network lifetime. In clustered networks, clustering creates unequal load distribution among cluster heads (CHs) and cluster member (CM) nodes. As a result, the entire network is subject to premature death because of the deficient active nodes within the network. In this paper, we present clustering‐based routing algorithms that can balance out the trade‐off between load distribution and network lifetime “green cluster‐based routing scheme.” This paper proposes a new energy‐aware green cluster‐based routing algorithm to preventing premature death of large‐scale dense WSNs. To deal with the uncertainty present in network information, a fuzzy rule‐based node classification model is proposed for clustering. Its primary benefits are flexibility in selecting effective CHs, reliability in distributing CHs overload among the other nodes, and reducing communication overhead and cluster formation time in highly dense areas. In addition, we propose a routing scheme that balances the load among sensors. The proposed scheme is evaluated through simulations to compare our scheme with the existing algorithms available in the literature. The numerical results show the relevance and improved efficiency of our scheme.     

有效降低无线网络节点能量的LEACH新算法

LEACH是一种低功耗自适应按簇分层路由算法.为了降低节点能耗,在LEACH协议的基础上提出了在选举簇头时,改变阈值T(n)的大小以降低节点成为簇头的概率,从而节省网络因分簇而消耗的能量.同时又提出了一种基于节点剩余能量的二层簇头的算法,该算法能使节点减少将冗余信息传输到基站,从而达到降低节点消耗能量的目的.通过实验仿真,表明这些方法能使网络节点能量的消耗减少,达到了延长网络生命周期的目的.     

Lifetime enhancement of wireless sensor networks by avoiding energy-holes with Gaussian distribution

Wireless sensor networks (WSNs) are receiving significant attention due to their potential applications in environmental monitoring and surveillance domains. In WSNs, preserving energy requires utmost attention, as they are highly resource constrained. One fundamental way of conserving energy is judicious deployment of nodes within the network for balancing energy flow throughout the network. Node deployment using Gaussian distribution is a standard practice and is widely acceptable when random deployment is used. Initially, an analysis is done to establish that Gaussian distribution based node deployment is not energy balanced. Standard deviation of Gaussian distribution is identified as the parameter responsible for energy balancing. A deployment strategy is proposed for energy balancing using customized Gaussian distribution by discretizing the standard deviation. Performance of the scheme is evaluated in terms of energy balance and network lifetime. Exhaustive simulation is performed to measure the extent of achieving our design goal of enhancing network lifetime while attaining energy balancing. The simulation results show that our scheme also provides satisfactory network performance in terms of end-to-end delay and throughput. Finally, all the results are compared with three competing schemes and the results confirm our scheme’s supremacy in terms of both design performance metrics as well as network performance metrics.     

一种基于历史信息的簇头选取机制

无线传感器网络（WSN,Wireless Sensor Network）中,如何减少节点的能耗一直是簇头选择机制的研究目标。现提出了一种基于历史能耗信息选择机制的簇头选择算法（CHCM,Cluster Head Choosing Mechanism）,该算法通过节点历史能耗信息和节点分布密度参数预测簇头能耗速度,并将该预测方法融入簇头选取过程当中,使网络生命期延长。最后利用CHCM对LEACH路由协议进行改进,得到CHCM＋LEACH路由协议。仿真结果表明CHCM＋LEACH在网络生命期和网络总剩余能量上分别比LEACH算法分别提高了27%和14%。     

Distributed Transmission Power Control for Network Programming in Wireless Sensor Networks

In wireless sensor networks, the necessity of network programming becomes more and more important due to the inaccessibility of the sensor nodes. Because the network programming produces a large amount of data, it consumes a great deal of energy and causes the network to suffer from much interference. Many conventional studies regarding the network programming attempted to reduce the energy consumption and the interference effect. However, they overlook transmission power effect on the energy-efficiency and the interference problem. In this paper, we present a novel network programming protocol that controls the transmission power at each sender node in a distributed manner. The protocol deals not only with the energy consumption of individual sensor node but also the network load distribution. Moreover, it reduces the interference effect on the network by decreasing the average transmission power of the sensor nodes. We verify that our protocol extends the lifetime of the sensor network and decreases the packet losses through simulation results.     

A Sink-Oriented Layered Clustering Protocol for Wireless Sensor Networks

Clustering is an effective technique to prolong network lifetime for energy-constrained wireless sensor networks. Due to the many-to-one traffic pattern in a multi-hop network, the nodes closer to the sink also help to relay data for those farther away from the sink, and hence they consume much more energy and tend to die faster. This paper proposes a sink-oriented layered clustering (SOLC) protocol to better balance energy consumption among nodes with different distances to the sink. In SOLC, the sensor field is divided into concentric rings, and the SOLC protocol consists of intra-ring clustering and inter-ring routing. We compute the optimal ring width and the numbers of cluster heads in different rings to balance energy consumption between intra-cluster data processing and inter-cluster data relaying. Cluster heads in a ring closer to the sink has smaller sizes than those in the rings farther away from the sink, and hence they can spend less energy for intra-cluster data processing and more energy for inter-cluster data relay. Simulation results show that the SOLC protocol can outperform several existing clustering protocols in terms of improved network lifetime.