Energy efficient path selection for mobile sink and data gathering in wireless sensor networks

Mobile sink (MS) has drawn significant attention for solving hot spot problem (also known as energy hole problem) that results from multihop data collection using static sink in wireless sensor networks (WSNs). MS is regarded as a potential solution towards this problem as it significantly reduces energy consumption of the sensor nodes and thus enhances network lifetime. In this paper, we first propose an algorithm for designing efficient trajectory for MS, based on rendezvous points (RPs). We next propose another algorithm for the same problem which considers delay bound path formation of the MS. Both the algorithms use k-means clustering and a weight function by considering several network parameters for efficient selection of the RPs by ensuring the coverage of the entire network. We also propose an MS scheduling technique for effective data gathering. The effectiveness of the proposed algorithms is demonstrated through rigorous simulations and comparisons with some of the existing algorithms over several performance metrics.     

Data gathering via mobile sink in WSNs using game theory and enhanced ant colony optimization

Optimal performance and improved lifetime are the most desirable design benchmarks for WSNs and the mechanism for data gathering is a major constituent influencing these standards. Several researchers have provided significant evidence on the advantage of mobile sink (MS) in performing effective gathering of relevant data. However, determining the trajectory for MS is an NP-hard-problem. Especially in delay-inevitable applications, it is challenging to select the best-stops or rendezvous points (RPs) for MS and also to design an efficient route for MS to gather data. To provide a suitable solution to these challenges, we propose in this paper, a game theory and enhanced ant colony based MS route selection and data gathering (GTAC-DG) technique. This is a distributed method of data gathering using MS, combining the optimal decision making skill of game theory in selecting the best RPs and computational swarm intelligence of enhanced ant colony optimization in choosing the best path for MS. GTAC-DG helps to reduce data transfer and management, energy consumption and delay in data delivery. The MS moves in a reliable and intelligent trajectory, extending the lifetime and conserving the energy of WSN. The simulation results prove the effectiveness of GTAC-DG in terms of metrics such as energy and network lifetime.

     

Energy efficient dispatch strategy for the dual-functional mobile sink in wireless rechargeable sensor networks

Scavenging energy from radio-frequency (RF) signals has drawn significant attention in recent years. By introducing the technology of RF energy harvesting into wireless sensor networks, a new type of network named mobile data gathering based wireless rechargeable sensor network (MGWRSN) is considered in this paper. In the MGWRSN, a dual-functional mobile sink (MS) which has the abilities of data collecting and RF energy generating is employed. Data sensed by sensor nodes is gathered at several selected head nodes (HNs). Through using the RF energy supplied by the MS, the HNs deliver the gathered data to the MS arriving at the corresponding rendezvous points (RPs). In our works, the network energy consumption model of the MGWRSN is built, and the energy efficient dispatch strategy for the MS is studied, aiming at cutting down the total network energy consumption. For the simplest case, i.e., the one-HN MGWRSN, the optimal location of the RP is provided to minimize the total network energy consumption. After that, the researches are extended into the case of multi-HN MGWRSN and a heuristic dispatch strategy named HEEDS is proposed. Theoretical analysis and numerical results show that: (1) in the one-HN MGWRSN, the optimal location of the RP is close related to the data bulk to be transmitted, the unit mobility energy cost, the required bit error rate, the modulation scheme, and the departure position of the MS; (2) comparing with the existing algorithm WRP which directly dispatches the MS to the locations of HNs to collect data, the proposed strategy HEEDS is shown to be more energy efficient. Moreover, when a high energy transfer power is available at the MS, HEEDS renders shorter packet delay compared to WRP.     

Efficient Approach for Maximizing Lifespan in Wireless Sensor Networks by Using Mobile Sinks

Recently, sink mobility has been shown to be highly beneficial in improving network lifetime in wireless sensor networks (WSNs). Numerous studies have exploited mobile sinks (MSs) to collect sensed data in order to improve energy efficiency and reduce WSN operational costs. However, there have been few studies on the effectiveness of MS operation on WSN closed operating cycles. Therefore, it is important to investigate how data is collected and how to plan the trajectory of the MS in order to gather data in time, reduce energy consumption, and improve WSN network lifetime. In this study, we combine two methods, the cluster‐head election algorithm and the MS trajectory optimization algorithm, to propose the optimal MS movement strategy. This study aims to provide a closed operating cycle for WSNs, by which the energy consumption and running time of a WSN is minimized during the cluster election and data gathering periods. Furthermore, our flexible MS movement scenarios achieve both a long network lifetime and an optimal MS schedule. The simulation results demonstrate that our proposed algorithm achieves better performance than other well‐known algorithms.     

