A secure over-the-air programming scheme in wireless sensor networks

Over-The-Air dissemination of code updates in Wireless Sensor Networks (WSNs) have been researchers’ point of interest in past a few years and more importantly security challenges toward remote propagation of code update have taken the majority of efforts in this context. Many security models have been proposed to establish a balance between the energy consumption and security strengthen with having their concentration on constraint nature of WSN nodes. For authentication purposes most of them have used Merkle-Hash-Tree to avoid using multiple public cryptography operations. These models mostly have assumed an environment in which security has to be in a standard level and therefore they have not investigated the tree structure for mission-critical situations in which security has to be in maximum possible extent (e.g. military zones). Two major problems have been identified in Merkle Tree structure which is used in Seluge scheme, including: 1) an exponential growth in number of overhead packets when block size of hash algorithm used in design is increased. 2) Limitation of using hash algorithms with larger block size of 11 bytes when payload size is set to 72 bytes. Then several existing security models are investigated for possible vulnerabilities and a set of countermeasures correspondingly named Security Model Requirements (SMR) is provided. After concentrating on Seluge’s design, a new secure Over-The-Air Programming (OTAP) scheme named Seluge++ is proposed that complies with SMR and replaces the use of inefficient Merkle Tree with a novel method

Shawn: A new approach to simulating wireless sensor networks

We consider the simulation of wireless sensor networks (WSN) using a new approach. We present Shawn, an open-source discrete-event simulator that has considerable differences to all other existing simulators. Shawn is very powerful in simulating large scale networks with an abstract point of view. It is, to the best of our knowledge, the first simulator to support generic high-level algorithms as well as distributed protocols on exactly the same underlying networks.Comment: 10 pages, 2 figures, 2 tables, Latex, to appear in Design, Analysis, and Simulation of Distributed Systems 200

Minimal Energy Efficient Routing (MEER) Protocol using GSP For Sensor Network

The most important criterion while designing wireless sensor network is the consumption of energy[5,6,7]. There are many schemes cited for conservation of energy issues[1,2,8]. Again the efficient minimal energy consumption routing schemes are an important consideration. In this paper, we have proposed an energy saving scheme, named as minimal energy efficient routing (MEER) Protocol, which uses GSP (Gossip based sleep Protocol) to achieve energy efficiency in sensor networks. Here, we have compared our work with the existing work given by GSP[1] . We have shown the correctness & effectiveness of our protocol by mathematical simulation studies

Cloud Enabled Emergency Navigation Using Faster-than-real-time Simulation

State-of-the-art emergency navigation approaches are designed to evacuate civilians during a disaster based on real-time decisions using a pre-defined algorithm and live sensory data. Hence, casualties caused by the poor decisions and guidance are only apparent at the end of the evacuation process and cannot then be remedied. Previous research shows that the performance of routing algorithms for evacuation purposes are sensitive to the initial distribution of evacuees, the occupancy levels, the type of disaster and its as well its locations. Thus an algorithm that performs well in one scenario may achieve bad results in another scenario. This problem is especially serious in heuristic-based routing algorithms for evacuees where results are affected by the choice of certain parameters. Therefore, this paper proposes a simulation-based evacuee routing algorithm that optimises evacuation by making use of the high computational power of cloud servers. Rather than guiding evacuees with a predetermined routing algorithm, a robust Cognitive Packet Network based algorithm is first evaluated via a cloud-based simulator in a faster-than-real-time manner, and any "simulated casualties" are then re-routed using a variant of Dijkstra's algorithm to obtain new safe paths for them to exits. This approach can be iterated as long as corrective action is still possible.Comment: Submitted to PerNEM'15 for revie

SEPSen: Semantic event processing at the sensor nodes for energy efficient wireless sensor networks

Traditionally in WSNs, the sensor nodes are used only for capturing data that is then later analyzed in the more powerful gateway nodes. This requires a continuous communication that wastes energy at the sensor nodes and greatly reduces the overall network lifetime. We propose a semantic-based in-network data processing that reduces energy consumption and improves the scalability of heterogeneous sensor networks. Ontology fragments in each sensor node help identify the data routed through the sensor network. We have adapted a matching algorithm to process a changing knowledge base. Simulation results show that the networks' energy consumption is considerably reduced

Cross-level sensor network simulation with COOJA

Simulators for wireless sensor networks are a valuable tool for system development. However, current simulators can only simulate a single level of a system at once. This makes system development and evolution difficult since developers cannot use the same simulator for both high-level algorithm development and low-level development such as device-driver implementations. We propose cross-level simulation, a novel type of wireless sensor network simulation that enables holistic simultaneous simulation at different levels. We present an implementation of such a simulator, COOJA, a simulator for the Contiki sensor node operating system. COOJA allows for simultaneous simulation at the network level, the operating system level, and the machine code instruction set level. With COOJA, we show the feasibility of the cross-level simulation approach

