Overlapping particle swarms for energy-efficient routing in sensor networks

Sensor networks are traditionally built using battery-powered, collaborative devices. These sensor nodes do not rely on dedicated infrastructure services (e.g., routers) to relay data. Rather, a communal effort is employed where the sensor nodes both generate data as well as forward data for other nodes. A routing protocol is needed in order for the sensors to determine viable paths through the network, but routing protocols designed for wired networks and even ad hoc networks are not sufficient given the energy overhead needed to operate them. We propose an energy-aware routing protocol, based on overlapping swarms of particles, that offers reliable path selection while reducing the energy consumption for the route selection process. Our particle-based routing with overlapping swarms for energy-efficiency algorithm shows promise in extending the life of battery-powered networks while still providing robust routing functionality to maintain network reliability.     

无线传感器网络能量高效混合MAC算法

针对无线传感器网络MAC协议中存在的能耗问题,提出了能量高效的无线传感器网络混合MAC(EEH-MAC)算法,采用基于TDMA机制的时槽系数动态调整簇内节点的时槽大小来降低数据的传输时延;同时,对部分不需要数据传输的节点不分配时槽来减少能耗;按簇内节点剩余能量系数形成时槽分配顺序来减少状态转换的能耗;在簇头之间采用CSMA/CA机制的随机分配策略进行通信.仿真结果表明,EEH-MAC协议能有效减少能耗并延长网络生命周期.     

An energy-efficient optimization deployment scheme for wireless sensor networks

Most of the current deployment schemes for Wireless Sensor Networks (WSNs) do not take the network coverage and connectivity features into account, as well as the energy consumption. This paper introduces topology control into the optimization deployment scheme, establishes the mathematical model with the minimum sum of the sensing radius of each sensors, and uses the genetic algorithm to solve the model to get the optimal coverage solution. In the optimal coverage deployment, the communication and channel allocation are further studied. Then the energy consumption model of the coverage scheme is built to analyze the performance of the scheme. Finally, the scheme is simulated through the network simulator NS-2. The results show the scheme can not only save 36% energy averagely, but also achieve 99.8% coverage rate under the condition of 45 sensors being deployed after 80 iterations. Besides, the scheme can reduce the five times interference among channels.     

A centralized energy-efficient routing protocol for wireless sensor networks

Wireless sensor networks consist of small battery powered devices with limited energy resources. Once deployed, the small sensor nodes are usually inaccessible to the user, and thus replacement of the energy source is not feasible. Hence, energy efficiency is a key design issue that needs to be enhanced in order to improve the life span of the network. Several network layer protocols have been proposed to improve the effective lifetime of a network with a limited energy supply. In this article we propose a centralized routing protocol called base-station controlled dynamic clustering protocol (BCDCP), which distributes the energy dissipation evenly among all sensor nodes to improve network lifetime and average energy savings. The performance of BCDCP is then compared to clustering-based schemes such as low-energy adaptive clustering hierarchy (LEACH), LEACH-centralized (LEACH-C), and power-efficient gathering in sensor information systems (PEGASIS). Simulation results show that BCDCP reduces overall energy consumption and improves network lifetime over its comparatives.     

一种节省能量的水声传感器网络组织结构与协议

本文为水声传感器网络提出了一种基于簇间协商的事件报告策略,网络节点以簇的形式组织起来,多址接入协议采用了一种适合水声环境的TDMA/CDMA混合式协议,建立了由簇头与网关组成的用于簇间通信的主干链路。仿真结果表明,基于簇间协商的事件报告策略能有效减少网络中的冗余通信量从而延长网络寿命。     

三维水声传感器网络能量高效路由算法

针对三维水声传感器网络,在研究水声信道能耗特性的基础上,设计了一种能量高效的路由算法Hybrid LEACH。它基于经典的LEACH算法,而在簇间传输中使用一种树状路由取代簇头与汇聚节点直接通信,减少了簇头节点的能耗,达到延长网络生存时间的目的。仿真结果显示,Hybrid LEACH算法在网络规模较大的情况下可以有效延长网络生存时间。     

