Balancing Energy Consumption to Maximize Network Lifetime in Data-Gathering Sensor Networks

Unbalanced energy consumption is an inherent problem in wireless sensor networks characterized by multihop routing and many-to-one traffic pattern, and this uneven energy dissipation can significantly reduce network lifetime. In this paper, we study the problem of maximizing network lifetime through balancing energy consumption for uniformly deployed data-gathering sensor networks. We formulate the energy consumption balancing problem as an optimal transmitting data distribution problem by combining the ideas of corona-based network division and mixed-routing strategy together with data aggregation. We first propose a localized zone-based routing scheme that guarantees balanced energy consumption among nodes within each corona. We then design an offline centralized algorithm with time complexity O(n) (n is the number of coronas) to solve the transmitting data distribution problem aimed at balancing energy consumption among nodes in different coronas. The approach for computing the optimal number of coronas in terms of maximizing network lifetime is also presented. Based on the mathematical model, an energy-balanced data gathering (EBDG) protocol is designed and the solution for extending EBDG to large-scale data-gathering sensor networks is also presented. Simulation results demonstrate that EBDG significantly outperforms conventional multihop transmission schemes, direct transmission schemes, and cluster-head rotation schemes in terms of network lifetime.     

Power control based topology construction for the distributed wireless sensor networks

Wireless sensor network consists of large number of sensor nodes with limited battery power, which are randomly deployed over certain area for several applications. Due to limited energy resource of sensors, each of them should minimize the energy consumption to prolong the network lifetime. In this paper, a distributed algorithm for the multi-hop wireless sensor network is proposed to construct a novel energy efficient tree topology, without having location information of the nodes. Energy conservation of the nodes is accomplished by controlling transmission power of the nodes. Besides, maintenance of the network topology due to energy scarcity of the gateway nodes is also proposed in the protocol. Simulation results show that our distributed protocol can achieve energy conservation up to an optimum level similar to the centralized algorithm that we have considered and can extend the network lifetime as compared to other distributed algorithms without any power control.     

无线网络中基于编码感知的能量优化路由算法

由电池供应电量的无线通信网络中,数据需要通过作为路由的中间节点进行传输,所以这些中间节点的能量消耗对整个网络的生存有很大的影响。本文从延长网络生存时间的目的出发,提出了一种能量优化的编码感知路由协议COER(Coding-aware based Optimal Energy Routing),利用能量门限值以及相对剩余能量来均衡网络节点能量的消耗,同时用网络编码来减少能量的消耗,并将两者统一来实现网络能量的优化。仿真结果表明:COER能够减少传输能耗,均衡网络能量消耗,延长网络生存时间。     

Improvement of battery lifetime in software-defined network using particle swarm optimization based cluster-head gateway switch routing protocol with fuzzy rules

The software-defined network (SDN) is one of the network architectures, in which the data plane and control plane is divided from each other, and the network can be handled using a sensibly centralized controller and this method is adopted to reconfigure the wireless sensor network automatically. In this article, to implement the SDN in MANET, in which control nodes can be chosen in SDN dynamically for the activation of MANET function to allocate the works to other mobile nodes to the base station. However, in the field of mobile ad hoc networks, the network lifetime, and battery lifetime is one of the major problems and the energy consumption can play a significant rule for the transmission of data in the SDN. Therefore, in this article, particle swarm optimization (PSO) based CGSR (cluster-head gateway switch routing protocol) algorithm with fuzzy rules is proposed to increase the network lifetime of battery powered mobile nodes by reducing the energy consumptions of each node in software-defined MANET. In this proposed method, a routing method that can permit various mobile nodes with low battery power to transmits the data from source node to base station. We design a PSO based CGSR routing protocol by selecting the routing mobile nodes using fuzzy rules for packet transmission. In CGSR process, the formation of cluster and selection of cluster head is executed depending on the particle swarm optimization method. This proposed routing protocol can be used to enhance the battery lifetime by extension of the network lifetime with numerical analysis for efficient route node selection.     

