The document discusses fault management in wireless sensor networks. It proposes a failure detection scheme for event-driven wireless sensor networks using the MANNA management architecture. The scheme aims to provide self-configuration, self-diagnosis, and self-healing capabilities to detect failures without incurring high overhead costs. The performance of the management solution is evaluated through simulations of a temperature monitoring application in event-driven wireless sensor networks under different failure scenarios.
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is an open access international journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Building Fault Tolerance Within Wsn-A Topology ModelIJAAS Team
This document presents a study on building fault tolerance within wireless sensor networks (WSNs) using different topology models. It discusses the need for fault tolerance in WSNs due to their susceptibility to various failures. The study analyzes existing tree topology-based WSNs and identifies issues like high packet loss. It then proposes a butterfly topology with multiple inputs and outputs to improve reliability. Simulation results in NS2 show that the butterfly topology provides higher throughput, lower delay, and higher packet delivery ratio compared to the tree topology. The document contributes towards making WSNs more reliable by implementing fault-tolerant topology designs.
A Comparative Review on Reliability and Fault Tolerance Enhancement Protocols...IRJET Journal
This document provides a comparative review of reliability and fault tolerance enhancement protocols in wireless sensor networks. It first discusses key challenges for wireless sensor networks related to node failures in harsh environments. It then summarizes several existing fault detection and recovery techniques. The document compares protocols like E2SRT, GARUDA, RCRT, and ZARB that aim to improve reliability. It highlights issues around achieving fault tolerance and concludes that no single approach can provide a fully reliable solution, requiring a hybrid method using the best features of different protocols.
Advanced Software Engineering course - Guest Lecture
A4WSN- Architecture 4 Wireless Sensor Networks
Here you can find the research paper presenting the concepts described in this lecture: http://goo.gl/XBB4k
This presentation has been developed in the context of the Advanced Software Engineering course at the DISIM Department of the University of L’Aquila (Italy).
http://www.di.univaq.it/malavolta
NOVEL HYBRID INTRUSION DETECTION SYSTEM FOR CLUSTERED WIRELESS SENSOR NETWORKIJNSA Journal
Wireless sensor network (WSN) is regularly deployed in unattended and hostile environments. The WSN is vulnerable to security threats and susceptible to physical capture. Thus, it is necessary to use effective mechanisms to protect the network. It is widely known, that the intrusion detection is one of the most efficient security mechanisms to protect the network against malicious attacks or unauthorized access. In this paper, we propose a hybrid intrusion detection system for clustered WSN. Our intrusion framework uses a combination between the Anomaly Detection based on support vector machine (SVM) and the Misuse Detection. Experiments results show that most of routing attacks can be detected with low false alarm.
This document summarizes key aspects of wireless sensor networks (WSNs) including common threats, operational paradigms, and key distribution techniques. It discusses the main operational paradigms of WSNs: simple collection and transmittal, forwarding, receive and process commands, self-organization, and data aggregation. For each, it outlines vulnerabilities and potential solutions. It also summarizes three common key distribution schemes: using a single network-wide key, asymmetric cryptography, and pairwise keys. For each it discusses properties and drawbacks regarding resilience, scalability, and memory requirements.
Sensors Scheduling in Wireless Sensor Networks: An Assessmentijtsrd
The wireless sensor networks WSN is a combination of a large number of low power, short lived, unreliable sensors. The main challenge of wireless sensor network is to obtain long system lifetime. Many node scheduling algorithms are used to solve this problem. This method can be divided into the following two major categories first is round based node scheduling and second is group based node scheduling. In this paper many node scheduling algorithm like one phase decomposition model, Tree Based distributed wake up scheduling and Clique based node scheduling Algorithm are analyzed. Manju Ghorse | Dr. Avinash Sharma "Sensors Scheduling in Wireless Sensor Networks: An Assessment" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29560.pdfPaper URL: https://www.ijtsrd.com/computer-science/computer-network/29560/sensors-scheduling-in-wireless-sensor-networks-an-assessment/manju-ghorse
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is an open access international journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Building Fault Tolerance Within Wsn-A Topology ModelIJAAS Team
This document presents a study on building fault tolerance within wireless sensor networks (WSNs) using different topology models. It discusses the need for fault tolerance in WSNs due to their susceptibility to various failures. The study analyzes existing tree topology-based WSNs and identifies issues like high packet loss. It then proposes a butterfly topology with multiple inputs and outputs to improve reliability. Simulation results in NS2 show that the butterfly topology provides higher throughput, lower delay, and higher packet delivery ratio compared to the tree topology. The document contributes towards making WSNs more reliable by implementing fault-tolerant topology designs.
A Comparative Review on Reliability and Fault Tolerance Enhancement Protocols...IRJET Journal
This document provides a comparative review of reliability and fault tolerance enhancement protocols in wireless sensor networks. It first discusses key challenges for wireless sensor networks related to node failures in harsh environments. It then summarizes several existing fault detection and recovery techniques. The document compares protocols like E2SRT, GARUDA, RCRT, and ZARB that aim to improve reliability. It highlights issues around achieving fault tolerance and concludes that no single approach can provide a fully reliable solution, requiring a hybrid method using the best features of different protocols.
Advanced Software Engineering course - Guest Lecture
A4WSN- Architecture 4 Wireless Sensor Networks
Here you can find the research paper presenting the concepts described in this lecture: http://goo.gl/XBB4k
This presentation has been developed in the context of the Advanced Software Engineering course at the DISIM Department of the University of L’Aquila (Italy).
http://www.di.univaq.it/malavolta
NOVEL HYBRID INTRUSION DETECTION SYSTEM FOR CLUSTERED WIRELESS SENSOR NETWORKIJNSA Journal
Wireless sensor network (WSN) is regularly deployed in unattended and hostile environments. The WSN is vulnerable to security threats and susceptible to physical capture. Thus, it is necessary to use effective mechanisms to protect the network. It is widely known, that the intrusion detection is one of the most efficient security mechanisms to protect the network against malicious attacks or unauthorized access. In this paper, we propose a hybrid intrusion detection system for clustered WSN. Our intrusion framework uses a combination between the Anomaly Detection based on support vector machine (SVM) and the Misuse Detection. Experiments results show that most of routing attacks can be detected with low false alarm.
This document summarizes key aspects of wireless sensor networks (WSNs) including common threats, operational paradigms, and key distribution techniques. It discusses the main operational paradigms of WSNs: simple collection and transmittal, forwarding, receive and process commands, self-organization, and data aggregation. For each, it outlines vulnerabilities and potential solutions. It also summarizes three common key distribution schemes: using a single network-wide key, asymmetric cryptography, and pairwise keys. For each it discusses properties and drawbacks regarding resilience, scalability, and memory requirements.
Sensors Scheduling in Wireless Sensor Networks: An Assessmentijtsrd
The wireless sensor networks WSN is a combination of a large number of low power, short lived, unreliable sensors. The main challenge of wireless sensor network is to obtain long system lifetime. Many node scheduling algorithms are used to solve this problem. This method can be divided into the following two major categories first is round based node scheduling and second is group based node scheduling. In this paper many node scheduling algorithm like one phase decomposition model, Tree Based distributed wake up scheduling and Clique based node scheduling Algorithm are analyzed. Manju Ghorse | Dr. Avinash Sharma "Sensors Scheduling in Wireless Sensor Networks: An Assessment" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29560.pdfPaper URL: https://www.ijtsrd.com/computer-science/computer-network/29560/sensors-scheduling-in-wireless-sensor-networks-an-assessment/manju-ghorse
Basic Architecture of Wireless Sensor NetworkKarthik
The document discusses software architecture design considerations for wireless sensor networks. It examines four key characteristics of wireless sensor networks that impact software architecture: self-organization, cooperative processing, energy efficiency, and modularity. It then describes common components of service-oriented wireless sensor network architectures, including sensor applications, node applications, network applications, and middleware. Finally, it analyzes two proposed software architectures and how they address the requirements of wireless sensor networks.
An Efficient Approach for Outlier Detection in Wireless Sensor NetworkIOSR Journals
This document discusses an efficient approach for outlier detection in wireless sensor networks. It proposes a fault-tolerant data aggregation (FTDA) scheme that uses locality sensitive hashing (LSH) for outlier detection in a distributed manner. The FTDA scheme reduces communication overhead by eliminating redundant data transmission. The document also applies kernel density estimation to sensor data from Intel labs to estimate density and detect outliers. Experiments show FTDA achieves high precision and recall for outlier detection, demonstrating the effectiveness of the proposed approach. Future work will explore other density estimation methods like wavelet transforms for multi-attribute sensor data.
