Lens-Oppositional Wild Geese Optimization Based Clustering Scheme for Wireless Sensor Networks Assists Real Time Disaster Management

Recently,wireless sensor networks(WSNs)find their applicability in several real-time applications such as disaster management,military,surveillance,healthcare,etc.The utilization of WSNs in the disaster monitoring process has gained significant attention among research communities and governments.Real-time monitoring of disaster areas using WSN is a challenging process due to the energy-limited sensor nodes.Therefore,the clustering process can be utilized to improve the energy utilization of the nodes and thereby improve the overall functioning of the network.In this aspect,this study proposes a novel Lens-Oppositional Wild Goose Optimization based Energy Aware Clustering(LOWGO-EAC)scheme for WSN-assisted real-time disaster management.The major intention of the LOWGO-EAC scheme is to perform effective data collection and transmission processes in disaster regions.To achieve this,the LOWGOEAC technique derives a novel LOWGO algorithm by the integration of the lens oppositional-based learning(LOBL)concept with the traditional WGO algorithm to improve the convergence rate.In addition,the LOWGO-EAC technique derives a fitness function involving three input parameters like residual energy(RE),distance to the base station(BS)(DBS),and node degree(ND).The proposed LOWGO-EAC technique can accomplish improved energy efficiency and lifetime of WSNs in real-time disaster management scenarios.The experimental validation of the LOWGO-EAC model is carried out and the comparative study reported the enhanced performance of the LOWGO-EAC model over the recent approaches.

Modeling of Sensor Enabled IrrigationManagement for Intelligent Agriculture Using Hybrid Deep Belief Network

Artificial intelligence(AI)technologies and sensors have recently received significant interest in intellectual agriculture.Accelerating the application of AI technologies and agriculture sensors in intellectual agriculture is urgently required for the growth of modern agriculture and will help promote smart agriculture.Automatic irrigation scheduling systems were highly required in the agricultural field due to their capability to manage and save water deficit irrigation techniques.Automatic learning systems devise an alternative to conventional irrigation management through the automatic elaboration of predictions related to the learning of an agronomist.With this motivation,this study develops a modified black widow optimization with a deep belief network-based smart irrigation system(MBWODBN-SIS)for intelligent agriculture.The MBWODBN-SIS algorithm primarily enables the Internet of Things(IoT)based sensors to collect data forwarded to the cloud server for examination purposes.Besides,the MBWODBN-SIS technique applies the deep belief network(DBN)model for different types of irrigation classification:average,high needed,highly not needed,and not needed.The MBWO algorithm is used for the hyperparameter tuning process.A wideranging experiment was conducted,and the comparison study stated the enhanced outcomes of the MBWODBN-SIS approach to other DL models with maximum accuracy of 95.73%.

Sensor management of LEO constellation based on covariance control

This paper studies the multi-sensor management problem for low earth orbit(LEO) infrared warning constellation used to track a midcourse missile. A covariance control approach, which selects sensor combinations or subset based on the difference between the desired covariance matrix and the actual covariance of each target, is used for sensor management, including some matrix metrics to measure the differentia between two covariance matrices. Besides, to meet the requirements of the space based warning system, the original covariance control approach is improved. Simulation results demonstrate that the covariance control approach is able to provide a better tracking performance by providing a well-designed desired covariance and balance tracking performance goals with system demands.

A Parking Management System Based on Wireless Sensor Network

This paper introduces a parking management system based on a wireless sensor network developed by our group. The system consists of a large amount of parking space monitoring nodes, a few parking guiding nodes, a sink node and a management station. All the nodes exchange information with each other through wireless communication. The prototype of the parking management system has been implemented and the preliminary test results show that the performance of the system can satisfy the requirements of the application.

Dynamic Cluster Key Management Scheme on Wireless Sensor Networks

Wireless sensor networks are open architectures, so any potential threat can easily intercept, wiretap and counterfeit the information. Therefore, the safety of WSN is very important. Since any single key system cannot guarantee the security of the wireless sensor network for communications, this paper introduces a hierarchical key management scheme based on the different abilities of different sensor nodes in the clustered wireless sensor network. In this scheme, the nodes are distributed into several clusters, and a cluster head must be elected for each cluster. Private communication between cluster heads is realized through the encryption system based on the identity of each head while private communication between cluster nodes in a same cluster head is achieved through the random key preliminary distribution system. Considering the characteristics of WSN, we adopt dynamic means called dynamic cluster key management scheme to deal with master key, so master key will be updated according to the changed dynamic network topology. For cluster head node plays a pivotal role in this scheme, a trust manage-ment system should be introduced into the election of the cluster head which will exclude the malicious node from outside the cluster, thus improve the whole network security.