WSNs中基于智能水滴的信宿路径规划算法

为了有效避免无线传感网络(WSNs)中的热点问题,常利用移动信宿收集数据。信宿依据预定路线遍历预定的驻留点(RPs)。而其他传感节点就将数据传输至离自己最近的驻留点。因此,构建最优的RPs非常重要。为此,提出基于智能水滴的信宿路径规划(IWD-SPP)算法。提出IWD-SPP算法的目的在于延长网络寿命,并最小化转发数据包的能量消耗。利用智能水滴算法构建最优的RPs,规划信宿的移动路径。仿真结果表明,提出的IWD-SPP算法在能量消耗和网络寿命方面的性能优于同类算法。     

A novel approach for designing delay efficient path for mobile sink in wireless sensor networks

In the recent years, the use of mobile sink has drawn enormous attention for data collection in wireless sensor networks (WSNs). Mobile sink is well known for solving hotspot or sinkhole problem. However, the design of an efficient path for mobile sink has tremendous impact on network lifetime and coverage in data collection process of WSNs. This is particularly an important issue for many critical applications of WSNs where data collection requires to be carried out in delay bound manner. In this paper, we propose a novel scheme for delay efficient trajectory design of a mobile sink in a cluster based WSN so that it can be used for critical applications without compromising the complete coverage of the target area. Given a set of gateways (cluster heads), our scheme determines a set of rendezvous points for designing path of the mobile sink for critical applications. The scheme is based on the Voronoi diagram. We also propose an efficient method for recovery of the orphan sensor nodes generated due to the failure of one or more cluster heads during data collection. We perform extensive simulations over the proposed algorithm and compare its results with existing algorithms to demonstrate the efficiency of the proposed algorithm in terms of network lifetime, path length, average waiting time, fault tolerance and adaptability etc. For the fault tolerance, we simulate the schemes using Weibull distribution and analyze their performances.     

WSNs中基于粒子群优化的信宿移动路径规划算法

感测数据,再将数据传输至信宿是无线传感网络(WSNs)中节点的首要任务。传感节点由电池供电,它们的多数能量用于传输数据,越靠近信宿的节点,传输的数据量越大。因此,这些节点的能耗速度快,容易形成能量-空洞问题。而通过移动信宿收集数据能够缓解能量-空洞问题。为此,提出基于粒子群优化的信宿移动路径规划(PSO-RPS)算法。PSO-RPS算法结合数据传递时延和信息速率两项信息选择驻留点,并利用粒子群优化算法选择最优的驻留点,进而构建时延有效的信宿收集数据的路径。仿真结果表明,提出的PSO-RPS算法有效地控制路径长度,缩短了收集数据的时延。     

Minimum spanning tree–based delay‐aware mobile sink traversal in wireless sensor networks

Energy efficient data collection in a delay‐bound application is a challenging issue for mobile sink–based wireless sensor networks. Many researchers have proposed the concept of rendezvous points (RPs) to design the path for the mobile sink. Rendezvous points are the locations in the network where the mobile sink halts and collects data from the nearby sensor nodes. However, the selection of RPs for the design of path has a significant impact on timely data collection from the network. In this paper, we propose an efficient algorithm for selection of the RPs for efficient design of mobile sink trajectory in delay‐bound applications of wireless sensor networks. The algorithm is based on a virtual path and minimum spanning tree and shown to maximize network lifetime. We perform extensive simulations on the proposed algorithm and compare results with the existing algorithms to demonstrate the efficiency of the proposed algorithm of various performance metrics.     

Rendezvous Planning in Wireless Sensor Networks with Mobile Elements

Recent research shows that significant energy saving can be achieved in wireless sensor networks by using mobile elements (MEs) capable of carrying data mechanically. However, the low movement speed of MEs hinders their use in data-intensive sensing applications with temporal constraints. To address this issue, we propose a rendezvous-based approach in which a subset of nodes serve as the rendezvous points (RPs) that buffer data originated from sources and transfer to MEs when they arrive. RPs enable MEs to collect a large volume of data at a time without traveling long distances, which can achieve a desirable balance between network energy saving and data collection delay. We develop two rendezvous planning algorithms, RP-CP and RP-UG. RP-CP finds the optimal RPs when MEs move along the data routing tree while RP-UG greedily chooses the RPs with maximum energy saving to travel distance ratios. We design the Rendezvous-based Data Collection protocol that facilitates reliable data transfers from RPs to MEs in presence of significant unexpected delays in ME movement and network communication. Our approach is validated through extensive simulations.     