能量高效的无线传感器网络路由协议

针对目前无线传感器网络分簇路由协议存在的节点能耗不均衡的问题,提出一种基于分簇思想的能量高效的多跳路由协议(EEMR)。该协议首先基于节点临近度将网络划分成簇,采用簇首自适应轮转模式优化簇内节点通信的能量消耗,以高剩余能量短路径向心角的适应度路由算法均衡簇间通信负载和能量消耗,有效避免多跳路由中出现的能量消耗不均衡问题。仿真结果表明,EEMR协议能有效均衡网络内节点的能量消耗,显著延长无线传感器网络的生命期并提高网络能量利用率。     

An energy-saving routing architecture with a uniform clustering algorithm for wireless body sensor networks

Wireless body sensor networks are expected to extend human-centered applications in large-scale sensing and detecting environments. Energy savings has become one of the most important features of the sensor nodes to prolong their lifetime in such networks. To provide reasonable energy consumption and to improve the network lifetime of wireless body sensor network systems, new and efficient energy-saving schemes must be developed. An energy-saving routing architecture with a uniform clustering algorithm is proposed in this paper to reduce the energy consumption in wireless body sensor networks. We adopted centralized and cluster-based techniques to create a cluster-tree routing structure for the sensor nodes. The main goal of this scheme is to reduce the data transmission distances of the sensor nodes by using the uniform cluster structure concepts. To make an ideal cluster distribution, the distances between the sensor nodes are calculated, and the residual energy of each sensor node is accounted for when selecting the appropriate cluster head nodes. On the basis of the uniform cluster location, the data transmission distances between the sensor nodes can be reduced by employing an adaptive multi-hop approach. The energy consumption is reduced, and the lifetime is extended for the sensor nodes by balancing the network load among the clusters. Simulation results show that the proposed scheme outperforms the previously known schemes in terms of the energy consumption and the network lifetime for the wireless body sensor networks.     

An energy-driven unequal clustering protocol for heterogeneous wireless sensor networks

Due to the limitation of energy resources, energy efficiency is a key issue in wireless sensor networks (WSNs). Clustering is proved to be an important way to realize hierarchical topology control, which can improve the scalability and prolong the lifetime of wireless sensor networks. In this paper, an energy-driven unequal clustering protocol (EDUC) for heterogeneous wireless sensor networks is proposed. EDUC includes an unequal clustering algorithm and an energy-driven adaptive cluster head rotation method. The unequal size of clusters can balance the energy consumption among clusters, and the energy-driven cluster head rotation method can achieve the balance of energy consumption among nodes within a cluster, which reduces the waste of energy. Simulation experiments show that EDUC balances the energy consumption well among the cluster heads and prolongs the network lifetime.     

基于非线性电池模型的WSNs节能技术研究

在无线传感器网络（WSNs）节能技术研究中,如何最大化节点电池能量效率从而延长整个网络寿命是一个关键问题。采用非线性电池模型,使用在低数据传输速率场合中较为节能的FSK调制技术,通过理论分析和参数优化方法,以电池能耗最小为目标,建立电池能耗模型,优化调制指数,使得电池能耗最低。仿真结果表明：该模型能够更加准确地评估节点能耗和寿命。在给定传输距离下,存在一个最优调制指数,使得电池能耗最低。最后给出了不同传输距离对应的最优调制指数。     

无线传感器网络权衡生存时间与数据分组跳数的分流路由算法*

无线传感器网络的节点大多采用电池供电.因而节能对无线传感器网络就显得至关重要.该文提出一种能耗感知的优化网络生存时间的路由算法,称之为分流路由算法(DTRA,Diffluent Traffic Routing Algorithm).DTRA算法采用一个优化模型以优化每个节点发出的数据比例,从而达到权衡网络生存时间和数据分组跳数.此外,采用一个简单的遗传算法求解该优化问题.仿真结果表明:DTRA算法能显著地提高网络的生存时间,同时将数据分组平均跳数保持在一个较低的水平;在网络生存时间上,DTRA算法比一些已有的知名算法更优.     

