A critical aspect of wireless sensor networks is network lifetime. Power-constrained wireless sensor networks are usable as long as they can communicate sensed data to the base station. Multi-hop data gathering consumes increased energy, especially for data-intensive applications. In this paper we propose a UAV-enabled data gathering mechanism for wireless sensor networks which prolongs network lifetime compared to a traditional data gathering mechanism. Some of the aspects that we address are UAV path planning, scheduled and opportunistic data gathering, and integration of the data gathering with a node scheduling mechanism. Simulations using ns3 show that our algorithm is more efficient in terms of energy consumed and packet delivery ratio compared to traditional data gathering.

Spatio-temporal events are used to model various events such as animal movement, storms (tornadoes, hurricanes, etc.), traffic control, and oil or chemical leakage. Wireless Sensor Networks (WSNs) have been widely used in event monitoring for many applications. Depending on the application, network energy can be a constraint when sensors are battery powered and their batteries cannot be replaced or recharged. In this paper we propose an anchor-based routing protocol for detecting and reporting spatio-temporal events. Anchor nodes are nodes closer to the sink and they act as relays between the convergecast tree and the sink. The sink is assumed to be mobile. We use several mechanisms to save energy: reactive event reporting, constrained route request flooding with a shortcut mechanism, a shortcut mechanism for data reporting, and dynamic clustering for minimizing the number of active clusters in the network. The performance of our protocol is analyzed using WSNet simulator, which is specially designed for event based WSNs. Various metrics such as the average residual energy, the number of active clusters, and the percentage of events processed successfully at the sink are measured.

Wireless sensor networks have been widely used in many applications, such as climate monitoring systems, fire detection, ocean activity monitoring, and smart cities. These networks can be homogeneous or heterogeneous, depending on the types of wireless devices used. Changes in the values of the attributes measured are known as events. We distinguish atomic and composite events. Atomic events measure changes of a single attribute in the environment, for example the temperature, while composite events consist of groups of atomic events. In this paper we propose a distributed algorithm for composite event detection and reporting that uses an event-based clustering mechanism. We compare the performance of our algorithm with another related work, the Cluster-based Energy efficient Composite event detection (CEC) protocol, where clusters are formed before the sensing starts. We analyze the performance of our mechanism using WSNeT simulator, which is specially designed for event based wireless sensor networks. This simulator is a free open source tool and runs using Linux operating system. We measure various metrics such as average residual energy, number of packets received by the sink and cluster heads, average number of hops, and average number of clusters. Based on the results of the simulations, we conclude that our event-based clustering mechanism outperforms the CEC mechanism.

Border surveillance has many applications in national security, infrastructure security, habitat monitoring, detecting illegal trespasses, military applications, and so on. This topic has received an increased attention recently. Sensing coverage and reliable data transmission are critical aspects in border surveillance using wireless sensor networks. In this paper we propose RMA-BS, a cognitive radio data collection scheme for border surveillance applications. RMA-BS aims to assign radios of neighboring monitoring sensors to different transmission channels, thus reducing interference and increasing network throughput and data delivery rate. RMA-BS is robust to the presence of a primary user or a signal jamming attack. We analyze the performance of our algorithm using ns-3 simulations.

In traditional wireless sensor networks communicating on a single channel the data throughput measured at the sink is constrained by the radio capability, contentions, and collisions, which increase in the region closer to the sink. Using SDR technology, different levels of configuration within a transceiver are allowed. In this paper we assume that the sink and sensor nodes are equipped with reconfigurable radios. We design a distributed algorithm used by sensor nodes to reconfigure their radio according to some predefined radio-modes, such that the resulting topology is connected to the sink. Collecting sensor data using this topology reduces the interference and increases the network throughput and the data delivery rate. We analyze the performance of our algorithm using ns-3 simulations.

Using SDR technology, the distributed algorithm RMA is used by sensor nodes to reconfigure their radio according to some predefined radio-modes, such that the resulting topology is connected to the sink. This mechanism reduces interference and increases data delivery rate. In this paper we extend RMA by adding a low overhead mechanism to be used in the presence of a primary user. Sensor nodes operating on the same frequency as the primary user will reassign their radio-mode such that the resulting topology does not interfere with the primary user. We analyze the performance of our distributed algorithm using ns-3 simulations.

