Large Wireless Sensor Networks Research Articles

An Energy-Balanced Clustering Routing Algorithm for Wireless Sensor Network

In this paper, we consider a network of energy constrained sensors deployed over a region. Each sensor node in such a network is systematically gathering and transmitting sensed data to a base station (via cluster- heads). This paper focuses on reducing the power consumption of wireless sensor networks. Firstly, we proposed an Energy-balanced Clustering Routing Algorithm called LEACH-L, which is suitable for a large scope wireless sensor network. Secondly, optimum hop-counts are deduced. Lastly, optimum position of transmitting node is estimated. Simulation results show that our modified scheme can extend the network lifetime by up to 80% before first node dies in the network. Through both theoretical analysis and numerical simulations, it is shown that the proposed algorithm achieves higher performance than the existing clustering algorithms such as LEACH, LEACH-M.

Energy-aware secure routing for large wireless sensor networks

Wireless Sensor Networks (WSN) are vulnerable to a wide set of attacks which threaten the network operation. Although communication and security technologies for computer networks have reached a mature stage, their applicability in WSNs is disputable due to their infrastructure-less operation and the limited node and network resources. Focusing on the routing procedure, this relies in the cooperation among neighboring nodes and a long list of attacks that can cause serious damage have already been identified. The situation is futher aggravated as the next generation wireless sensor network will be larger and larger. To face this problem, we propose a secure routing protocol (Ambient Trust Sensor Routing, ATSR) which adopts the geographical routing principle to cope with the network dimensions and part of the routing attacks, while it relies on a distributed trust model for the detection of another part of the routing attacks. Both direct and indirect trust information is taken into account to evaluate the trustworthiness of each neighbour. An important feature of the proposed routing solution is that it takes into account the remaining energy of each neighbour, thus allowing for better load balancing and network lifetime extension. Based on computer simulation results we evaluate the additional energy consumption caused by the exchange of indirect trust information and the benefits stemming from the adoption of our algorithm.

Sink-oriented Dynamic Location Service Protocol for Mobile Sinks with an Energy Efficient Grid-Based Approach

Sensor nodes transmit the sensed information to the sink through wireless sensor networks (WSNs). They have limited power, computational capacities and memory. Portable wireless devices are increasing in popularity. Mechanisms that allow information to be efficiently obtained through mobile WSNs are of significant interest. However, a mobile sink introduces many challenges to data dissemination in large WSNs. For example, it is important to efficiently identify the locations of mobile sinks and disseminate information from multi-source nodes to the multi-mobile sinks. In particular, a stationary dissemination path may no longer be effective in mobile sink applications, due to sink mobility. In this paper, we propose a Sink-oriented Dynamic Location Service (SDLS) approach to handle sink mobility. In SDLS, we propose an Eight-Direction Anchor (EDA) system that acts as a location service server. EDA prevents intensive energy consumption at the border sensor nodes and thus provides energy balancing to all the sensor nodes. Then we propose a Location-based Shortest Relay (LSR) that efficiently forwards (or relays) data from a source node to a sink with minimal delay path. Our results demonstrate that SDLS not only provides an efficient and scalable location service, but also reduces the average data communication overhead in scenarios with multiple and moving sinks and sources.

Target Tracking with QoS Support in Large Wireless Sensor Networks

Quality of Service (QoS) is important in the application of target tracking in wireless sensor networks (WSNs). When a target appears, it will trigger an event from one or more sensors. A target can only be accurately detected if a certain number of event packets are received by the sink in a predetermined detection time interval. In this paper, we propose a buffer management scheme based on event ordering to achieve QoS. We also propose a directional QoS-aware routing protocol (DQRP) for the dissemination of the event ordering list. After the dissemination, a priority queue buffer management scheme is used to ensure QoS. Our buffer management scheme works in conjunction with DQRP to ensure accurate as well as energy-efficient target detection in the presence of multiple targets. The novelty of our network architecture is that a distributed admission control scheme is implemented on each node based on a geographic routing algorithm. In our scenario, a target can only be accurately detected if a certain number of event packets are received by the sink in a predetermined detection time interval. Our main performance metric is the number of targets/events being detected. Our protocol maximizes the number of targets being detected.