Improved Development of Energy Efficient Routing Algorithm for Privacy Preser...IRJET Journal
This document proposes an algorithm to improve energy efficiency and privacy preservation for the sink node in wireless sensor networks. The algorithm uses node clustering, where sensor nodes are grouped into clusters with a cluster head node. Data is routed from cluster members to their cluster head, and then from cluster heads to the sink node. The algorithm elects a subset of cluster heads to broadcast data, obscuring the location of the sink node and distributing energy usage across nodes. Simulations analyze how effectively this approach preserves sink node anonymity while limiting energy depletion across varying network conditions.
This document summarizes a wireless sensor network system implemented by the authors. The system uses 4 sensor nodes to sense temperature and a control node interfaced with a base station PC. It implements a modified version of the TOPDISC topology discovery algorithm using DHCP for dynamic addressing. The routing algorithm uses a mixture of spanning tree and N-link state protocols. Future enhancements include implementing fail safes and fully configuring the wireless sensor network system.
Secure and Efficient DiDrip Protocol for Improving Performance of WSNsINFOGAIN PUBLICATION
1. The document proposes a new distributed data discovery and dissemination protocol called DiDrip for wireless sensor networks (WSNs) that aims to improve security and performance over existing protocols.
2. Existing protocols primarily use a centralized approach where a single node distributes data, which is not suitable for multiple owners and users, and they do not focus on security.
3. DiDrip allows for a distributed approach where multiple owners can authorize different users simultaneously to access sensor data with different priorities, while improving security.
Secure and Efficient Hierarchical Data Aggregation in Wireless Sensor NetworksIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Node Deployment in Homogeneous and Heterogeneous Wireless Sensor NetworkIJMTST Journal
Optimal sensor deployment is necessary condition in homogeneous and heterogeneous wireless sensor
network. Effective deployment of sensor nodes is a major point of concern as performance and lifetime of any
WSN. Proposed sensor deployment in WSN explore every sensor node sends its data to the nearest sink node
of the WSN. In addition to that system proposes a hexagonal cell based sensor deployment which leads to
optimal sensor deployment for both homogeneous and heterogeneous sensor deployment. Wireless sensor
networks are receiving significant concentration due to their potential applications ranging from surveillance
to tracking domains. In limited communication range, a WSN is divided into several disconnected sub-graphs
under certain conditions. We deploy sensor nodes at random locations so that it improves performance of the
network.This paper aims to study, discuss and analyze various node deployment strategies and coverage
problems for Homogeneous and Heterogeneous WSN.
Channel Aware Detection of Forwarding Attacks in WSN with Malicious Node Dete...IRJET Journal
This document proposes a cooperative method to detect malicious nodes in wireless sensor networks. It describes an existing Channel-aware Reputation System with adaptive detection threshold (CRS-A) that evaluates sensor nodes' data forwarding behaviors and identifies compromised nodes. The paper also discusses detecting malicious nodes by having each node transmit data, store a copy, and check if the next node forwarded it within a set time. If not, it increases a failure tally for that node. If the tally exceeds a threshold, the node is reported as malicious. The proposed method uses this process cooperatively across nodes to reliably analyze and detect malicious nodes. It aims to accurately detect selective forwarding attacks while limiting false detections of normal packet loss due to unstable wireless channels.
This document summarizes a research paper that proposes a methodology to improve source location privacy preservation in wireless sensor networks. The paper introduces the concept of "interval indistinguishability" to quantify anonymity. It maps the problem of breaching source anonymity to the statistical problem of binary hypothesis testing with nuisance parameters. The paper proposes modeling anonymity, describes the network and adversarial models, and reviews related work before introducing its methodology. The methodology aims to address issues with existing solutions and practically prove the efficiency of improving source location privacy through a modified statistical framework.
A Survey of Fault Tolerance Methods in Wireless Sensor NetworksIRJET Journal
This document summarizes and analyzes various fault tolerance mechanisms for wireless sensor networks. It discusses mobile agent mechanisms, relay node mechanisms, and handover mechanisms. The document analyzes several existing fault tolerance methods, including Bayesian network models, probabilistic combinatorial optimization, dynamic power level adjustment, and integrated fault tolerance frameworks. Overall, the document provides an overview of important fault tolerance issues in wireless sensor networks and different approaches that have been proposed to address faults and improve reliability.
This document discusses wireless sensor networks and middleware approaches for them. It describes wireless sensor networks as consisting of distributed autonomous sensor nodes that monitor physical environments cooperatively. It outlines common sensor node components and network architectures. It then defines middleware as a software layer that manages complexity and heterogeneity. Key middleware design principles for wireless sensor networks include supporting limited resources, scalability, and data aggregation. The document outlines several middleware approaches, including those based on global behavior, local behavior, virtual machines, databases, and modular programming.
Wireless sensor networks require a high level of security even though their resources are limited. They face many types of attacks due to their broadcast transmissions and deployment in hostile environments without physical protection. Attacks can target the information in transit, different layers of the protocol stack, and seek to overwhelm the network. While some challenges have been addressed, research is still needed to resolve conflicts between security and limited resources in wireless sensor networks.
This document provides an overview of wireless sensor network software architecture. It discusses the key components of WSNs including sensing units, processing units, power suppliers, and communication devices. It then examines various topics related to WSN software architecture, including network topologies, the IEEE 1451 standard for smart sensors, software architecture components like operating systems and middleware, services in sensor networks, and research challenges around security. The goal is to provide a reliable software architecture for WSNs to enable better performance and functionality.
IMPLEMENTATION OF SECURITY PROTOCOL FOR WIRELESS SENSORijcsa
Intrusion Detection is one of the methods of defending against these attacks. In the proposed a security protocol for homogeneous wireless sensor network; network with all nodes are of same type. Clustering is used to improve the energy efficiency. Zone-Based Cluster Protocol (ZBCA) is used for selection of cluster head which is effective in scalability and energy consumption. Single hop technique is used for
communication within normal nodes and cluster head to base station. Simulation of proposed algorithm is performed in MATLAB. Sleep Deprivation Attack has been analyzed where attacker changes the environmental values by an artificial event. Attacker produces an event in environment due to which nodes have to sense the environment more than once in the same round that increase the power consumption of
the node. This interrupt reduces the network life time as nodes are not allowed to go in sleep mode and they are not able to perform their function of data collection and reporting to Cluster head and Base Station properly. Proposed protocol identifies this attack and prevents it from happening by solating the attacker node.
A Survey of Various Data Communication Schemes in WSNIRJET Journal
This document summarizes various data communication schemes used in wireless sensor networks (WSNs). It discusses key issues in WSNs like energy efficiency, data aggregation, and network lifetime. It then summarizes several common routing protocols used in WSNs to address these issues, including LEACH, PEGASIS, HEED, DEEC, TEEN, and SEP. LEACH uses randomized clustering to distribute energy load among sensors. PEGASIS forms chains to reduce transmissions. HEED allows energy-aware cluster head selection. DEEC handles heterogeneity. TEEN and SEP aim to improve responsiveness and support multi-level heterogeneity. The document concludes with a brief introduction to using fuzzy logic in WSN routing
This document discusses wireless micro-sensor network models and classifies them according to communication functions, data delivery models, and network dynamics. It describes four data delivery models for sensor networks: continuous, event-driven, observer-initiated, and hybrid. The continuous model involves sensors communicating data continuously at a pre-specified rate. This taxonomy framework can help network designers choose appropriate communication protocols for different sensor network applications. The classifications are meant to aid in defining communication infrastructure and selecting protocol architectures matched to specific application requirements.
This document discusses wireless sensor networks and their role in the Internet of Things. It defines sensor networks and their architecture, including sensor nodes that communicate wirelessly to a base station. It outlines challenges for sensor networks like fault tolerance, scalability, and quality of service. It also describes how sensor networks can be integrated into the Internet of Things through different approaches, with the first using a single gateway and later approaches using hybrid networks and access points. Applications of sensor networks in IoT include wearable devices collecting biometric data and communicating it to servers.
This document provides an overview of wireless sensor networks (WSNs), including their technologies, applications, standards, design features, and evolutions. WSNs enable new applications through spatially distributed sensors that monitor physical conditions and wirelessly transmit data to a central location. They require a balance between communication and processing capabilities given constraints like low power and complexity. The IEEE 802.15.4 standard enables many WSN applications. Performance depends on network size and data type. Sensors are key network components that detect physical properties and convert them to signals. Common sensor types include thermal, electromagnetic, mechanical, and motion sensors. WSNs face unique challenges from ad hoc deployment and constrained node resources.
