Energy-efficent time synchronization algorithm for wireless sensor networks

Automatic localization is one of the major issues in Wireless Sensor Networks (WSN). DV-hop algorithm is a well-known localization algorithm in WSN but with limited localization accuracy. In this paper, an improved DV-hop localization algorithm in hybrid optical wireless sensor networks is proposed based on the optimization of the parameters in WSN. Various factors that affect the localization accuracy of the DV-hop algorithm in WSN are investigated, including the communication radius of the node, the number of beacon nodes and the number of the total nodes. As the DV-hop algorithm is applied into hybrid optical sensor and WSNs (O-WSN) with rectangular topology, different parameters have to be optimized accordingly. Simulation results show that the square topology outperforms the rectangle topology more than 45 % under the same network parameters using the improved DV-hop algorithm. Therefore another improved DV-hop called Sub-Square Weighted DV-hop (SSW DV-hop) is proposed for the rectangle topology. Both simulation and experiment results demonstrate that applying the SSW DV-hop algorithmin O-WSNs could significantly improve the localization accuracy.

Time Synchronization in WSNs with Random Communication Delays: A Constant Gain Design

This paper reviews the energy efficiency of several popular block-matching motion estimation algorithms that can be used in wireless video sensor network applications. Full search motion estimation provides the best image quality but requires high computing power. Therefore, only fast search algorithms are considered for deployment in wireless video sensor networks, which generally operate in remote, battery-constrained areas. However, the image quality of fast search algorithms also needs to be considered in the comparison. In this paper, those block-matching algorithms are compared using two criteria: 1) computing cost/energy consumption, and 2) image quality. The purpose of this review is to select the most energy efficient algorithm that retains image quality and can be applied to wireless video sensor network video compression applications.

The wireless sensor networks (WSNs) are usually deployed among widely area for environmental monitoring, data collection and other applications. In order to reduce the energy consumption and extend the lifetime of WSNs, as well as receive the data quickly, a source-based data aggregation algorithm (SBDA) for clustering wireless sensor networks is proposed. The method aggregated the data from sensor nodes and marked different transmission priority for the data. Simulation results show that, compared to existing protocols, the proposed method achieves a longer life time, and a lower packet drop ratio.

A large number of small sensors in wireless sensor network are battery-powered; one of the most important design criteria for this type of network is energy efficiency. Clustering provides an effective way for extending the lifetime of a sensor network. In this paper, we propose a maximum-votes and load-balance clustering algorithm (VLCA) for wireless sensor network Each sensor collects votes from their neighbors and calculates the total vote received. The more votes a sensor accumulates, the more important it is in the whole network During the clustering phase, sensors compete with each other based on the total votes each has received. The algorithm is completely distributed, locating-unaware and independent of network size and topology. Simulation results show that our VLCA can reduce the number of clusters by 20-50% and prolong the lifetime of a sensor network.

Concerning the problem that typical time synchronous algorithms used in multi-hop Wireless Sensor Network(WSN) mainly focus on increasing the network synchronization precision,but ignore such issues as the network energy,path hop and error accumulation,a cluster-based and energy-efficient hierarchical time synchronization algorithm was proposed based on a cluster hierarchical network structure.In this algorithm,a cluster node was selected to take a two-way synchronization with the cluster head,and its neighbor nodes achieved bidirectional synchronization indirectly through the passive monitoring mode.In such a way,the number of the packet's transmission was reduced while the digital signature pattern ensured the safety of transmission.In addition,the cycle update coefficient of synchronous group delay was quoted to further reduce the consumption of synchronization packets.The simulation results show that the algorithm reduces the energy consumption and prolongs the network life time,therefore this algorithm has certain practicability.

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.

In order to improve the location accuracy of unknown nodes in APIT algorithm in mobile wireless sensor networks, an improved APIT algorithm is proposed. A new test method called gravity center combination has been proposed for the InToOut and OutToIn errors in APIT. The algorithm further builds an anchor box by combining one-hop and two-hop information of nodes to limit the range and finally determine the location of unknown nodes to reduce the number of nodes that cannot be located. By improving the coverage and node availability, the positioning accuracy is eventually improved. The complexity is lowered by the lack of requirement of additional hardware, thus the improved algorithm is relatively easy to implement. The simulation results of the verification demonstrate that the updated algorithm improves the coverage ratio and the node usage efficiency compared with the other algorithm, thus makes the mobile node location more accurate.