无线传感器网络中能量有效自适应路由算法研究

针对无线传感器网络寿命最大化问题,基于无线传感器节点能耗分布特点和数据传输能耗模型,建立无线传感器网络生存周期的数学优化模型,并针对最小能耗路由的能耗不均衡问题和能量均衡路由的能耗开销问题,综合考虑网络中节点的剩余能量和节点间发送数据的能耗,提出一个适合无线多跳传感器网络的自适应路由算法。仿真结果表明,提出的路由算法能充分地利用有限的能量资源,较大地延长网络生存周期。     

Optimal energy allocation in heterogeneous wireless sensor networks for lifetime maximization

We consider the problem of optimal energy allocation and lifetime maximization in heterogeneous wireless sensor networks. We construct a probabilistic model for heterogeneous wireless sensor networks where sensors can have different sensing range, different transmission range, different energy consumption for data sensing, and different energy consumption for data transmission, and the stream of data sensed and transmitted from a sensor and the stream of data relayed by a sensor to a base station are all treated as Poisson streams. We derive the probability distribution and the expectation of the number of data transmissions during the lifetime of each sensor and the probability distribution and the expectation of the lifetime of each sensor. In all these analysis, energy consumption of data sensing and data transmission and data relay are all taken into consideration. We develop an algorithm to find an optimal initial energy allocation to the sensors such that the network lifetime in the sense of the identical expected sensor lifetime is maximized. We show how to deal with a large amount of energy budget that may cause excessive computational time by developing accurate closed form approximate expressions of sensor lifetime and network lifetime and optimal initial energy allocation. We derive the expected number of working sensors at any time. Based on such results, we can find the latest time such that the expected number of sensors that are still functioning up to that time is above certain threshold.     

多sink协同移动的最大化网络生存期优化算法

针对无线传感器网络中因能量消耗不平衡造成的"能量洞"问题,提出多Sink协同移动的最大化网络生存期优化算法。该算法将监测区域分割成有限个虚拟单元格,通过蚁群优化算法ACO(Ant Colony Optimization)协同多Sink节点移动;同时,将多Sink节点在备选位置的停留时间归结为LP(Linear Program),最大化网络寿命。仿真结果表明,LP-ACO(Linear Pro-gram-Ant Colony Optimization)较好地均衡了传感器网络节点间的负载,网络寿命优于多Sink节点静态部署(STATIC)和随机移动(RDM)时场景,且具有良好的可扩展性。     

WSN in cyber physical systems: Enhanced energy management routing approach using software agents

Recently, the cyber physical system has emerged as a promising direction to enrich the interactions between physical and virtual worlds. Meanwhile, a lot of research is dedicated to wireless sensor networks as an integral part of cyber physical systems. A wireless sensor network (WSN) is a wireless network consisting of spatially distributed autonomous devices that use sensors to monitor physical or environmental conditions. These autonomous devices, or nodes, combine with routers and a gateway to create a typical WSN system. Shrinking size and increasing deployment density of wireless sensor nodes implies the smaller equipped battery size. This means emerging wireless sensor nodes must compete for efficient energy utilization to increase the WSN lifetime. The network lifetime is defined as the time duration until the first sensor node in a network fails due to battery depletion. One solution for enhancing the lifetime of WSN is to utilize mobile agents. In this paper, we propose an agent-based approach that performs data processing and data aggregation decisions locally i.e., at nodes rather than bringing data back to a central processor (sink). Our proposed approach increases the network lifetime by generating an optimal routing path for mobile agents to transverse the network. The proposed approach consists of two phases. In the first phase, Dijkstra’s algorithm is used to generate a complete graph to connect all source nodes in a WSN. In the second phase, a genetic algorithm is used to generate the best-approximated route for mobile agents in a radio harsh environment to route the sensory data to the base-station. To demonstrate the feasibility of our approach, a formal analysis and experimental results are presented.     

