Objects In Wireless Sensor Networks Research Articles

Efficient Coverage and Connectivity Preservation With Load Balance for Wireless Sensor Networks

One of the primary objectives of wireless sensor networks is to provide full coverage of a sensing field as long as possible. Many tasks-such as object tracking and battlefield intrusion detection-require full coverage at any time. With the limited energy of sensor nodes, organizing these nodes into a maximal number of subgroups (or called set cover) capable of monitoring all discrete points of interest and then alternately activating them is a prevalent way to provide better quality of surveillance. In addition to maximizing the number of subgroups, how to guarantee the connectivity of sensor nodes (i.e., there exist links between the base station (BS) and sensor nodes) is also critically important while achieving full coverage. In this paper, thus, we develop a novel maximum connected load-balancing cover tree (MCLCT) algorithm to achieve full coverage as well as BS-connectivity of each sensing node by dynamically forming load-balanced routing cover trees. Such a task is particularly formulated as a maximum cover tree problem, which has been proved to be nondeterministic polynomial-complete. The proposed MCLCT consists of two components: 1) a coverage-optimizing recursive heuristic for coverage management and 2) a probabilistic load-balancing strategy for routing path determination. Through MCLCT, the burden of nodes in sensing and transmitting can be shared, so energy consumption among nodes becomes more evenly. Extensive simulation results show that our solution outperforms the existing ones in terms of energy efficiency and connectivity maintenance.

Spatiotemporal Correlation Based Fault-Tolerant Event Detection in Wireless Sensor Networks

Reliable event detection is one of the most important objectives in wireless sensor networks (WSNs), especially in the presence of faulty nodes. Existing fault-tolerant event detection approaches usually take the probability of faulty nodes into account and fusion techniques to weaken the influence of faulty readings are usually developed. Through extensive experiments, we discover a phenomenon that event detection accuracy degrades quickly when the faulty sensors ratio reaches a critical value. This problem has not drawn enough attention and a solution to the problem is our concern. In this paper, a spatiotemporal correlation based fault-tolerant event detection scheme (STFTED) is proposed, which leverages a two-stage decision fusion and spatiotemporal correlation to improve the event detection quality. In the low-level local stage, a location-based weighted voting scheme (LWVS) is developed to make decision fusion locally on each sensor node, which is based on neighboring nodes and the geographical distributions of two decision quorums. In the high-level global stage, a Bayesian fusion algorithm is adopted to reach a consensus among individual detection decisions made by sensor nodes. Simulation results demonstrate that the proposed approach is highly effective and a better quality of event detection can be obtained compared with the optimal threshold decision schemes (OTDS).

Ensuring Survivability of Resource-Intensive Sensor Networks Through Ultra-Low Power Overlays

Nodes in wireless sensor networks (WSNs) typically have limited power supply and networks are often expected to be functional for extended periods. Therefore, the minimization of energy consumption and the maximization of network lifetime are key objectives in WSN. This paper proposes an overlay, energy optimized, sensor network to extend the functional lifetime of an energy-intensive sensor network application. The overlay network consists of additional nodes that exploit recent advances in energy harvesting and wake-up radio technologies, coupled with an application specific, complementary, ultra-low power sensor. The experimental results and simulations demonstrate that this approach can ensure survivability of energy-inefficient sensor networks. Simulating applications using energy-intensive video cameras and air quality sensors, combined with the proposed overlayed ultra-low power sensor network, demonstrates that this approach can increase functional lifetime toward perpetual operation and is suitable for WSN applications in which complementarity exists between the required energy-intensive sensors and low-cost sensors that can be used as triggers.

Secure Ant-Based Routing Protocol for Wireless Sensor Network

Optimal path selection in wireless sensor networks (WSNs) is one of the challenging tasks. Several efficient routing protocols are proposed for specific scenarios to achieve particular objectives in WSN. However, such networks have many limitations such as low data rates and security threats. In this paper, we propose an adaptive secure routing protocol which is based on bioinspired mechanism. It uses distributed ant-based methodology to select two optimal paths keeping in view route security. Simulation results show that our routing protocol can perform better in many scenarios.

