A Green Approach for Selfish Misbehavior Detection in 802.11-Based Wireless Networks

IEEE 802.11 is one of the most well-established and widely used standard for wireless LAN. Its Medium Access control (MAC) layer assumes that the devices adhere to the standard’s rules and timers to assure fair access and sharing of the medium. However, wireless cards driver flexibility and configurability make it possible for selfish misbehaving nodes to take advantages over the other well-behaving nodes. The existence of selfish nodes degrades the QoS for the other devices in the network and may increase their energy consumption. In this paper we propose a green solution for selfish misbehavior detection in IEEE 802.11-based wireless networks. The proposed scheme works in two phases: Global phase which detects whether the network contains selfish nodes or not, and Local phase which identifies which node or nodes within the network are selfish. Usually, the network must be frequently examined for selfish nodes during its operation since any node may act selfishly. Our solution is green in the sense that it saves the network resources as it avoids wasting the nodes energy by examining all the individual nodes of being selfish when it is not necessary. The proposed detection algorithm is evaluated using extensive OPNET simulations. The results show that the Global network metric clearly indicates the existence of a selfish node while the Local nodes metric successfully identified the selfish node(s). We also provide mathematical analysis for the selfish misbehaving and derived formulas for the successful channel access probability.

Reliable link quality estimation in low-power wireless networks and its impact on tree-routing

Radio link quality estimation is essential for protocols and mechanisms such as routing, mobility management and localization, particularly for low-power wireless networks such as wireless sensor networks. Commodity Link Quality Estimators (LQEs), e.g. PRR, RNP, ETX, four-bit and RSSI, can only provide a partial characterization of links as they ignore several link properties such as channel quality and stability. In this paper, we propose F-LQE (Fuzzy Link Quality Estimator, a holistic metric that estimates link quality on the basis of four link quality properties—packet delivery, asymmetry, stability, and channel quality—that are expressed and combined using Fuzzy Logic. We demonstrate through an extensive experimental analysis that F-LQE is more reliable than existing estimators (e.g., PRR, WMEWMA, ETX, RNP, and four-bit) as it provides a finer grain link classification. It is also more stable as it has lower coefficient of variation of link estimates. Importantly, we evaluate the impact of F-LQE on the performance of tree routing, specifically the CTP (Collection Tree Protocol). For this purpose, we adapted F-LQE to build a new routing metric for CTP, which we dubbed as F-LQE/RM. Extensive experimental results obtained with state-of-the-art widely used test-beds show that F-LQE/RM improves significantly CTP routing performance over four-bit (the default LQE of CTP) and ETX (another popular LQE). F-LQE/RM improves the end-to-end packet delivery by up to 16%, reduces the number of packet retransmissions by up to 32%, reduces the Hop count by up to 4%, and improves the topology stability by up to 47%.

Replication vs erasure coding in data centric storage for wireless sensor networks

In-network storage of data in wireless sensor networks contributes to reduce the communications inside the network and to favor data aggregation. In this paper, we consider the use of n out of m codes and data dispersal in combination to in-network storage. In particular, we provide an abstract model of in-network storage to show how n out of m codes can be used, and we discuss how this can be achieved in five cases of study. We also define a model aimed at evaluating the probability of correct data encoding and decoding, we exploit this model and simulations to show how, in the cases of study, the parameters of the n out of m codes and the network should be configured in order to achieve correct data coding and decoding with high probability.

Distributed Forest Fire Monitoring Using Wireless Sensor Networks

Disaster management is one of the most relevant application fields of wireless sensor networks. In this application, the role of the sensor network usually consists of obtaining a representation or a model of a physical phenomenon spreading through the affected area. In this work we focus on forest firefighting operations, proposing three fully distributed ways for approximating the actual shape of the fire. In the simplest approach, a circular burnt area is assumed around each node that has detected the fire and the union of these circles gives the overall fire’s shape. However, as this approach makes an intensive use of the wireless sensor network resources, we have proposed to incorporate two in-network aggregation techniques, which do not require considering the complete set of fire detections. The first technique models the fire by means of a complex shape composed of multiple convex hulls representing different burning areas, while the second technique uses a set of arbitrary polygons. Performance evaluation of realistic fire models on computer simulations reveals that the method based on arbitrary polygons obtains an improvement of 20% in terms of accuracy of the fire shape approximation, reducing the overhead in-network resources to 10% in the best case.

Response Time Analysis of Slotted WiDOM in Noisy Wireless Channels

International Conference on Emerging Technologies and Factory Automation (ETFA 2015), Industrial Communication Technologies and Systems, Luxembourg, Luxembourg.

Host-Tailored Sensors for Leucomalachite Green Potentiometric Measurements

A new biomimetic sensor for leucomalachite green host-guest interactions and potentiometric transduction is presented. The artificial host was imprinted in methacrylic acid or acrylamido-2-methyl-1-propanesulfonic acid-based polymers. Molecularly imprinted particles were dispersed in 2-nitrophenyloctyl ether and trapped in poly(vinyl chloride). The potentiometric sensors exhibited a near-Nernstian response in steady state evaluations, with slopes and detection limits ranging from 45.8 to 81.2 mV and 0.28 to 1.01 , respectively. They were independent from the pH of test solutions within 3 to 5. Good selectivity was observed towards drugs that may contaminate water near fish cultures, such as oxycycline, doxycycline, enrofloxacin, trimethoprim, creatinine, chloramphenicol, and dopamine. The sensors were successfully applied to field monitoring of leucomalachite green in river samples. The method offered the advantages of simplicity, accuracy, applicability to colored and turbid samples, and automation feasibility.

