Dynamic Wireless Sensor Networks Research Articles

Fuzzy Based Unequal Clustering and Context-Aware Routing Based on Glow-Worm Swarm Optimization in Wireless Sensor Networks: Forest Fire Detection

Wireless sensor networks (WSNs) displays an encouraging outcome for forest fire (FF) identification. The most serious WSN investigation tasks is forest fire’s early prediction, which is used to save the ecosystem. For conveying the detected information to the BS (base station), the SNs (sensor nodes) are placed in remote forest region in WSN based FF discovery scheme that is manageable by the forest sector. Various studies have been finished in this field but they studied only few amount of constraints and the encountered situations influence has not discussed after the system positioning. In this work, fuzzy based unequal clustering and context aware routing (CAR) procedure with GSO (glow-worm swarm optimization) is developed in RWP (random way point) based dynamic WSNs. Based on FL (fuzzy logic) the unequal clustering is formed and the optimal CH (cluster head) is nominated to convey the information from CM (cluster member) to BS to increase the system lifespan and to decrease the energy consumption. Further, the routing process is performed by the CAR procedure with GSO process to enhance the efficiency of network. Lastly, a case study of FF identification is offered as a justification of the suggested method. The suggested work is executed in MATLAB. The simulation outcomes proved that the proposed approach provide the better outcomes in average energy consumption (0.025 J), PDR (99.4%), jitter (4.01 s), delay (0.0304 s), BER (15%), throughput (144.6Kbps), network lifetime (38.7 s) as related to other current protocols.

An adaptive multilevel location based key management system for dynamic wireless sensor networks

ABSTRACT A Key management system plays an important role in the process of wireless communication between the nodes of a Wireless Sensor Network (WSN). Unlike the wired networks, WSNs are more vulnerable to attacks from the malicious nodes. To overcome the shortcomings of the existing key management systems, this paper proposes an adaptive multilevel location-based key management system (AML-KBS), in which the keys are generated dynamically and shared among the nodes of the wireless networks. Since the proposed approach follows a location-based system for key management, the attackers can be differentiated based upon their location. Also, the proposed system has proven its withstanding against node capture attacks. Comparing with the existing approaches, the memory requirement of the proposed system has shown better improvement. Moreover, the proposed methodology provides better security mechanism than the existing key management systems.

DMTC: Optimize Energy Consumption in Dynamic Wireless Sensor Network Based on Fog Computing and Fuzzy Multiple Attribute Decision‐Making

Advances in wireless technologies and small computing devices, wireless sensor networks can be superior technology in many applications. Energy supply constraints are one of the most critical measures because they limit the operation of the sensor network; therefore, the optimal use of node energy has always been one of the biggest challenges in wireless sensor networks. Moreover, due to the limited lifespan of nodes in WSN and energy management, increasing network life is one of the most critical challenges in WSN. In this investigation, two computational distributions are presented for a dynamic wireless sensor network; in this fog‐based system, computing load was distributed using the optimistic and blind method between fog networks. The presented method with the main four steps is called Distribution‐Map‐Transfer‐Combination (DMTC) method. Also, Fuzzy Multiple Attribute Decision‐Making (Fuzzy MADM) is used for clustering and routing network based on the presented distribution methods. Results show that the optimistic method outperformed the blind one and reduced energy consumption, especially in extensive networks; however, in small WSNs, the blind scheme resulted in an energy efficiency network. Furthermore, network growth leads optimistic WSN to save higher energy in comparison with blinded ones. Based on the results of complexity analysis, the presented optimal and blind methods are improved by 28% and 48%, respectively.

Priority-Mobility Aware Clustering Routing Algorithm for Lifetime Improvement of Dynamic Wireless Sensor Network

Wireless sensor network with mobility is rapidly evolving and increasing in the recent decade. The cluster and hierarchical routing strategy demonstrates major changes in the lifespan of the network and the scalability. The latency, average energy consumption, packet distribution ratio is highly impacted due to a lack of coordination between cluster head and extreme mobile network nodes. Overall efficiency of highly mobile wireless sensor network is reduced by current techniques such as mobility-conscious media access control, sleep/wakeup scheduling and transmission of real-time services in wireless sensor network. This paper proposes a novel Priority-Mobility Aware Clustering Routing algorithm (p-MACRON) for high delivery of packets by assigning fair weightage to each and every packet of node. To automatically decide the scheduling policy, reinforcement learning approach is integrated. The mixed approach of priority and self-learning results into better utilization of energy. The experimental result shows comparisons of slotted sense multiple access protocol, AODV, MEMAC and P-MACRON, in which proposed algorithm delivered better results in terms of interval, packet size and simulation time.

