Coverage Hole Repair in WSNs Using Cascaded Neighbor Intervention

In mobility-centric environments, wireless sensor networks are designed to accommodate energy efficiency, dynamic self-organization and mobility. In typical applications of wireless sensor networks, fixed sensor nodes are mixed with mobile sensor nodes in "hot areas". Also, as they move, network topology needs to be reconstructed by reacting upon the mobility of sensor nodes quickly. In this paper we proposed an improved protocol called "LEACH-Mobile" for mobile nodes to declare the membership of a cluster as they move, and to confirm whether a mobile sensor node is able to communicate with a specific cluster head within a time slot allocated in TDMA schedule. The LEACH-Mobile protocol achieved definite improvement in data transfer success rate as mobile nodes increased compared to the non-mobility centric LEACH protocol

This paper focuses on Wireless Sensor Network (WSN) redeployment. A critical problem in WSN is handling the coverage hole because these nodes are normally spread randomly into a terrain area. The objective of this paper is to repair the coverage hole with a less movement from mobile sensor node that it can save energy. Initially, sensor nodes are deployed randomly. Static sensor nodes will be added to enhance the coverage of the network. This paper compares the performance of two WSN mobile node redeployment methods known as Hybrid Particle Swarm Algorithm (IHPSA) and Energy Balanced Redeployment Algorithm (EBRA). IHPSA choose the nodes from redundant to move to the holes location while EBRA use repulsive and attractive forces in order to maximize the coverage. Consequently it will maximize the coverage and all nodes can communicate with each other as well as sending all the data to the base station. The movements of the mobile sensor nodes are minimized to reduce the energy consumption due to mobility. Based on the simulation done, it is found that IHPSA outperforms EBRA in terms of coverage and connectivity. IHPSA algorithm not only solve the coverage hole problem but also solve the energy depletion that always occurs in sensor nodes movement and full connectivity can be guaranteed.

The quality of service (QoS) and lifetime of wireless sensor networks (WSNs) are severely degraded by coverage holes generated by random deployment or battery exhaustion of sensors. This work firstly introduces a novel confident information coverage CIC) model to dramatically reduce the density of sensor nodes and accurately detect confident information coverage holes (CICHs). Then, the problem of repairing confident information coverage holes (RCICHs) for big data collection in a large-scale heterogeneous WSN (LS-HWSN) which widely spreads over a geographic area with thousands of stationary sensor nodes and mobile sensor nodes is formulated, called as RCICH problem, which is to effectively repair CICHs considering that the transmitted data velocity of sensor nodes is different. Furthermore, we prove it to be NP-completeness. The target of the problem is to find a subset of mobile sensor nodes from all mobile sensor nodes while minimizing the amount of lost throughputs LTs) of all dispatched mobile sensor nodes or maximizing the amount of repairing transmission times (RTTs) for all dispatched mobile sensor nodes, with different objectives. Finally, based on the CIC model and the data-centric perspective, two heuristic schemes including a centralized dispatch scheme and a distributed dispatch scheme are proposed to effectively solve the RCICH problem. Simulation results show that the proposed schemes effectively repair CICHs while increasing the QoS and lifetime of the LS-HWSN with the topology control of a fan-shaped clustering (FSC) protocol.

SUMMARYLocation estimation of sensor nodes is an essential part of most applications for wireless sensor and actor networks. The ambiguous location information often makes the collected data useless in these applications. Environmental monitoring relies on an accurate position estimation to process or evaluate the collected data. In this paper, we present a novel and scalable approach for positioning of mobile sensor nodes with the goal of monitoring the Amazon river. The actors in the scenario are stationary and positioned at reachable spots on the land alongside the river whereas sensor nodes are thrown into the river to collect data such as water temperature, depth, and geographical features. The actors are not equipped with positioning adaptors, and they are only aware of their distances from the other actors. The sensor nodes collect data and forward it to the actors. While floating in the river, sensor nodes are often multiple hops away from the actors, which makes it challenging to apply traditional positioning techniques. Through extensive simulations, we show that the nodes can be efficiently positioned using a multi‐hop approach with local information exchange only. The introduced approach is also applied to a scenario, where monkey swarm monitoring is simulated, to test the generalizability of the algorithm. Copyright © 2011 John Wiley & Sons, Ltd.

