An Approach to Increase the Lifetime of a Linear Array of Wireless Sensor Nodes

The nodes in a wireless sensor network are generally energy constrained. The lifetime of such a network is limited by the energy dissipated by individual nodes during signal processing and communication with other nodes. The issues of modeling a sensor network and assessment of its lifetime have received considerable attention in recent years. This paper provides an analytical framework for placing a number of nodes in a linear array such that each node dissipates the same energy per data gathering cycle. This approach ensures that all nodes run out of battery energy almost simultaneously. It is shown that the network lifetime almost doubles with the proposed scheme as compared to other reported schemes. However, in practice, the nodes are not expected to be placed as per this theoretical requirement. The issue of random placement of nodes has also been investigated to obtain the statistics of energy consumption of a node. The analytical results for random node placement are validated through simulation studies.

An Energy Conservation MAC Protocol in Wireless Sensor Networks

Wireless sensor networks use battery-operated computing and sensing devices. Because of the limitation of battery power in the sensor nodes, energy conservation is a crucial issue in wireless sensor networks. Consequently, there is much literature presenting energy-efficient MAC protocols based on active/sleep duty cycle mechanisms to conserve energy. Convergecast is a common communication pattern across many sensor network applications featuring data gathering from many different source nodes to a single sink node. This leads to high data collision rates, high energy consumption, and low throughput near the sink node. This paper proposes an efficient slot reservation MAC protocol to reduce energy consumption and to make transmission more efficient in data gathering wireless sensor networks. The simulation results show that our protocol provides high throughput, low delivery latency and low energy consumption compared to other methods.

Locally Optimal Source Routing for energy-efficient geographic routing

We analyze the problem of finding an energy-efficient path from a source node to a destination using geographic routing. Existing schemes have neglected the fact that neighbors which are not closer to the destination than the current node can still reduce energy consumption by taking part in the selected path. Moreover, recent works have confirmed that the generally used Unit Disk Graph to model Wireless Sensor Networks does not represent accurately the behavior of real links. We propose a new scheme called Locally Optimal Source Routing (LOSR) that is able to use neighbors which do not provide advance toward the destination to reduce the overall energy consumption while still avoiding routing loops. Using an Automatic Repeat reQuest (ARQ) mechanism hop by hop we overcome the problems caused by errors in radio transmissions and we introduce a novel routing metric, which accounts for those errors in the energy consumption. Our simulation results show that the proposed scheme outperforms existing solutions over a variety of scenarios and network densities.

Very Low Energy Consumption Wireless Sensor Localization for Danger Environments with Single Mobile Anchor Node

In wireless sensor networks (WSN), it is very important for sensor nodes to locate with low energy consumption and high accuracy, especially in a dangerous environment. This paper describes a range-free layered localization scheme using one mobile anchor node which can transmit gradient signals, and whose moving track is a straight-line along the x-axis. And this paper proposes a sleep/wake mechanism called sensor sleep-time forecasting to save energy consumption during localization. The relationship, between the key factors in localization algorithm and the average location error, is analyzed in detail. Simulation results show that the scheme performs better than other range-free mechanisms—the average location error is less than 0.7 m, and it is independent on sensor nodes density or sensor nodes radio range, the accuracy of the algorithm can be adjusted in different occasions, and the algorithm beacon overhand is small and average localization time is short.

A dynamic-clustering reactive routing algorithm for wireless sensor networks

The clustering is a key routing method for large-scale wireless sensor networks, which effective extends the lifetime and the expansibility of network. In this paper, a node model is defined based on the structure and transmission principle of neuron, and a dynamic-clustering reactive routing algorithm is proposed. Once the event emergences, the cluster head is dynamic selected in the incident region according to the residual energy. The data collected by the cluster head is sent back to the Sink along the network backbone. Two kinds of accumulation ways are designed to increase the efficiency of data collection. Meanwhile through the fluctuation of action-threshold, the cluster head can trace the changing speed of incident; the nodes outside the incident region use this fluctuation to send data periodically. Finally, the simulation results verify that the DCRR algorithm extends the network’s lifetime considerably and adapts to the change of network scale. The analysis shows that DCRR has more prominent advantages under low and middle load.

Sequential Monte Carlo localization in mobile sensor networks

Node localization in wireless sensor networks is essential to many applications such as routing protocol, target tracking and environment surveillance. Many localization schemes have been proposed in the past few years and they can be classified into two categories: range-based and range-free. Since range-based techniques need special hardware, which increases the localization cost, many researchers now focus on the range-free techniques. However, most of the range-free localization schemes assume that the sensor nodes are static, the network topology is known in advance, and the radio propagation is perfect circle. Moreover, many schemes need densely distributed anchor nodes whose positions are known in advance in order to estimate the positions of the unknown nodes. These assumptions are not practical in real network. In this paper, we consider the sensor networks with sparse anchor nodes and irregular radio propagation. Based on Sequential Monte Carlo method, we propose an alterative localization method—Sequential Monte Carlo Localization scheme (SMCL). Unlike many previously proposed methods, our work takes the probabilistic approach, which is suitable for the mobile sensor networks because both anchors and unknown nodes can move, and the network topology need not be formed beforehand. Moreover, our algorithm is scalable and can be used in large-scale sensor networks. Simulation results show that SMCL has better localization accuracy and it can localize more sensor nodes when the anchor density is low. The communication overhead of SMCL is also lower than other localization algorithms.