A decentralized algorithm to combine topology control with network coding

Network coding and topology control techniques have been widely used to increase throughput and improve the lifetime of Wireless Sensor Networks (WSNs). This paper considers the simultaneous utilization of these techniques in a WSN and proposes convex non-linear programming. Since solving the problem for a large-scale and dynamic WSN is impractical and almost impossible, Lagrangian, sub-gradient and the decomposition methods are employed to provide a decentralized algorithm. In the proposed algorithm, a node makes the computations by acquiring local knowledge and information from its neighbors. This paper provides a mathematical language to build an analytic foundation for the design of a modularized and decentralized algorithm that provides transmission ranges and routes for a WSN. The simulation results show that increasing the number of sources, sinks, sensors, and traffic load leads to improving the lifetime which is acquired by the proposed algorithm.

HDDS: Hierarchical Data Dissemination Strategy for energy optimization in dynamic wireless sensor network under harsh environments

The primary issue in Wireless Sensor Network (WSN) based monitoring applications is the preservation of the sensing coverage under the harsh physical environment. WSN forms the monitoring infrastructure, where a large set of energy-constrained sensor nodes are deployed to collect the physical parameters of the environment. The sensor nodes communicate their data to the nearby edge server (ES) where data is processed locally before it is forwarded to the distant cloud platform. Most of WSN’s existing routing algorithms aim to develop an energy-efficient data transmission route without recognizing the effect of harsh external environment, rendering it non-adaptive to environmental changes. In this paper, we have focused to develop an energy-efficient hierarchical data dissemination protocol for the sensor to ES communication. Along with energy optimization, the proposed protocol aims to preserve the network coverage and supports the dynamic changes in network topology like node failure, node addition, etc., due to harsh environmental interface. As the sensor nodes are required to operate autonomously, the proposed protocols are designed by considering only the local information of a sensor node. Simulation and experimental results show the efficiency of the proposed protocol over many state-of-the-art protocols with respect to several parameters such as energy consumption, lifetime of the network, coverage ratio, packet delivery ratio, latency, etc.

An improved fast transform algorithm based on adaptive hybrid channel allocation in TSCH networks

Time Slotted Channel Hopping (TSCH) is one of the five access behavior technologies defined in the IEEE 802.15.4e standard. Research shows that the wireless sensor network with single dynamic and static channel allocation in TSCH mode has higher performance. The clogging rate results in unnecessary energy waste. Therefore, this paper proposes an adaptive hybrid channel allocation strategy (AHCA) to measure the link quality change of wireless sensor networks in TSCH mode. The strategy estimates the part of the channel quality and determines whether the node wants to transmit on this channel and the optimal channel for node information transmission. According to the change of the amount of information transmitted, the hybrid channel allocation scheme of the dynamic and static channel ratio is adaptively adjusted to reduce the energy consumption of the information transmission process. This article performs experimental simulation on Contiki-NG. The experimental results show that the proposed scheme has shorter transmission time and lower congestion rate than the single dynamic static channel allocation wireless sensor network. The more reasonable and effective measurement, analysis and use of channel resources can fundamentally increase the amount of information transfer in wireless sensor networks per unit time, and thus extend the lifetime of wireless sensor networks.

A Blockchain-Based Secure Key Management Scheme With Trustworthiness in DWSNs

Dynamic wireless sensor networks (DWSNs) as an important means of industrial data collection are a key part of industrial Internet of Things (IIoT), where security and reliability are important characteristics of trustworthiness. However, due to dynamics, the security of key management is caused by a nontrusted base station (BS) that is easily targeted. For the distribution key management scheme, the avianized BS also causes additional and heavy overhead on sensors. To tackle these issues, in this article, we propose a blockchain-based secure key management scheme (BC-EKM). First, stake blockchain is constructed based on the hybrid sensor network. In addition, we design a secure cluster formation algorithm and a secure node movement algorithm to implement key management, where stake blockchain as a trust machine replaces the majority functions of the BS. Finally, we conduct the security analysis and ample simulations. The results indicate that that the BC-EKM scheme is effective and efficient, and better suited to improve the trustworthiness of DWSNs in the IIoT.