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.     

REBTAM: reliable energy balance traffic aware data reporting algorithm for object tracking in multi-sink wireless sensor networks

Recently, Multi-sink Wireless Sensor Networks (WSNs) have received more and more attention due to their significant advantages over the single sink WSNs such as improving network throughput, balancing energy consumption, and prolonging network lifetime. Object tracking is regarded as one of the key applications of WSNs due to its wide real-life applications such as wildlife animal monitoring and military area intrusion detection. However, many object tracking researches usually focus on how to track the location of objects accurately, while few researches focus on data reporting. In this work, we propose an efficient data reporting method for object tracking in multi-sink WSNs. Due to the limited energy resource of sensor nodes, it seems especially important to design an energy efficient data reporting algorithm for object tracking in WSNs. Moreover, the reliable data transmission is an essential aspect that should be considered when designing a WSN for object tracking application, where the loss of data packets will affect the accuracy of the tracking and location estimation of a mobile object. In addition, congestion in WSNs has negative impact on the performance, namely, decreased throughput, increased per-packet energy consumption and delay, thus congestion control is an important issue in WSNs. Consequentially, this paper aims to achieve both minimum energy consumption in reporting operation and balanced energy consumption among sensor nodes for WSN lifetime extension. Furthermore, data reliability is considered in our model where the sensed data can reach the sink node in a more reliable way. Finally, this paper presents a solution that sufficiently exerts the underloaded nodes to alleviate congestion and improve the overall throughput in WSNs. This work first formulates the problem as 0/1 Integer Linear Programming problem, and proposes a Reliable Energy Balance Traffic Aware greedy Algorithm in multi-sink WSNs (REBTAM) to solve the optimization problem. Through simulation, the performance of the proposed approach is evaluated and analyzed compared with the previous work which is related to our topic such as DTAR, NBPR, and MSDDGR protocols.     

MiniTE: data acquisition routing for wireless sensor networks

Routing is one of the most important supporting parts in wireless sensor networks (WSNs) application that directly affects the application efficiency. Routing time and energy consumption are two major factors used to evaluate WSNs routing. This article proposes a minimum routing time and energy consumption (MiniTE) routing, which can ensure feasibility of the routing protocol both in routing time and energy consumption. Based on the MiniTE, WSNs can be partitioned into different regions according to the received signal strength indication (RSSI). Messages are sent by nodes in the region to their parent node and again up to their parent node until finally to the sink node. Theoretic evaluation and simulation results are given to verify the features of the protocol.     

Novel service protocol for supporting remote and mobile users in wireless sensor networks with multiple static sinks

A wireless sensor network typically consists of users, a sink, and a number of sensor nodes. The users may be remotely connected to a wireless sensor network and via legacy networks such as Internet or Satellite the remote users obtain data collected by the sink that is statically located at a border of the wireless sensor network. However, in practical sensor network applications, there might be two types of users: the traditional remote users and mobile users such as firefighters and soldiers. The mobile users may move around sensor fields and they communicate with the static sink only via the wireless sensor networks in order to obtain data like location information of victims in disaster areas. For supporting the mobile users, existing studies consider temporary structures. However, the temporary structures are constructed per each mobile user or each source nodes so that it causes large energy consumption of sensor nodes. Moreover, since some of them establish the source-based structure, sinks in them cannot gather collective information like mean temperature and object detection. In this paper, to effectively support both the remote users and the mobile users, we propose a novel service protocol relying on the typical wireless sensor network. In the protocol, multiple static sinks connect with legacy networks and divide a sensor field into the number of the multiple sinks. Through sharing queries and data via the legacy networks, the multiple static sinks provide high throughput through distributed data gathering and low latency through short-hops data delivery. Multiple static sinks deliver the aggregated data to the remote users via the legacy networks. In case of the mobile users, when a mobile user moves around, it receives the aggregated data from the nearest static sink. Simulation results show that the proposed protocol is more efficient in terms of energy consumption, data delivery ratio, and delay than the existing protocols.     

