Zone-based routing protocol with mobility consideration for wireless sensor networks

Hierarchical routing and clustering mechanisms in Wireless Sensor Networks (WSN) help to reduce the energy consumptions and the overhead created when all the sensor nodes in the network are sending information to the central data collection point. Most of the routing and clustering protocols proposed for WSN assume that the nodes are stationary. However, in applications like habitat monitoring or search and rescue, that assumption makes those clustering mechanisms invalid, since the static nature of sensors is not real. In this paper, we propose Zone-based Routing Protocol for Mobile Sensor Networks (ZoroMSN) that considers the design aspects such as mobility of sensors, zones and routes maintenance, information update and communication between sensor nodes. Simulation results show the effectiveness and strengths of the ZoroMSN protocol such as a low routing and mobility overhead, while achieving a good performance in WSN using small zone sizes and sensors with low speed. Simulation results also show that ZoroMSN outperforms existing LEACH-ME and LEACH-M protocols in terms of network lifetime and energy consumptions.     

Extending the Lifetime of Wireless Sensor Networks Through Mobile Relays

We investigate the benefits of a heterogeneous architecture for wireless sensor networks (WSNs) composed of a few resource rich mobile relay nodes and a large number of simple static nodes. The mobile relays have more energy than the static sensors. They can dynamically move around the network and help relieve sensors that are heavily burdened by high network traffic, thus extending the latter's lifetime. We first study the performance of a large dense network with one mobile relay and show that network lifetime improves over that of a purely static network by up to a factor of four. Also, the mobile relay needs to stay only within a two-hop radius of the sink. We then construct a joint mobility and routing algorithm which can yield a network lifetime close to the upper bound. The advantage of this algorithm is that it only requires a limited number of nodes in the network to be aware of the location of the mobile relay. Our simulation results show that one mobile relay can at least double the network lifetime in a randomly deployed WSN. By comparing the mobile relay approach with various static energy-provisioning methods, we demonstrate the importance of node mobility for resource provisioning in a WSN.      

Fish bone structure based data aggregation and routing in wireless sensor network: multi-agent based approach

Wireless sensor networks (WSNs) are constrained by limited node (device) energy, low network bandwidth, high communication overhead and latency. Data aggregation alleviates the constraints of WSN. In this paper, we propose a multi-agent based homogeneous temporal data aggregation and routing scheme based on fish bone structure of WSN nodes by employing a set of static and mobile agents. The primary components of fishbone structure are backbone and ribs connected to both sides of a backbone. A backbone connects a sink node and one of the sensor nodes on the boundary of WSN through intermediate sensor nodes. Our aggregation scheme operates in the following steps. (1) Backbone creation and identifying master centers (or nodes) on it by using a mobile agent based on parameters such as Euclidean distance, residual energy, backbone angle and connectivity. (2) Selection of local centers (or nodes) along the rib of a backbone connecting a master center by using a mobile agent. (3) Local aggregation process at local centers by considering nodes along and besides the rib, and delivering to a connected master center. (4) Master aggregation process along the backbone from boundary sensor node to the sink node by using a mobile agent generated by a boundary sensor node. The mobile agent aggregates data at visited master centers and delivers to the sink node. (5) Maintenance of fish bone structure of WSN nodes. The performance of the scheme is simulated in various WSN scenarios to evaluate the effectiveness of the approach by analyzing the performance parameters such as master center selection time, local center selection time, aggregation time, aggregation ratio, number of local and master centers involved in the aggregation process, number of isolated nodes, network lifetime and aggregation energy. We observed that our scheme outperforms zonal based aggregation scheme.     

Adaptive directed evolved NSGA2 based node placement optimization for wireless sensor networks

Wireless sensor network (WSN) is a wireless network composed of a large number of static or mobile sensors in a self-organizing and multi-hop manner. In WSN research, node placement is one of the basic problems. In view of the coverage, energy consumption and the distance of node movement, an improved multi-objective optimization algorithm based on NSGA2 is proposed in this paper. The proposed algorithm is used to optimize the node placement of WSN. The proposed algorithm can optimize both the node coverage and lifetime of WSN while also considering the moving distance of nodes, so as to optimize the node placement of WSN. The experiments show that the improved NSGA2 has improvements in both searching performance and convergence speed when solving the node placement problem.

