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Leach (low energy adaptive clustering hierarchy) algorithm is a self-clustering topology algorithm. Its execution process is cyclical. Each cycle is divided into two phases: cluster building phase and stable data communication phase. In the stage of cluster building, the adjacent nodes cluster dynamically and randomly generate cluster heads. In the data communication phase, the nodes in the cluster send the data to the cluster head, and the cluster head performs data fusion and sends the results to the aggregation node. Because the cluster head needs to complete data fusion, communication with the convergence node and other works, the energy consumption is large. Leach algorithm can ensure that each node acts as cluster head with equal probability, so that the nodes in the network consume energy relatively evenly. The basic idea of Leach algorithm is to randomly select cluster head nodes in a circular way. It evenly distributes the energy load of the whole network to each sensor node in the network. It can reduce network energy consumption and improve network life cycle. Leach repeatedly performs cluster refactoring during its operation. This paper studies the parameter detection of wireless sensor network based on Leach algorithm on the on-chip embedded debugging system. Because the classical low-power adaptive clustering layered protocol (Leach) has the problem of energy imbalance and short node life cycle, this paper uses embedded debugging technology based on Leach algorithm and the residual energy and position of nodes in wireless sensor networks were tested for research. This Leach algorithm uses the concept of wheel. Each round consists of two phases: initialization and stabilization. In the initialization stage, each node generates a random number between 0 and 1. If the random number generated by a node is less than the set threshold T (n), the node publishes a message that it is a cluster head. Through the research on the parameter detection, the simulation results show that the research in this paper has good feasibility and rationality. [ABSTRACT FROM AUTHOR]

APTEEN is a typical routing protocol for wireless sensor networks, but when clustering, cluster heads are randomly selected, which makes it easy to select nodes with low residual energy as cluster heads, thus forming network holes. At the same time, in multi hop transmission, the cluster head near the sink node is overloaded due to forwarding a large amount of data. Aiming at these problems, this paper introduces PSO algorithm and proposes ADCH-EPE-APTEEN routing protocol. In order to make the particle swarm optimization algorithm more suitable for routing protocol, this paper first proposes DCA-PSO based on particle swarm optimization algorithm. DCA-PSO uses the classification adaptive change inertia weight for different states of particles in the optimization process. At the same time, dynamic learning factor is used to improve the influence of particle experience and other particle experience on convergence speed and to improve the optimization accuracy and speed of the algorithm. Secondly, when APTEEN routing protocol is networked, the cluster head is selected by DCA-PSO, in which the residual energy of nodes, the location of nodes, and the energy distribution around nodes are fully taken into consideration. Thirdly, considering the distance between nodes and the sink node, the residual energy and the energy distribution around nodes, a front area is set up in the cluster located in the upper half and the assistant cluster head is selected in the front area through the DCA-PSO algorithm. The simulation results show that the DCA-PSO algorithm can significantly improve the search speed and precision compared with the PSO algorithm. Compared with APTEEN routing protocol, the ADCH-EPE-APTEEN routing protocol can reduce the network energy consumption rate and extend network lifetime by 173%. [ABSTRACT FROM AUTHOR]

Today, the wireless sensor network (WSN) plays an important role in our daily life. In addition, it is used in many applications such as military, medical, greenhouse, and transport. Due to the sending data between its nodes or to the base station requires a connection link, the sensor nodes can be exposed to the many attacks that exploit the weaknesses of the network. One of the most important types of these attacks is the denial of service (DoS). DoS attack exhausts the system's resources that lead the system to be out of service. In this paper, a cyber-security algorithm is proposed for physical level of WSN that adopts message queuing telemetry transport (MQTT) protocol for data transmission and networking. This algorithm predicts the DoS attacks at the first time of happening to be isolated from the WSN. It includes three stages of detecting the attack, predicting the effects of this attack and preventing the attacks by excluding the predicted nodes from the WSN. We applied a type of DoS attack that is a DoS injection attack (DoSIA) on the network protocol. The proposed algorithm is tested by adopting three case studies to cover the most common cases of attacks. The experiment results show the superior of the proposed algorithm in detecting and solving the cyber-attacks. [ABSTRACT FROM AUTHOR]