基于最短路径树的优化生存时间路由算法

为提高无线传感网的生存时间,提出基于最短路径树的优化生存时间路由算法(LORA_SPT).该算法引入节点分类概念,构造基于链路能耗因子、自身节点剩余能量因子、邻居节点剩余能量因子和类型权重因子等多个因子的权值函数.针对不同类型的节点采用不同的权重因子,最后利用dijkstra算法完成最短路径树,所有节点沿着最短路径树将...     

无线传感器网络能耗均衡路由模型及算法

在综合考虑传感器网络中节点链路接入、数据包传输能耗及节点剩余能量的基础上,提出了一种自适应能耗均衡路由策略,并给出了相应的数学最优化模型及求解算法.优化的目标是均衡网络能耗,进而最大化网络寿命.首先采用跨层分析的方法设计了符合传感器节点计算能力的分布式动态路由树生成算法及各节点的路由选择策略函数;然后通过构造一个双层规划模型使传感器网络的整体能耗趋向均衡,尽可能地延长网络寿命.一个数值例子说明,提出的路由选择策略、双层规划模型及求解算法是可行且有效的.     

基于加权路由思想的无线自组织网络生存时间优化算法研究

在无线自组织网络中,网络生存时间是衡量网络性能的重要指标之一.分析影响网络生存时间的众多因素后,提出了一种工作量加权路由模型以提高无线自组织网络的生存时间.在网络信息传输的过程中,综合每条链路的业务工作量对网络链路进行加权,建立距离加权传输数学模型.该模型通过降低工作较为繁忙节点的信息转发概率,从而到达均衡节点能耗的目的.最后,采用MATLAB进行数值仿真,结果显示本文提出的路由算法可以有效延迟网络生存时间,均衡网络节点的能耗.     

能量均衡的无线传感器网络短路径路由算法

如何均衡地使用无线传感器网络节点的能量并产生较小的网络延迟是无线传感器网络研究的一个难点. 本文提出了一种能量均衡的无线传感器网络短路径路由算法EB-SPR (Energy-balanced short path routing). 首先将网络构造成层次结构, 节点根据上一层邻节点能量水平并优先使用剩余能量多的节点作为下一跳来转发数据包, 这种方式有效地平衡了网络能耗, 进而提高了网络生命周期. 另外, EB-SPR通过在路由中限制数据包在同一层被转发的次数来降低数据到达基站的跳数. 本文证明了EB-SPR下源数据包到达基站所经历的跳数最多为最短路径路由算法的2倍, 所以本文算法产生的网络延迟具有明确的上界. 模拟实验表明EB-SPR有效地延长了网络生命周期并能产生较小的网络延迟.     

传感器网络中一种基于分层的功率控制算法

无线传感器网络的能耗决定了网络的生存时间,如何设计有效的算法来延长网络的生存时间是一个重要的研究课题。针对矩形传感器网络,提出一种基于分层的功率控制算法,通过分析节点的能耗来计算层的宽度和节点的通信半径,以达到网络能耗的均衡分布。仿真实验表明,算法能有效延长网络的生存时间。     

WSN中基于学习自动机的簇头选举算法

为均衡无线传感器网络节点能耗和网络负载,提出了一种基于学习自动机的簇头选举算法.该算法考虑节点的能量消耗及其与邻居节点的状态信息,在选举簇头时,通过把节点的剩余能量与平均能量相比较以及把节点的相互距离与平均距离比较,来更新学习自动机选择动作概率,以提高有利节点选举为簇头的概率.仿真结果表明,该算法在簇头的分布上更加合理,同时也减少了网络的能量消耗,延长了网络生存期.     

无线传感器网络高能效分簇路由算法

无线传感器网络与传统无线网络相比,网络节点在具有的电源能量、计算与处理能力、通信带宽等方面都十分有限。延长网络的生命周期成为无线传感器网络的一个关键问题。在低功耗自适应分簇路由算法(LEACH)的基础上提出了一种改进算法,其主要思想在于根据监测区域面积、节点数目及基站位置来确定最优簇个数而不是低功耗自适应算法中的固定值。最后仿真结果表明,改进后的算法与LEACH算法相比,无论是在能量消耗还是网络生命周期方面都有较大的提高。