Lightweight authentication for recovery in wireless sensor networks

Wireless sensor networks (WSNs) suffer from a wide range of security attacks due to their limited processing and energy capabilities. Their use in numerous mission critical applications, however, requires that fast recovery from such attacks be achieved. Much research has been completed on detection of security attacks, while very little attention has been paid to recovery from an attack. In this paper, we propose a novel, lightweight authentication protocol that can secure network and node recovery operations such as re-clustering and reprogramming. Our protocol is based on hash functions and we compare the performance of two well-known lightweight hash functions, SHA-1 and Rabin. We demonstrate that our authentication protocol can be implemented efficiently on a sensor network test-bed with TelosB motes. Further, our experimental results show that our protocol is efficient both in terms of computational overhead and execution times which makes it suitable for low resourced sensor devices.

Network resilience in low-resource mobile wireless sensor networks

Wireless sensor networks (WSNs) are deployed in numerous mission critical applications in which the network needs to remain active for as long as possible while delivering quality information to a base station. However, WSNs suffer from a wide range of attacks due to their limited processing and energy capabilities. Their resiliency, however, depends on fast recovery from such attacks being achieved. In recent work, the authors developed and implemented clustering, reprogramming and authentication protocols involved in recovering stationary WSNs with low resources. In this paper, we determine the additional resources required in implementing these protocols in a mobile WSN.

We present recovery protocols on TinyOS motes for a low-resourced, mobile deployment. We describe the issues we encountered in the implementation. We present times, RAM and ROM needed to run the recovery protocols and compare these with the stationary case, demonstrating that the additional cost of reprogramming in a mobile WSN is less than 25% of that in a stationary WSN and the additional cost of re-clustering in a mobile WSN is less than 9% of that in a stationary WSN. Authentication has an insignificant cost increase.

Enhancement of sensor data transmission by inference and efficient data processing

When wearable and personal health device and sensors capture data such as heart rate and body temperature for fitness tracking and health services, they simply transfer data without filtering or optimising. This can cause over-loading to the sensors as well as rapid battery consumption when they interact with Internet of Things (IoT) networks, which are expected to increase and de-mand more health data from device wearers. To solve the problem, this paper proposes to infer sensed data to reduce the data volume, which will affect the bandwidth and battery power reduction that are essential requirements to sensor devices. This is achieved by applying beacon data points after the inferencing of data processing utilising variance rates, which compare the sensed data with ad-jacent data before and after. This novel approach verifies by experiments that data volume can be saved by up to 99.5% with a 98.62% accuracy. Whilst most existing works focus on sensor network improvements such as routing, operation and reading data algorithms, we efficiently reduce data volume to reduce band-width and battery power consumption while maintaining accuracy by implement-ing intelligence and optimisation in sensor devices.

On the effect of path loss rates on the optimal receiver position in sensor networks

In this paper we examine the problem of finding an optimal position for a receiver node in a single-hop sensor network. The basic idea is to minimize the network energy consumption according to a particular network cost function. Our contribution is to simply show the effect of signal path loss rates and sensor weighting on the optimal receiver position.

Sensor node activity scheduling approach

Sensor networks, once deployed, are expected to continue to function unmanned. However, energy of the sensors is typically unrenewable thus making it a very scarce resource. Therefore, in order to extend the life of the sensor networks for the duration of a particular mission, energy has to be managed wisely. In this paper, we consider the problem of energy conservation for grid-based sensor networks. A wireless sensor network architecture that is based on mobile base station is presented. Based on this architecture, we propose an asynchronous duty-cycle scheduling scheme for extending the lifetime of the grid-based wireless sensor networks.

Towards optimization of a real-world robotic-sensor system of systems

The problem of threat detection in an unstructured environment is considered. Three systems, comprising of robots and sensors, are proposed to form a system of systems (SoS) to find a solution to the problem. System interactions are defined to provide a framework for formulation as an SoS optimization problem. Different cost and objective functions are introduced for optimization of local criteria. Using different weights, a linear combination of the local cost and objective functions is obtained to propose a global objective function. An algorithm is suggested to find an optimum value for the global objective function leading towards optimization of the SoS.

Dynamic route construction for mobile collectors in wireless sensor networks

Wireless sensor networks with mobile data collectors have been recently proposed for extending the sensor network lifetime. Powerful mobile collectors are deployed to patrol the network and approach the static sensors for collecting their data buffers using single hop communication. The route followed by the mobile collector is very crucial for the data collection operation performed in the network and highly impacts the data collection time. This paper presents a practically efficient algorithm for constructing the mobile collector route. The route is constructed dynamically during the network operational time regardless of the sensors data generation rates. The algorithm acts on minimizing the sleeping time and the number of sensors waiting for the arrival of the mobile collector. Simulation results demonstrate that the presented algorithm can effectively reduce the overall data collection time.

A practical framework for data collection in wireless sensor networks

Optimizing energy consumption for extending the lifetime in wireless sensor networks is of dominant importance. Groups of autonomous robots and unmanned aerial vehicles (UAVs) acting as mobile data collectors are utilized to minimize the energy expenditure of the sensor nodes by approaching the sensors and collecting their buffers via single hop communication, rather than using multihop routing to forward the buffers to the base station. This paper models the sensor network and the mobile collectors as a system-of-systems, and defines all levels and types of interactions. A practical framework that facilitates deploying heterogeneous mobiles without prior knowledge about the sensor network is presented. Realizing the framework is done through simulation experiments and tested against several performance metrics.

