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The Constrained Application Protocol (CoAP) is one of the most emerging messaging protocols that have successfully fulfilled the need of the lightweight features required to handle communication between constrained devices in IoT environment. However, these devices are generating a huge amount of messages and notifications which cause the network congestion. Then, the challenge addressed in this paper; consists of designing a suitable congestion control mechanism for CoAP that ensures a safe network operation while keeping the use of network resources efficiently. To do so, this paper presents an improved congestion control algorithm for the estimation of a Retransmission Time Out (RTO) value to use in each transaction based on the packet loss ratio and the Round-Trip Time RTT of the previous transmission. A comprehensive analysis and evaluation of simulated results show that the proposed mechanism can appropriately achieve higher performance compared to the basic CoAP congestion control, TCP and TCP/ Linux. [ABSTRACT FROM AUTHOR]

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]

Large-scale wireless sensor networks (LSWSNs) are currently one of the most influential technologies and have been widely used in industry, medical, and environmental monitoring fields. The LSWSNs are composed of many tiny sensor nodes. These nodes are arbitrarily distributed in a certain area for data collection, and they have limited energy consumption, storage capabilities, and communication capabilities. Due to limited sensor resources, traditional network protocols cannot be directly applied to LSWSNs. Therefore, the issue of maximizing the LSWSNs' lifetime by working with duty cycle design algorithm has been extensively studied in this paper. Encouraged by annealing algorithm, this work provides a new elite adaptive simulated annealing (EASA) algorithm to prolong LSWSNs' lifetime. We then present a sensor duty cycle models, which can make sure the full coverage of the monitoring targets and prolong the network lifetime as much as possible. Simulation results indicate that the network lifetime of EASA algorithm is 21.95% longer than that of genetic algorithm (GA) and 28.33% longer than that of particle swarm algorithm (PSO). [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]

A Wireless Sensor Network (WSN) is an aggregation of sensor nodes which are remotely deployed in large numbers and operate the environmental condition and have limited energy resource. In most of the hierarchical routing protocols, the cluster head (CH) selection is on the basis of random probability equation. There is a scope to reduce the energy dissipation by improving CH selection procedure. This research paper proposed a multi hop hierarchical routing protocol called Energy Efficient - Adaptive Periodic Threshold Sensitive Protocol (EE-APTSP), and makes use of evolutionary algorithm for improving cluster head selection of routing protocol in the sensor networks. The concept of relay node is introduced, which acts as an intermediary between Cluster Head (CH) and Base Station (BS) to ease the communication between the CH and BS. The simulation results obtained supports that our proposed algorithm is efficient in terms of network lifetime. APTSP based theory that can be used to create faster, smaller, and more energetic and efficient sensitive threshold. Network Simulator (NS2) is used to implement and test the proposed system. The proposed periodic sensitive protocol provides more energy with secured transmission, further it reduces routing overhead, improves packet delivery ratio and throughput. [ABSTRACT FROM AUTHOR]

In this paper, the time triggered hybrid scheduler (TTH) is implemented in the distributed real time embedded systems along with the operation of dynamic frequency scaling (DFS) since it overcomes the problem of time triggered cooperative scheduler (TTC) for distributed systems and also the decreases the power consumption. This scheduler is implemented along with the token ring network protocol for the communication scheduling. In hard real time systems, ideally, no deadline may ever be missed and hence the co-operative and pre-emptive are combined in this paper to achieve optimum efficiency. DFS is used to provide robustness to the network and also reduces the power utilization. This TTH scheduler is more advantageous than TTC scheduler in distributed system, since long task problem can be overcome by means of this algorithm. The model is simulated using the TORSCHE toolbox of the MATLAB. Some of the applications of this scheduling are data acquisition and sampling in wireless sensor networks, control system engineering, patient monitoring using wireless sensor networking and so on. [ABSTRACT FROM AUTHOR]