Constructing a Large Scale Wireless Sensors Network and Resources Scheduling among Multiple Personal Area Networks

Constructing a Large Scale Wireless Sensors NetworkA real challenge of wireless sensors network applications is how to expand it to a larger scale. We proposed the idea of “One Zone Multi-PAN (Personal Area Network)” to build a Large-Scale Wireless Sensors Network (LS-WSN). Its key points include: the elementary component of LS-WSN is PAN; different PANs work on different channels; different PANs use customized policies and execute different tasks; every PAN covers and surveillances the same area, but senses different circumstance information. Based on the idea, we proposed a two-level distributed LS-WSN model. The first level is the PAN-level, which works in a distributed mode. On this level, the up to 16 PANs bridged by a specially designed gateway coexist like a multi-layer sandwich. This gateway is a common children node of different PANs; therefore it can join in different PANs in a time-sharing mode. The second level is the inner-PAN-level, whose work mode is determined by the specific manufacturer. The size of this model can be expanded up to 16 times of the size of a single PAN. Furthermore, QoS of LS-WSN can be guaranteed, data fusion and data management can be simplified and improved. Using Zigbee stack, we set up a prototype system of LS-WSN, whose performances are validated by our experiments. Resources Scheduling among PANsFor executing resource reconfiguration in LS-WSN, we proposed an application framework of resources scheduling (RSAF). Its key principles include: radio channels, superframe time-slots, and energy resources are named as “Common Resources;” “the whole network is more important than a single PAN” in LS-WSN; keep the key PANs alive; the lifespan of a LS-WSN is determined by that of key PANs. RSAF can be comprehended as a collaboration mechanism at PAN level. It includes three components: superframe time-slots scheduling, radio channel scheduling, and energy scheduling. Their algorithms are different. Especially, a typical working cycle of energy scheduling contains four steps. First, the coordinators of different PANs gather different PANs' state information in a piggyback mode. Then the gateway periodically evaluates different PANs' states and makes the decisions of resources scheduling. After that, the specified coordinators send the control messages to certain nodes. Finally, the specified nodes will join and reinforce the key PAN in danger due to certain reasons (e.g., out of energy). Our experimental results validate the feasibility of RSAF in our prototype system.

Unsynchronized Energy-Efficient Medium Access Control and Routing in Wireless Sensor Networks

SUMMARY The challenge in the design of energy-efficient medium access protocols for Wireless Sensor Networks (WSNs) is to use the radio only in an “on demand” manner, as the radio transceiver is a major source of WSN energy consumption. Energy-efficient MAC protocols periodically switch the radio transceiver hardware between the costly operation modes receive and transmit, and an energy-saving sleep mode. Most existing power saving MAC approaches synchronize the nodes in the network to let the nodes synchronously wake up at designated instants to exchange pending messages. Synchronization however is expensive and uneasy to achieve. With low traffic, the overhead for maintaining synchronization and slot coordination across a large multi-hop WSN may exceed the energy spent for the actual data. Mechanisms renouncing on synchronization are likely to be more efficient in low-traffic scenarios. We investigate modifications and optimizations on recently proposed fully unsynchronized power saving MAC protocols for wireless sensor networks based on asynchronous wake-up patterns and intended for sensor networks with low traffic requirements.

H-TOSSIM: Extending TOSSIM with Physical Nodes

As the development of Wireless Sensor Network (WSN), software testing for WSN-based applications be-comes more and more important. Simulation testing is an important approach to WSN-based software testing, and TOSSIM is the most widely used simulation testing tool targeted at TinyOS which is the most popular operating system nowadays. However, simulation testing tools such as TOSSIM can not reveal program er-rors about communication detail or timing, and lack accurate power consumption model and even can not support power consumption estimation. In this paper, a hybrid testbed H-TOSSIM is proposed, which ex-tends TOSSIM with physical nodes. H-TOSSIM uses three physical nodes, of which, one shares the simu-lated environment with all virtual nodes to test the WSN program, and the other two bridge the real world and the simulated environment. H-TOSSIM combines the advantages of both the simulation in physical node and the simulation testing tools in WSN software testing. Through experiments, we show that H-TOSSIM really reveals program errors which the pure simulation testing can not capture, and can support power con-sumption estimation for large WSN with high accuracy and low hardware cost.