Cognitive radios allow secondary users to use the underutilized spectrum. However, in the presence of a primary user, the unlicensed users must vacate the spectrum, leading to a decrease in network performance or even network partition. In this paper we address the problem of robust topology control in wireless sensor networks with the objective of assigning a sensor channel on each radio such that the resulting topology is robust to the presence of a primary user. That means that if a channel is reclaimed by a primary user, the resulting secondary user topology still preserves the connectivity between any two nodes. In this paper we propose a distributed algorithm for channel assignment which has low overhead and is scalable with the number of sensor nodes. We analyze the performance of our algorithm using ns-3 simulations.

This paper presents a REST-compliant service oriented architecture of a web-based heterogeneous wireless sensor network monitoring system that has applicability in remote patient monitoring in healthcare. As smartphone and web-page technologies are ubiquitous nowadays, our architecture uses smartphone as a gateway between the data collected and the Internet. The system uses a heterogeneous WSN consisting of environmental sensors, medical sensors, and smartphone's internal sensors. To validate the system, a prototype experiment of the system is implemented using Android smartphone platform, Crossbow Micaz motes, and Alive Technology hart and activity monitor sensor.

Abstract A wireless sensor network can detect single (or atomic) events or composite events. Since sensors are battery powered and in general, it is hard to recharge them, energy management is always an important issue. In this paper, we study the SCED problem; given a wireless sensor network deployed for watching a composite event x1, x2, … , xM, design a sensor scheduling mechanism such that the set of active sensors ensure the coverage and connectivity conditions and WSN lifetime is maximized. Network lifetime is organized in rounds. Each round has two phases: initialization and data collection. In the initialization phase, the goal is to choose a set of active sensors as sensing nodes or relay nodes such that to achieve both coverage and connectivity requirements. Sensors which are not chosen to be active go to sleep to save energy. In the data collection phase, active sensors perform sensing and data relaying. When another round begins, a new set of active sensors are determined. Two solutions are proposed for the SCED problem, a grid‐based distributed algorithm and a localized algorithm. We analyze their performance through simulations. Copyright © 2010 John Wiley & Sons, Ltd.

In the United States, there has been a high incidence of hurricanes over the past decade. Before a hurricane makes landfall it is important, for safety, that people who live in potentially dangerous areas, such as along the coast, evacuate. Nursing homes have an even greater concern during an evacuation as the patients are primarily elderly or disabled, and require additional assistance. In this paper we investigate the characteristics and challenges associated with hurricane evacuation of health care centers, such as nursing homes. Then, we propose a patient centric hurricane evacuation management system that allow healthcare providers to continuously monitor and track patients. The hardware and software architecture, and the main operations are presented. The proposed system is able to operate in difficult conditions, such as lack of basic communication services such as cellular and Internet, temporary network partition, and scarce energy resources.

In this paper we propose a QoS based routing protocol for wireless sensor network applications that support both periodic and event-based data reporting. A geographic routing mechanism combined with QoS support is used to forward packets in the network. Data is routed based on the packet type. To route packets with different priorities, multiple transmission queues are used. In choosing the next hop, the node that is closer to the sink, has high residual energy, high link quality, and low load is selected. Congestion control is achieved by using a ring or barrier mechanism that captures and aggregates messages that report the same event to the same sink. We present the main operations of the barrier mechanism, including barrier formation, repair, enlarge, shrink, and termination. Simulation results using JIST/SWANS simulator show the performance of our routing protocol compared with other related works.

Sensors are widely used in everyday life in household appliances, fire alarms, traffic control systems, battlefields, banks, and museums. Sensors are used either as standalone devices or in networks. Understanding the basic structure of a sensor node is essential to be able to use the sensors in different types of devices and different kinds of environments. Many applications require different types of sensor nodes that communicate with each other to perform a specific function. We present a pattern that describes an abstract view of the architecture of a sensor node. This description would help the application designer to choose from different types of sensor nodes for his application and to integrate it with other functional units. Moreover, this model also helps the designer to reuse, combine, or modify the architecture of a node to suit more complex needs.