This paper presents a radial cluster heads selection mechanism for homogenous wireless sensor networks. It aims to ensure a good load balancing and enhance the network lifetime. A performance comparison between LEACH, Mod_LEACH, Multi-Chain-PEGASIS, M-GEAR protocols and our proposal in term of network lifetime, stability/instability periods and the evolution of the number of cluster heads is carried out in this work. Obtained results show that developing an efficient cluster heads selection algorithm enhances considerably the network lifetime and the QoS in the network. Simulations results under NS3 simulator showed that our proposal can extend the network life more than 300% compared to the famous LEACH protocol and ensure a network lifetime of about 5000 rounds while it does not exceed 2500 rounds using M-GEAR. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSN) with the Internet of Things (IoT) play a vital key concept while performing the information transmission process. The WSN with IoT has been effectively utilized in different research contents such as network protocol selection, topology control, node deployment, location technology and network security, etc. Among that, node location is one of the crucial problems that need to be resolved to improve communication. The node location is directly influencing the network performance, lifetime and data sense. Therefore, this paper introduces the Bird Swarm Optimized Quasi-Affine Evolutionary Algorithm (BSOQAEA) to fix the node location problem in sensor networks. The proposed algorithm analyzes the node location, and incorporates the dynamic shrinking space process is to save time. The introduced evolutionary algorithm optimizes the node centroid location performed according to the received signal strength indications (RSSI). The created efficiency in the system is determined using high node location accuracy, minimum distance error, and location error. [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 byzantine model is widely used to depict a variety of node faults in networks. Previous studies on byzantine-resilient protocols in wireless networks assume reliable communications and do not consider the jamming behavior of byzantine nodes. Such jamming, however, is a very critical and realistic behavior to be considered in modern wireless networks. In this paper, for the first time, we integrate the jamming behavior of byzantine nodes into the network setting. We show that, in this much more comprehensive and harsh model, efficient distributed communication protocols can be still devised with elaborate protocol design. In particular, we developed an algorithm that can accomplish the basic multiple-message dissemination task close to the optimal solution in terms of running time. Empirical results validate the byzantine-resilience and efficiency of our algorithm. [ABSTRACT FROM AUTHOR]

Quality of Service (QoS) assurance in Wireless Sensor Network (WSN) is a tough task, and it is more exciting due to the scarcity of resources. The requirement of different WSN applications running over has different constraints. In QoS, routing protocol the network has to balance the traffic. This paper presents a novel heuristic routing algorithm known as QoS assured Multi-objective Hybrid Routing Algorithm (Q-MOHRA) for Heterogeneous WSN. Q-MOHRA takes into account the link (energy, hop count, link quality indicator etc.) and path (jitter) metrics for optimal path selection. The performance of Q-MOHRA is evaluated through intensive simulation and equated with Simple Hybrid Routing Protocol (SHRP) and Dynamic Multi-objective Routing Algorithm (DyMORA). The metrics such as average energy consumption, residual energy, packet delivery ratio, jitter, and normalized routing load are used for comparison. The performance of Q-MOHRA has been observed to outclass SHRP and DyMORA. It improves the packet delivery ratio by 24.31% as compared to SHRP and 11.86% as compared to DyMORA. Q-MOHRA outperforms DyMORA in terms of average energy consumption by a factor of 8.27%. [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]

Cognitive radio sensor networks (CRSNs) are event-based systems such that sensor nodes detect events and the event readings of the sensors are collaboratively conveyed in a multi-hop manner through vacant channels from event regions to a sink. Hence, the event-to-sink communication and the dynamic radio environment require a coordination scheme in CRSNs. In this paper, we propose a spectrum-aware clustering protocol to address the event-to-sink communication coordination issue in mobile CRSNs. Our clustering scheme consists of two phases. The first phase is the determination of nodes eligible for clustering, and the second phase is to form clusters among those nodes according to vacant spectrum bands. Clusters are temporary and they are not preserved after the end of events. Furthermore, we find average re-clustering probability, expected cluster coverage area, and find maximum event generation frequency for energy-efficient operation of our protocol. We study performance of our protocol in terms of control and data packet exchange, time steps required for clustering, connectivity of clusters, energy consumed for clustering, and re-clustering ratio due to the mobility. Performance comparison simulations show that our algorithm has better performance in terms of connectivity and energy consumption. [ABSTRACT FROM PUBLISHER]