Scoped Bellman-Ford Geographic Routing for Large Dynamic Wireless Sensor Networks

Routing is a fundamental problem in wireless sensor networks. Most previous routing protocols are challenged when used in large dynamic networks as they suffer from either poor scalability or the void problem. In this paper, we propose a new geographic routing protocol, SBFR (Scoped Bellman-Ford Routing), for large dynamic wireless sensor networks. The basic idea is that each node keeps a view scope of the network by computing distance vectors using the distributed Bellman-Ford method, and maintains a cost for routing to the sink. When forwarding a packet, a node picks the node with minimum cost in its routing table as a temporary landmark. While achieving good scalability, it also solves the void problem in an efficient manner through the combination of Bellman-Ford routing and cost-based geographic routing. Analytical and simulation results show that SBFR outperforms other routing protocols not only because of its robustness and scalability but also its practicality and simplicity.

GBP-WAHSN: A Group-Based Protocol for Large Wireless Ad Hoc and Sensor Networks

Grouping nodes gives better performance to the whole network by diminishing the average network delay and avoiding unnecessary message forwarding and additional overhead. Many routing protocols for ad-hoc and sensor networks have been designed but none of them are based on groups. In this paper, we will start defining group-based topologies, and then we will show how some wireless ad hoc sensor networks (WAHSN) routing protocols perform when the nodes are arranged in groups. In our proposal connections between groups are established as a function of the proximity of the nodes and the neighbor's available capacity (based on the node's energy). We describe the architecture proposal, the messages that are needed for the proper operation and its mathematical description. We have also simulated how much time is needed to propagate information between groups. Finally, we will show a comparison with other architectures.

Distributed Estimation in Large Wireless Sensor Networks via a Locally Optimum Approach

A wireless sensor network (WSN) engaged in a decentralized estimation problem is considered. The nonrandom unknown parameter lies in some small neighborhood of a nominal value and, exploiting this knowledge, a locally optimum estimator (LOE) is introduced. Under the LOE paradigm, the sensors of the network process their observations by means of a suitable nonlinearity (the score function), before delivering data to the fusion center that outputs the final estimate. Usually continuous-valued data cannot be reliably delivered from sensors to the fusion center, and some form of data compression is necessary. Accordingly, we design the scalar quantizers that must be used at the network's nodes in order to comply with the estimation problem at hand. Such a difficult multiterminal inference problem is shown to be asymptotically equivalent to the already solved problem of designing optimum quantizers for reconstruction (as opposed to inference) purposes.

Training Data Compression Algorithms and Reliability in Large Wireless Sensor Networks

Abstract With the availability of low-cost sensor nodes there have been many standards developed to integrate and network these nodes to form a reliable network allowing many different types of hardware vendors to coexist. Most of these solutions however have aimed at industry-specific interoperability but not the size of the sensor network and the large amount of data which is collected in course of its lifetime. In this paper we use well studied data compression algorithms which optimize on bringing down the data redundancy which is related to correlated sensor readings and using a probability model to efficiently compress data at the cluster heads. As in the case of sensor networks the data reliability goes down as the network resource depletes and these types of networks lacks any central synchronization making it even more a global problem to compare different reading at the central coordinator. The complexity of calibrating each sensor and using an adaptable measured threshold to correct the reading from sensors is a severe drain in terms of network resources and energy consumption. In this paper we separate the task of comparative global analysis to a central coordinator and use a reference PM ax which is a normalized probability of individual source which reflects the current lifetime reliability of the sensors calculated at the cluster heads which then is compared with the current global reliability index based on all the PMax of cluster heads. As this implementation does not need any synchronization at the local nodes it uses compress once and stamp locally without any threshold such as application specific calibration values (30±C ) and the summarization can be application independent making it more a sensor network reliability index and using it independent of the actual measured values.

Analysis of Lifetime of Large Wireless Sensor Networks Based on Multiple Battery Levels

Due to the limited transmission range, data sensed by each sensor has to be forwarded in a multi-hop fashion before being delivered to the sink. The sensors closer to the sink have to forward comparatively more messages than sensors at the periphery of the network，and will deplete their batteries earlier. Besides the loss of the sensing capabilities of the nodes close to the sink, a more serious consequence of the death of the first tier of sensor nodes is the loss of connectivity between the nodes at the periphery of the network and the sink; it makes the wireless networks expire. To alleviate this undesired effect and maximize the useful lifetime of the network, we investigate the energy consumption of different tiers and the effect of multiple battery levels, and demonstrate an attractively simple scheme to redistribute the total energy budget in multiple battery levels by data traffic load. We show by theoretical analysis, as well as simulation, that this substantially improves the network lifetime.