Current and potential applications of wireless sensor networks (WSNs) include military sensing, physical security, traffic surveillance, and environment monitoring, etc. Due to the fact that WSNs are composed of a large number of low-cost but energy constrained nodes, scalable and energy-efficient routing protocols are requisite for the WSN applications. In this paper, we study energy-efficient geographic routing protocols in environmentally powered WSNs, where the sensor nodes are capable of extracting energy from the environment. We propose a protocol, geographic energy-aware blacklisting routing with energy supply (GEBRES), which makes routing decision locally by jointly taking into account multiple factors-the realistic wireless channel condition, packets advancement to the destination, the energy availability on the node with environmental energy supply. Simulation results show that GEBRES is more energy efficient than the corresponding residual energy based protocols without considering the property of the energy changing (including recharging and consuming) rate. In particular, given the same energy and traffic models, GEBRES maintains higher minimum residual energy on nodes and achieves better load balancing in terms of having a smaller standard deviation of residual energy among nodes. GEBRES exhibits a little degradation on end-to-end delay, but does not compromise the end-to-end throughput performance

For mission-critical applications of wireless sensor networks (WSNs) involving extensive battlefield surveillance, medical healthcare, etc., it is crucial to have low-power, new protocols, methodologies and structures for transferring data and information in a network with full sensing coverage capability for an extended working period. The upmost mission is to ensure that the network is fully functional providing reliable transmission of the sensed data without the risk of data loss. WSNs have been applied to various types of mission-critical applications. Coverage preservation is one of the most essential functions to guarantee quality of service (QoS) in WSNs. However, a tradeoff exists between sensing coverage and network lifetime due to the limited energy supplies of sensor nodes. In this study, we propose a routing protocol to accommodate both energy-balance and coverage-preservation for sensor nodes in WSNs. The energy consumption for radio transmissions and the residual energy over the network are taken into account when the proposed protocol determines an energy-efficient route for a packet. The simulation results demonstrate that the proposed protocol is able to increase the duration of the on-duty network and provide up to 98.3% and 85.7% of extra service time with 100% sensing coverage ratio comparing with LEACH and the LEACH-Coverage-U protocols, respectively.

Barrier coverage is a fundamental problem for lots of applications in wireless sensor networks. In reality, sensor nodes’ true locations may not be known to us considering that not every sensor node is equipped with a GPS. The measured locations of sensor nodes obtained by applying node localization algorithm often have errors, which makes it difficult to form a line-based barrier with mobile sensor nodes. In this paper, we study how to efficiently schedule mobile sensor nodes to form a barrier when sensor nodes suffer from location errors. We explore the relationship between the existence of uncovered hole and location errors and find that the lengths of uncovered holes are decided by the cumulative location errors. We also propose a method in frequency domain to efficiently calculate the distributions of the cumulative location errors. The possibility of the existence of uncovered holes can be derived by analyzing the step responses of the cumulative location errors. Extensive experimental results demonstrate the effectiveness of the proposed algorithm.

Although advance network planning and dense node deployment, wireless sensor networks (WSNs) may achieve the required performance, it still face the fundamental challenge of meeting stringent power and time requirements using nodes with limited sensing capacities. To better cope with the power consumption problem, mobile sensor nodes can be introduced to dynamically reconfigure the sensor network capacity in an on-demand manner. Through data gathering and relaying, mobile nodes can reduce the amount of data transmitting between the static nodes then conserve the power of these nodes to prolong the lifetime of network. In this paper we describe the DataTruck, a new open-source sensing platform specifically designed to support our experimental research in mobile sensor networks, which is used to collect or relay data from static sensors. The DataTruck node is designed around the S3C2440A ARM920T RISC microprocessor and the IEEE 802.15.4 compliant CC2431 radio from Chipcon. Mobility is enabled with an additional accessory board that allows the node to drive its 4 linear motion actuators. To reduce power consumption, a long term sleep mode is supported through different power supplying methods for main board and clock. Furthermore, we integrated a smart antenna system to gather the data from multiple static nodes concurrently which transmitting data using the same frequency of channel. The experiments show that DataTruck collects data efficiently to reduce the average data transmission delay by using SDMA technology.

In the various applications of wireless sensor networks (WSN), the event occurrence information or data sensed by the sensor node has no significance until the location of an event/sensor node is not known. Therefore, localization is an important parameter in WSN for tracking these deployed sensor nodes in the sensing area. To localize these sensor nodes, there are various existing localization models in available detailed literature. One solution to this problem is to deploy a set of static anchor nodes (GPS equipped) in the sensing area, that broadcast their coordination information to help unknown nodes to localize themselves. Another way is to use a single mobile anchor node that will follow a specific path and localize unknown nodes. But a mobile anchor node must follow an optimal path that helps to achieve high accuracy and able to localize a large number of unknown nodes in less computational time. In this paper, the author design and developed a localization algorithm in which a GPS equipped single mobile anchor node follows a new path trajectory i.e. spiral pentagon. Once the target node falls under the communication diameter of the virtual node, six virtual anchor nodes are projected in the shape of a ring around the anchor node and localize all the unknown nodes in the sensing area by using the application of Salp Swarm Algorithm (SSA) for optimization. The hypothesis of six virtual anchor nodes is to avoid the problem of Line of Sight. This proposed method assured that each target node can estimate their node coordinates at least once with a low localization error.