An Energy Conservation MAC Protocol in Wireless Sensor Networks

Wireless sensor networks use battery-operated computing and sensing devices. Because of the limitation of battery power in the sensor nodes, energy conservation is a crucial issue in wireless sensor networks. Consequently, there is much literature presenting energy-efficient MAC protocols based on active/sleep duty cycle mechanisms to conserve energy. Convergecast is a common communication pattern across many sensor network applications featuring data gathering from many different source nodes to a single sink node. This leads to high data collision rates, high energy consumption, and low throughput near the sink node. This paper proposes an efficient slot reservation MAC protocol to reduce energy consumption and to make transmission more efficient in data gathering wireless sensor networks. The simulation results show that our protocol provides high throughput, low delivery latency and low energy consumption compared to other methods.

Multi-channel support for DMAC in WSNs

Currently most wireless sensor network applications assume the presence of single-channel medium access control (MAC) protocols. However, lower sensing range result in dense networks, single-channel MAC protocols may be inadequate due to higher demand for the limited bandwidth. In this paper we proposed a method of multi-channel support for DMAC in Wireless sensor networks (WSNs). The channel assignment method is based on local information of nodes. Our multi-channel DMAC protocol implement channel distribution before message collecting from source nodes to sink node and made broadcasting possible in DMAC. Analysis and simulation result displays this multi-channel protocol obviously decreases the latency without increasing energy consumption.     

无线传感器网络中联合功率 控制和速率调整

 无线传感器网络本质上是能量受限的,而且,传感器节点扮演着数据收集和数据转发的双重角色.本文提出了怎样分配传感器节点的功率用于转发其它节点的数据.在节点的转发功率分配比确定后,研究了采用价格作为一种方法,刺激节点与它到数据采集节点路径上的所有节点合作.通过把无线传感器网络中数据收集和传输抽象为一个网络效用最大化问题,通过采用对偶分解技术,提出了一种迭代价格与联合功率控制和速率调整的分布式算法.实验表明,该算法能提高系统的性能,同时降低功率的消耗.     

时延受限的移动sink数据收集算法

在实时性要求比较高的应用中,时延要求限制了sink的移动速率与移动轨迹,sink的移动速率限制了节点与sink的通信时间,因此很难兼顾时延要求与数据收集效率。提出一种时延受限的移动sink数据收集算法MSDC,在低能耗缓存区内找到一条sink的最优移动轨迹,在有限的时间限制内利用sink的移动性来提升传感器网络的数据收集性能。仿真结果表明,与已有算法比较,该方案能够提高网络数据采集量,降低能耗,延长网络生命周期。     

BECPA: Bandwidth Efficient Cluster Based Packet Aggregation in Wireless Sensor Network

In recent years, energy consumption and data gathering is a foremost concern in many applications of wireless sensor networks (WSNs). The major issue in WSNs is effective utilization of the resource as energy and bandwidth with a large gathering of data from the monitoring and control applications. This paper proposes novel Bandwidth Efficient Cluster based Packet Aggregation algorithm for heterogeneous WSNs. It combines the idea of variable packet generation rate of each node with random data. The nodes are randomly distributed with different energy level and are equal in numbers. It uses the perfectly compressible aggregation function at cluster head based on the correlation of packets and data generated by each node. Compare to state-of-the-art solutions, the algorithm shows 4.43 % energy savings with reduced packet delivery ratio (62.62 %) at the sink. It shows better bandwidth utilization in packet aggregation than data aggregation.     

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.     

Virtual region based data gathering method with mobile sink for sensor networks

To solve the hotspot problem in wireless sensor networks, a type of virtual region based data gathering method (VRDG) with one mobile sink is proposed. Network is divided into several virtual regions consisting of three or less data gathering unit. One or more leaders are selected in each region according to their residual energy as well as the distance to all of the neighbors. Only the leaders upload data to sink in data gathering phase that effectively reduce energy consumption and end-to-end delay. Moreover, the “maximum step distance” could be calculated out by nodes to find out the best transmission path to the leader which further balance energy consumption of the whole network. Simulation results show that VRDG is energy efficient in comparing with MSE, SEP and LEACH. It also does well in prolonging network lifetime as well as in enhancing the efficiency of data collection.