In this paper, we propose an adaptive sensing period adjustment scheme (ASPA) which adaptively adjusts sensing periods by considering the dynamics of the channel conditions in cognitive radio sensor networks (CRSNs). The ASPA with a linearly increasing and exponentially decreasing (LIED) algorithm is a simple but robust scheme because secondary users (SUs) can adaptively adjust their sensing periods, even when sensing errors or collisions with control messages exist. A performance model for analyzing the efficiency of the ASPA is also proposed, and it is compared with simulation results. It is shown in our results that the ASPA outperforms the existing protocol in terms of the average sensing overhead and throughput as well as the average energy consumption. [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]

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]

The CoRE working group at the IETF has proposed a Resource Directory (RD) solution to facilitate the discovery of the resources provided by constrained wireless sensor and actuator networks. For such a mechanism to be effectively deployable, nodes must first discover the existence of an RD in the network before being able to exploit its functionalities. This paper presents Proactive RD Discovery (PRD); a scalable, reliable, and effective mechanism to discover an RD. To achieve such qualities, the proposed mechanism deploys adaptive Trickle timers. PRD is implemented in Contiki OS and evaluated using emulated sensor/actuator nodes in the Cooja simulator. Simulation results show important performance enhancements in terms of energy consumption, generated traffic, RD discovery time, and reliability when compared with the default discovery mechanism bundled with the RD. [ABSTRACT FROM AUTHOR]

Contiki's Cooja is a very popular wireless sensor network (WSN) simulator, but it lacks support for modelling sensing coverage, focusing instead on network connectivity and protocol performance. However, in practice, it is the ability of a sensor network to provide a satisfactory level of coverage that defines its ultimate utility for end-users. We introduce WSN-Maintain, a Cooja-based tool for coverage and network lifetime evaluation in an in-building WSN. To extend the network lifetime, but still maintain the required quality of coverage, the tool finds coverage redundant nodes, puts them to sleep and automatically turns them on when active nodes fail and coverage quality decreases. WSN-Maintain together with Cooja allow us to evaluate different approaches to maintain coverage. As use cases to the tool, we implement two redundant node algorithms: greedy-maintain, a centralised algorithm, and local-maintain, a localised algorithm to configure the initial network and to turn on redundant nodes. Using data from five real deployments, we show that our tool with simple redundant node algorithms and reading correlation can improve energy efficiency by putting more nodes to sleep. [ABSTRACT FROM AUTHOR]

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]

The low-rate denial of service (LDoS) attack mainly exploits security vulnerabilities of adaptive mechanisms in network protocols and application services. The high-rate attack pulses within a short time interval are sent periodically, which will result in the degradation of service quality. The attack traffic is similar to normal traffic from legitimate users in the network, consequently, it is easy to escape the traditional detection methods because of its intermittence. Research works have demonstrated that there are fractal characteristics (self-similarity) of the network traffic over the large scale of time. Although the fractal characteristics of the network traffic will be changed under the LDoS attack, the variations of the fractal characteristics in some network states are not apparent in real-time detection. Based on the fractal characteristics, the fractal residual of the network traffic is analyzed through the Hurst parameters calculating process by R/S algorithm in this article. It can be found that the fractal residual of the network traffic can better reflect the different states of the LDoS attack. Combining the idea behind the sliding window, a novel fractal residual based real-time detection (FR-RED) method of the LDoS attack is proposed. The effectiveness of the method in this article is verified by performing some experiments on two platforms, the NS2 and test-bed. The results manifest the beginning and end of the LDoS attack can be estimated in real-time with high detection accuracy. [ABSTRACT FROM AUTHOR]