J. Sens. Actuator Netw.2014, 3(4), 245-273; doi:10.3390/jsan3040245 - published 14 October 2014 Show/Hide Abstract
Abstract: In this paper, a novel concept of coupling the actuators of an automated order picking system for pouch packed goods with an embedded CCD camera sensor by means of image processing and machine learning is presented. The picking system mechanically combines the conveyance and singularization of a still-connected chain of pouch packed goods in a single machinery. The proposed algorithms perform a per-frame processing of the captured images in real-time to detect the sealed seams of the ongoing pouches. The detections are used to deduce cutting decisions in order to control the system’s actuators, namely the drive pulley for conveyance and the cutting device for the separation. Within this context, two controlling strategies are presented as well which specify the interaction of the sensor and the actuators. The detection is carried out by two different marker detection strategies: enhanced Template Matching as a heuristic and Support Vector Machines as a supervised classification based concept. Depending on the employed marker, detection rates of almost 100% with a calculation time of less than 40 ms are possible. From a logistic point of view, sealed seam widths of 20 mm prove feasible.
J. Sens. Actuator Netw.2014, 3(3), 224-244; doi:10.3390/jsan3030224 - published 3 September 2014 Show/Hide Abstract
Abstract: Designing secure authentication mechanisms in wireless sensor networks in order to associate a node to a secure network is not an easy task due to the limitations of this type of networks. In this paper, we propose different multi-hop node authentication protocols for wireless sensor networks. For each protocol, we provide a formal proof to verify the security of our proposals using Scyther, which is an automatic cryptographic protocols verification tool. We also provide implementation results in terms of execution time consumption obtained by real measurements on TelosB motes. These protocols offer different security mechanisms depending on the design of the protocol itself. Moreover, we evaluate the overhead of protection of each solution by studying the effect on execution time overhead of each protocol. Finally, we propose a mechanism to detect possible attack based on our evaluation results.
J. Sens. Actuator Netw.2014, 3(3), 207-223; doi:10.3390/jsan3030207 - published 4 August 2014 Show/Hide Abstract
Abstract: Solar energy harvesting allows for wireless sensor networks to be operated over extended periods of time. In order to select an appropriate harvesting architecture and dimension for its components, an effective method for the comparison of system implementations is required. System simulations have the capability to accomplish this in an accurate and efficient manner. In this paper, we evaluate the existing work on solar energy harvesting architectures and common methods for their modeling. An analysis of the existing approaches demonstrates a mismatch between the requirement of the task to be both accurate and efficient and the proposed modeling methods, which are either accurate or efficient. As a result, we propose a data-driven modeling method based on artificial neural networks for further evaluation by the research community. Preliminary results of an initial investigation demonstrate the capability of this method to accurately capture the behavior of a solar energy harvesting architecture, while providing a time-efficient model generation procedure based on system-level data.
J. Sens. Actuator Netw.2014, 3(3), 181-206; doi:10.3390/jsan3030181 - published 1 July 2014 Show/Hide Abstract
Abstract: We propose a new authenticated key agreement scheme based on Blom’s scheme, but using multiple master keys and public keys in permutations to compute the private keys in each node. The computations are over a small prime field, and by storing them in a random order in the node, the private-public-master-key associations (PPMka) of the private keys are lost. If a node is captured, the PPMka of the private keys cannot be determined with certainty, making it difficult to begin to attack the scheme. We obtained analytical results to show that, using suitable keying parameters, the probability of discovering the correct PPMka can be made so small, that a very powerful adversary needs to capture the entire network of tens of thousands of nodes or expend an infeasible amount of effort to try all of the possible solutions. We verified our results using computer-simulated attacks on the scheme. The unknown PPMka enables our scheme to break free from the capture threshold of the original Blom’s scheme, so that it can be used in large networks of low-resource devices, such as sensor nodes.
J. Sens. Actuator Netw.2014, 3(2), 150-180; doi:10.3390/jsan3020150 - published 20 June 2014 Show/Hide Abstract
Abstract: Wireless sensor networks (WSNs) have attracted considerable interest in the research community, because of their wide range of applications. However, due to the distributed nature of WSNs and their deployment in remote areas, these networks are vulnerable to numerous security threats that can adversely affect their proper functioning. Resource constraints in sensor nodes mean that security mechanisms with a large overhead of computation and communication are impractical to use in WSNs; security in sensor networks is, therefore, a challenge. Access control is a critical security service that offers the appropriate access privileges to legitimate users and prevents illegitimate users from unauthorized access. However, access control has not received much attention in the context of WSNs. This paper provides an overview of security threats and attacks, outlines the security requirements and presents a state-of-the-art survey on access control models, including a comparison and evaluation based on their characteristics in WSNs. Potential challenging issues for access control schemes in WSNs are also discussed.
J. Sens. Actuator Netw.2014, 3(2), 113-149; doi:10.3390/jsan3020113 - published 22 May 2014 Show/Hide Abstract
Abstract: Understanding the dynamics of bodies of water and their impact on the global environment requires sensing information over the full volume of water. In this article, we develop a gradient-based decentralized controller that dynamically adjusts the depth of a network of underwater sensors to optimize sensing for computing maximally detailed volumetric models. We prove that the controller converges to a local minimum and show how the controller can be extended to work with hybrid robot and sensor network systems. We implement the controller on an underwater sensor network with depth adjustment capabilities. Through simulations and in-situ experiments, we verify the functionality and performance of the system and algorithm.