A series of challenges exist in the process of sensor network research which can not be solved by one sensor node. Cooperative communication, based on the idea of spatial diversity, which makes different users or nodes in wireless network share their antennas or other network resources, is a promising technique toward improving performance of wireless sensor network significantly. This article adopts cooperation between nodes and opportunistic collaboration transmission strategy is proposed. Energy efficient power allocation algorithm in wireless sensor network is put forward to optimize performance of opportunistic cooperative transmission. Through the simulation, regardless of statistical feature of channel state of opportunistic node, opportunistic cooperation can effectively improve the performance of the system. Using energy efficient power allocation algorithm can effectively reduce energy consumption of the network and improve the network performance

Energy efficiency is critical in wireless sensor networks (WSN) for system reliability and deployment cost. The power consumption of the communication in multi-hop WSN is primarily decided by three factors: routing distance, signal interference, and computation cost of routing. Several routing algorithms designed for energy efficiency or interference avoidance had been proposed. However, they are either too complex to be useful in practices or specialized for certain WSN architectures. In this paper, we propose two energy efficient geographic routing algorithms (EEGRA) for wireless sensor networks, which are based on existing geographic routing algorithms and take all three factors into account. The first algorithm combines the interference into the routing cost function, and uses it in the routing decision. The second algorithm transforms the problem into a constrained optimization problem, and solves it by searching the optimal discretized interference level. We integrate four geographic routing algorithms: GOAFR+, Face Routing, GPSR, and RandHT, to both EEGRA algorithms and compare them with three other routing methods in terms of power consumption and computation cost for the grid and irregular sensor topologies. The results of our experiments show both algorithms conserve sensor's routing energy 30% ~ 50% comparing to general geographic routing algorithms. In addition, the time complexity of EEGRA algorithms is similar to the geographic greedy routing methods, which is much faster than the optimal SINR-based algorithm.

Wireless sensor networks, by providing an unprecedented way of interacting with the physical environment, have become a hot topic for research over the last few years. As with any new technology, results from real experimentations using these networks are still scarce, as real deployments are either costly, or still unfeasible in the current state of technology. There is therefore an increasing need for simulation tools allowing the testing of different architectures, communication protocols or information processing algorithms in sensor networks. In this paper, we investigate a simulation framework for the testing of data processing in wireless sensor network applications. In a first stage, data is generated using partial differential equations, allowing the modeling of a large panel of physical phenomena. In a second stage, sensing unit operating system and network constraints are simulated using an instance of a versatile simulator to account for the platform characteristics. Insights provided by the proposed simulation frame are illustrated by a set of experiments on a heat source detection task.

Clustering is an efficient technique to improve scalability and life time of wireless sensor networks (WSNs). However, energy efficiency of the sensor nodes and load balancing of the cluster heads (CHs) are the two most important issues that must be addressed in designing clustering algorithm for WSNs. In this paper, we first present a clustering algorithm called energy efficient load-balanced clustering algorithm (EELBCA) that addresses energy efficiency of the sensor nodes and load balancing of the CHs in terms of cardinality of the clusters. EELBCA is a min-heap-based clustering algorithm which is shown to run in O(n log m) time for n sensor nodes and m CHs. We next propose a parameter-based clustering algorithm (PBCA) that considers the energy efficiency of the sensor nodes and also the load balancing of the CHs in terms of overall energy consumption by incorporating communication load of the CHs with respect to the base station. The algorithm requires O(n log n) time. The experimental results show the efficiency of the proposed algorithms in terms of execution time, load balancing, energy consumption, number of live sensor nodes and the number of live CHs.

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.

Battery recovery effect is a phenomenon that the available capacity of a battery could increase if the battery can sleep for a while since its last discharging. Accordingly, the battery can work for a longer time when it takes some rest between consecutive discharging processes than when it works all the time. However, to the best of our knowledge, this impact has not been considered in the design of energy-efficient topology control algorithms for wireless sensor networks. In this paper, we propose a distributed battery recovery effect aware connected dominating set constructing algorithm for wireless sensor networks. In this algorithm, each node in the network periodically decides to be in the dominating set or not. Nodes that have taken sleep in the preceding round are encouraged to involve in the dominating set in the current round while nodes that have worked in the preceding round are encouraged to sleep in the current round for battery recovery. Detailed design description is presented. The complexity of the proposed algorithm is deduced to be O(D2), where D represents node degree. Simulation results show that our algorithm can significantly improve the network lifetime performance as compared with existing work.

In wireless sensor networks, the interference around the application environment may cause the actual distance between any pair of nodes to fail to be measured accurately. Enclosure graph (EG) model uses this distance between nodes as its weight to construct the topology, which does not fully consider the interference. Consequently it will lead to a large amount of energy consumption induced by the application environment. Even it shortens the survival time. According to the feature of network energy inequality in a wireless sensor network and the defect of EG, we first introduce the adjustable factor of node degree, establish a model of communication metric and a model for the node actual survival time. Then according to the demand of network energy equalization and maximum network lifetime, we quantitatively analyze the network node degree, and achieve its regular pattern. In accordance with this regular pattern and sufficient conditions of function extremum, the maximum node energy consumption and the maximum node actual survival time are deduced. And the corresponding optimal node degree is achieved. Finally, according to the above model, in this paper we propose an energy balance and robustness adjustable topology control algorithm for wireless sensor networks. Theoretical analyses show that this algorithm can guarantee that the network is connected and the link of the network is bi-directionally connected. Experiments show that the network takes advantage of this optimal node degree to obtain the high robustness, thus guaranteeing that the information can be transferred unfailingly. This algorithm can effectively balance the node energy, improve the node survival time, enhance the network robustness, and prolong the network's lifetime.