A type of energy-efficient secure localization algorithm FM based in dynamic sensor networks

Since dynamic wireless sensor networks are widely used in the military field, the location information is the basis of various applications, because each node in the dynamic sensor network is moving continuously, and it is quite possible to be attacked by various forms of information. Aiming at the problem of secure localization in dynamic sensor networks, a new secure localization algorithm—frequency modulation secure localization (FMSL)—for dynamic sensor networks is proposed with the support of FM signal and Monte Carlo method. The algorithm uses FM signals which are widely covered to locate randomly distributed nodes loaded with FM signal receiving module, filters some malicious attack anchors in the network, and uses the improved Monte Carlo algorithm to locate the nodes, so as to improve the positioning accuracy. Meanwhile, according to the moving path and the localization time, energy consumption of the network could be estimated and also give the sleep scheduling strategy for the node to be localized. The simulation results show that the FMSL algorithm can significantly improve the security performance and positioning accuracy of mobile sensor networks compared with the existing security positioning algorithms such as Monte Carlo and convex programming. In the process of motion, the positioning accuracy can reach less than 10%.

Key Management and Cryptography in Wireless Sensor Networks

The use of Wireless Sensor Networks (WSN) in the field of military, battlefield, healthcare applications etc has seen a plethora of growth towards variety of sensory devices. Irrespective of different locations, the sensor nodes has to do its task. Hence, the dynamic wireless sensor networks should ensure better quality of sensor nodes that covers wider network area and additional services in relative to static WSNs systems. By doing so, it requires secure data communication among the sensor nodes in wireless environment. Key Management is the recent security concept enabled to provide secure communication between sender and receiver nodes. In this paper, we have proposed efficient key updates systems between the nodes. In any scenario, the nodes may join or leaves the network environment which facilitates to initiate a secret key between intended sender and intended receiver. A certificate less key secrecy system is designed for secure communication in wireless links. By designing so, we have addressed the issues like node authentication, data confidentiality and data integrity. Experimental analyses have shown the effectiveness of proposed system.

Intelligent Agent-Based Assessment of a Resilient Multi-hop Routing Protocol for Dynamic WSN

Wireless sensor networks (WSN) constitute a current field of interest in which the major concerns are related to mobility, spatial distribution, connectivity and dynamic creation of networks between autonomous nodes for cooperative detection and data transfer in diverse areas (e.g., healthcare, environmental or industrial monitoring). To this end, the present work describes the theoretical and practical development of a communication protocol for WSNs based on Bluetooth. The interaction between mobile nodes is performed with a multi-hop scheme in response to traffic needs without requiring a scatternet formation procedure. The interest of this algorithm—based on the concept of routing vector—is that it was designed to withstand changes in the node distribution for high-mobility scenarios, thus allowing the implementation of a robust data routing in low-resource microcontrolled devices with no operability loss. As the main contribution, we present the hardware and software implementation of the communication protocol in real devices along several case studies. With this aim, a long-term experimentation in a dense scenario has been carried out through an intelligent agent-based approach to formally validate the protocol considering three different performance metrics: packet delivery ratio, feedback overhead and round-trip time.

Fuzzy-based Adaptive Multipath for En-route Filtering in Dynamic Wireless Sensor Network

Wireless sensor network is formed with limited energy resources, easily compromised by an adversary because of hostile environments. Adversary may use compromised nodes to inject false reports and launch DoS attacks, thus, sensor nodes are prone to failure and which makes the network topology configurations highly dynamic in real world applications. A variety of en-route filtering schemes have been proposed to drop and defeat these attacks by using their own cryptographic methods. Some of them ask for a fixed path between a base station and each cluster, so they are not feasible for dynamic network. Additionally, other proposals do not consider various environmental variables in a dynamic environment, so they only choose static paths. In contrast, we consider topology changes, communication costs, the maximum number of key dissemination hops, and the spread of nodes for providing optimum filtering capacity. This paper presents a fuzzy-based adaptive multipath selection method in dynamic environment of a wireless sensor network. Our proposed method can adjust the optimized number of multipaths during key dissemination. Experimental results show that relatively higher filtering capacity with lower energy consumption and suitable nodes for highly dynamic networks.

Implementation of Secure Energy Efficient Network Priority Routing(SEENPR) Protocol with Secure Key Management in WSN

Wireless sensor networks (WSNs) consist of sensor nodes, which act as source and link nodes through which the data forward to sink node. However, the nodes in network have limited computation complexity, transmission capability and restricted battery life. Several routing protocols are available to improve the performance of network but very few concentrates on security issues. The performance of routing and security protocol in WSN affect due to unreliable low power links, insecure communication, threats, and resource limitations which limits the design of an efficient routing and security algorithm in wireless sensor networks. In this paper, we propose a secure energy efficient routing protocol with effective data collection and key management in dynamic WSN. The routing protocol prolongs network lifetime and minimizes energy consumption. The routing protocol implement with A* algorithm and security improve with EECLDSA (Enhanced Elliptic Curve Logic Discrete Algorithm). The combined Secure Energy Efficient Network Priority Routing (SEENPR) apply for effective data collection and key management in WSNs. SEENPR uses k-means algorithm to improve cluster head (CH) selection using Euclidean distance. The SEENPR implement in testbed to evaluate performance with respect to security and key management.