The development of intrusion detection systems (IDS) that are adapted to allow routers and network defence systems to detect malicious network traffic disguised as network protocols or normal access is a critical challenge. This paper proposes a novel approach called SCDNN, which combines spectral clustering (SC) and deep neural network (DNN) algorithms. First, the dataset is divided into k subsets based on sample similarity using cluster centres, as in SC. Next, the distance between data points in a testing set and the training set is measured based on similarity features and is fed into the deep neural network algorithm for intrusion detection. Six KDD-Cup99 and NSL-KDD datasets and a sensor network dataset were employed to test the performance of the model. These experimental results indicate that the SCDNN classifier not only performs better than backpropagation neural network (BPNN), support vector machine (SVM), random forest (RF) and Bayes tree models in detection accuracy and the types of abnormal attacks found. It also provides an effective tool of study and analysis of intrusion detection in large networks. [ABSTRACT FROM AUTHOR]

In wireless sensor networks, in order to satisfy the requirement of long working time of energy-limited nodes, we need to design an energy-efficient and lifetime-extended medium access control (MAC) protocol. In this paper, a node cooperation mechanism that one or multiple nodes with higher channel gain and sufficient residual energy help a sender relay its data packets to its recipient is employed to achieve this objective. We first propose a transmission power optimization algorithm to prolong network lifetime by optimizing the transmission powers of the sender and its cooperative nodes to maximize their minimum residual energy after their data packet transmissions. Based on it, we propose a corresponding power-optimized cooperative MAC protocol. A cooperative node contention mechanism is designed to ensure that the sender can effectively select a group of cooperative nodes with the lowest energy consumption and the best channel quality for cooperative transmissions, thus further improving the energy efficiency. Simulation results show that compared to typical MAC protocol with direct transmissions and energy-efficient cooperative MAC protocol, the proposed cooperative MAC protocol can efficiently improve the energy efficiency and extend the network lifetime. [ABSTRACT FROM AUTHOR]

This paper addresses a transmission energy problem for distributed (or decentralized) estimation in multihop wireless sensor networks (WSN). A primary advantage of distributed estimation is its energy efficiency when compared to centralized estimation. Two distributed estimation schemes are considered in this paper: progressive estimation and consensus estimation. We develop a generalized energy planning algorithm for a progressive estimation method which exploits routing tree and channel state information. We also analyze the energy cost for a consensus estimation method used in broadcast multihop WSN. We demonstrate by analysis and simulation that, subject to an equivalent performance, the total energy cost for consensus estimation is typically much higher than that for progressive estimation, but the peak energy for the former can be less than that for the latter. [ABSTRACT FROM PUBLISHER]

Desynchronization degrades the performance of many signal processing algorithms in Wireless Acoustic Sensor Networks. It is mainly caused by the different distances between the source and each node and by the clock phase offset and frequency skew. Classical solutions use clock synchronization protocols and algorithms in the communication layer, but these alternatives do not tackle the lack of synchronization caused by the distances between sources and nodes. In this paper, we present a novel study of the synchronization problem in acoustic sensor networks from a signal processing point of view. First, we propose a theoretical framework that allows us to study the effects of misalignment over any short-time based algorithm, focusing on the requirements of the effective length of the analysis time frame. From this framework, a theoretical synchronization delay is established aimed at reducing the required length of the time frame. Second, two novel alignment methods are developed and are tuned up to reduce the amount of synchronization information required for transmission. The results obtained demonstrate that our proposed methods represent a good solution in terms of performance over the quality of a standard Blind Source Separation algorithm, allowing us to reduce the transmission bandwidth required for synchronization data. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are a family of wireless networks that usually operate with irreplaceable batteries. The energy sources limitation raises the need for designing specific protocols to prolong the operational lifetime of such networks. These protocols are responsible for messages exchanging through the wireless communications medium from the sensors to the base station (sink node). Therefore, the determination of the optimal location of the sink node becomes crucial to assure both the prolongation of the network’s operation and the quality of the provided services. This paper proposes a novel algorithm based on a Particle Swarm Optimization (PSO) approach for designing an energy-aware topology control protocol. The deliverable of the algorithm is the optimal sink node location within a deployment area. The proposed objective function is based on a number of topology control protocol’s characteristics such as numbers of neighbors per node, the nodes’ residual energy, and how they are far from the center of the deployment area. The simulation results show that the proposed algorithm reveals significant effectiveness to both topology construction and maintenance phases of a topology control protocol in terms of the number of active nodes, the topology construction time, the number of topology reconstructions, and the operational network’s lifetime. [ABSTRACT FROM AUTHOR]