A Cross-Layer Framework for Network Management in Wireless Sensor Networks Using Weighted Cognitive Maps

Achieving the end-to-end goals and objectives of Wireless Sensor Networks (WSN) is a highly challenging task. Such objectives include maximizing network lifetime, guaranteeing connectivity and coverage, and maximizing throughput. In addition, some of these goals are in conflict such as network lifetime and throughput. Cross-layer design can be efficient in proposing network management techniques that can consider different network objectives and conflicting constraints. This can be highly valuable in challenging applications where multiple Quality of Service (QoS) requirements may be demanded. In this paper, a novel cross-layer framework for network management is proposed that particularly targets WSN with challenging applications. The proposed framework is designed using the tool known as Weighted Cognitive Map (WCM). The inference properties of WCMs allow the system to consider multiple objectives and constraints while maintaining low complexity. Methods for achieving different objectives using WCMs are illustrated, as well as how system processes can operate coherently to achieve common end-to-end goals. Using extensive computer simulations, the proposed system is evaluated. The results show that it achieves good performance results in metrics of network lifetime, throughput, and Packet Loss Ratio (PLR).

RAPS: a precision‐adaptive protocol towards improved data fidelity in wireless sensor networks

ABSTRACTAchieving high data quality and efficient network resource utilization is two major design objectives of wireless sensor networks (WSNs). However, these two objectives are often conflictive. By allowing sensors to report sampled data at high rates, fine‐grained data quality can be obtained. However, the limited resources of a WSN make it difficult to support very high traffic rate. Therefore, the capability of adaptively adjusting sensor nodes' traffic‐generating rates on the basis of the availability of network resources and application requirements is critical. This issue has attracted much attention recently, and some work has been carried out.To achieve high data quality and improved utilization of network resources, in this paper, we propose rate‐based adaptive precision setting (RAPS) protocol, which works in a way that each sensor can adaptively adjust its traffic‐generating rate on the basis of the current network resources availability and application requirements. RAPS introduces the following two key factors into its design: application's precision requirement and packet arrival rate. Analytical and simulation results show that RAPS can achieve improved data quality while reducing packet delivery latency. Copyright © 2012 John Wiley & Sons, Ltd.

Survey of mobile object tracking protocols in wireless sensor networks: a network-centric perspective

Mobile object tracking in Wireless Sensor Networks (WSNs) has gained much attention during recent years owing to its growing application potential for the ubiquitous society. In this paper, we present an investigation and taxonomy of the state-of-the-art in tracking moving objects in WSNs. To this end, we define the target tracking problem in general and introduce the major design considerations for an efficient Object Tracking Sensor Network (OTSN) in particular. We typify a complete object tracking solution as a system of signal processing-based algorithms in charge of target identification/classification and network-centric protocols as the communication substrate. Our special highlight would be on the discussion of the network-centric protocols built around the notion of OTSN. We outline the advantages as well as the performance issues in relevant schemes and conduct a brief comparative study. The survey concludes with several key open problems together with a summary of directions for future works.

EasyLoc: RSS-Based Localization Made Easy

Localization based on Received Signal Strength (RSS) is a key method for locating objects in Wireless Sensor Networks (WSNs). However, current RSS-based methods are ineffective at both deployment and operation design levels since they (i.) usually require a labor-intensive pre-deployment profiling operations to map the RSS to either locations or distances and (ii.) rely on heavy processing operations. These two designs problems limit the possibility of implementing the localization technique on resources constrained sensor nodes and also restrict its scalability and practical use. In this paper, we tackle the challenge of devising a self-organizing and practical RSS-based localization technique that improves on previous approaches in terms of ease of deployment, ease of implementation while still providing a reasonable accuracy. To this end, we come up with a new solution, EasyLoc, a plug-and-play and distributed RSS-based localization method that requires zero pre-deployment configuration. The idea consists in exploiting the available distance information between anchors to derive an online and anchor-specific RSS-to-distance mapping. We show that, in addition to its simplicity, EasyLoc provides location errors of 90% less than 1m and an average error of 0.48m in small environment and 1.8m in large environment.