On the tradeoff between privacy and energy in wireless sensor networks

Source location privacy is becoming an increasingly important property of some wireless sensor network applica- tions. The fake source technique has been proposed as an approach for handling the source location privacy problem in these situations. However, whilst the efficiency of the fake source techniques is well documented, there are several factors that limit the usefulness of current results: (i) the assumption that fake sources are known a priori, (ii) the selection of fake sources based on an prohibitively expensive pre-configuration phase and (iii) the lack of a commonly adopted attacker model. In this paper we address these limitations by investigating the efficiency of the fake source technique with respect to possible implementations, configurations and extensions that do not require a pre-configuration phase or a priori knowledge of fake sources. The results presented demonstrate that one possible implementation, in presence of a single attacker, can lead to a decrease in capture ratio of up to 60% when compared with a flooding baseline. In the presence of multiple attackers, the same implementation yields only a 30% decrease in capture ratio with respect to the same baseline. To address this problem we investigate a hybrid technique, known as phantom routing with fake sources, which achieves a corresponding 50% reduction in capture ratio

Modeling power in multi-functionality sensor network applications

Rachit Agarwal, Rafael V. Martinez-Catala, Sean Harte, Cedric Segard, Brendan O'Flynn, "Modeling Power in Multi-functionality Sensor Network Applications," sensorcomm, pp.507-512, 2008 Proceedings of the Second International Conference on Sensor Technologies and Applications, August 25-August 31 2008, Cap Esterel, FranceWith the migration of a Wireless Sensor Network (WSN) over various evolving applications, power estimation and profiling during the design cycle become critical issues and present hurdles in reducing the design time. Furthermore, with a growing size of the network, simulating the behavior of each sensor node is not feasible. It is important to devise an approach that provides a network-wide picture of power consumption and of variations in power usage under changes in the network and/or node application in the network. In this paper, we present a modular power estimation technique which simplifies the power modeling of any sensor network application. In particular, we are interested in analyzing the behavior of power consumption if one or more modules of the WSN platform in the application are changed during the design cycle or after the deployment. The proposed technique is susceptible to applications changes on the fly and is particularly beneficial in networks with large number of nodes. We perform experiments modifying parameters of a ZigBee based sensor network application such as packet size, sampling rate, functionality (encryption) and sensor types. We present the results, demonstrating an error less than 3% in all the experiments performed, and insights into the results

Measuring Power Consumption for Image Processing on Android Smartphone

The energy consumption of smartphones can be undertaken in multiple levels of hardware and software. Generally, there are two approaches in measuring power consumption of a smartphone application which are the measurement-based and estimation-based methods. The goal of this study is to compare the two power consumption measuring approaches in quantifying the power consumed by image processing applications in Android smartphone. For measurement-based approach, a simple wattmeter is designed whereas for the estimation-based approach, an Android application called the PowerTutor will be utilized. The wattmeter and PowerTutor will measure the power consumption of eight image processing methods running on modified Android library with self implemented algorithm called the CamTest. According to t-test analysis that has been conducted, the p values of all of the image processing methods show that there are no significant differences between the wattmeter and the PowerTutor application (p>0.01). Even though measurement based method is more accurate than estimation-based method in term of measuring power consumption, PowerTutor application proved it provides accurate, real-time power consumption estimation for Android platform smartphones. Application developers still can use PowerTutor as an option to determine the impact of software design on power consumption

Accuracy improvement of connectivity-based sensor network localization

The early results from connectivity-based sensor network localization suffer from disappointing accuracy. The reason is partly due to the limited information of the problem, and also the deficiencies of the algorithms. This paper proposes a two-level range/indication of connectivity between each pair of nodes, which would indicate three levels of connectivity: strong, weak or nil. Theoretically, the two-level connectivity localization problem can be modeled as a non-convex optimization problem in mathematics, which contains the convex constraints and non-convex constraints. Besides using two-level range to enrich the given information, a two-objective evolutionary algorithm is also used for searching a solution. The simulation is carried out using five different topology networks all containing 100 nodes. Simulation results have shown that better solution can be obtained by using two-level range connectivity when compared with the usual one-level range connectivity-based localization.published_or_final_versionThe 25th IEEE Canadian Conference on Electrical & Computer Engineering (CCECE 2012), Montreal, QC., 29 April-2 May 2012. In IEEE Canadian Conference on Electrical and Computer Engineering Proceedings, 2012, p. 1-