An Energy Aware and Secure MAC Protocol for Tackling Denial of Sleep Attacks in Wireless Sensor Networks

Wireless sensor networks which form part of the core for the Internet of Things consist of resource constrained sensors that are usually powered by batteries. Therefore, careful energy awareness is essential when working with these devices. Indeed,the introduction of security techniques such as authentication and encryption, to ensure confidentiality and integrity of data, can place higher energy load on the sensors. However, the absence of security protection c ould give room for energy drain attacks such as denial of sleep attacks which have a higher negative impact on the life span ( of the sensors than the presence of security features. This thesis, therefore, focuses on tackling denial of sleep attacks from two perspectives A security perspective and an energy efficiency perspective. The security perspective involves evaluating and ranking a number of security based techniques to curbing denial of sleep attacks. The energy efficiency perspective, on the other hand, involves exploring duty cycling and simulating three Media Access Control ( protocols Sensor MAC, Timeout MAC andTunableMAC under different network sizes and measuring different parameters such as the Received Signal Strength RSSI) and Link Quality Indicator ( Transmit power, throughput and energy efficiency Duty cycling happens to be one of the major techniques for conserving energy in wireless sensor networks and this research aims to answer questions with regards to the effect of duty cycles on the energy efficiency as well as the throughput of three duty cycle protocols Sensor MAC ( Timeout MAC ( and TunableMAC in addition to creating a novel MAC protocol that is also more resilient to denial of sleep a ttacks than existing protocols. The main contributions to knowledge from this thesis are the developed framework used for evaluation of existing denial of sleep attack solutions and the algorithms which fuel the other contribution to knowledge a newly developed protocol tested on the Castalia Simulator on the OMNET++ platform. The new protocol has been compared with existing protocols and has been found to have significant improvement in energy efficiency and also better resilience to denial of sleep at tacks Part of this research has been published Two conference publications in IEEE Explore and one workshop paper

Coverage Protocols for Wireless Sensor Networks: Review and Future Directions

The coverage problem in wireless sensor networks (WSNs) can be generally defined as a measure of how effectively a network field is monitored by its sensor nodes. This problem has attracted a lot of interest over the years and as a result, many coverage protocols were proposed. In this survey, we first propose a taxonomy for classifying coverage protocols in WSNs. Then, we classify the coverage protocols into three categories (i.e. coverage aware deployment protocols, sleep scheduling protocols for flat networks, and cluster-based sleep scheduling protocols) based on the network stage where the coverage is optimized. For each category, relevant protocols are thoroughly reviewed and classified based on the adopted coverage techniques. Finally, we discuss open issues (and recommend future directions to resolve them) associated with the design of realistic coverage protocols. Issues such as realistic sensing models, realistic energy consumption models, realistic connectivity models and sensor localization are covered

Pheromone-based In-Network Processing for wireless sensor network monitoring systems

Monitoring spatio-temporal continuous fields using wireless sensor networks (WSNs) has emerged as a novel solution. An efficient data-driven routing mechanism for sensor querying and information gathering in large-scale WSNs is a challenging problem. In particular, we consider the case of how to query the sensor network information with the minimum energy cost in scenarios where a small subset of sensor nodes has relevant readings. In order to deal with this problem, we propose a Pheromone-based In-Network Processing (PhINP) mechanism. The proposal takes advantages of both a pheromone-based iterative strategy to direct queries towards nodes with relevant information and query- and response-based in-network filtering to reduce the number of active nodes. Additionally, we apply reinforcement learning to improve the performance. The main contribution of this work is the proposal of a simple and efficient mechanism for information discovery and gathering. It can reduce the messages exchanged in the network, by allowing some error, in order to maximize the network lifetime. We demonstrate by extensive simulations that using PhINP mechanism the query dissemination cost can be reduced by approximately 60% over flooding, with an error below 1%, applying the same in-network filtering strategy.Fil: Riva, Guillermo Gaston. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Universidad Tecnológica Nacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Finochietto, Jorge Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Estudios Avanzados en Ingeniería y Tecnología. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Estudios Avanzados en Ingeniería y Tecnología; Argentin