An event-aware cluster-head rotation algorithm for extending lifetime of wireless sensor Network with smart nodes

Smart sensor nodes can process data collected from sensors, make decisions, and recognize relevant events based on the sensed information before sharing it with other nodes. In wireless sensor networks, the smart sensor nodes are usually grouped in clusters for effective cooperation. One sensor node in each cluster must act as a cluster head. The cluster head depletes its energy resources faster than the other nodes. Thus, the cluster-head role must be periodically reassigned (rotated) to different sensor nodes to achieve a long lifetime of wireless sensor network. This paper introduces a method for extending the lifetime of the wireless sensor networks with smart nodes. The proposed method combines a new algorithm for rotating the cluster-head role among sensor nodes with suppression of unnecessary data transmissions. It enables effective control of the cluster-head rotation based on expected energy consumption of sensor nodes. The energy consumption is estimated using a lightweight model, which takes into account transmission probabilities. This method was implemented in a prototype of wireless sensor network. During experimental evaluation of the new method, detailed measurements of lifetime and energy consumption were conducted for a real wireless sensor network. Results of these realistic experiments have revealed that the lifetime of the sensor network is extended when using the proposed method in comparison with state-of-the-art cluster-head rotation algorithms

Extending the Lifetime of Wireless Sensor Networks Based on an Improved Multi-objective Artificial Bees Colony Algorithm

Reducing the sensors\u27 energy expenditure to prolong the network lifespan as long as possible remains a fundamental problem in the field of wireless networks. Particularly in applications with inaccessible environments, which impose crucial constraints on sensor replacement. It is, therefore, necessary to design adaptive routing protocols, taking into account the environmental constraints and the limited energy of sensors. To have an energy-efficient routing protocol, a new cluster heads’ (CHs) selection strategy using a modified multi-objective artificial bees colony (MOABC) optimization is defined. The modified MOABC is based on the roulette wheel selection over non-dominated solutions of the repository (hyper-cubes) in which a rank is assigned to each hypercube based on its density in dominated solutions of the current iteration and then a random food source is elected by roulette from the densest hypercube. The proposed work aims to find the optimal set of CHs based on their residual energies to ensure an optimal balance between the nodes\u27 energy consumption. The achieved results proved that the proposed MOABC-based protocol considerably outperforms recent studies and well-known energy-efficient protocols, namely: LEACH, C-LEACH, SEP, TSEP, DEEC, DDEEC, and EDEEC in terms of energy efficiency, stability, and network lifespan extension

A network-aware framework for energy-efficient data acquisition in wireless sensor networks

Wireless sensor networks enable users to monitor the physical world at an extremely high fidelity. In order to collect the data generated by these tiny-scale devices, the data management community has proposed the utilization of declarative data-acquisition frameworks. While these frameworks have facilitated the energy-efficient retrieval of data from the physical environment, they were agnostic of the underlying network topology and also did not support advanced query processing semantics. In this paper we present KSpot+, a distributed network-aware framework that optimizes network efficiency by combining three components: (i) the tree balancing module, which balances the workload of each sensor node by constructing efficient network topologies; (ii) the workload balancing module, which minimizes data reception inefficiencies by synchronizing the sensor network activity intervals; and (iii) the query processing module, which supports advanced query processing semantics. In order to validate the efficiency of our approach, we have developed a prototype implementation of KSpot+ in nesC and JAVA. In our experimental evaluation, we thoroughly assess the performance of KSpot+ using real datasets and show that KSpot+ provides significant energy reductions under a variety of conditions, thus significantly prolonging the longevity of a WSN

An efficient quality of services based wireless sensor network for anomaly detection using soft computing approaches

Wireless sensor network (WSN) is widely acceptable communication network where human-intervention is less. Another prominent factors are cheap in cost and covers huge area of field for communication. WSN as name suggests sensor nodes are present which communicate to the neighboring node to form a network. These nodes are communicate via radio signals and equipped with battery which is one of most challenge in these networks. The battery consumption is depend on weather where sensors are deployed, routing protocols etc. To reduce the battery at routing level various quality of services (QoS) parameters are available to measure the performance of the network. To overcome this problem, many routing protocol has been proposed. In this paper, we considered two energy efficient protocols i.e. LEACH and Sub-cluster LEACH protocols. For provision of better performance of network Levenberg-Marquardt neural network (LMNN) and Moth-Flame optimisation both are implemented one by one. QoS parameters considered to measure the performance are energy efficiency, end-to-end delay, Throughput and Packet delivery ratio (PDR). After implementation, simulation results show that Sub-cluster LEACH with MFO is outperforms among other algorithms.Along with this, second part of paper considered to anomaly detection based on machine learning algorithms such as SVM, KNN and LR. NSLKDD dataset is considered and than proposed the anomaly detection method.Simulation results shows that proposed method with SVM provide better results among others