Sensor management based on fisher information gain

Multi-sensor system is becoming increasingly important in a variety of military and civilian applications. In general, single sensor system can only provide partial information about environment while multi-sensor system provides a synergistic effect, which improves the quality and availability of information. Data fusion techniques can effectively combine this environmental information from similar and/or dissimilar sensors. Sensor management, aiming at improving data fusion performance by controlling sensor behavior, plays an important role in a data fusion process. This paper presents a method using fisher information gain based sensor effectiveness metric for sensor assignment in multi-sensor and multi-target tracking applications. The fisher information gain is computed for every sensor-target pairing on each scan. The advantage for this metric over other ones is that the fisher information gain for the target obtained by multi-sensors is equal to the sum of ones obtained by the individual sensor, so standard transportation problem formulation can be used to solve this problem without importing the concept of pseudo sensor. The simulation results show the effectiveness of the method.

Review of Key Management Mechanisms in Wireless Sensor Networks

Recent advancements in wireless communication and microchip techniques have accelerated the development of wireless sensor networks (WSN). Key management in WSN is a critical and challenging problem because of the inner characteristics of sensor networks: deployed in hostile environments, limited resource and ad hoc nature. This paper investigates the constraints and special requirements of key management in sensor network environment, and some basic evaluation metrics are introduced. The key pre-distribution scheme is thought as the most suitable solution for key management problem in wireless sensor networks. It can be classified into four classes: pure probabilistic key pre-distribution, polynomial-based, Blom's matrix-based, and deterministic key pre-distribution schemes. In each class of methods, the related research papers are discussed based on the basic evaluation metrics. Finally, the possible research directions in key management are discussed.

Internet of Things Enabled Energy Aware Metaheuristic Clustering for Real Time Disaster Management

Wireless Sensor Networks(WSNs)are a major element of Internet of Things(IoT)networks which offer seamless sensing and wireless connectivity.Disaster management in smart cities can be considered as a safety critical application.Therefore,it becomes essential in ensuring network accessibility by improving the lifetime of IoT assisted WSN.Clustering and multihop routing are considered beneficial solutions to accomplish energy efficiency in IoT networks.This article designs an IoT enabled energy aware metaheuristic clustering with routing protocol for real time disaster management(EAMCR-RTDM).The proposed EAMCR-RTDM technique mainly intends to manage the energy utilization of nodes with the consideration of the features of the disaster region.To achieve this,EAMCR-RTDM technique primarily designs a yellow saddle goatfish based clustering(YSGF-C)technique to elect cluster heads(CHs)and organize clusters.In addition,enhanced cockroach swarm optimization(ECSO)based multihop routing(ECSO-MHR)approach was derived for optimal route selection.The YSGF-C and ECSO-MHR techniques compute fitness functions using different input variables for achieving improved energy efficiency and network lifetime.The design of YSGF-C and ECSO-MHR techniques for disaster management in IoT networks shows the novelty of the work.For examining the improved outcomes of the EAMCR-RTDM system,a wide range of simulations were performed and the extensive results are assessed in terms of different measures.The comparative outcomes highlighted the enhanced outcomes of the EAMCRRTDM algorithm over the existing approaches.

An Efficient Key Management Protocol for Wireless Sensor Networks

Key management is a fundamental security service in wireless sensor networks. The communication security problems for these networks are exacerbated by the limited power and energy of the sensor devices. In this paper, we describe the design and implementation of an efficient key management scheme based on low energy adaptive clustering hierarchy（LEACH） for wireless sensor networks. The design of the protocol is motivated by the observation that many sensor nodes in the network play different roles. The paper presents different keys are set to the sensors for meeting different transmitting messages and variable security requirements. Simulation results show that our key management protocol based-on LEACH can achieve better performance. The energy consumption overhead introduced is remarkably low compared with the original Kerberos schemes.