Minimum delay routing for wireless networks with STDMA

STDMA emerges as a promising channel access technique for providing Quality of Service (QoS) guarantees in multi-hop ad hoc networks such as community mesh and sensor networks. The contention-free channel access combined with spatial reuse of the channel provide significant benefits in the energy/throughput trade-off. On the other hand, the time-multiplexed communication introduces extra delay on the packets when relayed by intermediate nodes. Hence in large wireless sensor networks or mesh networks, where data is routed over several hops before reaching the data sink, STDMA protocols may introduce high end-to-end latency due to the reservation-based access policy. We argue that a suitable routing protocol specifically designed for reservation-based Medium Access Control (MAC) protocols can alleviate their high-latency drawback. Following this argument, we propose first such routing algorithms working on top of a generic STDMA MAC protocol. First, we consider routing with data fusion and present our GreenWave routing idea. We show that our algorithm significantly reduces the end-to-end delay when compared to routing over the shortest-hop paths. Second, we consider routing without data fusion, by taking into account the effect of congestion along the paths on the end-to-end delays. We provide a QIP formulation of the problem, and present a lower bound and a heuristic algorithm to bound the optimal solution. Based on the centralized heuristic algorithm, we propose a distributed, dynamic routing protocol GreenWave routing with Congestion and Flow control (GWCF), which uses a novel congestion and flow control technique utilizing the underlying contention-free protocol. We show by simulations that GWCF routing significantly improves the end-to-end delay while increasing the network throughput when compared to routing over shortest paths.

Key management issues in wireless sensor networks: current proposals and future developments

Key management has remained a challenging issue in wireless sensor networks (WSNs) due to the constraints of sensor node resources. Various key management schemes that trade off security and operational requirements have been proposed in recent years. In this article, we first examine the security and operational requirements of WSNs and then review five key management protocols: Eschenauer, Du, LEAP, SHELL, and Panja. Eschenauer's scheme is a classical random key distribution scheme for WSNs. Du's scheme improves on Eschenauer's scheme by using key matrices. LEAP provides a highly flexible key management scheme using four types of keys. SHELL focuses on achieving high robustness, and Panja is optimized for hierarchical WSNs. LEAP, SHELL, and Panja support cluster-based operations and are more aligned with current trends as shown by the new standards, IEEE 802.15.4b and the ZigBee enhanced standard. Future developments likely will incorporate the features of LEAP and adjustable robustness enhancements from Eschenauer or Du; extremely security-critical applications may benefit from restructuring SHELL to ease implementation and maintenance. Developments for extremely large WSNs should consider improving Panja's scheme due to its hierarchical scalability feature.

Exploiting agents for modelling and simulation of coverage control protocols in large sensor networks

A sensor network is composed of low-cost, low-power nodes densely deployable over a (possibly in-hospitable) territory in order to monitor the state of the environment, e.g. temperature, sound, radiation and so forth. Sensors have the ability to self-organize into an interconnected network and to cooperate for collecting, aggregating and disseminating information to end users. Major challenges in dealing with sensor networks are the strong limitations imposed by finite onboard power capacity. This paper proposes a lightweight actor infrastructure that is well-suited to modelling and simulation of complex sensor networks and, more in general, of multi-agent systems. This infrastructure is exploited for designing and implementing an efficient actor-based distributed simulation model for studying specific aspects of large wireless sensor networks. The paper proposes and compares the performances of two protocols for the coverage control problem that achieve their objective as an emergent property. In particular, one of the two protocols adopts a novel approach based on an evolutionary game. Distributed simulation of the achieved actor-based models is characterized by good execution performances witnessed by reported experimental results.