In wireless sensor and actor networks (WSANs), a group of sensors and actors are connected by a wireless medium to perform distributed sensing and acting tasks. Sensors usually gather information in an event area and pass it on to actors, which are resource-rich devices that make decisions and perform necessary actions. Therefore, it is vital to maintain connections between sensors and actors for effective sensor- actor coordination. We first define several sensor- actor connection requirements, including weak and strong actor-connectivity, and then propose several local solutions that put as many sensors as possible to sleep for energy saving purposes, while meeting different actor-connectivity requirements. We also prove the relationship between the proposed actor-connectivity and the connectivity in regular graphs, which helps with the implementation of the proposed solutions. Comprehensive performance analysis is conducted through simulations.

In this paper, we consider the issue of efficient broadcasting in mobile ad hoc networks (MANETs) using network coding and directional antennas. Network coding-based broadcasting focuses on reducing the number of transmissions each forwarding node performs in the multiple source/multiple message broadcast application, where each forwarding node combines some of the received messages for transmission. With the help of network coding, the total number of transmissions can be reduced compared to broadcasting using the same forwarding nodes without coding. We exploit the usage of directional antennas to network coding-based broadcasting to further reduce energy consumption. A node equipped with directional antennas can divide the omnidirectional transmission range into several sectors and turns some of them on for transmission. In the proposed scheme using a directional antenna, forwarding nodes selected locally only need to transmit broadcast messages, original or coded, to restricted sectors. We also study two extensions. The first extension applies network coding to both dynamic and static forwarding node selection approaches. In the second extension, we design two approaches for the single source/single message issue in the network coding-based broadcast application. Performance analysis via simulations on the proposed algorithms using a custom simulator is presented.

Good sensor deployment is vital for wireless sensor networks (WSNs). To improve the initial deployment and to prolong network lifetime, one approach is to relocate sensors in different densities which vary with the distance to the sink. Since sensors located closer to the sink are involved in more data forwarding, sensors in this region should have a higher density. In this paper, we address the problem of Movement-assisted Sensor Positioning (MSP) to increase network lifetime with the objective to achieve the theoretical sensor densities while minimizing sensor movement. We propose three solutions: an Integer-Programming formulation, a localized matching method, and a distributed corona-radius scanning algorithm. Simulation results are presented to evaluate the proposed solutions.

A critical issue for data gathering in wireless sensor networks is the formation of energy holes near the sinks. Sensors near the sinks have to participate in relaying data on behalf of other sensors and thus will deplete their energy very quickly, resulting in network partitioning and limitation of the network lifetime. The solution that we propose in this paper is to use mobile sinks that change their location when the nearby sensorspsila energy becomes low. In this way the sensors located near sinks change over time. In deciding a new location, a sink searches for zones with richer sensor energy. First, we study the improvement in network lifetime when sinks move on a predetermined path, along the perimeter of a hexagonal tiling. Two cases are considered for data gathering when sinks stop in the hexagonpsilas corners and when the sinks stop on multiple locations on the hexagon perimeter. This study shows an improvement of up to 4.86 times in network lifetime. Second, we design a distributed and localized algorithm used by the sinks to decide their next movement location such that the virtual backbone formed by the sinks remains interconnected at all times. Simulation results are presented to verify our approaches.

This paper addresses fault-tolerant topology control in a heterogeneous wireless sensor network consisting of several resource-rich supernodes, used for data relaying, and a large number of energy-constrained wireless sensor nodes. We introduce the k-degree anycast topology control (fc-ATC) problem, with the objective of selecting each sensor's transmission range such that each sensor is k-vertex supernode connected and the total power consumed by sensors is minimized. Such topologies are needed for applications that support sensor data reporting, even in the event of failures of up to k - 1 sensor nodes. We propose three solutions for the k-ATC problem: a k-approximation algorithm, a greedy centralized algorithm that minimizes the maximum transmission range between all sensors, and a distributed and localized algorithm that incrementally adjusts sensors' transmission range such that the k-vertex supernode connectivity requirement is met. Extended simulation results are presented to verify our approaches.