Connectivity sharing for wireless mesh networks

Tesi en modalitat de cotutela: Universitat Politècnica de Catalunya i Katholieke Universiteit LeuvenInternet access is still unavailable to one-third of the world population due to the lack of infrastructure, high cost, and the digital divide. Many access-limited communities opt for shared Internet access where they build common network infrastructures to mitigate the cost. Internet connectivity in such infrastructures is typically provided by several limited, sometimes non-dedicated, gateways. Client nodes, i.e., the end-user hosts, use one gateway and switch to another when the first fails. In this scheme, the gateway configuration is done manually on the end-user side. This form of Internet connectivity is widespread and has the advantage that no central control is required, but it is also unreliable and inefficient due to several factors, such as unbalanced traffic load across the gateways. There is no doubt that the network would benefit from a gateway selection mechanism that can provide good connectivity to the client node as well as balanced load distribution and a dynamic adaptation to the current network state. However, providing such a dynamic gateway selection is complicated: since the perceived performance of the gateways changes frequently and might depend on the location of the client node in the network, and optimal selection would require the continuous monitoring of the gateway performance by the client node. The cost of such network-wide performance monitoring is high in large-scale networks and can outweigh the benefits of the dynamic gateway selection. The thesis's goal is to design a low-cost, distributed mechanism that provides an efficient and dynamic gateway selection while considering the overall balanced gateway selection distribution. To this end, we have split the problem of gateway selection into different sub-problems. First, we focus on reducing the cost of gateway performance monitoring. We propose an approach to reduce the number of monitoring requests generated by each node and analyze its effect on the gateway selection. Then, we present a collaborative monitoring method that allows neighbor nodes to share the load of the gateway monitoring. We show that every node can carry out the necessary tasks: performance monitoring, collaboration with its neighbors, and fault tolerance measures, with little computation and communication overhead. Second, to improve the gateway selection, we focus on making a selection decision that fulfills the individual performance requirements of the client nodes as well as global load balancing requirements. The solutions developed by us for the different sub-problems are embedded into a general and extensible, layered framework for gateway selection that we have called the Sense-Share-Select framework. Experimental validation and comparison with existing methods show that our framework provides accurate collaborative performance monitoring, improves the QoE for the nodes, and distributes the client nodes over the gateways in a balanced manner. The simplicity and flexibility of the framework make it adaptable to other network domains such as IoT networks and other scenarios where resource monitoring and load balancing are required.El acceso a Internet aún no está disponible para un tercio de la población mundial debido a la falta de infraestructuras, el alto costo y la brecha digital. Muchas comunidades con acceso limitado optan por el acceso compartido a Internet donde construyen infraestructuras de red comunitaria para mitigar el costo. La conectividad a Internet en dichas infraestructuras suele estar a cargo de varias puerta de enlaces limitadas en recursos, y a veces no dedicadas. Los nodos de cliente, es decir, los hosts de usuario final, utilizan una puerta de enlace y cambian a otra cuando falla la primera. En este esquema, la configuración de la puerta de enlace se realiza manualmente en el lado del usuario final. Esta forma de conectividad a Internet está muy extendida y tiene la ventaja de que no se requiere un control central, pero tampoco es confiable y eficiente debido a varios factores, como una carga desequilibrada de tráfico a través de las puertas de enlace. No hay duda de que la red se beneficiaría de un mecanismo de selección de pasarela que pueda proporcionar una buena conectividad al nodo cliente, así como una distribución equilibrada de la carga y una adaptación dinámica al estado actual de la red. Sin embargo, proporcionar una selección de puerta de enlace tan dinámica es complicado: dado que el rendimiento percibido de las puertas de enlace cambia con frecuencia y podría depender de la ubicación del nodo cliente en la red, y la selección óptima requeriría la supervisión continua del rendimiento de la puerta de enlace por parte del nodo cliente. El costo de dicha supervisión del rendimiento en toda la red es muy alto en redes de gran escala y puede superar los beneficios de la selección de puerta de enlace dinámica. El objetivo de la tesis es diseñar un mecanismo distribuido de bajo costo que proporcione una selección de puerta de enlace dinámica y eficiente al tiempo que considera la distribución general de selección de puerta de enlace equilibrada. Con este fin, hemos dividido el problema de la selección de la puerta de enlace en diferentes subproblemas. Primero, nos enfocamos en reducir el coste del monitoreo del rendimiento de la puerta de enlace. Proponemos un enfoque para reducir la cantidad de solicitudes de monitoreo generadas por cada nodo y analizar su efecto en la selección de la puerta de enlace. Luego, presentamos un método de monitoreo colaborativo que permite a los nodos vecinos compartir la carga del monitoreo de la puerta de enlace. Demostramos que cada nodo puede realizar las tareas necesarias: monitoreo del rendimiento, colaboración con sus vecinos y medidas de tolerancia a fallas, con poca sobrecarga de cómputo y comunicación. En segundo lugar, para mejorar la selección de la puerta de enlace, nos centramos en tomar una decisión de selección que cumpla con los requisitos de rendimiento individuales de los nodos del cliente, así como con los requisitos de equilibrio de carga global. Las soluciones desarrolladas por nosotros para los diferentes subproblemas están integradas en un marco general y extensible en capas para la selección de puertas de enlace que hemos llamado el marco Sense-Share-Select. La validación experimental y la comparación con los métodos existentes muestran que nuestro marco proporciona un monitoreo de rendimiento colaborativo preciso, mejora la QoE para los nodos y distribuye los nodos del cliente a través de las puertas de enlace de manera equilibrada. La simplicidad y flexibilidad del marco lo hacen adaptable a otros dominios de red, como las redes de IoT y otros escenarios donde se requiere monitoreo de recursos y equilibrio de carga.Postprint (published version