     

A boolean spider monkey optimization based energy efficient clustering approach for WSNs

Wireless sensor network (WSN) consists of densely distributed nodes that are deployed to observe and react to events within the sensor field. In WSNs, energy management and network lifetime optimization are major issues in the designing of cluster-based routing protocols. Clustering is an efficient data gathering technique that effectively reduces the energy consumption by organizing nodes into groups. However, in clustering protocols, cluster heads (CHs) bear additional load for coordinating various activities within the cluster. Improper selection of CHs causes increased energy consumption and also degrades the performance of WSN. Therefore, proper CH selection and their load balancing using efficient routing protocol is a critical aspect for long run operation of WSN. Clustering a network with proper load balancing is an NP-hard problem. To solve such problems having vast search area, optimization algorithm is the preeminent possible solution. Spider monkey optimization (SMO) is a relatively new nature inspired evolutionary algorithm based on the foraging behaviour of spider monkeys. It has proved its worth for benchmark functions optimization and antenna design problems. In this paper, SMO based threshold-sensitive energy-efficient clustering protocol is proposed to prolong network lifetime with an intend to extend the stability period of the network. Dual-hop communication between CHs and BS is utilized to achieve load balancing of distant CHs and energy minimization. The results demonstrate that the proposed protocol significantly outperforms existing protocols in terms of energy consumption, system lifetime and stability period.     

Relay Node Deployment Strategies in Heterogeneous Wireless Sensor Networks

In a heterogeneous wireless sensor network (WSN), relay nodes (RNs) are adopted to relay data packets from sensor nodes (SNs) to the base station (BS). The deployment of the RNs can have a significant impact on connectivity and lifetime of a WSN system. This paper studies the effects of random deployment strategies. We first discuss the biased energy consumption rate problem associated with uniform random deployment. This problem leads to insufficient energy utilization and shortened network lifetime. To overcome this problem, we propose two new random deployment strategies, namely, the lifetime-oriented deployment and hybrid deployment. The former solely aims at balancing the energy consumption rates of RNs across the network, thus extending the system lifetime. However, this deployment scheme may not provide sufficient connectivity to SNs when the given number of RNs is relatively small. The latter reconciles the concerns of connectivity and lifetime extension. Both single-hop and multihop communication models are considered in this paper. With a combination of theoretical analysis and simulated evaluation, this study explores the trade-off between connectivity and lifetime extension in the problem of RN deployment. It also provides a guideline for efficient deployment of RNs in a large-scale heterogeneous WSN.     

Deploying mobile nodes for maximal energy matching in WSNs

This paper proposes a self‐stabilizing distributed algorithm for deploying mobile nodes with loaded energy to the stationary nodes by considering the energy those stationary nodes need. The goal is to deploy mobile nodes to appropriate locations for energy supplements such that the network lifetime can be extended. The problem of maximizing the lifetime is NP‐hard. Therefore, it is unrealistic to search for an optimal solution in sensor networks. In this paper, we design several simple rules for mobile nodes and stationary nodes separately in order to find a feasible solution. Simple rules are especially suitable and necessary for low computability sensor networks. Our algorithm is simple and distributed. We prove that our method is stable and has good performance. Simulations show its efficiency too. Copyright © 2010 John Wiley & Sons, Ltd.     

Survey on Wireless Sensor Network Applications and Energy Efficient Routing Protocols

Wireless sensor network (WSN) is a group of small power-constrained nodes that sense data and communicate it to the base station (BS). These nodes cover a vast region of interest (ROI) for several purposes according to the application need. The first challenge encountered in WSNs is how to cover the ROI perfectly and send the monitored data to the BS. Although the energy introduced during setup phase and the violation of energy fairness constraint of dynamic routing topologies, they achieve high network performance in terms of coverage and connectivity. In this paper, we categorize the applications of WSN based on different aspects to show the major protocol design issues. Thus, the energy efficiency of the recent proactive routing protocols is studied from different angles. The energy overhead and energy fairness of each protocol were carefully analyzed. The most energy efficient routing protocols for homogeneous proactive networks were studied and compared to highlight the research challenges and existing problems in this area. The results proved that energy overhead and route selection are the most effective aspects of network lifetime and network efficiency.