QoS evaluation of energy-efficient ML-MAC protocol for wireless sensor networks

Power management is an important issue in wireless sensor networks (WSNs) because wireless sensor nodes are usually battery powered, and an efficient use of the available battery power becomes an important concern specially for those applications where the system is expected to operate for long durations. This necessity for energy efficient operation of a WSN has prompted the development of new protocols in all layers of the communication stack. If the radio transceiver is the most power consuming component of a typical sensor node, large gains can be achieved at the link layer where the medium access control (MAC) protocol controls the usage of the radio transceiver unit.     

An event-driven energy-efficient routing protocol for water quality sensor networks

Due to the limited resources of water quality sensor networks, how to design a routing protocol which can prolong the network life cycle is one of a research hotspots. In this paper, according to the event level and the node energy of the sensor networks, the nodes’ types are defined, which can help to determine the cluster node. Then, an event driven routing protocol (EDRP) is proposed, which considers the event information and the remaining energy of the whole network. Simulation results show that, compared with distributed energy-efficient clustering algorithm, EDRP can reduce the overall energy consumption of the network by 138–172%, based on different kinds of events. Besides, EDRP can effectively prolong the life cycle and greatly increase the amount of data transmission of the network.

     

无线传感网络中能耗均衡的混合通信算法研究

基于经典的低能耗自适应分簇算法(LEACH),提出了一种能耗均衡的混合通信算法(EEHCA).由基站根据节点剩余能量和簇头之间的距离选举簇头,节点用单跳模式和多跳模式交替与簇头进行通信且概率分别是p和1-p,从而使簇头的分布更均匀,节点的负载更均衡.仿真结果表明该算法有效地平衡了节点的能量消耗,在延长生命周期方面明显好于LEACH.     

具有小世界现象的无线传感器网络构造方法

小世界特性是复杂网络最重要的特性之一,将小世界理论引入到无线传感器网络(WSNs),对优化网络拓扑结构及提高其性能具有十分重要的意义。 提出了一种新的具有小世界现象的WSNs构造方法RSLCS (Removing Superfluous Links and Creating Shortcuts). 该方法首先基于对集聚系数的分析,有选择性地删除一些边,然后基于Sink节点建立捷径,两个步骤交替进行,直到两个小世界特性同时达到最优。仿真表明此方法不仅增大了网络的集聚系数,降低了平均路径长度,使网络具有明显的小世界特性,而且简化了网络拓扑结构,使网络在低冗余的条件下具有好的抗毁性。      

Dynamic energy-efficient surveillance routing in uncertain group-based industrial wireless sensor networks

Wireless Networks - Smart factories in harsh large-scale environments are achieved by installation of group-based industrial wireless sensor networks (GIWSNs), in which a group of sensors are...     

A robust and energy-efficient data dissemination framework for wireless sensor networks

Wireless sensor networks (WSNs) are appealing in obtaining fine-granular observations about the physical world. Due to the fact that WSNs are composed of a large number of low-cost and energy-constrained sensor nodes, along with the notorious time-varying and error-prone nature of wireless links, scalable, robust and energy-efficient data dissemination techniques are needed for the emerging WSN applications such as environment monitoring and surveillance. In this paper, we examine this emerging field from the point of view of supply chain management and propose a hybrid data dissemination framework for WSNs. In particular, for each sensing task, the whole sensor field is conceptually partitioned into several functional regions based on the supply chain management methodology. Different routing schemes are applied to different regions in order to provide better performance in terms of reliability and energy consumption. For this purpose, we also propose a novel zone flooding scheme, essentially a combination of conventional geometric routing and flooding techniques. Our hybrid data dissemination framework features low overhead, high reliability, good scalability and flexibility, and preferable energy efficiency. Detailed simulation studies are carried out to validate the effectiveness and efficiency of our scheme.     