This paper addresses fault-tolerant topology control in a heterogeneous wireless sensor network consisting of several resource-rich supernodes used for data relaying and a large number of energy constrained wireless sensor nodes. We introduce the fc-degree Anycast Topology Control (fc-ATC) problem with the objective of selecting each sensor's transmission range such that each sensor is fc-vertex supernode connected and the maximum sensor transmission power is minimized. Such topologies are needed for applications that support sensor data reporting even in the event of failures of up to k-1 sensor nodes. We propose two solutions for the k-ATC problem: a greedy centralized algorithm that produces the optimal solution and a distributed and localized algorithm that incrementally adjusts sensors' transmission range such that the k-vertex supernode connectivity requirement is met. Simulation results are presented to verify our approaches.

Sensor deployment in mobile sensor networks has received significant attention in recent years. Goals during sensor deployment include improving coverage, achieving load balance, and prolonging the network lifetime. To improve the initial deployment, one possible method is to use mobile sensors, thus allowing sensors to relocate. In this paper, we present a sensor deployment strategy in mobile sensor networks. Our goal is to improve coverage and prolong network lifetime through sensor relocation after the initial deployment. The problem in this paper is defined as Movement-assisted Sensor Positioning (MSP) for network lifetime increase problem. With the observation that the sensors closer to the sink tend to consume more energy than those farther away from the sink, we first compute the desired non-uniform sensor density in the monitored area to reduce the energy holes near the sink and to prolong network lifetime. Assuming that sensors can move only once, we then propose a centralized algorithm to relocate mobile sensors to satisfy the density requirement with minimum cost. We construct the virtual multi-flow graph and solve the sensor relocation problem using a maximum-flow minimum-cost algorithm. The improvement in network lifetime is proved both mathematically and by simulations.

This paper considers a heterogeneous wireless sensor network consisting in several resource-rich supernodes used for data relaying and a large number of energy constrained wireless sensor nodes. Sensor nodes are deployed randomly to monitor a number of targets. Since targets are redundantly covered by more sensors, in order to conserve energy resources, we organize the sensors in set covers that are activate successively. In this paper we introduce the heterogeneous connected set covers (HCSC) problem that has as objective finding a maximum number of set covers such that each set cover monitors all targets and is connected to at least one supernode. A sensor can participate in multiple set covers, but sum of the energy spent in all sets is constrained by the initial energy resources. This is the first paper to address the target coverage problem in heterogeneous wireless sensor networks. We show that HCSC is NP-complete and propose several distributed algorithms for the HCSC problem. Simulation results are presented to verify our approaches

In this paper, we address the Topology control with Cooperative Communication (TCC) problem in ad hoc wireless networks. Cooperative communication is a novel model introduced recently that allows combining partial messages to decode a complete message. The objective of the TCC problem is to obtain a strongly-connected topology with minimum total energy consumption. We show that the TCC problem is NIP-complete and design two distributed and localized algorithms to be used by the nodes to set up their communication ranges. Both algorithms can be applied on top of any symmetric, strongly-connected topology to reduce total power consumption. The first algorithm uses a distributed decision process at each node that makes use of only 2-hop neighborhood information. The second algorithm sets up the transmission ranges of nodes iteratively, over a maximum of six steps, using only 1-hop neighborhood information. We analyze the performance of our approaches through extensive simulation.

We propose a notion of an extended dominating set where each node in an ad hoc network is covered by either a dominating neighbor or several 2-hop dominating neighbors. This work is motivated by cooperative communication in ad hoc networks whereby transmitting independent copies of a packet generates diversity and combats the effects of fading. We first show the NP-completeness of the minimum extended dominating set problem. Then, several heuristic algorithms, global and local, for constructing a small extended dominating set are proposed. These are nontrivial extensions of the existing algorithms for the regular dominating set problem. The application of the extended dominating set in efficient broadcasting is also discussed. The performance analysis includes an analytical study in terms of approximation ratio and a simulation study of the average size of the extended dominating set derived from the proposed algorithms