     

Double Cluster Based Energy Efficient Routing Protocol for Wireless Sensor Network

Reducing the energy consumption of sensor nodes and prolonging the life of the network is the central topic in the research of wireless sensor network (WSN) protocol. The low-energy adaptive clustering hierarchy (LEACH) is one of the hierarchical routing protocols designed for communication in WSNs. LEACH is clustering based protocol that utilizes randomized rotation of local cluster-heads to evenly distribute the energy load among the sensors in the network. But LEACH is based on the assumption that each sensor nodes contain equal amount of energy which is not valid in real scenarios. A developed routing protocol named as DL-LEACH is proposed. The DL-LEACH protocol cluster head election considers residual energy of nodes, distance from node to the base station and neighbor nodes, which makes cluster head election reasonable and node energy consumption balance. The simulation results of proposed protocols are compared for its network life time in MATLAB with LEACH protocol. The DL-LEACH is prolong the network life cycle by 75 % than LEACH.     

无线传感网络移动分簇路由策略

无线传感网络(WSN)路由协议中,分簇路由具有拓扑管理方便、能量高效和数据融合简单等优点,成为当前重点研究的路由技术。通过研究各种环境下的移动传感器网络,有效地降低能耗则是研究移动无线传感器网络的重要目的之一。针对无线传感网络中移动性问题,基于LEACH协议,利用移动传感器网络中节点距离、速度和剩余能量等因素提出了能量高效的移动分簇路由算法。实验结果表明此算法能够较好地支持节点移动,从而降低网络能耗,延长网络生存时间。     

System lifetime optimization for heterogeneous sensor networks with a hub-spoke technology

As a specific area of sensor networks, wireless in-home sensor networks differ from general sensor networks in that the network has nodes with heterogeneous resources and dissimilar mobility attributes. For example, sensor with different radio coverage, energy capacity, and processing capabilities are deployed, and some of the sensors are mobile and others are fixed in position. The architecture and routing protocol for this type of heterogeneous sensor networks must be based on the resources and characteristics of their member nodes. In addition, the sole stress on energy efficiency for performance measurement is not sufficient. System lifetime is more important in this case. We propose a hub-spoke network topology that is adaptively formed according to the resources of its members. A protocol named resource oriented protocol (ROP) was developed to build the network topology. This protocol principally divides the network operation into two phases. In the topology formation phase, nodes report their available resource characteristics, based on which network architecture is optimally built. We stress that due to the existence of nodes with limitless resources, a top-down appointment process can build the architecture with minimum resource consumption of ordinary nodes. In the topology update phase, mobile sensors and isolated sensors are accepted into the network with an optimal balance of resources. To avoid overhead of periodic route updates, we use a reactive strategy to maintain route cache. Simulation results show that the hub-spoke topology built by ROP can achieve much longer system lifetime.     

Energy Efficient Clustering Scheme (EECS) for Wireless Sensor Network with Mobile Sink

The participants in the Wireless Sensor Network (WSN) are highly resource constraint in nature. The clustering approach in the WSN supports a large-scale monitoring with ease to the user. The node near the sink depletes the energy, forming energy holes in the network. The mobility of the sink creates a major challenge in reliable and energy efficient data communication towards the sink. Hence, a new energy efficient routing protocol is needed to serve the use of networks with a mobile sink. The primary objective of the proposed work is to enhance the lifetime of the network and to increase the packet delivered to mobile sink in the network. The residual energy of the node, distance, and the data overhead are taken into account for selection of cluster head in this proposed Energy Efficient Clustering Scheme (EECS). The waiting time of the mobile sink is estimated. Based on the mobility model, the role of the sensor node is realized as finite state machine and the state transition is realized through Markov model. The proposed EECS algorithm is also been compared with Modified-Low Energy Adaptive Clustering Hierarchy (MOD-LEACH) and Gateway-based Energy-Aware multi-hop Routing protocol algorithms (M-GEAR). The proposed EECS algorithm outperforms the MOD-LEACH algorithm by 1.78 times in terms of lifetime and 1.103 times in terms of throughput. The EECS algorithm promotes unequal clustering by avoiding the energy hole and the HOT SPOT issues.     