Reactive ID Assignment for Wireless Sensor Networks

Globally unique ID allocation is usually not applicable in a sensor network due to the massive production of cheap sensor nodes, the limited bandwidth, and the size of the payload. However, locally unique IDs are still necessary for nodes to implement unicast communications to save power consumption. Several solutions have been proposed for locally unique ID assignment in sensor networks. However, they bring much communication overhead, which is not desirable due to the limited power supply in a sensor node. Combined with a directed diffusion communication paradigm, a reactive ID assignment scheme with security mechanisms is proposed in this paper. It defers ID conflict resolution until data communications are initiated and thus saves communication overhead.

A connectivity-based approach for the construction of hierarchical WDM network topology

A hierarchical network model can effectively reduce the complexity of routing and wavelength assignment (RWA) in wavelength division multiplexing (WDM) networks compared to a flat model. However, the resource utilization may greatly suffer if the hierarchical architecture is not properly arranged. By considering the degree of each WDM node and the location effect, this paper proposes a systematic approach to construct the hierarchical topology in WDM networks so that resource utilization can be maximized. Simulation results demonstrate that the performance of the proposed scheme is superior to that of another scheme.

Network Lifetime Optimization by KKT Optimality Conditions in Wireless Sensor Networks

Energy saving is a critical issue for typical wireless sensor networks (WSNs) and the energy consumption is a big challenge to the design of WSNs. In this paper, we investigate this problem by a cross-layer design approach to minimize energy consumption and maximize network lifetime (NL) for a multiple-source and single-sink (MSSS) WSN with energy constraints. The optimization problem for the MSSS WSNs can be formulated as a mixed integer convex optimization problem with adoption of time division multiple access (TDMA) at medium access control (MAC) layer and it becomes a convex problem by relaxing an integer constraint on time slots. First of all, we have employed the Karush-Kuhn-Tucker(KKT) optimality conditions to derive analytical expressions of the globally optimal NL for a linear SSSS topology. Then a decomposition and combination (D&C) approach has been proposed to obtain suboptimal solutions. As a result, an analytical expression of the suboptimal NL has been derived for WSNs with a linear MSSS topology. To validate the analysis, numerical results show that the upper-bounds of the NL obtained by our proposed optimization models are tight. Important insights into the NL and benefits of cross-layer design for WSN NLM are also summarized.

Resource optimization in distributed biometric recognition using wireless sensor network

Distributed, autonomous and energy efficient protocols are best suited for wireless sensor networks, where network needs and events are dynamic. In this paper, a wireless face recognition system with limited resources such as energy, memory and bandwidth is analyzed. The performance of the applications is influenced by the protocol adaptability and quality of information. Performance comparisons are completed using 1. In-network image compression using Contourlet and Wavelet transforms versus raw image data transmission, 2. longevity of sensors versus network throughput. Balancing resource constraints, maintaining network lifetime and throughput is a non-deterministic polynomial computation time problem. Thus a meta-heuristic combinatorial algorithm, based on swarm intelligence, forms the cognitive routing protocol. The network efficiency considers energy consumption, response time, probability of correct acceptance, processing and computation time for wireless image transmission.

A Channel based Fair Scheduling Scheme for Downlink Data Transmission in TD-CDMA Networks

High speed data transmission in wireless networks demands better radio resource management schemes. A fair packet scheduling is proposed for downlinks of a cellular TD-CDMA system for delay-tolerant applications. It is based on the combined consideration of channel conditions, required throughput and achieved average throughput. A system dependent parameter is introduced to control the maximum achievable date rate as well as the degree of fairness. Through analysis and simulation, we study the tradeoff between system throughout (i.e., efficiency) and individual throughput (i.e., fairness). The relative performance between the proposed scheme and the traditional schemes is evaluated through simulation to confirm the analytical observations. The sensitivity of the system tolerance factor towards efficiency and fairness is also investigated.

EasiTPQ: QoS-Based Topology Control in Wireless Sensor Network

With the rapid development of wireless sensor networks (WSNs), the requirements for quality of service (QoS) are growing, particularly in applications where real time imaging, video or audio communications are involved. The system needs to meet both optimized energy consumption design metric and to satisfy certain QoS requirements simultaneously from long view. Different from most of the existing works which deal with resource allocation (e.g., scheduling or buffering) or routing strategy to achieve QoS, we extend QoS support to the topology control layer by introducing a number of active nodes distributed in a gradient fashion based on their logical distances to the sink node. In this paper, a novel topology control algorithm, namely EasiTPQ (Easy QoS-based topology control) is proposed to improve QoS performance in wireless sensor networks. Simulation results show that data loss rate and latency are averagely improved by 55 and 45%, respectively.

