A Survey on Wireless Sensor Network Security

Wireless sensor networks (WSNs) have recently attracted a lot of interest in the research community due their wide range of applications. Due to distributed nature of these networks and their deployment in remote areas, these networks are vulnerable to numerous security threats that can adversely affect their proper functioning. This problem is more critical if the network is deployed for some mission-critical applications such as in a tactical battlefield. Random failure of nodes is also very likely in real-life deployment scenarios. Due to resource constraints in the sensor nodes, traditional security mechanisms with large overhead of computation and communication are infeasible in WSNs. Security in sensor networks is, therefore, a particularly challenging task. This paper discusses the current state of the art in security mechanisms for WSNs. Various types of attacks are discussed and their countermeasures presented. A brief discussion on the future direction of research in WSN security is also included.Comment: 24 pages, 4 figures, 2 table

Online Learning Algorithm for Time Series Forecasting Suitable for Low Cost Wireless Sensor Networks Nodes

Time series forecasting is an important predictive methodology which can be applied to a wide range of problems. Particularly, forecasting the indoor temperature permits an improved utilization of the HVAC (Heating, Ventilating and Air Conditioning) systems in a home and thus a better energy efficiency. With such purpose the paper describes how to implement an Artificial Neural Network (ANN) algorithm in a low cost system-on-chip to develop an autonomous intelligent wireless sensor network. The present paper uses a Wireless Sensor Networks (WSN) to monitor and forecast the indoor temperature in a smart home, based on low resources and cost microcontroller technology as the 8051MCU. An on-line learning approach, based on Back-Propagation (BP) algorithm for ANNs, has been developed for real-time time series learning. It performs the model training with every new data that arrive to the system, without saving enormous quantities of data to create a historical database as usual, i.e., without previous knowledge. Consequently to validate the approach a simulation study through a Bayesian baseline model have been tested in order to compare with a database of a real application aiming to see the performance and accuracy. The core of the paper is a new algorithm, based on the BP one, which has been described in detail, and the challenge was how to implement a computational demanding algorithm in a simple architecture with very few hardware resources.Comment: 28 pages, Published 21 April 2015 at MDPI's journal "Sensors

A Lightweight Medium Access Protocol (LMAC) for Wireless Sensor Networks: Reducing Preamble Transmissions and Transceiver State Switches

In this paper, we present an energy-efficient medium access protocol designed for wireless sensor networks. Although the protocol uses TDMA to give nodes in the WSN the opportunity to communicate collision-free, the network is self-organizing in terms of time slot assignment and synchronization. The main goal of the medium access protocol is to minimize overhead of the physical layer. The protocol reduces the number of transceiver state switches and hence the energy wasted in preamble transmissions. The protocol is compared to SMAC and EMACs by simulation. The LMAC protocol is able to extend the network lifetime by a factor 2.4 and 3.8, compared to EMACs and SMAC respectively

MOBILITY CONTROL IN WIRELESS SENSOR NETWORK

Wireless sensor networks (WSNs) have become one of the most important topics in wireless communication during the last decade. WSNs integrates many different technologies such as in hardware, software, data fusion, and applications. Hence, WSNs has received recently special research activities. WSNs have so many applications in different areas such as health-care systems, monitoring and control systems, rescue systems, and military applications. Since WSNs are usually deployed with large numbers of nodes in wide areas, they should be reliable, inexpensive, with very low power consumption, and with high redundancy to preserve the life-time of the whole network. In this M.Sc. thesis we consider one extremely important research topic in WSNs which is the mobility control. The mobility control is analyzed theoretically as well as with extensive simulations. In the simulation scenarios, static sensor nodes are first randomly deployed to the decided area. Then a reference trajectory for the mobile node is created based on the observed point phenomena, and the network guides the mobile node to move along the trajectory. A simulation platform called PiccSIM is used to simulate the scenarios. It is developed by the Communication and Control Engineering Groups at Helsinki University of Technology (TKK). The obtained results from these simulations are discussed and analyzed. This work opens the doors for more real applications in this area in the nearby future.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

From carbon nanotubes and silicate layers to graphene platelets for polymer nanocomposites

In spite of extensive studies conducted on carbon nanotubes and silicate layers for their polymer-based nanocomposites, the rise of graphene now provides a more promising candidate due to its exceptionally high mechanical performance and electrical and thermal conductivities. The present study developed a facile approach to fabricate epoxy–graphene nanocomposites by thermally expanding a commercial product followed by ultrasonication and solution-compounding with epoxy, and investigated their morphologies, mechanical properties, electrical conductivity and thermal mechanical behaviour. Graphene platelets (GnPs) of 3.5