Performance of smart antennas with receive diversity in wireless sensor networks

In this paper we propose a Geometrically Based Single Bounce Elliptical Model (GBSBEM) for multipath components involving randomly placed scatterers in the scattering region with sensors deployed on a field. The system model assumes a cluster based wireless sensor network (WSN) which collects information from the sensors, filters and modulates the data and transmit it through a wireless channel to be collected at the receiver. We first develop a GBSBE model and based on this model we develop our channel model. Use of Smart antenna system at the receiver end, which exploits various receive diversity combining techniques like Maximal Ratio Combining (MRC), Equal Gain Combining (EGC), and Selection Combining (SC), adds novelty to this system. The performance of these techniques have been proved through matlab simulations and further ahead based on different number of antenna elements present at the receiver array, we calculate the performance of our system in terms of bit-error-rate (BER). Based on the transmission power we quantify for the energy efficiency of our communication model.

Energy-efficient medium access control in wireless sensor networks

Medium access control for wireless sensor networks has been an active
research area in the past decade. This chapter discusses a set of important medium access control (MAC) attributes and possible design trade-offs in protocol design, with an emphasis on energy efficiency. Then we categorize existing MAC protocols into five groups, outline the representative protocols, and compare their advantages and disadvantages in the context of wireless sensor network. Finally, thoughts for practitioners are presented and open research issues are also discussed.

Power saving in sensor networks via mobile base station repositioning

This research investigated the effect of dynamically repositioning the geographic location of a mobile base station within a sensor network in order to reduce energy consumption and increase network lifetime. Through simulation and experimental methodology, the proposed approach outperformed existing methods by extending network lifetime whilst reducing energy consumption.

Fast recovery from node compromise in wireless sensor networks

Wireless Sensor Networks (WSNs) are susceptible to a wide range of security attacks in hostile environments due to the limited processing and energy capabilities of sensor nodes. Consequently, the use of WSNs in mission critical applications requires reliable detection and fast recovery from these attacks. While much research has been devoted to detecting security attacks, very little attention has been paid yet to the recovery task. In this paper, we present a novel mechanism that is based on dynamic network reclustering and node reprogramming for recovering from node compromise. In response to node compromise, the proposed recovery approach reclusters the network excluding compromised nodes; thus allowing normal network operation while initiating node recovery procedures. We propose a novel reclustering algorithm that uses 2-hop neighbourhood information for this purpose. For node reprogramming we propose the modified Deluge protocol. The proposed node recovery mechanism is both decentralized and scalable. Moreover, we demonstrate through its implementation on a TelosB-based sensor network testbed that the proposed recovery method performs well in a low-resource WSN.

Wireless sensor networks for in-situ image validation for water and nutrient management

Water and Nitrogen (N) are critical inputs for crop production. Remote sensing data collected from multiple scales, including ground-based, aerial, and satellite, can be used for the formulation of an efficient and cost effective algorithm for the detection of N and water stress. Formulation and validation of such techniques require continuous acquisition of ground based spectral data over the canopy enabling field measurements to coincide exactly with aerial and satellite observations. In this context, a wireless sensor in situ network was developed and this paper describes the results of the first phase of the experiment along with the details of sensor development and instrumentation set up. The sensor network was established based on different spatial sampling strategies and each sensor collected spectral data in seven narrow wavebands (470, 550, 670, 700, 720, 750, 790 nm) critical for monitoring crop growth. Spectral measurements recorded at required intervals (up to 30 seconds) were relayed through a multi-hop wireless network to a base computer at the field site. These data were then accessed by the remote sensing centre computing system through broad band internet. Comparison of the data from the WSN and an industry standard ground based hyperspectral radiometer indicated that there were no significant differences in the spectral measurements for all the wavebands except for 790nm. Combining sensor and wireless technologies provides a robust means of aerial and satellite data calibration and an enhanced understanding of issues of variations in the scale for the effective water and nutrient management in wheat.

Performance analysis of receive diversity in wireless sensor networks over GBSBE models

Wireless sensor networks have attracted a lot of attention recently. In this paper, we develop a channel model based on the elliptical model for multipath components involving randomly placed scatterers in the scattering region with sensors deployed on a field. We verify that in a sensor network, the use of receive diversity techniques improves the performance of the system. Extensive performance analysis of the system is carried out for both single and multiple antennas with the applied receive diversity techniques. Performance analyses based on variations in receiver height, maximum multipath delay and transmit power have been performed considering different numbers of antenna elements present in the receiver array, Our results show that increasing the number of antenna elements for a wireless sensor network does indeed improve the BER rates that can be obtained.

Secure connectivity model in wireless sensor networks (WSN) using first order Reed-Muller codes

In this paper, we suggest the idea of separately treating the connectivity and communication model of a Wireless Sensor Network (WSN). We then propose a novel connectivity model for a WSN using first order Reed-Muller Codes. While the model has a hierarchical structure, we have shown that it works equally well for a Distributed WSN. Though one can use any communication model, we prefer to use the communication model suggested by Ruj and Roy [1] for all computations and results in our work. Two suitable secure (symmetric) cryptosystems can then be applied for the two different models, connectivity and communication respectively. By doing so we have shown how resiliency and scalability are appreciably improved as compared to Ruj and Roy [1].