Reliability/energy trade-off in Bluetooth error control schemes

Two important objectives in wireless sensor networks are reliability and reducing energy consumption. Hence, overcoming energy constraints and utilizing error control schemes such as Automatic Repeat Request (ARQ) and Forward Error Correction (FEC) are necessary to improve the energy efficiency and reliability. However, these two concerns are at odds, so there is a trade-off between them. Considering this point, the impact of various error control schemes on these objectives and the trade-off between them has been considered in Bluetooth networks recently. However, all these works consider ideal assumptions (e.g., perfect error detection) only. This work evaluates the energy-efficiency of Bluetooth error control schemes in Rayleigh fading channels taking into consideration both ideal assumptions and residual error probability of the CRC code in ARQ schemes. A comparative analysis of coding techniques using different BCH codes on the AUX1 packet is provided. In addition, the impact of variations in number of hops and SNR on the effectiveness of proposed coding techniques is analyzed through simulation. This analysis provides information that help network designers to choose suitable packet types and coding techniques for Bluetooth networks depending on the network situation.

Accurate location estimation of moving object In Wireless Sensor network

One of the central issues in wirless sensor networks is track the location, of moving object which have overhead of saving data, an accurate estimation of the target location of object with energy constraint .We do not have any mechanism which control and maintain data .The wireless communication bandwidth is also very limited. Some field which is using this technique are flood and typhoon detection, forest fire detection, temperature and humidity and ones we have these information use these information back to a central air conditioning and ventilation. In this research paper, we propose protocol based on the prediction and adaptive based algorithm which is using less sensor node reduced by an accurate estimation of the target location. We had shown that our tracking method performs well in terms of energy saving regardless of mobility pattern of the mobile target. We extends the life time of network with less sensor node. Once a new object is detected, a mobile agent will be initiated to track the roaming path of the object.

Weaving a proper net to catch large objects in wireless sensor networks

Wireless sensor networks consist of a large number of sensors and have been broadly used for intrusion detection in surveillance systems. To guarantee detection quality, such networks are usually over-engineered, i.e., more than required sensors are deployed and remain active in order to cover each point in the monitored field with a high probability at any time instance. Existing sensor scheduling schemes based on the point coverage model tightly weave a sensor that is unnecessarily dense. Intuitively, when the size and the shape of intrusion objects are considered, any net with holes no smaller than the size of the intrusion object would work fine. With this design philosophy in mind, we build a new mathematical model to investigate the impact of size and shape of intrusion objects on network configuration. We derive analytical results that provide practitioners with insights on how to weave an effective sensor for intrusion object detection with minimum number of active sensors.

Diffusion-based approach to deploying wireless sensor networks

An important objective of Wireless Sensor Networks (WSNs) is to reliably sense data about the environment in which they are deployed. Reliability in WSNs has been widely studied in terms of providing reliable routing protocols for message dissemination and reliability of communication from sink to sensors. In this work, we define a reliability metric by the amount of data sensed by the network. In order to satisfy this reliability constraint, we propose a diffusion-based approach for a deployment pattern for the sensor nodes. We show that this deployment pattern achieves sufficient coverage and connectivity and requires lesser number of sensors than popular regular deployment patterns. We further obtain the bounds on establishing connectivity between nodes in the WSN and extend this analysis for heterogeneous WSNs.

Algorithms for energy efficient mobile object tracking in wireless sensor networks

Wireless sensor networks have found more and more applications in a variety of pervasive computing environments, in their functions as data acquisition in pervasive applications. However, how to get better performance to support data acquisition of pervasive applications over WSNs remains to be a nontrivial and challenging task. The network lifetime and application requirement are two fundamental, yet conflicting, design objectives in wireless sensor networks for tracking mobile objects. The application requirement is often correlated to the delay time within which the application can send its sensing data back to the users in tracking networks. In this paper we study the network lifetime maximization problem and the delay time minimization problem together. To make both problems tractable, we have the assumption that each sensor node keeps working since it turns on. And we formulate the network lifetime maximization problem as maximizing the number of sensor nodes who don't turn on, and the delay time minimization problem as minimizing the routing path length, after achieving the required tracking tasks. Since we prove the problems are NP-complete and APX-complete, we propose three heuristic algorithms to solve them. And we present several experiments to show the advantages and disadvantages referring to the network lifetime and the delay time among these three algorithms on three models, random graphs, grids and hypercubes. Furthermore, we implement the distributed version of these algorithms.

Data Management of Mobile Object Tracking Applications in Wireless Sensor Networks

In this paper, we focus on the data management problem of object tracking applications in wireless sensor networks. We propose link-segment storage and query protocol to track mobile object in wireless sensor network dynamically. The main idea of our protocol is to combine advantages of local storage with data centric storage methods to support the query of object movement information efficiently. Object’s movement information will be stored in node near detecting sensor and the relation of storage nodes is maintained using multiple access entry linked list along the moving path of the object. Index-store node (a designated node) stores the access entry messages of linked list. Performance analysis and simulation studies show that the proposed protocol is energy efficient, with high probability of successful query and low query latency.