Performance analysis of an improved soft preemptive scheme for unevenly distributed traffic in optical wavelength-division multiplexing networks

In optical wavelength-division multiplexing (WDM) networks, traffic can be unevenly distributed across the network causing inefficient utilization of resources. To solve this problem, an improved soft preemptive (SP) scheme is proposed by considering dynamic resource distribution to deal with the uneven network utilization. A novel unevenly distributed traffic model in cross-time-zone networks is also presented to evaluate the efficiency of the new scheme. Compared with other schemes such as normal shortest path first (SPF) routing and wavelength conversion (WC), the new proposed scheme results demonstrate significantly better performance with respect to the network utilization and overall network blocking probability.

A New Routing Metric for Satisfying Both Energy and Delay Constraints in Wireless Sensor Networks

Besides energy constraint, wireless sensor networks should also be able to provide bounded communication delay when they are used to support real-time applications. In this paper, a new routing metric is proposed. It takes into account both energy and delay constraints. It can be used in AODV. By mathematical analysis and simulations, we have shown the efficiency of this new routing metric.

Cluster-Based Autoconfiguration for Mobile Ad hoc Networks

IP address autoconfiguration of mobile nodes is highly desirable in the practical usage of most mobile ad hoc networks (MANETs). This paper proposes cluster-based autoconfiguration, a novel approach for the efficient address autoconfiguration of MANETs. The cluster structure derived from clustering techniques is used to manage address assignment and conflict resolution. By introducing the concept of virtual address agents (AAs), the proposed approach can be applicable to many existing clustering protocols. Finally, analysis and simulation demonstrate that the proposed scheme outperforms the previous autoconfiguration approaches.

A framework for the multicast lifetime maximization problem in energy-constrained wireless ad-hoc networks

We consider the problem of maximizing the lifetime of a given multicast connection in wireless networks that use directional antennas and have limited energy resources. We provide a globally optimal solution to this problem for a special case of using omni-directional antennas. This graph theoretic approach provides us insights into more general case of using directional antennas, and inspires us to produce a group of heuristic algorithms. Experimental results show that our algorithms outperform other energy-aware multicast algorithms significantly in terms of multicast lifetime.

Information-Theoretic Integration of Sensing and Communication for Active Robot Networks

This paper presents an information-theoretic approach to sensor placement that incorporates communication capacity into an optimal formulation. A new formulation is presented that maximizes the information rate achievable by a set of sensors communicating wirelessly to a single collection node. Shannon capacity and the standard radio propagation model are used to model the throughput achievable by a sensor configuration. Likewise, the d-optimality criterion from the active sensing literature is used to model information gain provided by range and bearing sensors. The combination of information-theoretic measures leads to a metric equivalent to the expected information rate achievable by the system. Sensor positions are selected that optimize this measure.

Information Regularized Sensor Fusion: Application to Localization With Distributed Motion Sensors

We propose the information regularization principle for fusing information from sets of identical sensors observing a target phenomenon. The principle basically proposes an importance-weighting scheme for each sensor measurement based on the mutual information based pairwise statistical similarity matrix between sensors. The principle is applied to maximum likelihood estimation and particle filter based state estimation. A demonstration of the proposed regularization scheme in centralized data fusion of dense motion detector networks for target tracking is provided. Simulations confirm that the introduction of information regularization significantly improves localization accuracy of both maximum likelihood and particle filter approaches compared to their baseline implementations. Outlier detection and sensor failure detection capabilities, as well as possible extensions of the principle to decentralized sensor fusion with communication constraints are briefly discussed.

Secure and Efficient Localization Scheme in Ultra-Wideband Sensor Networks

This paper addresses the problem of secure localization in hostile environments. We propose a secure and efficient localization scheme to enhance the security function of Ultra-Wideband sensor networks. The method does not only provide strong security against distance reduction attacks, but also distance enlargement attacks. Furthermore, it is a device-independent scheme with strong function of more accurate localization. Based on Petri net, an attack-driven model is also developed. , which provides a formal method to verify our scheme when considering distance enlargement attacks. State analysis, which proves that the potential insecure states are unreachable, shows that the model can provide strong security in the environment with these attacks.

Improving Spectral Capacity and Wireless Network Coverage by Cognitive Radio Technology and Relay Nodes in Cellular Systems

Methods to enhance the use of the frequency spectrum by automatical spectrum sensing plus spectrum sharing in a cognitive radio technology context have been presented and discussed in this paper. Ideas to improve the wireless transmission by orthogonal OFDM-based communication and to increase the coverage of cellular systems by future wireless networks, relay channels, relay stations and collaborate radio have been presented as well. A revised hierarchical deployment of the future wireless and wired networks are shortly discussed.