ENHANCED THREE TIER SECURITY ARCHITECTURE FOR WSN AGAINST MOBILE SINK REPLI...ijwmn
Recent developments on Wireless Sensor Networks have made their application in a wide range
such as military sensing and tracking, health monitoring, traffic monitoring, video surveillance and so on.
Wireless sensor nodes are restricted to computational resources, and are always deployed in a harsh,
unattended or unfriendly environment. Therefore, network security becomes a tough task and it involves
the authorization of admittance to data in a network. The problem of authentication and pair wise key
establishment in sensor networks with mobile sink is still not solved in the mobile sink replication attacks.
In q-composite key pre distribution scheme, a large number of keys are compromised by capturing a
small fraction of sensor nodes by the attacker. The attacker can easily take a control of the entire network
by deploying a replicated mobile sinks. Those mobile sinks which are preloaded with compromised keys
are used authenticate and initiate data communication with sensor node. To determine the above problem
the system adduces the three-tier security framework for authentication and pair wise key establishment
between mobile sinks and sensor nodes. The previous system used the polynomial key pre distribution
scheme for the sensor networks which handles sink mobility and continuous data delivery to the
neighbouring nodes and sinks, but this scheme makes high computational cost and reduces the life time of
sensors. In order to overcome this problem a random pair wise key pre distribution scheme is suggested
and further it helps to improve the network resilience. In addition to this an Identity Based Encryption is
used to encrypt the data and Mutual authentication scheme is proposed for the identification and
isolation of replicated mobile sink from the network.
This document discusses localization techniques in wireless sensor networks (WSNs). It begins with an introduction to WSNs and their applications that require location information. While GPS could provide location data, it is not practical for WSNs due to cost and physical constraints. The document then categorizes localization methods as range-based, which use distance or angle measurements, and range-free, which do not directly measure distance. Specific techniques like time of arrival, received signal strength, and DV-Hop localization are described. The document concludes with classifications of localization methods and topics for future work.
A self-managing fault management mechanism for wireless sensor networks ijwmn
A sensor network can be described as a collection of sensor nodes which co-ordinate with each other to
perform some specific function. These sensor nodes are mainly in large numbers and are densely
deployed either inside the phenomenon or very close to it. They can be used for various application areas
(e.g. health, military, home). Failures are inevitable in wireless sensor networks due to inhospitable
environment and unattended deployment. Therefore, it is necessary that network failures are detected in
advance and appropriate measures are taken to sustain network operation. We previously proposed a
cellular approach for fault detection and recovery. In this paper we extend the cellular approach and
propose a new fault management mechanism to deal with fault detection and recovery. We propose a
hierarchical structure to properly distribute fault management tasks among sensor nodes by introducing
more ‘self-managing’ functions. The proposed failure detection and recovery algorithm has been
compared with some existing related work and proven to be more energy efficient.
This document discusses detection of collision attacks in wireless sensor networks using rule-based packet flow rates. It proposes detection algorithms that monitor the packet flow rate to the base station node. The algorithms aim to have low false detection and tolerance rates and quickly detect attacks. Simulation results show the algorithms achieve these goals. The document also reviews related work on intrusion detection in wireless sensor networks.
Basic Architecture of Wireless Sensor NetworkKarthik
The document discusses software architecture design considerations for wireless sensor networks. It examines four key characteristics of wireless sensor networks that impact software architecture: self-organization, cooperative processing, energy efficiency, and modularity. It then describes common components of service-oriented wireless sensor network architectures, including sensor applications, node applications, network applications, and middleware. Finally, it analyzes two proposed software architectures and how they address the requirements of wireless sensor networks.
An Efficient Approach for Outlier Detection in Wireless Sensor NetworkIOSR Journals
This document discusses an efficient approach for outlier detection in wireless sensor networks. It proposes a fault-tolerant data aggregation (FTDA) scheme that uses locality sensitive hashing (LSH) for outlier detection in a distributed manner. The FTDA scheme reduces communication overhead by eliminating redundant data transmission. The document also applies kernel density estimation to sensor data from Intel labs to estimate density and detect outliers. Experiments show FTDA achieves high precision and recall for outlier detection, demonstrating the effectiveness of the proposed approach. Future work will explore other density estimation methods like wavelet transforms for multi-attribute sensor data.
Improved Development of Energy Efficient Routing Algorithm for Privacy Preser...IRJET Journal
This document proposes an algorithm to improve energy efficiency and privacy preservation for the sink node in wireless sensor networks. The algorithm uses node clustering, where sensor nodes are grouped into clusters with a cluster head node. Data is routed from cluster members to their cluster head, and then from cluster heads to the sink node. The algorithm elects a subset of cluster heads to broadcast data, obscuring the location of the sink node and distributing energy usage across nodes. Simulations analyze how effectively this approach preserves sink node anonymity while limiting energy depletion across varying network conditions.
This document summarizes a wireless sensor network system implemented by the authors. The system uses 4 sensor nodes to sense temperature and a control node interfaced with a base station PC. It implements a modified version of the TOPDISC topology discovery algorithm using DHCP for dynamic addressing. The routing algorithm uses a mixture of spanning tree and N-link state protocols. Future enhancements include implementing fail safes and fully configuring the wireless sensor network system.
Secure and Efficient DiDrip Protocol for Improving Performance of WSNsINFOGAIN PUBLICATION
1. The document proposes a new distributed data discovery and dissemination protocol called DiDrip for wireless sensor networks (WSNs) that aims to improve security and performance over existing protocols.
2. Existing protocols primarily use a centralized approach where a single node distributes data, which is not suitable for multiple owners and users, and they do not focus on security.
3. DiDrip allows for a distributed approach where multiple owners can authorize different users simultaneously to access sensor data with different priorities, while improving security.
Secure and Efficient Hierarchical Data Aggregation in Wireless Sensor NetworksIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Node Deployment in Homogeneous and Heterogeneous Wireless Sensor NetworkIJMTST Journal
Optimal sensor deployment is necessary condition in homogeneous and heterogeneous wireless sensor
network. Effective deployment of sensor nodes is a major point of concern as performance and lifetime of any
WSN. Proposed sensor deployment in WSN explore every sensor node sends its data to the nearest sink node
of the WSN. In addition to that system proposes a hexagonal cell based sensor deployment which leads to
optimal sensor deployment for both homogeneous and heterogeneous sensor deployment. Wireless sensor
networks are receiving significant concentration due to their potential applications ranging from surveillance
to tracking domains. In limited communication range, a WSN is divided into several disconnected sub-graphs
under certain conditions. We deploy sensor nodes at random locations so that it improves performance of the
network.This paper aims to study, discuss and analyze various node deployment strategies and coverage
problems for Homogeneous and Heterogeneous WSN.
Channel Aware Detection of Forwarding Attacks in WSN with Malicious Node Dete...IRJET Journal
This document proposes a cooperative method to detect malicious nodes in wireless sensor networks. It describes an existing Channel-aware Reputation System with adaptive detection threshold (CRS-A) that evaluates sensor nodes' data forwarding behaviors and identifies compromised nodes. The paper also discusses detecting malicious nodes by having each node transmit data, store a copy, and check if the next node forwarded it within a set time. If not, it increases a failure tally for that node. If the tally exceeds a threshold, the node is reported as malicious. The proposed method uses this process cooperatively across nodes to reliably analyze and detect malicious nodes. It aims to accurately detect selective forwarding attacks while limiting false detections of normal packet loss due to unstable wireless channels.
This document summarizes a research paper that proposes a methodology to improve source location privacy preservation in wireless sensor networks. The paper introduces the concept of "interval indistinguishability" to quantify anonymity. It maps the problem of breaching source anonymity to the statistical problem of binary hypothesis testing with nuisance parameters. The paper proposes modeling anonymity, describes the network and adversarial models, and reviews related work before introducing its methodology. The methodology aims to address issues with existing solutions and practically prove the efficiency of improving source location privacy through a modified statistical framework.