A wireless sensor network consisting of resources, size, and cost-limited sensors is used in many military and civil applications. This paper proposes an energy-efficient clustering algorithm that extends the lifetime of sensor networks. The proposed clustering algorithm is an extended hierarchical clustering protocol that minimizes the overall amount of consumed energy in the network. The proposed approach dynamically updates clusters and distributes the load on the heavily loaded cluster heads among different nodes. It also balances the remaining energy on nodes in the network, which leads to prolonged network lifetime. The performance is evaluated in terms of network lifetime, average energy consumption, and standard deviation of residual energy. [ABSTRACT FROM AUTHOR]

In this paper, we examine routing protocols with the shortest path in sensor networks. In doing this, we propose a genetic algorithm (GA)-based Ad Hoc On-Demand Multipath Distance Vector routing protocol (GA-AOMDV). We utilize a fitness function that optimizes routes based on the energy consumption in their nodes. We compare this algorithm with other existing ad hoc routing protocols including LEACH-GA, GA-AODV, AODV, DSR, EPAR, EBAR_BFS. Results prove that our protocol enhances the network performance in terms of packet delivery ratio, throughput, round trip time and energy consumption. GA-AOMDV protocol achieves average gain that is 7 to 22% over other protocols. Therefore, our protocol extends the network lifetime for data communications. [ABSTRACT FROM AUTHOR]

Broadcasting is a common and basic operation used to support various network protocols in wireless networks. To achieve energy-efficient broadcasting is especially important for ad hoc wireless sensor networks because sensors are generally powered by batteries with limited lifetimes. Energy consumption for broadcast operations can be reduced by minimizing the number of relay nodes based on the observation that data transmission processes consume more energy than data reception processes in the sensor nodes, and how to improve the network lifetime is always an interesting issue in sensor network research. The minimum-energy broadcast problem is then equivalent to the problem of finding the minimum Connected Dominating Set (CDS) for a connected graph that is proved NP-complete. In this paper, we introduce an Efficient Minimum CDS algorithm (EMCDS) with help of a proposed ordered sequence list. EMCDS does not concern itself with node energy and broadcast operations might fail if relay nodes are out of energy. Next we have proposed a Minimum Energy-consumption Broadcast Scheme (MEBS) with a modified version of EMCDS, and aimed at providing an efficient scheduling scheme with maximized network lifetime. The simulation results show that the proposed EMCDS algorithm can find smaller CDS compared with related works, and the MEBS can help to increase the network lifetime by efficiently balancing energy among nodes in the networks. [ABSTRACT FROM AUTHOR]