A critical aspect of applications with wireless sensor networks is network lifetime. Power-constrained wireless sensor networks are usable as long as they can communicate sensed data to a processing node. Sensing and communications consume energy, therefore judicious power management and sensor scheduling can effectively extend network lifetime. To cover a set of targets with known locations when ground access in the remote area is prohibited, one solution is to deploy the sensors remotely, from an aircraft. The lack of precise sensor placement is compensated by a large sensor population deployed in the drop zone, that would improve the probability of target coverage. The data collected from the sensors is sent to a central node (e.g. cluster head) for processing. In this paper we propose un efficient method to extend the sensor network life time by organizing the sensors into a maximal number of set covers that are activated successively. Only the sensors from the current active set are responsible for monitoring all targets and for transmitting the collected data, while all other nodes are in a low-energy sleep mode. By allowing sensors to participate in multiple sets, our problem formulation increases the network lifetime compared with related work [M. Cardei et al], that has the additional requirements of sensor sets being disjoint and operating equal time intervals. In this paper we model the solution as the maximum set covers problem and design two heuristics that efficiently compute the sets, using linear programming and a greedy approach. Simulation results are presented to verify our approaches.

We consider a wireless sensor network consisting of a set of sensors deployed randomly. A point in the monitored area is covered if it is within the sensing range of a sensor. In some applications, when the network is sufficiently dense, area coverage can be approximated by guaranteeing point coverage. In this case, all the points of wireless devices could be used to represent the whole area, and the working sensors are supposed to cover all the sensors. Many applications related to security and reliability require guaranteed k-coverage of the area at all times. In this paper, we formalize the k-(connected) coverage set (k-CCSlk-CS) problems, develop a linear programming algorithm, and design two non-global solutions for them. Some theoretical analysis is also provided followed by simulation results

This paper addresses the target coverage problem in wireless sensor networks with adjustable sensing range. Communication and sensing consume energy, therefore efficient power management can extend network lifetime. In this paper, we consider a large number of sensors with adjustable sensing range that are randomly deployed to monitor a number of targets. Since targets are redundantly covered by more sensors, in order to conserve energy resources, sensors can be organized in sets, activated successively. In this paper we address the adjustable range set covers (AR-SC) problem that has as its objective finding a maximum number of set covers and the ranges associated with each sensor, such that each sensor set covers all the targets. A sensor can participate in multiple sensor sets, but sum of the energy spent in each set is constrained by the initial energy resources. In this paper we mathematically model solutions to this problem and design heuristics that efficiently compute the sets. Simulation results are presented to verify our approaches.

In this paper, we address the topology control with hitch-hiking (TCH) problem. Hitch-hiking [M. Agrawal et al., 2004] is a novel model introduced recently that allows the combination of partial messages to decode a complete message. By the effective use of partial signals, a specific topology can be obtained with less transmission power. The objective of the TCH problem is to obtain a strongly-connected topology with minimum total energy consumption. We prove the TCH problem to be NP-complete and design a distributed and localized algorithm (DTCH) that can be applied on top of any symmetric, strongly-connected topology to reduce total power consumption. We analyze the performance of our approach through simulation.

In ad hoc wireless networks, to compute the transmission power of each wireless node such that the resulting network is connected and the total energy consumption is minimized is defined as a Minimum Energy Network Connectivity (MENC) problem, which is an NP-complete problem. In this paper, we consider the approximated solutions for the MENC problem in ad hoc wireless networks. We present a theorem that reveals the relation between the energy consumption of an optimal solution and that of a spanning tree and propose an optimization algorithm that can improve the result of any spanning tree-based topology. Two polynomial time approximation heuristics are provided in the paper that can be used to compute the power assignment of wireless nodes in both static and low mobility ad hoc wireless networks. The two heuristics are implemented and the numerical results verify the theoretical analysis.

The paper presents an innovative hierarchical feedback adaptation method that efficiently controls the dynamic QoS behavior of real time distributed data flow applications, such as sensor based data streams or mission-critical command and control applications. We applied this method in the context of the Real Time Adaptive Resource Management system, a middleware integrated services, developed at the Honeywell Technology Center. We present the analytical model for Automatic Target Recognition pipeline application and the impact of hierarchical feedback adaptation on the application behavior and its QoS parameters.