A Survey of Fault Tolerance Methods in Wireless Sensor NetworksIRJET Journal
This document summarizes and analyzes various fault tolerance mechanisms for wireless sensor networks. It discusses mobile agent mechanisms, relay node mechanisms, and handover mechanisms. The document analyzes several existing fault tolerance methods, including Bayesian network models, probabilistic combinatorial optimization, dynamic power level adjustment, and integrated fault tolerance frameworks. Overall, the document provides an overview of important fault tolerance issues in wireless sensor networks and different approaches that have been proposed to address faults and improve reliability.
This document discusses wireless sensor networks and middleware approaches for them. It describes wireless sensor networks as consisting of distributed autonomous sensor nodes that monitor physical environments cooperatively. It outlines common sensor node components and network architectures. It then defines middleware as a software layer that manages complexity and heterogeneity. Key middleware design principles for wireless sensor networks include supporting limited resources, scalability, and data aggregation. The document outlines several middleware approaches, including those based on global behavior, local behavior, virtual machines, databases, and modular programming.
Wireless sensor networks require a high level of security even though their resources are limited. They face many types of attacks due to their broadcast transmissions and deployment in hostile environments without physical protection. Attacks can target the information in transit, different layers of the protocol stack, and seek to overwhelm the network. While some challenges have been addressed, research is still needed to resolve conflicts between security and limited resources in wireless sensor networks.
This document provides an overview of wireless sensor network software architecture. It discusses the key components of WSNs including sensing units, processing units, power suppliers, and communication devices. It then examines various topics related to WSN software architecture, including network topologies, the IEEE 1451 standard for smart sensors, software architecture components like operating systems and middleware, services in sensor networks, and research challenges around security. The goal is to provide a reliable software architecture for WSNs to enable better performance and functionality.
IMPLEMENTATION OF SECURITY PROTOCOL FOR WIRELESS SENSORijcsa
Intrusion Detection is one of the methods of defending against these attacks. In the proposed a security protocol for homogeneous wireless sensor network; network with all nodes are of same type. Clustering is used to improve the energy efficiency. Zone-Based Cluster Protocol (ZBCA) is used for selection of cluster head which is effective in scalability and energy consumption. Single hop technique is used for
communication within normal nodes and cluster head to base station. Simulation of proposed algorithm is performed in MATLAB. Sleep Deprivation Attack has been analyzed where attacker changes the environmental values by an artificial event. Attacker produces an event in environment due to which nodes have to sense the environment more than once in the same round that increase the power consumption of
the node. This interrupt reduces the network life time as nodes are not allowed to go in sleep mode and they are not able to perform their function of data collection and reporting to Cluster head and Base Station properly. Proposed protocol identifies this attack and prevents it from happening by solating the attacker node.
A Survey of Various Data Communication Schemes in WSNIRJET Journal
This document summarizes various data communication schemes used in wireless sensor networks (WSNs). It discusses key issues in WSNs like energy efficiency, data aggregation, and network lifetime. It then summarizes several common routing protocols used in WSNs to address these issues, including LEACH, PEGASIS, HEED, DEEC, TEEN, and SEP. LEACH uses randomized clustering to distribute energy load among sensors. PEGASIS forms chains to reduce transmissions. HEED allows energy-aware cluster head selection. DEEC handles heterogeneity. TEEN and SEP aim to improve responsiveness and support multi-level heterogeneity. The document concludes with a brief introduction to using fuzzy logic in WSN routing
This document discusses wireless micro-sensor network models and classifies them according to communication functions, data delivery models, and network dynamics. It describes four data delivery models for sensor networks: continuous, event-driven, observer-initiated, and hybrid. The continuous model involves sensors communicating data continuously at a pre-specified rate. This taxonomy framework can help network designers choose appropriate communication protocols for different sensor network applications. The classifications are meant to aid in defining communication infrastructure and selecting protocol architectures matched to specific application requirements.
This document discusses wireless sensor networks and their role in the Internet of Things. It defines sensor networks and their architecture, including sensor nodes that communicate wirelessly to a base station. It outlines challenges for sensor networks like fault tolerance, scalability, and quality of service. It also describes how sensor networks can be integrated into the Internet of Things through different approaches, with the first using a single gateway and later approaches using hybrid networks and access points. Applications of sensor networks in IoT include wearable devices collecting biometric data and communicating it to servers.
This document provides an overview of wireless sensor networks (WSNs), including their technologies, applications, standards, design features, and evolutions. WSNs enable new applications through spatially distributed sensors that monitor physical conditions and wirelessly transmit data to a central location. They require a balance between communication and processing capabilities given constraints like low power and complexity. The IEEE 802.15.4 standard enables many WSN applications. Performance depends on network size and data type. Sensors are key network components that detect physical properties and convert them to signals. Common sensor types include thermal, electromagnetic, mechanical, and motion sensors. WSNs face unique challenges from ad hoc deployment and constrained node resources.
ENHANCED THREE TIER SECURITY ARCHITECTURE FOR WSN AGAINST MOBILE SINK REPLI...ijwmn
Recent developments on Wireless Sensor Networks have made their application in a wide range
such as military sensing and tracking, health monitoring, traffic monitoring, video surveillance and so on.
Wireless sensor nodes are restricted to computational resources, and are always deployed in a harsh,
unattended or unfriendly environment. Therefore, network security becomes a tough task and it involves
the authorization of admittance to data in a network. The problem of authentication and pair wise key
establishment in sensor networks with mobile sink is still not solved in the mobile sink replication attacks.
In q-composite key pre distribution scheme, a large number of keys are compromised by capturing a
small fraction of sensor nodes by the attacker. The attacker can easily take a control of the entire network
by deploying a replicated mobile sinks. Those mobile sinks which are preloaded with compromised keys
are used authenticate and initiate data communication with sensor node. To determine the above problem
the system adduces the three-tier security framework for authentication and pair wise key establishment
between mobile sinks and sensor nodes. The previous system used the polynomial key pre distribution
scheme for the sensor networks which handles sink mobility and continuous data delivery to the
neighbouring nodes and sinks, but this scheme makes high computational cost and reduces the life time of
sensors. In order to overcome this problem a random pair wise key pre distribution scheme is suggested
and further it helps to improve the network resilience. In addition to this an Identity Based Encryption is
used to encrypt the data and Mutual authentication scheme is proposed for the identification and
isolation of replicated mobile sink from the network.
This document discusses localization techniques in wireless sensor networks (WSNs). It begins with an introduction to WSNs and their applications that require location information. While GPS could provide location data, it is not practical for WSNs due to cost and physical constraints. The document then categorizes localization methods as range-based, which use distance or angle measurements, and range-free, which do not directly measure distance. Specific techniques like time of arrival, received signal strength, and DV-Hop localization are described. The document concludes with classifications of localization methods and topics for future work.
A self-managing fault management mechanism for wireless sensor networks ijwmn
A sensor network can be described as a collection of sensor nodes which co-ordinate with each other to
perform some specific function. These sensor nodes are mainly in large numbers and are densely
deployed either inside the phenomenon or very close to it. They can be used for various application areas
(e.g. health, military, home). Failures are inevitable in wireless sensor networks due to inhospitable
environment and unattended deployment. Therefore, it is necessary that network failures are detected in
advance and appropriate measures are taken to sustain network operation. We previously proposed a
cellular approach for fault detection and recovery. In this paper we extend the cellular approach and
propose a new fault management mechanism to deal with fault detection and recovery. We propose a
hierarchical structure to properly distribute fault management tasks among sensor nodes by introducing
more ‘self-managing’ functions. The proposed failure detection and recovery algorithm has been
compared with some existing related work and proven to be more energy efficient.
This document discusses detection of collision attacks in wireless sensor networks using rule-based packet flow rates. It proposes detection algorithms that monitor the packet flow rate to the base station node. The algorithms aim to have low false detection and tolerance rates and quickly detect attacks. Simulation results show the algorithms achieve these goals. The document also reviews related work on intrusion detection in wireless sensor networks.
SECURED AODV TO PROTECT WSN AGAINST MALICIOUS INTRUSIONIJNSA Journal
One of the security issues in Wireless Sensor Networks (WSN) is intrusion detection. In this paper, we propose a new defence mechanism based on the Ad hoc On-Demand Vector (AODV) routing protocol. AODV is a reactive protocol designed for ad hoc networks and has excellent flexibility to be adapted to a new secure version. The main objective of the proposed secured AODV routing protocol is to protect WSN against malicious intrusion and defend against adversary attacks. This secured AODV protocol works well with the WSN dynamics and topology changes due to limited available resources. It establishes secure multi-hop routing between sensor nodes with high confidence, integrity, and availability. The secured AODV utilizes an existing intrusion dataset that facilitates new collection from all the exchanged packets in the network. The protocol monitors end to end delay and avoid any additional overhead over message transfer between sensor nodes. The experimental results showed that this secured AODV could be used to fight against malicious attacks such as black hole attacks and avoid caused large transmission delays.