E‐LiteSense: Self‐adaptive energy‐aware data sensing in WSN environments

SummaryCurrently deployed in a wide variety of applicational scenarios, wireless sensor networks (WSNs) are typically a resource‐constrained infrastructure. Consequently, characteristics such as WSN adaptability, low‐overhead, and low‐energy consumption are particularly relevant in dynamic and autonomous sensing environments where the measuring requirements change and human intervention is not viable. To tackle this issue, this article proposes e‐LiteSense as an adaptive, energy‐aware sensing solution for WSNs, capable of auto‐regulate how data are sensed, adjusting it to each applicational scenario. The proposed adaptive scheme is able to maintain the sensing accuracy of the physical phenomena, while reducing the overall process overhead. In this way, the adaptive algorithm relies on low‐complexity rules to establish the sensing frequency weighting the recent drifts of the physical parameter and the levels of remaining energy in the sensor. Using datasets from WSN operational scenarios, we prove e‐LiteSense effectiveness in self‐regulating data sensing accurately through a low‐overhead process where the WSN energy levels are preserved. This constitutes a step‐forward for implementing self‐adaptive energy‐aware data sensing in dynamic WSN environments.

Multi-requests satisfied based on energy optimization for the service composition in wireless sensor network

Wireless sensor network based on service-oriented architecture has provided important support for Internet of Things in smart city; therefore, multi-requests can be satisfied through service composition. However, as the number and complexity of requests increase, the dynamic and low energy of sensors in wireless sensor network gradually limit the development of the service-oriented architecture in Internet of Things; therefore, optimizing energy under the condition that multi-requests can be satisfied in the dynamic wireless sensor network becomes an important problem. To address this challenge, first, this paper analyzes the mobility of sensors to predict the path stability and manage the information and capabilities on them so that we can find the satisfactory service provider candidates. Then, this article proposes a service mapping pre-process to achieve the work flow reduction in a service layer to save energy in advance and a service mapping process to find the optimal sensors in a network layer that can satisfy the requests. Simulation results show that our strategies can achieve the goal of energy conservation, load balancing, and network lifetime extension under the premise of guaranteeing requests function and non-function attributes and have better performance than traditional ones.

DDoS attack aware environment with secure clustering and routing based on RPL protocol operation

Routeing protocol for low-power and lossy networks (RPL) are widely used in dynamic wireless sensor network. Several types of researches worked on RPL and designed hybrid energy-efficient cluster-parent-based RPL, queue utilisation (QU)-RPL, improved RPL, attack detection RPL etc. to support from vulnerable threats, provide efficient routeing and balance dynamic nodes in the network. Previous research findings dealt with certain limitations and problems. In this study, a new coordinative-balanced clustering algorithm is proposed which is enabled to balance destination-oriented directed acyclic graph (DODAG) that is formed in each cluster. Pruning of nodes from DODAG effectively maintains cluster with minimised complexity. This study also resolves the problem of two common security attacks such as distributed denial of service attack (DDoS) and version number attack. Then, enriched-ant colony optimisation is used for DDoS detection and a secure route is chosen to perform data transmission. At the instance of selecting best parent for forwarding data, the authors use residual energy and scoring factor. Scoring factor of each node denotes the legitimacy to be selected as the best parent. Finally, results obtained from Network Simulator 3 indicate better performances on the following metrics: packet delivery ratio, end-to-end delay, node death minimisation, packet loss rate and power consumption.

Compressive Sensing-Based Data Aggregation Approaches for Dynamic WSNs

Among various data aggregation approaches proposed for wireless sensor networks (WSNs), the one based on compressive sensing (CS) has the merit of low traffic cost. The key step to design a CS-based data aggregation protocol is to construct a measurement matrix ${\Phi }$ based on the network structure and to assign each node a unique column vector of ${\Phi }$ . Assuming an expanded scenario, where some new nodes join in the network, the data aggregation scheme has to entirely re-generate a new matrix ${\Phi ^{\prime }}$ with a larger size to meet the node number and CS property simultaneously. Apparently, it is energy-consuming to reallocate the weight vectors from the new measurement matrix to all the nodes. Thus, we propose an approach which aims to keep the weight vectors of existing sensors unchanged but assign only optimized measurement vectors to the newly added nodes. In order to solve the relevant non-convex optimization problem, two efficient methods with good data aggregation performance are proposed. Numeric experiments validate the effectiveness of our proposed methods.