Trust management-based and energy efficient hierarchical routing protocol in wireless sensor networks

The single planar routing protocol has a slow convergence rate in the large-scale Wireless Sensor Network(WSN).Although the hierarchical routing protocol can effectively cope with large-scale application scenarios,how to elect a secure cluster head and balance the network load becomes an enormous challenge.In this paper,a Trust Management-based and Low Energy Adaptive Clustering Hierarchy protocol(LEACH-TM)is proposed.In LEACH-TM,by using the number of dynamic decision cluster head nodes,residual energy and density of neighbor nodes,the size of the cluster can be better constrained to improve energy efficiency,and avoid excessive energy consumption of a node.Simultaneously,the trust management scheme is introduced into LEACH-TM to defend against internal attacks.The simulation results show that,compared with LEACH-SWDN protocol and LEACH protocol,LEACH-TM outperforms in prolonging the network lifetime and balancing the energy consumption,and can effectively mitigate the influence of malicious nodes on cluster head selection,which can greatiy guarantee the security of the overall network.

Sensors Dynamic Energy Management in WSN

A wireless sensor node is typically battery operated and energy constrained. Therefore, it is apparent that optimal energy management is one of the most important challenges in WSN development. However, energy management requires in-depth knowledge and detailed insight concerning specific scenarios. After Carrying out a large number of experiments in precision agriculture, we find that it is the sensors that have never been concerned consuming the most energy of the node. In order to conserve energy and prolong the lifetime of WSN, we design and carry out a dynamic energy management strategy for sensors. The basic idea is to shut down all sensors’ power when not needed and wake them up when necessary. Valuable conclusions are extracted and analyzed.

Study on key management scheme for heterogeneous wireless sensor networks

Heterogeneous wireless sensor network( HWSN) is composed of different functional nodes and is widely applied. With the deployment in hostile environment,the secure problem of HWSN is of great importance; moreover,it becomes complex due to the mutual characteristics of sensor nodes in HWSN. In order to enhance the network security,an asymmetric key pre-distributed management scheme for HWSN is proposed combining with authentication process to further ensure the network security; meanwhile,an effective authentication method for newly added nodes is presented. Simulation result indicates that the proposed scheme can improve the network security while reducing the storage space requirement efficiently.

Key-insulated encryption based group key management for wireless sensor network

The key exposure problem is a practical threat for many security applications. In wireless sensor networks (WSNs), keys could be compromised easily due to its limited hardware protections. A secure group key management scheme is responsible for secure distributing group keys among valid nodes of the group. Based on the key-insulated encryption (KIE), we propose a group key management scheme (KIE-GKMS), which integrates the pair-wise key pre-distribution for WSN. The KIE-GKMS scheme updates group keys dynamically when adding or removing nodes. Moreover, the security analysis proves that the KIE-GKMS scheme not only obtains the semantic security, but also provides the forward and backward security. Finally, the theoretical analysis shows that the KIE-GKMS scheme has constant performance on both communication and storage costs in sensor nodes.

An Authenticated Dynamic Key Management Scheme for Clustered Sensor Networks

Secure sensor networks has received much attention in the last few years.A sensor network always works unattended possibly in a hostile environment such as a battlefield.In such environments,sensor networks are subject to node capture.Constrained energy,memory,and computational capabilities of sensor nodes mandate a clever design of security solutions to minimize overhead while maintaining secure communication over the lifespan of the network.In this paper,an authenticated dynamic key management scheme,ADKM has been proposed.It provides efficient,scalable,and survivable dynamic keying in a clustered sensor network with a large number of sensor nodes.ADKM employs a combinatorial exclusion basis system (EBS) for efficiency and one-way hash chains for authentication.Analysis of security and performance demonstrate that ADKM is efficient in security of sensor networks.

Lightweight Key Management Scheme Using Fuzzy Extractor for Wireless Mobile Sensor Network

The mature design of wireless mobile sensor network makes it to be used in vast verities of applications including from home used to the security surveillance.All such types of applications based on wireless mobile sensor network are generally using real time data,most of them are interested in real time communication directly from cluster head of cluster instead of a base station in cluster network.This would be possible if an external user allows to directly access real time data from the cluster head in cluster wireless mobile sensor network instead of accessing data from base station.But this leads to a serious security breach and degrades the performance of any security protocol available in this domain.Most existing schemes for authentication and cluster key management for external users,exchange a number of messages between cluster head and base station to allow external to access real time data from the base station instead of cluster head.This increase communication cost and delay in such real time access information.To handle this critical issue in cluster wireless mobile sensor network,we propose a lightweight authentication and key management scheme using a fuzzy extractor.In this scheme,any external user can access data directly from the cluster head of any cluster without the involvement of the base station.The proposed scheme only uses the one-way hash functions and bitwise XOR operations,apart from the fuzzy extractor method for the user biometric verification at the login phase.The presented scheme supports scalability for an increasing number of nodes using polynomials.The proposed scheme increases the life-time of the network by decreasing the key pool size.