On the energy-efficient organization and the lifetime of multi-hop sensor networks

Due to hardware, energy, cost and other physical constraints, sensor-based networks present various design, implementation and deployment challenges. An analytical model is presented to estimate and evaluate the node and network lifetime in a randomly deployed multi-hop sensor network. Based on this, we provide a procedure for the creation of an energy efficient sensor network organization, that attempts to extend the lifetime of the communication critical nodes, and as a result the overall network's operational lifetime.     

A hierarchical energy-efficient framework for data aggregation in wireless sensor networks

A network of sensors can be used to obtain state-based data from the area in which they are deployed. To reduce costs, the data, sent via intermediate sensors to a sink, are often aggregated (or compressed). This compression is done by a subset of the sensors called "aggregators." Inasmuch as sensors are usually equipped with small and unreplenishable energy reserves, a critical issue is to strategically deploy an appropriate number of aggregators so as to minimize the amount of energy consumed by transporting and aggregating the data. In this paper, the authors first study single-level aggregation and propose an Energy-Efficient Protocol for Aggregator Selection (EPAS) protocol. Then, they generalize it to an aggregation hierarchy and extend EPAS to Hierarchical EPAS. The optimal number of aggregators with generalized compression and power-consumption models was derived, and fully distributed algorithms for aggregator selection were presented. Simulation results show that the algorithms significantly reduce the energy consumption for data collection in wireless sensor networks. Moreover, the algorithms do not rely on particular routing protocols and are thus applicable to a broad spectrum of application environments.     

Towards trusted and energy-efficient data collection in unattended wireless sensor networks

Wireless Networks - The Internet of Things (IoT), including wireless sensors, is one of the highly anticipated contributors to big data; therefore, avoiding misleading or forged data gathering in...     

DR-NAP: Data reduction strategy using neural adaptation phenomenon in wireless sensor networks

Internet of Things (IoT) has got significant popularity among the researchers' community as they have been applied in numerous application domains. Most of the IoT applications are implemented with the help of wireless sensor networks (WSNs). These WSNs use different sensor nodes with a limited battery power supply. Hence, the energy of the sensor node is considered as one of the primary constraints of WSN. Besides, data communication in WSN dissipates more energy than processing the data. In most WSNs applications, the sensed data generated from the same location sensor nodes are identical or time-series/periodical data. This redundant data transmission leads to more energy consumption. To reduce the energy consumption, a data reduction strategy using neural adaptation phenomenon (DR-NAP) has been proposed to decrease the communication energy in routing data to the BS in WSN. The neural adaptation phenomenon has been utilized for designing a simple data reduction scheme to decrease the amount of data transmitted. In this way, the sensor node energy is saved and the lifetime of the network is enhanced. The proposed approach has been implanted in the existing gravitational search algorithm (GSA)-based clustered routing for WSN. The sensed data are transmitted to CH and BS using DR-NAP. Real sensor data from the Intel Berkeley Research lab have been used for conducting the experiments. The experiment results show 47.82% and 51.96% of improvement in network lifetime when compared with GSA-based clustered routing and clustering scheme using Canada Geese Migration Principle (CS-CGMP) for routing, respectively.     

EEGBRP: an energy-efficient grid-based routing protocol for underwater wireless sensor networks

Wireless Networks - Underwater sensor networks (UWSN) include a set of sensor nodes equipped with limited batteries. These batteries are not rechargeable and replacement of them is difficult and...     

无线传感器网络中的MAC协议及其节能技术研究

由于受到传感器网络节点数量巨大和能量有限的限制,设计一种节能的MAC协议是非常必要的,也是当前此领域的研究重点之一.现给出了无线传感器网络中引起能量浪费的主要因素,综述了无线传感器网络MAC协议最新的研究进展,讨论了MAC层节能技术,为无线传感器网络中MAC协议的进一步研究提供了有价值的参考.