Towards energy efficient clustering in wireless sensor networks: A comprehensive review

Clustering is one of the fundamental approaches used to optimize energy consumption in wireless sensor networks. Clustering protocols proposed in the literature can be classified according to different criteria related to their features such as the clustering methodology, objectives, cluster count and size, etc. This paper reviews the existing feature-based classifications of clustering protocols and elaborates a more generic and unified classification. It also analyzes and discusses the relevant design factors that may influence the energy efficiency of clustering protocols and accordingly proposes a new energy-oriented taxonomy. State-of-the-art clustering solutions are then reviewed and evaluated following the proposed taxonomy

Autonomic Role and Mission Allocation Framework for Wireless Sensor Networks.

Pervasive applications incorporate physical components that are exposed to everyday use and a large number of conditions and external factors that can lead to faults and failures. It is also possible that application requirements change during deployment and the network needs to adapt to a new context. Consequently, pervasive systems must be capable to autonomically adapt to changing conditions without involving users becoming a transparent asset in the environment. In this paper, we present an autonomic mechanism for initial task assignment in sensor networks, an NP-hard problem. We also study on-line adaptation of the original deployment which considers real-time metrics for maximising utility and lifetime of applications and smooth service degradation in the face of component failures. © 2011 IEEE

Energy Efficient and Secure Wireless Sensor Networks Design

Wireless Sensor Networks (WSNs) are emerging technologies that have the ability to sense, process, communicate, and transmit information to a destination, and they are expected to have significant impact on the efficiency of many applications in various fields. The resource constraint such as limited battery power, is the greatest challenge in WSNs design as it affects the lifetime and performance of the network. An energy efficient, secure, and trustworthy system is vital when a WSN involves highly sensitive information. Thus, it is critical to design mechanisms that are energy efficient and secure while at the same time maintaining the desired level of quality of service. Inspired by these challenges, this dissertation is dedicated to exploiting optimization and game theoretic approaches/solutions to handle several important issues in WSN communication, including energy efficiency, latency, congestion, dynamic traffic load, and security. We present several novel mechanisms to improve the security and energy efficiency of WSNs. Two new schemes are proposed for the network layer stack to achieve the following: (a) to enhance energy efficiency through optimized sleep intervals, that also considers the underlying dynamic traffic load and (b) to develop the routing protocol in order to handle wasted energy, congestion, and clustering. We also propose efficient routing and energy-efficient clustering algorithms based on optimization and game theory. Furthermore, we propose a dynamic game theoretic framework (i.e., hyper defense) to analyze the interactions between attacker and defender as a non-cooperative security game that considers the resource limitation. All the proposed schemes are validated by extensive experimental analyses, obtained by running simulations depicting various situations in WSNs in order to represent real-world scenarios as realistically as possible. The results show that the proposed schemes achieve high performance in different terms, such as network lifetime, compared with the state-of-the-art schemes