IEEMARP- a novel energy efficient multipath routing protocol based on ant Colony optimization (ACO) for dynamic sensor networks

In the past few years, research and development in Wireless Sensor networks (WSNs) have gained momentum due to its numerous applications in agriculture, industrial manufacturing, military surveillance, environmental monitoring, consumer electronics, medical & healthcare, disaster recovery operations etc. Dynamic WSNs offer a robust blend of distributed sensing, computing and communication. Dynamic sensor networks are characterized by large scale deployment, dynamic and unstructured topology, power limitations, less memory and limited computational capabilities. Sensor nodes deployed in real-time environment’s for sensing data have power-limitations which hampers the overall performance of WSNs. So, the only obvious solution is to propose an energy efficient routing protocol to optimize WSN real-time performance. Different specialists have proposed various directing conventions for WSNs dependent on Fuzzy Logic, Genetic Algorithms, Meta-Heuristics, and other improvement strategies. However, every solution suggested till date has its advantages and limitations. In this paper, our primary objective is to utilize Swarm-Intelligence based approach i.e. “Ant Colony Optimization (ACO)”, for routing protocol development. Ant colony optimization (ACO) based approach gives optimal solution in terms of efficient routing path determination, energy efficiency and delivering high performance in terms of packet delivery and throughput. In this paper, we propose a novel energy efficient ACO based multipath routing protocol for WSN i.e. IEEMARP (Improvised Energy Efficient Multipath ACO based Routing Protocol). The proposed protocol works in three phases (Neighbor Discovery via Link Knowledge, Packet Transmission via exponentially weighted moving average method and ACKR packet delivery for assuring end-to-end delivery. To validate the performance of the protocol proposed, extensive simulations were conducted using NS-2.35-allinone simulator on diverse parameters like (PDR), throughput, routing overhead, energy consumption and end-to-end delay. In addition to this, the performance of protocol is compared with traditional routing protocols like Basic ACO, DSDV and DSR and other ACO based WSN protocols like ACEAMR, AntChain, EMCBR, IACR, AntHQSeN, FACOR and ANTALG. Simulation based results, clearly states that as compared to Basic ACO, DSDV and DSR, the performance of WSN network is improvised to around 10% in all performance metrics via IEEMARP routing protocol. And as compared to ACEAMR, AntChain, EMCBR and IACR, IEEMARP performs 20% better in overall functionality and almost 10–12% better as compared to AntHQSeN, FACOR, ANTLAG routing protocols in varied WSN scenarios. It is also observed that IEEMARP protocol is highly efficient in TCP packet transmission from source to destination node.

Simple and Effective Secure Group Communications in Dynamic Wireless Sensor Networks.

Wireless Sensor Network (WSN) is a growing area of research in terms of applications, life enhancement and security. Research interests vary from enhancing network performance and decreasing overhead computation to solving security flaws. Secure Group Communication (SGC) is gaining traction in the world of network security. Proposed solutions in this area focus on generating, sharing and distributing a group key among all group members in a timely manner to secure their communication and reduce the computation overhead. This method of security is called SGC-Shared Key. In this paper, we introduce a simple and effective way to secure the network through Hashed IDs (SGC-HIDs). In our proposed method, we distribute a shared key among the group of nodes in the network. Each node would have the ability to compute the group key each time it needs to. We provide a security analysis for our method as well as a performance evaluation. Moreover, to the best of our knowledge, we present for the first time a definition of joining or leaving attack. Furthermore, we describe several types of such an attack as well as the potential security impacts that occur when a network is being attacked.

Fuzzy Logic-Based Geographic Routing Protocol for Dynamic Wireless Sensor Networks.

The geographic routing protocol only requires the location information of local nodes for routing decisions, and is considered very efficient in multi-hop wireless sensor networks. However, in dynamic wireless sensor networks, it increases the routing overhead while obtaining the location information of destination nodes by using a location server algorithm. In addition, the routing void problem and location inaccuracy problem also occur in geographic routing. To solve these problems, a novel fuzzy logic-based geographic routing protocol (FLGR) is proposed. The selection criteria and parameters for the assessment of the next forwarding node are also proposed. In FLGR protocol, the next forward node can be selected based on the fuzzy location region of the destination node. Finally, the feasibility of the FLGR forwarding mode is verified and the performance of FLGR protocol is analyzed via simulation. Simulation results show that the proposed FLGR forwarding mode can effectively avoid the routing void problem. Compared with existing protocols, the FLGR protocol has lower routing overhead, and a higher packet delivery rate in a sparse network.