Optimal deployment of large wireless sensor networks

A spatially distributed set of sources is creating data that must be delivered to a spatially distributed set of sinks. A network of wireless nodes is responsible for sensing the data at the sources, transporting them over a wireless channel, and delivering them to the sinks. The problem is to find the optimal placement of nodes, so that a minimum number of them is needed. The critical assumption is made that the network is massively dense, i.e., there are so many sources, sinks, and wireless nodes, that it does not make sense to discuss in terms of microscopic parameters, such as their individual placements, but rather in terms of macroscopic parameters, such as their spatial densities. Assuming a particular interference-limited, capacity-achieving physical layer, and specifying that nodes only need to transport the data (and not to sense them at the sources, or deliver them at the sinks once their location is reached), the optimal node placement induces a traffic flow that is identical to the electrostatic field created if the sources and sinks are replaced by a corresponding distribution of positive and negative charges. Assuming a general model for the physical layer, and specifying that nodes must not only transport the data, but also sense them at the sources and deliver them at the sinks, the optimal placement of nodes is given by a scalar nonlinear partial differential equation found by calculus of variations techniques. The proposed formulation and derived equations can help in the design of large wireless sensor networks that are deployed in the most efficient manner, not only avoiding the formation of bottlenecks, but also striking the optimal balance between reducing congestion and having the data packets follow short routes.

Understanding optimal data gathering in the energy and latency domains of a wireless sensor network

The problem of optimal data gathering in wireless sensor networks (WSNs) is addressed by means of optimization techniques. The goal of this work is to lay the foundations to develop algorithms and techniques that minimize the data gathering latency and at the same time balance the energy consumption among the nodes, so as to maximize the network lifetime. Following an incremental-complexity approach, several mathematical programming problems are proposed with focus on different network performance metrics. First, the static routing problem is formulated for large and dense WSNs. Optimal data-gathering trees are analyzed and the effects of several sensor capabilities and constraints are discussed, e.g., radio power constraints, energy consumption model, and data aggregation functionalities. Then, dynamic re-routing and scheduling are considered. An accurate network model is proposed that captures the tradeoff between the data gathering latency and the energy consumption, by modeling the interactions among the routing, medium access control and physical layers.For each problem, extensive simulation results are provided. The proposed models provide a deeper insight into the problem of timely and energy efficient data gathering. Useful guidelines for the design of efficient WSNs are derived and discussed.

Stochastic Sleeping for Energy-Conserving in Large Wireless Sensor Networks

Stochastic Sleeping for Energy-Conserving in Large Wireless Sensor Networks

Distributed Detection and Fusion in a Large Wireless Sensor Network of Random Size

For a wireless sensor network (WSN) with a random number of sensors, we propose a decision fusion rule that uses the total number of detections reported by local sensors as a statistic for hypothesis testing. We assume that the signal power attenuates as a function of the distance from the target, the number of sensors follows a Poisson distribution, and the locations of sensors follow a uniform distribution within the region of interest (ROI). Both analytical and simulation results for system-level detection performance are provided. This fusion rule can achieve a very good system-level detection performance even at very low signal-to-noise ratio (SNR), as long as the average number of sensors is sufficiently large. For all the different system parameters we have explored, the proposed fusion rule is equivalent to the optimal fusion rule, which requires much more prior information. The problem of designing an optimum local sensor-level threshold is investigated. For various system parameters, the optimal thresholds are found numerically by maximizing the deflection coefficient. Guidelines on selecting the optimal local sensor-level threshold are also provided.

Distributed detection in a large wireless sensor network

A distributed detection and decision fusion scheme is proposed for a wireless sensor network (WSN) consisting of a large number of sensors. At the fusion center, the total number of detections reported by local sensors are employed for hypothesis testing. Based on the assumption that the received signal power decays as the distance from the target increases, system level detection performance measures, namely probabilities of detection and false alarm, are derived analytically through approximation by using the central limit theorem (CLT). If the number of sensors is sufficiently large, the proposed fusion rule can provide very good system level detection performance, in the absence of the knowledge of local sensors' performances and at low signal to noise ratio (SNR). It is shown that for all the different system parameters we have explored, this fusion rule is equivalent to the optimal fusion rule, which requires much more prior information. To achieve a better system level detection performance, the local sensor level decision threshold should be designed optimally. Numerical methods are employed to find the optimal local sensor level threshold for different sets of system parameters. Guidelines on selecting the optimal local sensor level decision threshold are also provided.