A Hybrid Key Management Scheme Based on Clustered Wireless Sensor Networks

According to the weakness of session key construction based on node’s own location, we propose a hybrid key management scheme which based on clustered wireless sensor networks. The use of hierarchical thinking, reducing the amount of key storage and computing, while supporting network topology, dynamic key management for which aims to prevent leakage. Through analyzing, it shows that the scheme have certain advantages in key connectivity, security, communication and energy consumption.

An Adaptive Key Management Framework for the Wireless Mesh and Sensor Networks

Wireless sensor networks (WSNs) and wireless mesh networks (WMNs) are popular research subjects. The interconnection of both network types enables next-generation applications and creates new optimization opportunities. Currently, plenty of protocols are available on the security of either wireless sensor networks or wireless mesh networks, an investigation in peer work underpins the fact that neither of these protocols is adapt to the interconnection of these network types. The internal cause relies on the fact that they differ in terms of complexity, scalability and network abstraction level. Therefore, in this article, we propose a unified security framework with three key management protocols, MPKM, MGKM, and TKM which are able to provide basic functionalities on the simplest devices and advanced functionalities on high performance nodes. We perform a detailed performance evaluation on our protocols against some important metrics such as scalability, key connectivity and compromise resilience, and we also compare our solution to the current keying protocols for WSNs and WMNs.

COCM: Class Based Optimized Congestion Management Protocol for Healthcare Wireless Sensor Networks

Wireless Sensor Networks (WSNs) consist of numerous sensor nodes which can be used in many new emerging applications like healthcare. One of the major challenges in healthcare environments is to manage congestion, because in applications, such as medical emergencies or patients remote monitoring, transmitted data is important and critical. So it is essential in the first place to avoid congestion as much as possible and in cases when congestion avoidance is not possible, to control the congestion. In this paper, a class based congestion management protocol has been proposed for healthcare applications. We distinguish between sensitive, non-sensitive and control traffics, and service the input traffics based on their priority and quality of service requirements (QoS). The proposed protocol which is called COCM avoids congestion in the first step using multipath routing. The proposed AQM algorithm uses separate virtual queue's condition on a single physical queue to accept or drop the incoming packets. In cases where input traffic rate increases and congestion cannot be avoided, it mitigates congestion by using an optimized congestion control algorithm. This paper deals with parameters like end to end delay, packet loss, energy consumption, lifetime and fairness which are important in healthcare applications. The performance of COCM was evaluated using the OPNET simulator. Simulation results indicated that COCM achieves its goals.

An Auto-Configuration of 4M Group Management Using Wireless Sensor Networks

The first tier of automotive manufacturers has faced to pressures about move, modify, updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor company and process innovation purpose for productivity. For meets this requirements, it has to require absolutely lead time to re-wiring of physical interface for production equipment, needs for change existing program and test over again. For prepare this constraints, it needs studying an auto-configuration functions that build for both visibility and flexibility based on the 4M (Man, Machine, Material, Method) group management which is supports from WSN (Wireless Sensor Network) of the open embedded device called M2M (Machine to Machine) and major functions of middleware including point manager for real-time device communication, real-time data management, Standard API (Application Program Interface) and application template management. To be application system to RMS (Reconfigurable Manufacturing System) for rapidly response from various orders and model from motor company that is beginning to establishing the mapping of manufacturing resources of 4M using WSN.

A Compact Trust Computation and Management Approach for Defending against Derailed Attacks for Wireless Sensor Networks and Its Applications

One of the most effective measurements of intercommunication and collaboration in wireless sensor networks which leads to provide security is Trust Management. Most popular decision making systems used to collaborate with a stranger are tackled by two different existing trust management systems: one is a policy-based approach which verifies the decision built on logical properties and functionalities;the other approach is reputation-based approach which verifies the decision built on physical properties and functionalities of WSN. Proofless authorization, unavailability, vagueness and more complexity cause decreased detection rate and spoil the efficacy of the WSN in existing approaches. Some of the integrated approaches are utilized to improve the significance of the trust management strategies. In this paper, a Compact Trust Computation and Management (CTCM) approach is proposed to overcome the limitations of the existing approaches, also it provides a strong objective security with the calculability and the available security implications. Finally, the CTCM approach incorporates the optimum trust score for logical and physical investigation of the network resources. The simulation based experiment results show that the CTCM compact trust computation and management approach can provide an efficient defending mechanism against derailing attacks in WSN.