Real-Time, Fault Tolerance and Energy-Efficiency (REFER) Enhancement in Wirel...IRJET Journal
This document discusses enhancing real-time capabilities, fault tolerance, and energy efficiency in wireless sensor and actuator networks (WSANs). It proposes a new network architecture called REFER that embeds Kautz graphs for routing to provide these enhancements. REFER connects the Kautz graphs using a distributed hash table for scalability. It also develops an efficient fault-tolerant routing protocol that allows nodes to quickly identify alternate paths upon failures based on node IDs alone, without retransmission from the source. The document reviews related work on WSAN routing and discusses fault diagnosis and recovery techniques. It presents the methodology and simulation results demonstrating REFER's improvements over existing WSAN systems in real-time communication, energy efficiency, fault tolerance and scalability
Wireless Sensor Networks UNIT-1
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Requisite Trust Based Routing Protocol for WSNAM Publications
This document summarizes a research paper on using a trust-based routing protocol (RTSR) for wireless sensor networks (WSNs). The summary is:
1) The RTSR protocol uses a cluster-based approach and calculates trust values between nodes to securely discover routes while reducing message and route redundancy.
2) Trust values from neighboring nodes are used to calculate a single trust value for each node. Route discovery and trust information is stored at fixed cluster heads.
3) The protocol aims to improve on previous approaches that did not consider security during route discovery. It analyzes performance metrics like energy consumption, number of hops, and delay compared to the LEEACH routing algorithm for WSNs.
Deep Learning Fault Detection Algorithms in WSNsIRJET Journal
This document discusses using deep learning algorithms to detect faults in wireless sensor networks (WSNs). It begins with an introduction to WSNs and some of the challenges in detecting faults. It then discusses existing fault detection methods and their limitations. The document proposes using deep learning techniques like convolutional neural networks, artificial neural networks, and LSTMs for fault detection. It describes the architectures of these algorithms and evaluates their performance on sensor datasets. The research finds that deep learning methods can accurately detect different types of faults in WSN data.
IRJET-Multipath based Routing and Energy Efficient Multicasting for Wireless ...IRJET Journal
The document discusses the Real-Time, Fault Tolerant and Energy-Efficient (REFER) protocol for wireless sensor and actuator networks (WSANs). It proposes embedding Kautz graphs into the physical topology of a WSAN to enable real-time communication and connecting the graphs using a distributed hash table for scalability. The REFER protocol also includes an efficient fault-tolerant routing mechanism that allows nodes to quickly identify alternate paths upon failures based on node IDs rather than retransmissions. Simulation results show REFER outperforms existing WSAN approaches in terms of real-time performance, energy-efficiency, fault-tolerance and scalability.
Improving reliability & performance of wsn via routing errorsijctet
The document proposes a scheme called Link Scanner (LS) for detecting faulty links in wireless sensor networks. LS operates passively by collecting hop count data from probe flooding processes. It analyzes mismatches between expected and received hop counts to infer which links may be faulty. Having a blacklist of potential faulty links allows further analysis and recovery, including adjusting routing strategies, identifying root causes of observed network issues, and providing spare link options. The scheme aims to not only detect currently faulty links but also evaluate unused links, to help guide rerouting for better performance. It was tested on a 60-node sensor network and in simulation and found to accurately detect faulty links with low overhead.
A Survey on Security Issues to Detect Wormhole Attack in Wireless Sensor Networkpijans
Sensor nodes, when deployed to form Wireless sensor network operating under control of central authority
i.e. Base station are capable of exhibiting interesting applications due to their ability to be deployed
ubiquitously in hostile & pervasive environments. But due to same reason security is becoming a major
concern for these networks. Wireless sensor networks are vulnerable against various types of external and
internal attacks being limited by computation resources, smaller memory capacity, limited battery life,
processing power & lack of tamper resistant packaging. This survey paper is an attempt to analyze threats
to Wireless sensor networks and to report various research efforts in studying variety of routing attacks
which target the network layer. Particularly devastating attack is Wormhole attack- a Denial of Service
attack, where attackers create a low-latency link between two points in the network. With focus on survey of
existing methods of detecting Wormhole attacks, researchers are in process to identify and demarcate the
key research challenges for detection of Wormhole attacks in network layer.
Energetic Slot Allotment for Improving Interchange in Wireless Sensor NetworkIRJET Journal
This document discusses improving energy efficiency and throughput in wireless sensor networks. It begins with an introduction to wireless sensor networks and their design challenges, including limited energy capacity. It then discusses how existing medium access control protocols provide energy efficiency but at the cost of increased delay and limited throughput. The document proposes dynamic slot allocation as a way to adapt bandwidth based on traffic load, maintaining low duty cycles with light traffic but scheduling more transmission opportunities with increased traffic. This allows energy to only be used when needed to carry application traffic. The document surveys dynamic slot allocation approaches in wireless sensor networks.
This document provides an introduction to wireless sensor networks. It describes a wireless sensor network as a network consisting of distributed sensors that monitor conditions like temperature, sound, and pollutants and pass data to a central location. Each sensor node contains a radio transceiver, microcontroller, sensor interface electronics, and a power source. The sensors form a multi-hop network to transmit data across long distances. Event-driven wireless sensor networks only transmit messages when events of interest occur to avoid overloading the network and wasting energy.
The document summarizes a neighbor assisted distributed self-healing protocol (NDSP) for compromised node recovery in wireless sensor networks. The NDSP protocol allows a compromised sensor node to continuously and collectively recover from a compromised stage to a normal stage with the help of its neighbor nodes. The protocol detects compromised nodes and then replaces their seed values, which are used to generate encryption keys, with the seed values from neighboring healthy nodes in order to recover the compromised nodes and maintain data secrecy across the network. Simulation results showed that the presented NDSP scheme is effective and efficient at recovering compromised sensor nodes.
Ndsp: Neighbor Assisted Distributed Self-Healing Protocol for Compromised Nod...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
The document discusses implementing Zigbee in home automation using wireless sensors. It describes wireless sensor networks (WSN) which consist of distributed autonomous devices using sensors to monitor environmental conditions. WSN integrate a gateway providing wireless connectivity back to wired networks and distributed sensor nodes. The document outlines challenges for WSN including converting raw sensor data to usable knowledge, maintaining system robustness over time as conditions change, dealing with open and heterogeneous systems, and addressing security, privacy, real-time and actuation issues.
Denial of Service (DoS) Attacks at Network Layer in WSNIJERA Editor
Recent advancements in technology, tiny size, cost effectiveness have made sensors as a crucial part of real
world sensitive applications. These sensor nodes are scattered over an area to monitor the situations like fire,
flood and record the data and to forward meaningful data to the center head node for observation, resulting an
advance prompt to control the situation. In last decade, WSN have grown significantly in variety of areas and
applications, resulted the high, consistent security mechanism. Also, there is variety of attacks on WSN at their
different layers of architecture. Though sensor nodes are not capable enough in terms of power, processing etc.
but applications based on these sensors demand on-time collection of information or data and then to send same
on reliable, secure delivery medium. Small sensors with limited hardware, processing cannot afford traditional
security mechanisms to face or sustain the attacks. There is variety of attacks at different layers of WSN
architecture to affect sensor‟s roles like signaling, framing, transmission etc. Many Denial of Service (DoS)
attacks are identified at each layer of WSN which are purposeful, planned attacks to hamper the availability of
service, restricting the sensor node‟s utility for problem solution. In this paper we will focus on the WSN
architecture, characteristics, constraints and various types of DoS attacks primarily on physical and data link
layer and particularly at network layer in details with some suggestions against attacks.
DYNAMIC NEURAL NETWORKS IN THE DETECTION OF DISTRIBUTED ATTACKS IN MOBILE AD-...IJNSA Journal
This document summarizes research on developing a distributed intrusion detection system for mobile ad hoc networks (MANETs) using dynamic neural networks. The system uses learning vector quantization neural networks distributed across nodes to identify patterns of network attacks. In a simulation of 18 nodes, the system successfully detected 80% of man-in-the-middle attacks on the ad hoc on-demand distance vector routing protocol. The distributed nature of the neural network approach helps overcome limitations of bandwidth and connectivity in MANETs compared to traditional centralized intrusion detection systems.