Data broadcast is a fundamental operation in wireless sensor networks (WSNs). The existence of wireless interference makes it nontrivial to design a minimum-latency broadcast scheme, which is known to be NP-hard. Existing works all assume strict time synchronization and provide centralized TDMA scheduling algorithms. However, WSNs in practice are more likely to be distributed asynchronous systems. In this paper, we investigate the problem of data broadcast with minimum latency for distributed asynchronous WSNs. To this end, we propose a Distributed Asynchronous Broadcast (DAB) algorithm which crucially leverages an elaborately optimized carrier-sensing range together with collision-backoff schemes to coordinate the transmissions among the nodes on a predetermined broadcast backbone. Theoretical analysis shows that DAB is order-optimal and achieves constant factor approximation to the optimal delay. We then conduct extensive simulations to evaluate the practical capability of DAB in asynchronous WSNs and the results corroborate our theoretical analysis. [ABSTRACT FROM AUTHOR]

In order to achieve the equal usage of limited resources in the wireless sensor networks (WSNs), we must aggregate the sensor data before passing it to the base station. In WSNs, the aggregator nodes perform a data aggregation process. Careful selection of the aggregator nodes in the data aggregation process results in reducing large amounts of communication traffic in the WSNs. However, network conditions change frequently due to sharing of resources, computation load, and congestion on network nodes and links, which makes the selection of the aggregator nodes difficult. In this paper, we study an aggregator node selection method in the WSNs. We formulate the selection process as a top-k query problem, where we efficiently solve the problem by using a modified Sort-Filter-Skyline (SFS) algorithm. The main idea of our approach is to immediately perform a skyline query on the sensor nodes in the WSNs, which enables to extract a set of sensor nodes that are potential candidates to become an aggregator node. The experiments show that our method is several times faster compared to the existing approaches. [ABSTRACT FROM AUTHOR]

In order to solve contradictions between real-time applications of wireless sensor networks and limited energy of nodes, Cross-Layer Power Control Algorithm (CLPCA) is proposed in this paper. Moreover, Power-Control-Based Real-Time Routing Protocol (PCBRRP) is designed capable with CLPCA. In this protocol, the transmission power of the node is adjusted dynamically to increase the energy efficiency The next hop node is selected via the link quality of the communication and the residual energy of every node. Simulation results show that the energy consumption of the network is reduced while real-time end-to-end data transmission is guaranteed. [ABSTRACT FROM AUTHOR]

The distributed computing scenario is rapidly evolving for integrating self-organizing and dynamic wireless networks. Unreliable failure detectors (FDs) are classical mechanisms that provide information about process failures and can help systems to cope with the high dynamics of these networks. A number of failure detection algorithms have been proposed so far. Nonetheless, most of them assume a global knowledge about the membership as well as a fully communication connectivity; additionally, they are time-based, requiring that eventually some bound on the message transmission will permanently hold. These assumptions are no longer appropriate to the new scenario. This paper presents a new FD protocol that implements a new class of detectors, namely ⋄ Sℳ, which adapts the properties of the ⋄ S class to a dynamic network with an unknown membership. It has the interesting feature of being time-free, so that it does not rely on timers to detect failures; moreover, it tolerates the mobility of nodes and message losses. [ABSTRACT FROM PUBLISHER]

Abstract: In line with recent research efforts made to conceive energy saving protocols and algorithms and power sensitive network architectures, in this paper we propose a transmission strategy to minimize the energy consumption in a sensor network when using a localization technique based on the measurement of the strength (RSS) or the time of arrival (TOA) of the received signal. In particular, we find the transmission power and the packet transmission rate that jointly minimize the total consumed energy, while ensuring at the same time a desired accuracy in the RSS or TOA measurements. We also propose some corrections to these theoretical results to take into account the effects of shadowing and packet loss in the propagation channel. The proposed strategy is shown to be effective in realistic scenarios providing energy savings with respect to other transmission strategies, and also guaranteeing a given accuracy in the distance estimations, which will serve to guarantee a desired accuracy in the localization result. [ABSTRACT FROM AUTHOR]