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.     

Assimilation of fuzzy clustering approach and EHO‐Greedy algorithm for efficient routing in WSN

The problems related to energy consumption and improvement of the network lifetime of WSN (wireless sensor network) have been considered. The base station (BS) location is the main concern in WSN. BSs are fixed, yet, they have the ability to move in some situations to collect the information from sensor nodes (SNs). Recently, introducing mobile sinks to WSNs has been proved to be an efficient way to extend the lifespan of the network. This paper proposes the assimilation of the fuzzy clustering approach and the Elephant Herding Optimization (EHO)‐Greedy algorithm for efficient routing in WSN. This work considers the separate sink nodes of a fixed sink and movable sink to decrease the utilization of energy. A fixed node is deployed randomly across the network, and the movable sink node moves to different locations across the network for collecting the data. Initially, the number of nodes is formed into the multiple clusters using the enhanced expectation maximization algorithm. After that, the cluster head (CH) selection done through a fuzzy approach by taking the account of three factors of residual energy, node centrality, and neighborhood overlap. A suitable collection of CH can extremely reduce the utilization of energy and also enhancing the lifespan. Finally, the routing protocol of the hybrid EHO‐Greedy algorithm is used for efficient data transmission. Simulation results display that the proposed technique is better to other existing approaches in regard to energy utilization and the system lifetime.     

Reinforcement learning movement path for multiple mobile sinks in wireless sensor networks

Mobile sink nodes play a very active role in wireless sensor network (WSN) routing. Because hiring these nodes can decrease the energy consumption of each node, end-to-end delay, and network latency significantly. Therefore, mobile sinks can soar the network lifetime dramatically. Generally, there are three movement paths for a mobile sink, which are as follows: (1) Random/stochastic, (2) controlled, and (3) fixed/ predictable/predefined paths. In this paper, a novel movement path is introduced as a fourth category of movement paths for mobile sinks. This path is based on deep learning, so a mobile sink node can go to the appropriate region that has more data at a suitable time. Thereupon, WSN routing can improve very much in terms of end-to-end delay, network latency, network lifetime, delivery ratio, and energy efficiency. The new proposed routing suggests a reinforcement learning movement path (RLMP) for multiple mobile sinks. The network in the proposed work consists of a couple of regions; each region can be employed for a special purpose, so this method is hired for any application and any size of the network. All simulations in this paper are done by network simulator 3 (NS-3). The experimental results clearly show that the RLMP overcomes other approaches by at least 32.48% in the network lifetime benchmark.     

Clustering Based Two Dimensional Motion of Sink Node in Wireless Sensor Networks

The wireless sensor network (WSN) is always known for its limited-energy issues and finding a good solution for energy minimization in WSNs is still a concern for researchers. Implementing mobility to the sink node is used widely for energy conservation or minimization in WSNs which reduces the distance between sink and communicating nodes. In this paper, with the intention to conserve energy from the sensor nodes, we designed a clustering based routing protocol implementing a mobile sink called ‘two dimensional motion of sink node (TDMS)’. In TDMS, each normal sensor node collects data and send it to their respective leader node called cluster head (CH). The sink moves in the two dimensional direction to collect final data from all CH nodes, particularly it moves in the direction to that CH which has the minimum remaining energy. The proposed protocol is validated through rigorous simulation using MATLAB and comparisons have been made with WSN’s existing static sink and mobile sink routing protocols over two different geographical square dimensions of the network. Here, we found that TDMS model gives the optimal result on energy dissipation per round and increased network lifetime.