The International Journal of Engineering and Science (The IJES)theijes
The document summarizes a study on the Enhanced Adaptive Acknowledge (EAACK) scheme for detecting misbehaving nodes in mobile ad hoc networks (MANETs). It discusses the limitations of existing acknowledgment-based intrusion detection systems like Watchdog, TWOACK, and AACK in handling receiver collisions. The key issues related to acknowledgment-based schemes for detecting misbehavior in MANETs are addressed. The focus is on analyzing the limitations of acknowledgment approaches like AACK and studying EAACK as an improved approach for addressing receiver collisions in MANETs.
A STUDY ON HYBRID CONGESTION CONTROL MECHANISM IN WIRELESS SENSOR NETWORKSJournal For Research
Congestion in WSN is a current research area. There are so many studies to avoid, detect and control congestion in WSN. This paper discussing about current studies going in this field.
EVENT DRIVEN ROUTING PROTOCOLS FOR WIRELESS SENSOR NETWORK- A SURVEYijcsa
Advances in embedded systems have resulted in the development of wireless sensor networks, which not
only provide unique opportunities for monitoring but also controlling homes, cities and the environments.
Recent advancements in wireless sensor network have resulted into many new protocols some of them are
specifically designed for sensor network for detecting the event and routing the event related information to
the base station in efficient manner. This paper surveys recent event driven routing protocols for wireless
sensor network. We have compared various event driven routing protocols using different parameters like
Sink Centric, Node Centric, Reliability, Congestion control, Energy Efficiency, Loss reliability and loss
recovery. We have also described LEACH and MECN protocols but as they are not e
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GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
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Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
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HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
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Ao03402350245
1. International Journal of Computational Engineering Research||Vol, 03||Issue, 4||
www.ijceronline.com ||April||2013|| Page 235
Fault Management in Wireless Sensor Networks
1,
S.Irfan , 2,
K.Sravani, 3,
K.Manohar
1, 3
Lecturer, Electrical Engineering Department, Wollo University, Ethiopia
2
Assistant Professor, Swarna Bharathi College of Engineering, Khammam, A.P.
I. INTRODUCTION
Continuing advances in computational power and radio components, as well as reduction in the cost of
processing and memory elements have led to the proliferation of micro-sensor nodes that integrate computation,
communication, and sensing capabilities into a single device. Wireless sensor networks are self-organized
networks that typically consist of a large number of such sensing devices with severely limited processing,
storage and communication capabilities and finite energy supply. Sensor networks are now rapidly permeating a
variety of applications domains such as avionics, environmental monitoring, structural sensing, tele-medicine,
space exploration, and command and control. With multi hop wireless communication, sensor nodes have made
it possible to build reactive systems that have the ability to monitor and react to physical events/phenomena. In
addition to resource constraints, sensor networks are also failure-prone. Therefore, fault tolerance is as critical as
other performance metrics such as energy efficiency, latency and accuracy in supporting distributed sensor
applications. Due to the small dimensions, sensor nodes have strong hardware and software restrictions in terms
of processing power, memory capability, power supply, and communication throughput.
The power supply is the most critical restriction, given that it is typically not rechargeable. For this
reason faults are likely to occur frequently and will not be isolated events. Besides, large-scale deployment of
cheap individual nodes means that node failures from fabrication defects will not be uncommon. Attacks by
adversaries could happen because these networks will be often embedded in critical applications. Worse, attacks
could be facilitated because these networks will be often deployed in open spaces or enemy territories, where
adversaries can not only manipulate the environment (so as to disrupt communication, for example, by
jamming), but have also physical access to the nodes. At the same time, ad-hoc wireless communication by
radio frequencies means that adversaries can easily put themselves in the network and disrupt infrastructure
functions (such as routing) that are performed by the individual nodes themselves. Finally, the sensors nodes are
susceptible to natural phenomenons like rain, fire, or even falls of trees since they are commonly used to
monitor external environments. For all these reasons faults in WSNs need to be tackled differently than in
traditional networks. Fault management, an essential component of any network management system, will play
an equal, if not more, crucial role in WSNs. Failure detection, in particular, is vital not only for fault
management, but also for security and performance. If, in addition to detecting a failure, the management
application can also determine (or gather indicatives) that it has malicious origin, then the management
application can trigger security management services. On the other hand, if it has not a malicious origin, i.e., if it
Abstract
Wireless sensor networks (WSNs) are resource-constrained self-organizing systems that are
often deployed in inaccessible and inhospitable environments in order to collect data about some
outside world phenomenon. For most sensor network applications, point to- point reliability is not the
main objective; instead, reliable event-of-interest delivery to the server needs to be guaranteed
(possibly with a certain probability). The nature of communication in sensor networks is unpredictable
and failure-prone, even more so than in regular wireless ad hoc networks. Therefore, it is essential to
provide fault tolerant techniques for distributed sensor applications. In this work we propose and
evaluate a failure detection scheme using management architecture for WSNs, called MANNA. We
take a deep look at its fault management capabilities supposing the existence of an event-driven WSN.
This is a challenging and attractive kind of WSN and we show how the use of automatic management
services defined by MANNA can provide self- configuration, self-diagnostic, and self-healing (some of
the self-managing capabilities). We also show that the management solution promote the resources
productivity without incurring a high cost to the network.
Keywords :Wireless Sensor Networks, Fault Management, Self-management, Network Monitoring.
2. Fault Management In Wireless...
www.ijceronline.com ||April||2013|| Page 236
is an accidental or natural failure, backup nodes" could be activated in order to substitute the unavailable nodes,
hence maintaining quality of service. Given the motivation for applying fault management in WSNs, in this
paper we propose a failure detection scheme using MANNA - a network management architecture for WSNs
proposed in [8]. Since WSNs have different characteristics and restrictions when compared to traditional
networks, the adoption of a management solution which takes this into account is essential. In this work, we
focus on event-driven WSNs. An event driven WSN is a type of WSN network which reports data to the
observer only when certain event occur (as opposed to continuous networks which reports data at regular
intervals). To the best of our knowledge, there has not been much research on failure detection in WSNs and
even though proposals do exist, their focus is on continuous networks. Event driven networks pose special
challenges to the problem (we discuss them in detail in Section 2).
In order to evaluate the performance the management solution, we analyze the impact of management
functions over the network and also its effectiveness in detecting failures. In particular, we analyze the fault
management aspect for this kind of network supposing different scenarios. As a case study, we define a simple
event-driven application that runs in the WSN for monitoring the environment temperature. We show that our
solution achieves a reasonable detection rate, and that it incurs an overhead that is acceptable for mission critical
applications. The rest of this paper is organized as follows. In Section 2 we discuss the problem of failure
detection in WSNs, briey describes the MANNA management architecture for WSNs, and propose a failure
detection scheme for event driven WSNs using this architecture. In Section 3 we describe the management
services and functions defined in MANNA and used in management application considered. The simulation
model used in our experiments is described in Section 4 and the experimental results in Section 5. Finally, our
concluding remarks are presented in Section 6.
II. FAILURE DETECTION IN WIRELESS SENSOR NETWORKS
WSNs are embedded in applications to monitor the environment and sometimes, act upon it. In
applications where we are interested in the conditions of the environment at all times, sensor nodes will be
programmed to sense and send back their measurements at regular intervals or continuously. We call these
networks programmed and continuous, respectively. In other applications (probably a large class of them), we
are only interested in hearing from the network when certain events occur. We call these networks event-driven
networks. On the other hand, when the network is able to answer to queries of the observers, we refer to this
network as on demand. Configuring the network as event-driven is an attractive option for a large class of
applications since it typically sends far fewer messages. This is translated into a significant energy saving, since
message transmissions are much more energy-intensive when compared to sensing and (CPU) processing. For
instance, if the application is temperature monitoring, it could be possible just to report data when the
temperature of the area being monitored goes above or below certain thresholds. In terms of failure detection,
event-driven networks present challenges not found in continuous networks. Under normal conditions, the
observer of a continuous network receives sensing data at regular intervals. This stream of data not only delivers
the content we are interested in, but also works as an indicative of the network operation quality.
If data are received from every single node, then it knows that all is well (of course, assuming that the
messages are authenticated, and cannot be spoofed). If, however, the management application stops receiving
data from certain nodes or entire regions of the network, it cannot distinguish if a failure has occurred or if no
application event has occurred. Leveraging precisely on this indication, and supposing that nodes periodically
send messages to the base station, Staddon et al. [5] proposed a scheme for tracing failed nodes in continuous
sensor networks. Their scheme takes advantages of periodic transmission of sensor reports to do the tracing.