Biomimetic sensors of molecularly-imprinted polymers for chlorpromazine determination

A new man-tailored biomimetic sensor for Chlorpromazine host-guest interactions and potentiometric transduction is presented. The artificial host was imprinted within methacrylic acid, 2-vinyl pyridine and 2-acrylamido-2-methyl-1-propanesulfonic acid based polymers. Molecularly imprinted particles were dispersed in 2-nitrophenyloctyl ether and entrapped in a poly(vinyl chloride) matrix. Slopes and detection limits ranged 51–67 mV/decade and 0.46–3.9 μg/mL, respectively, in steady state conditions. Sensors were independent from the pH of test solutions within 2.0–5.5. Good selectivity was observed towards oxytetracycline, doxytetracycline, ciprofloxacin, enrofloxacin, nalidixic acid, sulfadiazine, trimethoprim, glycine, hydroxylamine, cysteine and creatinine. Analytical features in flowing media were evaluated on a double-channel manifold, with a carrier solution of 5.0 × 10−2 mol/L phosphate buffer. Near-Nernstian response was observed over the concentration range 1.0 × 10−4 to 1.0 × 10−2 mol/L. Average slopes were about 48 mV/decade. The sensors were successfully applied to field monitoring of CPZ in fish samples, offering the advantages of simplicity, accuracy, automation feasibility and applicability to complex samples.

Biomimetic norfloxacin sensors made of molecularly-imprinted materials for potentiometric transduction

A biomimetic sensor for norfloxacin is presented that is based on host-guest interactions and potentiometric transduction. The artificial host was imprinted into polymers made from methacrylic acid and/or 2-vinyl pyridine. The resulting particles were entrapped in a plasticized poly(vinyl chloride) (PVC) matrix. The sensors exhibit near-Nernstian response in steady state evaluations, and detection limits range from 0.40 to 1.0 μg mL−1, respectively, and are independent of pH values at between 2 and 6, and 8 and 11, respectively. Good selectivity was observed over several potential interferents. In flowing media, the sensors exhibit fast response, a sensitivity of 68.2 mV per decade, a linear range from 79 μM to 2.5 mM, a detection limit of 20 μg mL−1, and a stable baseline. The sensors were successfully applied to field monitoring of norfloxacin in fish samples, biological samples, and pharmaceutical products.

Carnitine tailored Sensors on Surface Molecular Imprinting based on Graphene layers

III Jornadas de Electroquímica e Inovação (Electroquímica e Nanomateriais), na Universidade de Trás-os-Montes e Alto Douro, Vila Real, 16 a 17 de Setembro de 2013

Host-Tailored Sensors for Carnitine Potentiometric Measurements based on Surface Molecular Imprinting

Graduate Student Symposium on Molecular Imprinting 2013, na Queen’s University, Belfast, United Kingdom, 15 a 17 de Agosto de 2013

Bringing Context Awareness to IoT-Based Wireless Sensor Networks

IEEE International Conference on Pervasive Computing and Communications (PerCom). 23 to 26, Mar, 2015, PhD Forum. Saint Louis, U.S.A..

On the Scalability of Constructive Interference in Low-Power Wireless Networks

12th European Conference on Wireless Sensor Networks (EWSN 2015). 9 to 11, Feb, 2015. Porto, Portugal

A framework for using real data with distributed low cost sensors

Currently, due to the widespread use of computers and the internet, students are trading libraries for the World Wide Web and laboratories with simulation programs. In most courses, simulators are made available to students and can be used to proof theoretical results or to test a developing hardware/product. Although this is an interesting solution: low cost, easy and fast way to perform some courses work, it has indeed major disadvantages. As everything is currently being done with/in a computer, the students are loosing the “feel” of the real values of the magnitudes. For instance in engineering studies, and mainly in the first years, students need to learn electronics, algorithmic, mathematics and physics. All of these areas can use numerical analysis software, simulation software or spreadsheets and in the majority of the cases data used is either simulated or random numbers, but real data could be used instead. For example, if a course uses numerical analysis software and needs a dataset, the students can learn to manipulate arrays. Also, when using the spreadsheets to build graphics, instead of using a random table, students could use a real dataset based, for instance, in the room temperature and its variation across the day. In this work we present a framework which uses a simple interface allowing it to be used by different courses where the computers are the teaching/learning process in order to give a more realistic feeling to students by using real data. A framework is proposed based on a set of low cost sensors for different physical magnitudes, e.g. temperature, light, wind speed, which are connected to a central server, that the students have access with an Ethernet protocol or are connected directly to the student computer/laptop. These sensors use the communication ports available such as: serial ports, parallel ports, Ethernet or Universal Serial Bus (USB). Since a central server is used, the students are encouraged to use sensor values results in their different courses and consequently in different types of software such as: numerical analysis tools, spreadsheets or simply inside any programming language when a dataset is needed. In order to do this, small pieces of hardware were developed containing at least one sensor using different types of computer communication. As long as the sensors are attached in a server connected to the internet, these tools can also be shared between different schools. This allows sensors that aren't available in a determined school to be used by getting the values from other places that are sharing them. Another remark is that students in the more advanced years and (theoretically) more know how, can use the courses that have some affinities with electronic development to build new sensor pieces and expand the framework further. The final solution provided is very interesting, low cost, simple to develop, allowing flexibility of resources by using the same materials in several courses bringing real world data into the students computer works.

A module for Data Centric Storage in ns-3

Demo in Workshop on ns-3 (WNS3 2015). 13 to 14, May, 2015. Castelldefels, Spain.

Towards the Development of XDense, A Sensor Network for Dense Sensing

Poster in 12th European Conference on Wireless Sensor Networks (EWSN 2015). 9 to 11, Feb, 2015, pp 24-25. Porto, Portugal.