     

Energy efficient clustering algorithms for wireless sensor networks: novel chemical reaction optimization approach

Clustering has been accepted as one of the most efficient techniques for conserving energy of wireless sensor networks (WSNs). However, in a two-tiered cluster based WSN, cluster heads (CHs) consume more energy due to extra overload for receiving data from their member sensor nodes, aggregating them and transmitting that data to the base station (BS). Therefore, proper selection of CHs and optimal formation of clusters play a crucial role to conserve the energy of sensor nodes for prolonging the lifetime of WSNs. In this paper, we propose an energy efficient CH selection and energy balanced cluster formation algorithms, which are based on novel chemical reaction optimization technique (nCRO), we jointly called these algorithms as novel CRO based energy efficient clustering algorithms (nCRO-ECA). These algorithms are developed with efficient schemes of molecular structure encoding and potential energy functions. For the energy efficiency, we consider various parameters such as intra-cluster distance, sink distance and residual energy of sensor nodes in the CH selection phase. In the cluster formation phase, we consider various distance and energy parameters. The algorithm is tested extensively on various scenarios of WSNs by varying number of sensor nodes and CHs. The results are compared with original CRO based algorithm, namely CRO-ECA and some existing algorithms to demonstrate the superiority of the proposed algorithm in terms of energy consumption, network lifetime, packets received by the BS and convergence rate.     

A distributed lightweight Redundancy aware Topology Control Protocol for wireless sensor networks

WSN consists of a large number of sensor nodes randomly deployed, and, in many cases, it is impossible to replace sensors when a node failure occurs. Thus, applications tend to deploy more nodes than necessary to cope with possible node failures and to increase the network lifetime, which leads to create some sensing and communication redundancy. However, sensors in the same region, may collect and forward the same information, which will waste more energy. In this paper, we propose a distributed Lightweight Redundancy aware Topology Control Protocol (LRTCP) for wireless sensor networks. It exploits the sensor redundancy in the same region by dividing the network into groups so that a connected backbone can be maintained by keeping a minimum of working nodes and turning off the redundant ones. LRTCP identifies equivalent nodes in terms of communication based on their redundancy degrees with respect of some eligibility rules. Simulation results indicate that, compared with existing distributed topology control algorithms, LRTCP improves network capacity and energy efficiency.     

Betweenness centrality based connectivity aware routing algorithm for prolonging network lifetime in wireless sensor networks

Network lifetime is the key design parameter for wireless sensor network protocols. In recent years, based on energy efficient routing techniques numerous methods have been proposed for enhancing network lifetime. These methods have mainly considered residual energy, number of hops and communication cost as route selection metrics. This paper introduces a method for further improvement in the network lifetime by considering network connectivity along with energy efficiency for the selection of data transmission routes. The network lifetime is enhanced by preserving highly connected nodes at initial rounds of data communication to ensure network connectivity during later rounds. Bassed on the above mentioned concept, a connectivity aware routing algorithm: CARA has been proposed. In the proposed algorithm, connectivity factor of a node is calculated on the basis of Betweenness centrality of a node and energy efficient routes are found by using fuzzy logic and ant colony optimization. The simulation results show that the proposed algorithm CARA performs better than other related state-of-the-art energy efficient routing algorithms viz. FML, EEABR and FACOR in terms of network lifetime, connectivity, energy dissipation, load balancing and packet delivery ratio.     

Prediction‐based cluster management for target tracking in wireless sensor networks

The key impediments to a successful wireless sensor network (WSN) application are the energy and the longevity constraints of sensor nodes. Therefore, two signal processing oriented cluster management strategies, the proactive and the reactive cluster management, are proposed to efficiently deal with these constraints. The former strategy is designed for heterogeneous WSNs, where sensors are organized in a static clustering architecture. A non‐myopic cluster activation rule is realized to reduce the number of hand‐off operations between clusters, while maintaining desired estimation accuracy. The proactive strategy minimizes the hardware expenditure and the total energy consumption. On the other hand, the main concern of the reactive strategy is to maximize the network longevity of homogeneous WSNs. A Dijkstra‐like algorithm is proposed to dynamically form active cluster based on the relation between the predictive target distribution and the candidate sensors, considering both the energy efficiency and the data relevance. By evenly distributing the energy expenditure over the whole network, the objective of maximizing the network longevity is achieved. The simulations evaluate and compare the two proposed strategies in terms of tracking accuracy, energy consumption and execution time. Copyright © 2010 John Wiley & Sons, Ltd.