An Optimal Clustering Routing Algorithm for Wireless Sensor Networks with Small-World Property

Popularity of Mobile Wireless Sensor Network (MWSN) has increased tremendously due to the ability to connect the physical world with the virtual world. In MWSN, Sensor nodes move freely in a target area without the need of any special infrastructure. MWSN has attracted many researchers as it has introduced unique challenges in aspects like resource management, coverage, routing protocols, security in many applications such as target tracking in military applications, detection of catastrophic events, environment monitoring, health applications etc. Due to mobility, routing process in MWSN has become more complicated as connections in the network can change dynamically. This paper proposes a Mobility-Aware Multi-Objective Hybrid Routing Algorithm (MMOHRA) for Wireless Sensor Network (WSN). MMOHRA selects the best route and forwards the data packets from source to sink using multiple metrics such as Average Energy consumption, Control Overhead, Reaction Time, LQI, and HOP Count. Performance of MMOHRA is compared with Simple Hybrid Routing Protocol (SHRP) and Dynamic Multi-objective Routing Algorithm (DyMORA) using metrics such as Average Energy Consumption, Packet Delivery Ratio, and Jitter. MMOHRA improves the Average Energy Consumption (AEC) by a factor of 14.1% as compared with SHRP and 8.13 % as compared to DyMORA. MMOHRA outperformed SHRP and DyMORA in terms of packet Delivery Ratio (PDR) by 10.17 % and 9.83 % respectively.

Energy balance is an important performance index in the design of routing algorithm for wireless sensor networks. A swarm intelligence optimization based routing algorithm for wireless sensor networks is proposed, whose kernel idea is taking less hop numbers into consideration and choosing the nodes with less pheromone as next hop to avoid some nodespsila prematurely exhausting their energy because of too concentrated routes through the nodes. The experiments show that the algorithm proposed in this paper is better than the directed diffusion routing protocol both in end-to-end delay and global energy balance and can effectively balance the global energy consumption and prolong the network lifetime.

Recent years have witnessed a proliferation of routing algorithms for Wireless Sensor Networks (WSNs), hence complicating the choice of the proper algorithm to be used for a given application. Simulation frameworks represent a viable solution to anticipate crucial choices, however existing solutions do not encompass the impact of changes (e.g., route updates, node crashes) on the nodes behavior and vice-versa. This article proposes a novel adaptive modeling approach to master the complexity of the thorough simulation of routing algorithms for WSN. Experimental results are provided showing the effectiveness of the proposed approach at managing changes, and dealing with detailed aspects, during the simulation and comparison of several routing algorithms.

The energy constraint sensor nodes operate on limited batteries, so the energy consumption is a key design criterion for the routing protocols in wireless sensor networks. Comparing with single path routing algorithm, multi-path routing algorithm can balance the network energy distribution and extend the network lifetime better. In this paper, we propose an Ant Colony- Based Multi-path Routing Algorithm, which uses Ant Colony Algorithm(ACA) to discover disjoint multipaths between the source nodes and sink node. We also propose a load balancing scheme to distribute the traffic over multipaths discovered. Simulation results show that our proposed algorithm achieves a higher node energy efficiency and longer network lifetime than that of the previous multipath routing algorithm.


 
 
 Cluditem is a routing algorithm for wireless sensor networks developed for applications of environmental monitoring with periodic measurement of variables. These applications tolerate a maximum phase shift of the clocks of nodes in the order of milliseconds. This paper proposes two centralized synchronization schemes that introduce a limited processing load. The objective of the work was to assess the impact on the energy consumption of the incorporation of synchronization techniques described. Simulations of the full communication protocol were conducted in the NS2 environment and a comparative study of results was performed. This study showed that the first proposed schema is more convenient with respect to energy consumption, when the area to monitor has reduced dimensions. On the other hand, the second scheme, although it permits to work in larger areas, introduces a decrease in the network lifetime in the order of 14%.
 