Because we consider event-driven networks, their solution is not directly applicable. In [4], it is proposed a
scheme where nodes police each other in order to detect faults and misbehaviour. More specifically, nodes
listen-in on the neighbour it is currently routing to, and can determine whether the message it sent was for-
warded. If the message was not forwarded, the node concludes that its neighbour has failed and chooses a new
neighbour to route to. Unfortunately, this scheme does not help in cases in which an entire region is
compromised.In our work, we study the problem of failure detection for an event-driven WSN and propose a
fault management solution using some management services, management functions, and WSN models which
are part of the MANNA architecture [8]. In MANNA management services for WSNs are defined. These
management services are performed by a set of functions which take executing conditions from the WSN
models. The WSN models, as defined in the MANNA architecture, represent the states of the network and serve
as a reference for the management. The definition of the management services and functions is based on three
management dimensions, namely management functional areas, management levels, and WSN functionalities.
3. Fault Management In Wireless...
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In the following, we discuss how the MANNA architecture can cope with this kind of network promoting its
self- managing. We also describe the management application defined for providing fault management.
III. FAULT MANAGEMENT APPLICATION USING MANNA
In order to evaluate the fault management capabilities of the management solution proposed, we have
simulated an application that monitors an environment to collect temperature data. As said before, we have
considered an event-driven WSN. We suppose this network as being heterogeneous and hierarchical. The sensor
nodes only disseminate data when the temperature of the area being monitored goes above or below certain
thresholds. In a hierarchical network, nodes are grouped into clusters and there is a special node called cluster-
head. In a heterogeneous network, the cluster-heads have more resources and, thus, are more powerful than the
common-nodes. Furthermore, they are responsible for sending data to a base station (BS). The BS also
communicates with the observer, which is a network entity or a final user that wants to have information about
data collected from the sensor nodes. In our implementation, the management agents execute in the cluster-
heads where aggregation of management and application data is performed. This mechanism decreases the
information flow and energy consumption as well. A manager is located externally to the WSN where it has a
global vision of the network and can perform complex tasks that would not be possible inside the network. In
this work we use automatic management services and functions, i.e., executed by management entities (manager
or agent) invoked as a result of information acquired from a WSN model. The computational cost of some
autonomic process (automatic management services) could be expensive to the architecture proposed. The
external manager then extends the computation capabilities avoiding the consumption of network energy to
carry out this task. Locations for managers and agents, and the functions they can execute are suggested by the
functional architecture. MANNA architecture also proposes two other architectures: physical and information.
More details can be found in [8].
The management application is divided into two phases: installation and operation. The installation
phase occurs as soon as the nodes are deployed in the network. In this phase, each node finds out its position in
the area and reports it to the agent located in the cluster-head. The agent aggregates the information received
from the nodes in the group and sends a LOCATION TRAP of its localization to the manager. The common-
nodes also inform their energy level that the agent aggregates in an ENERGY TRAP sent to the manager. The
management application builds all needed WSN models based on both local information and data sent by the
agents, i.e., the WSN topology map model and the WSN energy model. These two models are used to build the
WSN coverage area model, which the manager uses to monitor the sensing and communication coverage area.
In the operation phase, while the sensor nodes are performing their functions, i.e., collecting and sending
temperature data, management activities take place. Among them, energy level monitoring plays a central role.
Each node checks its energy level and sends a message to the agent whenever there is a state change. This
information is transmitted to the manager via another ENERGY TRAP. Any information the agent receives is
recorded in its MIB. The manager can, then, recalculate the energy and topology maps, as well as the coverage
area, which characterizes the coverage area maintenance service. Also, operations can be sent to the agents in
order to execute the failure detection management service. The manager sends GET operations in order to
retrieve the node state. The GET-RESPONSEs are used to build the WSN audit map. If an agent or a node does
not answer to a GET operation, the manager consults the energy map to verify if it has residual energy. If so, the
manager detects a failure and sends a notification to the observer. In this way, MANNA architecture provides
failure detection in event-driven WSN. In the next section we describe the experiments conducted in order to
evaluate MANNA's performance as a solution for failure detection.
IV. SIMULATION MODEL
For our study, we have conducted a set of experiments taking into account distinct simulation
scenarios. We have defined a WSN application and some management functions, as mentioned before, and
evaluated the performance of the system using the Network Simulator (ns-2) [6], version 2.1b8a. Each scenario
was simulated 33 times. In our application, the temperature is the monitoring object. Although the nodes sense
the temperature continuously along the time, data are sent only when the minimum or the maximum value
collected differs 2% from the last data sent, inducing the event-driven property to the sensing application. In
order to simulate the temperature behaviour of the environment, random numbers were generated following a
normal distribution, taking into consideration standard deviation of one from an average temperature of 25°C.
Figure 1 presents nodes distribution in the monitored area. Table 1 describes the network parameters and the
features of the nodes. We use UDP, IEEE 802.11, and single hop communication between cluster-heads and
base station. Between the base station and cluster-heads we use SNMP for the application layer but between
common-node and cluster head we use a new light-weight protocol, MNMP (MANNA Network Management
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Protocol) which we designed [7]. Table 2 presents the parameters of the management application which was
simulated.
Figure 1: Hierarchical network comprised of common-nodes, cluster-heads and a base-station.
V. EXPERIMENTAL RESULTS
In order to evaluate the results, we have considered two sets of experiments with two distinct goals.
The first set aimed at evaluating the impact of management functions over the WSN, analyzing the management
cost. The second one was meant to identify the effectiveness of the management architecture in detecting
failures. For both sets we have simulated an unexpected event to happen at the middle of the simulation time.
This event puts the nodes, confined in a predefined region, out of operation. We could think of this event as a
car passing over the network, the fall of a tree, a spot of fire, or another external event which could ruin the
nodes.
5.1 Evaluating Management Impact
In this section we evaluate the impact of management functions over the WSN, analyzing its costs.
Table 3 shows the three scenarios considered in the first set of experiments in respect to management functions.
For this set of experiments, we have considered the unexpected event to cause the failure of 32 nodes located at
the centre of the network (which have x and y coordinates between 30 and 90). This event happens at 45 s of
simulation. Three metrics were chosen in order to analyze the results. The first one was the delivery rate, which
measures the ratio of messages received by the nodes in the network to messages sent by the nodes, during the
simulation time. This metric computes the ability of the network to deliver messages at their destinations. The
second metric chosen was the average energy consumption, which measures the ratio of total dissipated energy
by the nodes to the num-ber of nodes in the network. This metric defines the cost of transmitting and receiving
packets per node and sensing. The third metric chosen was the number of messages transmitted. This metric
shows the traffic imposed by the nodes tasks.
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Figure 2 shows the delivery rate for sensing application and management messages. It is observed that for
scenarios 1 and 2 the delivery rate for management messages and application messages were similar. This is
expected since they are transmitted in the same wireless environment and to and from the same nodes. We can
also notice that the introduction of detection (see results for scenario 2) had no influence on this metric. Another
result exhibited in Figure 2 concerns the delivery rate of application messages. The introduction of management
had little impact on the sensing application.
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Figure 3 shows the traffic of messages in the WSN. Comparing the results for scenarios 2 and 3, we can notice
that management contributed with only a small increase (18.49%) in the WSN traffic. This is due to the fact
that, like the sensing application, management was implemented as eventdriven. However, the number of
messages sent almost dou- bled (increase of 93.33%) when management with detection is concerned. This is an
expected result since OPERATIONAL STATUS GETs have to be sent to all nodes in the network and be
responded by them. Fortunately, as shown before, this is not a problem since the delivery rate of sensing
application messages is not greatly impacted. Figure 4 shows the energy consumption of common-nodes and
cluster-heads for scenarios 1, 2, and 3. It is observed that, as far as detection is not concerned, the energy
consumption increased with management in 18% for cluster heads and 29.45% for nodes. But when the
detection mechanism was taken into account, management caused an increase of 101.2% and 129.45% in the
energy consumption for cluster-heads and nodes, respectively.
This result was expected since the act of transmitting and receiving messages are the most determinant activities
for energy consumption according to the simulated energy model.