A coverage problem is one of the important issues to prolong the lifetime of a wireless sensor network while guaranteeing that the target region is monitored by a sufficient number of active nodes. Most of existing protocols use geometric algorithm for each node to estimate the degree of coverage and determine whether to monitor around or sleep. These algorithms require accurate information about the location, sensing area, and sensing state of neighbor nodes. Therefore, they suffer from localization error leading to degradation of coverage and redundancy of active nodes. In addition, they introduce communication overhead leading to energy depletion. In this paper, we propose a novel coverage control mechanism, where each node relies on neither accurate location information nor communication with neighbor nodes. To enable autonomous decision on nodes, we adopt the nonlinear mathematical model of adaptive behavior of biological systems to dynamically changing environment. Through simulation, we show that the proposal out performs the existing protocol in terms of the degree of coverage per node and the overhead under the influence of localization error. [ABSTRACT FROM AUTHOR]

This paper studies data-centric storage (DCS) as a suitable system to perform data aggregation on wireless sensor and actor networks (WSANs), in which sensor and actor nodes collaborate together in a fully distributed way without any central base station that manages the network or provides connectivity to the outside world. The authors compare different multi-replication DCS proposals and choose the best one to be applied when studying data aggregation. In addition, the authors provide mathematical models for the production, consumption and overall network traffic for different application profiles. Those application profiles are based on the ability of a particular application to perform data aggregation and on what type of traffic is dominant, either the consumption or the production one. Furthermore, the authors provide closed formulas for each application profile that defines the optimal number of replicas that minimise the overall network traffic. Finally, the authors validate the proposed models via simulation. [ABSTRACT FROM AUTHOR]

Abstract: A wireless sensor network is a set of nodes, each is equipped with a sensing device and a wireless communication device. Because centralized control is hard to achieve in a large scale sensor network, self- is a key concept in the design of a wireless sensor network. Self-stabilization is one of the self- properties, and it is one of the most promising theoretical backgrounds for self-organizing wireless sensor network protocols. Herman [T. Herman, Models of self-stabilization and sensor networks, in: Proceedings of the 5th International Workshop of Distributed Computing, IWDC, 2003, pp. 205–214] proposed Cached Sensornet Transform (CST for short) for design and implementation of self-stabilizing algorithms for sensor networks. It transforms a self-stabilizing algorithm in a high-level computational model to a program for sensor networks. Our contribution in this paper is threefold. We show that there exists a non-silent algorithm that behaves correctly in a high-level computational model but its transformed version by CST does not behave correctly if packets are lost. We show a sufficient condition for original algorithms and networks such that the algorithm transformed by CST behaves correctly. As a case study, we present a token circulation algorithm that behaves correctly by CST and derive the upper bound of its expected convergence time. [Copyright &y& Elsevier]

In Delay Tolerant Mobile Sensor Networks (DTMSNs) that have the inherent features of intermitted connectivity and frequently changing network topology it is reasonable to utilize multi-replica schemes to improve the data gathering performance. However, most existing multi-replica approaches inject a large amount of message copies into the network to increase the probability of message delivery, which may drain each mobile node's limited battery supply faster and result in too much contention for the restricted resources of the DTMSN, so a proper data gathering scheme needs a trade off between the number of replica messages and network performance. In this paper, we propose a new data gathering protocol called DRADG (for Distance-aware Replica Adaptive Data Gathering protocol), which economizes network resource consumption through making use of a self-adapting algorithm to cut down the number of redundant replicas of messages, and achieves a good network performance by leveraging the delivery probabilities of the mobile sensors as main routing metrics. Simulation results have shown that the proposed DRADG protocol achieves comparable or higher message delivery ratios at the cost of the much lower transmission overhead than several current DTMSN data gathering schemes. [ABSTRACT FROM AUTHOR]