 

Recently, network localization systems that are based on inter-node ranges have received significant attention. Geographic routing has been considered an application which can utilize the location information from these localization systems. In this paper, we firstly recognize that sensor network localization algorithms generate positioning data with different error patterns compared to those networks where node positions are determined directly from GNSS measurements. Secondly, by simulating practical sensor network scenarios using data from our localization algorithm, we observe that existing geographic routing algorithms in wireless sensor networks (WSNs) adopt very simplistic methods in the treatment of position error, without due consideration of error distribution. Additionally, an insight is given into localization algorithms for WSNs with inhomogeneous error environments. Our observations represent an initial step toward a detailed understanding and design of efficient geographic routing algorithms in location aware WSNs.

Wireless Sensor Networks (WSNs) are usually comprised of a large number of sensor nodes which have limited power resources and require energy efficient routing algorithms. We have presented an Adaptive Transmission Power - Geographical and Energy Aware Routing (ATP-GEAR) algorithm in this paper, which routes the packet towards the destination by calculating the cost of the neighbors of a node in terms of their location and current battery level and transmitting the packet to the lowest costing node with the minimum required transmission power. We analyze the performance of our algorithm based on total power consumption and end-to-end delay from source to destination. Simulation results show that ATP-GEAR yields almost 25% less power consumption and 17% less end-to-end delay when compared with traditional Cluster Based Routing (CBR).

The main goal of research concerning energy aware routing algorithm for wireless sensor network is to increase the lifetime and long-term connectivity of the wireless sensor networks. However, most of energy aware routing algorithms do not take into account the clustering mechanism efficiently. In this paper, we present an efficient energy aware routing algorithm for the wireless sensor networks. In our algorithm, the data aggregation technique and adaptive clustering mechanism are considered for reducing and compacting the cumulative size of packets on the wireless sensor networks. Simulation results show that the energy usage of EAR-ACM is significantly reduced compared with the previous clustering based routing algorithm for the sensor networks.KeywordsSensor NetworkSensor NodeWireless Sensor NetworkCluster HeadData PacketThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Routing algorithms for large-scale sensor networks should be capable of finding energy efficient paths to prolong the lifetime of the networks in a decentralized manner. With this respect, Ant System has several proper characteristics for routing algorithm in large-scale wireless sensor networks. First, its distributed mechanism enables routing algorithm to find a solution with only local information and be robust for uncertainties in wireless sensor networks. Second, the framework of the Ant System is proper to solve dynamic problems such as routing problem. Transition probability in Ant System can be used to estimate how good a given routing path is. Capturing these features, this work proposes two Ant Systems based routing algorithms, which are AS-RWSNs (Ant System for Routing in Wireless Sensor Networks) and SAAS-RWSN (Structure-Aware AS-RWSN). The AS-RWSN applies the original Ant System to routing algorithm for wireless sensor network and SAAS-RSN upgrades AS-RWSN with considering properties of network structure such as degree of node. In SAAS-RSN, sensors with high node degree have high data traffic since they have more routing paths. Consequently, SAAS-RSN achieves an energy balance over sensor network through this routing scheme. We demonstrate the effectiveness of the proposed algorithms by comparing three existing routing algorithms.

Wireless sensor networks area collection of a large number of unattended sensor nodes. The sensor nodes are dynamically deployed in the region. In wireless sensor networks, the unlicensed sensor nodes use their temporarily available vacant licensed channels or spectrum band in a telecommunication network. The many open challenges with issues such as adaptive in self-organisation, fault-tolerance and network scalability with cooperative spectrum sensing and sharing are identifying new challenges in wireless sensor networks. In this paper, we proposed the bio-inspired adaptive routing algorithm for cognitive radio wireless sensor networks. The utilisation of the foraging approach of ANTs and BEEs for making the decision of using the available spectrum sensing and sharing of channels over multi-hops communication, provides the method to utilise idle channel and decrease the delay for communication in wireless sensor network. In this paper, we design the algorithm to solve the issue of wireless sensor network and performance of classical routing protocol LEACH and cognitive radio sensor networks (CRSN) evaluates the parameters which proof the self-organisation routing algorithm.