DEMOCO: Energy-Efficient Detection and Monitoring for Continuous Objects in Wireless Sensor Networks

The proliferation of research on target detection and tracking in wireless sensor networks has kindled development of monitoring continuous objects such as fires and hazardous bio-chemical material diffusion. In this paper, we propose an energy-efficient algorithm that monitors a moving event region by selecting only a subset of nodes near object boundaries. The paper also shows that we can effectively reduce report message size. It is verified with performance analysis and simulation results that total average report message size as well as the number of nodes which transmit the report messages to the sink can be greatly reduced, especially when the density of nodes over the network field is high.

A distributed activity scheduling algorithm for wireless sensor networks with partial coverage

One of the most important design objectives in wireless sensor networks (WSN) is minimizing the energy consumption since these networks are expected to operate in harsh conditions where the recharging of batteries is impractical, if not impossible. The sleep scheduling mechanism allows sensors to sleep intermittently in order to reduce energy consumption and extend network lifetime. In applications where 100% coverage of the network field is not crucial, allowing the coverage to drop below full coverage while keeping above a predetermined threshold, i.e., partial coverage, can further increase the network lifetime. In this paper, we develop the distributed adaptive sleep scheduling algorithm (DASSA) for WSNs with partial coverage. DASSA does not require location information of sensors while maintaining connectivity and satisfying a user defined coverage target. In DASSA, nodes use the residual energy levels and feedback from the sink for scheduling the activity of their neighbors. This feedback mechanism reduces the randomness in scheduling that would otherwise occur due to the absence of location information. The performance of DASSA is compared with an integer linear programming (ILP) based centralized sleep scheduling algorithm (CSSA), which is devised to find the maximum number of rounds the network can survive assuming that the location information of all sensors is available. DASSA is also compared with the decentralized DGT algorithm. DASSA attains network lifetimes up to 92% of the centralized solution and it achieves significantly longer lifetimes compared with the DGT algorithm.

Constructing a Message-Pruning Tree with Minimum Cost for Tracking Moving Objects in Wireless Sensor Networks Is NP-Complete and an Enhanced Data Aggregation Structure

Wireless sensor networks have often been used to monitor and report the locations of moving objects. Since sensors can also be used for storage, a wireless sensor network can be considered a distributed database, enabling us to update and query the location information of moving objects. Many researchers have studied the problem of how to construct message-pruning trees that can update a database and query objects with minimum cost (the Minimum Cost Message-Pruning Tree problem). The trees are constructed in such a way that the total cost of updating the database and querying objects is kept as minimum as possible, while the hardness of the Minimum Cost Message-Pruning Tree problem remains unknown. In this paper, we first show that the Minimum Cost Message-Pruning Tree problem is NP-complete. Subsequently, since the message-pruning tree with minimum cost is hard to be constructed in polynomial time, we propose a new data aggregation structure, a message-pruning tree with shortcuts, instead of the message-pruning tree. Simulation results show that the proposed data aggregation structure significantly reduces the total cost of updating the database and querying objects, as compared to the message-pruning tree.

Rate-lifetime tradeoff for reliable communication in wireless sensor networks

The network lifetime and application performance are two fundamental, yet conflicting, design objectives in wireless sensor networks . There is an intrinsic tradeoff between network lifetime maximization and application performance maximization, the latter being often correlated to the rate at which the application can send its data reliably in sensor networks. In this paper we study this tradeoff by investigating the interactions between the network lifetime maximization problem and the rate allocation problem with a reliable data delivery requirement. Severe bias on the allocated rates of some sensor nodes may exist if only the total throughput of the sensor network is maximized, hence we enforce fairness on source rates of sensor nodes by invoking the network utility maximization (NUM) framework. To guarantee reliable communication, we adopt the hop-by-hop retransmission scheme. We formulate the network lifetime maximization and fair rate allocation both as constrained maximization problems. We characterize the tradeoff between them, give the optimality condition, and derive a partially distributed algorithm to solve the problem. Furthermore, we propose an approximation of the tradeoff problem using NUM framework, and derive a fully distributed algorithm to solve the problem.