5.2 Failure Detection Effectiveness
The results for the first set of experiments gave a motivation for identifying the effectiveness of the
detection mechanism provided by the management architecture. The second set of experiments was conducted
in order to evaluate if it is worth the increase in traffic and energy consumption. For this second set of
experiments, we have tried to modify the region where the ruin of nodes occurred in terms of location and also
in terms of dimension. Table 4 presents the description of the simulated scenarios, represented in the Figures
5(b), 5(c), 5(d), 5(e), and 5(f). For space reasons, the captions are omitted in these figures and shown in Figure
5(a). For these experiments, we simulated an event which harms the nodes at 45 s of simulating, putting them
out of operation until the end of the simulation. The manager was programmed to start the detection mechanism,
i.e., to send the OPERATIONAL STATUS GETs at times 25, 50, and 75 s and to report the results at times 50,
75, and 100 s, respect- tively. So, at the time when the unexpected event occurs, there was time enough for the
manager to have come to a conclusion regarding the availability of the nodes. This means that only the reports
in 75 and 100 s would have to contain any conclusion regarding this event. Thus, the report at 50 s shows the
results obtained before the event occurrence. The results, shown in histograms, present the total number of
failures detected by the manager for each scenario, comparing with the number of genuine (forced) failures. The
number of failures detected that were not real failures (false positives) and the number of failures not detected
are also presented. Just as an illustration, Figure 6 demonstrates the results obtained for one simulation,
regarding scenario 1 (caption is shown in Figure 5(a)).
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Figure 7 shows the effectiveness of the detection mechanism for scenario 1. The numbers in the x axis represent
the points in time when the manager reports the availability of the nodes in the network. We can observe in
Figure 7 that there was some detection in time 50 s, although at this time the destruction of the nodes could not
yet be perceived. Drops of OPERATIONAL STATUS GETs or OPERATIONAL STATUS GETRESPONSEs
cause the manager to be misled and, consequently, produce false positives. This problem also occurs at points
75 and 100 for the same reason, representing 27.93% and 26.06% of the detections, respectively. The quantity
of false positives at these points is considerably higher than the quantity for point 50 due to the harm of some
cluster heads where the agents run. What happens is that after the unexpected event occurs, some common-
nodes, which were not harmed, lost their cluster-heads if they are located inside the damaged region. As a
consequence, these common-nodes stop receiving the OPERATIONAL STATUS GETs from the manager,
since they are sent to them through the agents. As a result, the manager does not receive answers from these
common-nodes provoking false positives. In respect to scenario 1, the number of orphan" nodes were 8.
Besides the false positives, the results in Figure 7 also show the amount of non-detected failures, representing
14.81% of the failures in both points 75 and 100. The manager cannot recognize a failure if it does not have
knowledge of the damaged node. This may be caused by drops at the initial phase of the network when nodes
send their positions to the agents and the agents aggregate the information received in a POSITION TRAP for
the manager. Another reason is that the distribution of common-nodes and cluster-heads is random and since the
transmission range is limited, there is no guarantee that every common-node will be connected to a cluster-head.
Figure 8 shows the results for scenario 2. We can see that the results for point 50 are almost the same as the
results for the centered region (scenario 1). As mentioned before, at that point the unexpected event had not yet
been perceived, meaning that the results seem to be independent from the region chosen. However, as far as
points 75 and 100 are concerned, it is possible to observe considerable dissimilarities. The number of false
positives has decreased to 10.26% (point 75) and 10.36% (point 100) of the detections. The reason is that in this
experiment the number of orphan nodes are only 4, i.e., two times less than the number of orphan nodes for
scenario 1.
Figure 8 also shows the results for non-detected failures. Comparing with the results for scenario 1, the
amount of non-detections is similar, representing 15.59% of the failures.This shows that the number of initial
messages drops in the center is similar to the region near the BS. Figure 9 shows the results for scenario 3. We
can notice that the quantity of false positives in point 50 is smaller when compared to the previous results.
However, as stated before, this result is independent from the region chosen. Regarding points 75 and 100, a
slight decrease in the number of false positives when compared to scenario 1 was produced. In terms of
percentage of detections, this quantity represents now 21.48% and 21.67% for points 75 and 100, respectively.
The number of orphan nodes for this experiment is 7, very similar to the number produced for scenario 1. Thus,
another cause for the decrease exists. Through the logs of the simulations, it is possible to notice that the highest
quantity of drops generally takes place in regions far from the BS. This is due to the wireless propagation
behaviour. The farthest the source of a message is from the destination, the lower is the probability of this
message being delivered. For this reason, most of the false positives are nodes far from the BS (since their
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agents are located far too). Therefore, when these nodes are damaged the number of false positives is likely to
decrease. Figure 9 also presents the results for non-detected failures. Comparing with the previous results, the
amount of non-detections is higher, representing 27.87% of the failures. This clearly shows that the initial
message drop is higher at regions far from the BS, as just said. As a result, most of
the nodes, which the manager does not know, are located far from it.
Figure 10 shows the results for scenario 4. It can be noticed that the results for point 50 are almost the same as
the results shown in Figure 7 for scenario 1. As said before, the results are independent from the region chosen.
On the other hand, in points 75 and 100 a great difference can be perceived in the number of false positives,
which has decreased as expected, since the number of orphan nodes is smaller. The percentage of false positives
in relation to detections is now 14.24% and 13.95%. Figure 10 also presents the results for non-detected failures.
Comparing to the results of scenario 1, the amount of non-detections is lower. However, in terms of percentage,
it represented 27.87% of the failures, i.e., a higher result. This is due to the fact that the region chosen, as seen in
Figure 1, almost coincides with one group and if an initial message from this group is lost, the manager lacks the
knowledge of the whole group.
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Figure 11 shows the results for scenario 5. It can be noticed that the results for point 50 are almost the
same as the results shown before. Nevertheless, in points 75 and 100 some differences can be observed.
Regarding the false positive results and comparing with the results shown in Figure 7 (scenario 1), the quantity
of false positives has increased slightly for the enlarged region. Providing that the number of orphan nodes is a
lot higher, a greater increase would be expected. However, since the undamaged region is smaller, there are less
drops of OPERATIONAL STATUS GETs and OPERATIONAL STATUS GET- RESPONSEs not due to
unavailability. This provokes the number of false positive to reduce. The quantity of false positives shown in
Figure 11 is, thus, a result of two opposed factors. As a consequence, as far as the percentage in relation to
detections is concerned, there was a decrease (18.45% for both points).
This shows that the detection mechanism seems to scale well. Figure 11 also presents the results for non-
detected failures. In comparison to the results for scenario 1, the amount of non-detections is higher. This was
expected since the number of damaged nodes is higher as well as their probability of being unknown to the
manager. In terms of percentage, it represented 11.36% of the failures, i.e., a lower result. This shows again a
good scalability.
VI. CONCLUSION
We have conducted two sets of experiments. The results for the first one proved that the introduction of
fault management in the WSN was responsible for a great increase in the number of messages transmitted in the
network. Although the delivery rate of the sensing application messages was not affected, the energy
consumption of the network grew considerably. In spite of that, the second set of experiments shows that the
number of nodes harmed and also their location does not influence much the effectiveness of the detection
mechanism. Concerning the second set and the results for point 50, we could notice a small fixed number of
false positives. At point 75, the percentage of false positive in relation to the detections varies from 10% to 28%
whereas the non-detected failures vary from 11% to 28% of the forced failures. Point 100 presented almost the
same results, meaning that the timehas worthless influence. The main reasons for these high portions of false
positives and non-detections were message drops and the creation of orphan nodes after the occurrenceof the
unexpected event. Sensor nodes have to communicate via wireless channels and message drops will exist. The
problem could be reduced by sending redundant information or using acknowledge schemes. However, the use
of these solutions would result in an increase in the energy consumption, which is undesirable for WSNs.
Hence, there is a trade-off between benefits and costs which need to be investigated more thoroughly. The
problem of orphan nodes, on the other hand, could be solved by the use of an adoption schema assigning
undamaged or redundant cluster-heads to the orphan nodes. The main conclusion we could draw about our
approach is that its cost is fixed and its effectiveness is the same, independent from the failures which take
place. Although one might think at first sight that the cost introduced by management is high enough to be paid
for, this could be worth, and since failures are a common fact in WSNs. Applications which have critical
requirements could be a lot beneficed with the knowledge provided by MANNA fault detection. In this paper,
we evaluated the MANNA management architecture for WSNs, considering an event-driven WSN. From the
experiments presented above, we can see that the solution proposed achieves a reasonable detection rate, and
that it incurs an overhead that is acceptable for mission-critical applications.
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