With the advent of ubiquitous computing society, many advanced technologies have enabled wireless sensor networks which consist of small sensor nodes. However, the sensor nodes have limited computing resources such as small size memory, low battery life, short transmission range, and low computational capabilities. Thus, decreasing energy consumption is one of the most significant issues in wireless sensor networks. In addition, numerous applications for wireless sensor networks are recently spreading to various fields (health-care, surveillance, location tracking, unmanned monitoring, nuclear reactor control, crop harvesting control, u-city, building automation etc.). For many of them, supporting security functionalities is an indispensable feature. Especially in case wireless sensor networks should provide a sufficient variety of security functions, sensor nodes are required to have more powerful performance and more energy demanding features. In other words, simultaneously providing security features and saving energy faces a trade-off problem. This paper presents a novel energy-efficient security architecture in an IEEE 802.15.4-based wireless sensor network called the Hybrid Adaptive Security (HAS) framework in order to resolve the trade off issue between security and energy. Moreover, we present a performance analysis based on the experimental results and a real implementation model in order to verify the proposed approach.

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.

The ever-growing increase in modern and ubiquitous applications of wireless sensor networks (WSNs) is causing energy scarcity, which is a serious threat to the lifetime of the network. Wireless power transfer emerges as a promising solution to replenish the sensor nodes. In wireless power transfer, energy is transferred to sensor nodes through dedicated energy transmitters. In addition, software-defined WSNs (SDWSNs) have been recently realized to fully explore and efficiently utilize the resources of WSNs. In this paper, we present an energy efficient SDWSN with wireless power transfer. We propose a mechanism to place energy transmitters and determine minimum number of energy transmitters. For placement of energy transmitters, a tradeoff between maximum energy charged in the network and fair distribution of energy is studied. We present this mechanism by defining a utility function to maximize both total energy charged and fairness. For minimum number of energy transmitters, an optimization problem is formulated and solved while satisfying the constraint on minimum energy charged by each sensor node. We also propose an energy-efficient scheduling scheme for energy transmitters for the given tasks of energy charging. The focus is to minimize the energy consumption of energy transmitters while keeping sensor nodes sufficiently charged. Finally, this paper is supported by extensive simulation results, which illustrate the performance of energy-efficient SDWSNs with wireless power transfer in terms of energy charged, fairness, number of energy transmitters, number of tasks, and energy consumption.

Resource Management Approach to an Efficient Wireless Sensor Network

ABSTRACTLocation information of sensor nodes is of vital importance for most applications in wireless sensor networks (WSNs). This paper proposes a new range-free localisation algorithm using support vector machine (SVM) and polar coordinate system (PCS), LSVM-PCS. In LSVM-PCS, two sets of classes are first constructed based on sensor nodes’ polar coordinates. Using the boundaries of the defined classes, the operation region of WSN field is partitioned into a finite number of polar grids. Each sensor node can be localised into one of the polar grids by executing two localisation algorithms that are developed on the basis of SVM classification. The centre of the resident polar grid is then estimated as the location of the sensor node. In addition, a two-hop mass-spring optimisation (THMSO) is also proposed to further improve the localisation accuracy of LSVM-PCS. In THMSO, both neighbourhood information and non-neighbourhood information are used to refine the sensor node location. The results obtained verify that the proposed algorithm provides a significant improvement over existing localisation methods.

We present Sensei-UU, a testbed that supports mobile sensor nodes. The design objectives are to provide wireless sensor network (WSN) experiments with repeatable mobility and to be able to use the same testbed at different locations, including the target location. The testbed is inexpensive, expandable, relocatable and it is possible to reproduce it by other researchers. Mobile sensor nodes are carried by robots that use floor markings for navigation and localization. The testbed is typically used to evaluate WSN applications when sensor nodes move in meters rather than millimeters, eg. when human carries a mobile data sink (mobile phone) collecting data while passing fixed sensor nodes. To investigate the repeatability of robot movements, we have measured the achieved precision and timing of the robots. This precision is of importance to ensure the same radio link characteristics from one protocol experiment to another. We find that our robot localization is accurate to ±1 cm and variations in link characteristics are acceptably low to capture fading phenomena in IEEE 802.15.4. In the paper we show repeatable experiment results from three environments, two university corridors and from an anechoic chamber. We conclude that the testbed is relocatable between different environments and that the precision is good enough to capture fading effects in a repeatable way.