LEACH routing algorithm is an important routing algorithm in wireless sensor networks (WSN s), There exist imperfections in the LEACH algorithm, which can be summarized as the uneven number of cluster heads, the unreasonable distribution of cluster heads and inappropriate selection of cluster heads. Researchers has put forward algorithms based on LEACH as improvement. In this paper, we focused on analysis of inappropriate selection of clusters in LEACH routing algorithm from energy consumption approach. To solve this existing issue in LEACH routing algorithm, a new algorithm that maximum the efficiency of energy consumption is proposed in this paper, which is LEACH-OptCluster. This paper analyses the disadvantages of LEACH routing algorithm. LEACH-C routing algorithm is introduced as comparison with proposed algorithm. Simulation of LEACH-OptCluster is conducted through Matlab. With simulation results, further analysis indicates the proposed LEACH-OptCluster routing algorithm can prolong the WSNs network working time effectively through balancing the overall energy consumption of network nodes.

Due to the lack of accurate evaluation of the transmission characteristics of the wireless communication links, routing algorithms in wireless sensor networks may result in poor network performance. This paper presents a link quality-based reliable routing algorithm. According to the link qualities evaluated by RSSI, neighbor nodes can be partitioned into different regions. First, based on a realistic link model and test results, an asymmetric link region is indicated, where selecting a neighboring node in this region as the next hop node will greatly degrade the transmission reliability. Based on this, the neighboring area of a node is divided into four regions, that is, connected, transitional, asymmetric, and disconnected regions. Then, route selection ways for different regions are presented, and different priorities of the nodes in different regions to be selected as the next hop node are assigned. Finally, the performance of the RSRE is tested in a real-world test-bed consists of 40 nodes, and compared with the Min-hop routing algorithm and the ETX based routing algorithm. The results show that the RSRE has better data transmission reliability, and hop distribution.

This paper reports on a project to investigate, build upon and test a relatively new routing algorithm for wireless sensor networks. The algorithm is based on the behaviour of ants in nature. It attempts to address the need for an energy-efficient routing algorithm for wireless sensor networks. This journal article briefly discusses the algorithm’s design, including the algorithm outline and relevant data structures and formulae. The article proceeds to discuss the testing procedure and test results for the algorithm. Finally, a conclusion summarising findings and recommendations for future work is included.

The work of wireless sensor networks (WSNs) depends on reliable coverage of the area to be monitored. The problem of coverage holes arises when one or more nodes fail due to energy depletion or harsh physical environments. Furthermore, random deployment of nodes could lead to a high degree of overlapping coverage among the sensor nodes. While there are many research papers on optimal deployment of sensor nodes, coverage holes that appear post-deployment are not often considered. In this paper, we propose an algorithm that employs adjustable sensing ranges and exploits node mobility to repair emergent coverage holes. The algorithm selects suitable nodes by gauging the degree of overlap and the residual energy of each node in the vicinity of the coverage hole. We have evaluated the performance of the algorithm via simulation, and compared with baseline approaches in terms of coverage performance and energy cost. Simulations have shown that our approach outperforms others in terms of coverage and network lifetime.

This paper introduces the measure of information as a new criterion for the performance analysis of routing algorithms in wireless sensor networks. We argue that since the objective of a sensor network is to estimate a two dimensional random field, a routing algorithm must maximize information flow about the underlying field over the lifetime of the sensor network. We develop two novel algorithms, MIR (maximum information routing) and CMIR (conditional maximum information routing) designed to maximize information flow, and present a comparison of the algorithms to a previously proposed algorithm-MREP (maximum residual energy path) through simulations. We show that the proposed algorithms give significant improvement in terms of information flow, when compared to MREP.