Energy efficiency and balancing is one of the primary challenges for wireless sensor networks (WSNs) since the tiny sensor nodes cannot be easily recharged once they are deployed. Up to now, many energy efficient routing algorithms or protocols have been proposed with techniques like clustering, data aggregation and location tracking etc. However, many of them aim to minimize parameters like total energy consumption, latency etc., which cause hotspot nodes and partitioned network due to the overuse of certain nodes. In this paper, a Distance-based Energy Aware Routing (DEAR) algorithm is proposed to ensure energy efficiency and energy balancing based on theoretical analysis of different energy and traffic models. During the routing process, we consider individual distance as the primary parameter in order to adjust and equalize the energy consumption among involved sensors. The residual energy is also considered as a secondary factor. In this way, all the intermediate nodes will consume their energy at similar rate, which maximizes network lifetime. Simulation results show that the DEAR algorithm can reduce and balance the energy consumption for all sensor nodes so network lifetime is greatly prolonged compared to other routing algorithms. [ABSTRACT FROM AUTHOR]

The traditional Low Energy Adaptive Cluster Hierarchy (LEACH) routing protocol is a clustering-based protocol. The uneven selection of cluster heads results in premature death of cluster heads and premature blind nodes inside the clusters, thus reducing the overall lifetime of the network. With a full consideration of information on energy and distance distribution of neighboring nodes inside the clusters, this paper proposes a new routing algorithm based on differential evolution (DE) to improve the LEACH routing protocol. To meet the requirements of monitoring applications in outdoor environments such as the meteorological, hydrological and wetland ecological environments, the proposed algorithm uses the simple and fast search features of DE to optimize the multi-objective selection of cluster heads and prevent blind nodes for improved energy efficiency and system stability. Simulation results show that the proposed new LEACH routing algorithm has better performance, effectively extends the working lifetime of the system, and improves the quality of the wireless sensor networks. [ABSTRACT FROM AUTHOR]

Many sensor network applications are tightly coupled with the geometric environment where the sensor nodes are deployed. The topological skeleton extraction for the topology has shown great impact on the performance of such services as location, routing, and path planning in wireless sensor networks. Nonetheless, current studies focus on using skeleton extraction for various applications in wireless sensor networks. How to achieve a better skeleton extraction has not been thoroughly investigated. There are studies on skeleton extraction from the computer vision community; their centralized algorithms for continuous space, however, are not immediately applicable for the discrete and distributed wireless sensor networks. In this paper, we present a novel Connectivity-bAsed Skeleton Extraction (CASE) algorithm to compute skeleton graph that is robust to noise, and accurate in preservation of the original topology. In addition, CASE is distributed as no centralized operation is required, and is scalable as both its time complexity and its message complexity are linearly proportional to the network size. The skeleton graph is extracted by partitioning the boundary of the sensor network to identify the skeleton points, then generating the skeleton arcs, connecting these arcs, and finally refining the coarse skeleton graph. We believe that CASE has broad applications and present a skeleton-assisted segmentation algorithm as an example. Our evaluation shows that CASE is able to extract a well-connected skeleton graph in the presence of significant noise and shape variations, and outperforms the state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

In this paper, three clock-synchronization algorithms for wireless sensor networks (WSNs) under unknown delay are derived. They include the maximum-likelihood estimator (MLE), a generalization of the estimator of Noh et al., and a novel low-complexity estimator. Their corresponding performance bounds are derived and compared, and complexities are also analyzed. It is found that the MLE achieves the best performance with the price of high complexity. For the generalized version of the estimator of Noh et al., although it has low complexity, its performance is degraded with respect to the MLE. On the other hand, the newly proposed estimator achieves the same performance as the MLE, and the complexity is at the same level as that of the generalized version of the estimator of Noh et al. [ABSTRACT FROM AUTHOR]

The energy consumption is a key design criterion for the routing protocols in wireless sensor networks. Some of the conventional single path routing schemes may not be optimal to maximize the network lifetime and connectivity. In this paper, we propose a distributed, scalable and localized multipath search protocol to discover multiple node-disjoint paths between the sink and source nodes. We also propose a load balancing algorithm to distribute the traffic over the multiple paths discovered. We compare our proposed scheme with the directed diffusion, directed transmission, N-to-1 multipath routing, and the energy-aware routing protocols. Simulation results show that our proposed scheme has a higher node energy efficiency, lower average delay and control overhead than those protocols. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]