Coverage based inter cluster communication for load balancing in heterogeneous wireless sensor networks

Effective energy management in heterogeneous wireless sensor networks is more challenging issue compared to homogeneous wireless sensor networks. Much of the existing research focuses on homogeneous wireless sensor networks. The energy conservation schemes for the homogeneous wireless sensor networks do not perform efficiently when applied to heterogeneous wireless sensor networks. The proposed algorithm in this paper exploits the redundancy properties of the wireless sensor networks and also changes the inter cluster communication pattern depending on the energy condition of the high energy nodes during the life cycle of the heterogeneous wireless sensor networks. Performance studies indicate that the proposed algorithm effectively solves the problem of load balancing across the network and is more energy efficient compared to multi hop versions of the standard low energy adaptive clustering hierarchy protocol.     

An automated sensor nodes’ speed estimation for wireless sensor networks

Wireless sensor networks (WSNs) have become more and more notorious thanks to their numerous advantages. But, some of the WSN weaknesses, inherent to sensor nodes’ particularities (low memory, finite battery, etc.), make these networks vulnerable especially for some particular scenarios such as nodes’ mobility which alters the correct network functioning and completely compromises its normal behavior. Thus, we propose in this paper a novel mobility prediction model called the general Bayesian-based mobility prediction (G-BMP) model where sensor nodes’ speed values are derived based on a Bayesian inference paradigm and upon the occurrence of “expired links” and “non-expired links” events. Moreover, to make the implementation of G-BMP possible on sensor devices, we introduce some simplifications during the computation and the transmission of speed distributions. The evaluation of G-BMP using python illustrates the accuracy of the model in deriving the correct speed values in a timely manner. We also compare the performance of G-BMP to the native BMP model that only considers the expired link events when updating the nodes’ speed distributions. The results show that the convergence to real speed values within sensor nodes is faster with G-BMP than that with the native BMP model. In addition, all the simulations illustrate the accuracy of the simplifications used to reduce the overhead generated by the frequent exchange of speed distributions.     

Identity-based key agreement and encryption for wireless sensor networks

1 Introduction WSN has received considerable attention during last decade [1?4] (see, for example, the proceedings of the ACM and IEEE Workshops on WSN). It has wide variety of applications, including military sensing and tracking, environment and securit…     

Robust multi-path routing for dynamic topology in wireless sensor networks

Wireless sensor networks are being widely researched and are expected to be used in several scenarios. On the leading edge of treads, on-demand, high-reliability, and low-latency routing protocol is desirable for indoor environment applications. This article proposes a routing scheme called robust multi-path routing that establishes and uses multiple node-disjoint routes. Providing multiple routes helps to reduce the route recovery process and control the message overhead. The performance comparison of this protocol with dynamic source routing (DSR) by OPNET simulations shows that this protocol is able to achieve a remarkable improvement in the packet delivery ratio and average end-to-end delay.     

An energy efficient clustering routing algorithm for wireless sensor networks

~~An energy efficient clustering routing algorithm for wireless sensor networks1. Mainwaring A, Polastre J, Szewczyk R, et al. Wireless sensor networks for habitat monitoring. Proceedings of the ACM International Workshop on Wireless Sensor Networks and A…     

Providing trust in wireless sensor networks using a bio-inspired technique

Wireless Sensor Networks (WSNs) are becoming more and more spread and both industry and academia are focusing their research efforts in order to improve their applications. One of the first issues to solve in order to achieve that expected improvement is to assure a minimum level of security in such a restrictive environment. Even more, ensuring confidence between every pair of interacting nodes is a critical issue in this kind of networks. Under these conditions we present in this paper a bio-inspired trust and reputation model, called BTRM-WSN, based on ant colony systems aiming at providing trust and reputation in WSNs. Experiments and results demonstrate the accuracy, robustness and lightness of the proposed model in a wide set of situations.     

Greedy algorithms for actor redeployment in wireless sensor–actor networks

In a wireless sensor–actor network, an actor usually has to provide services as soon as the actor receives the event signals from the sensors. Therefore, the performance of a wireless sensor–actor network depends on the actor deployment. In many circumstances, actors may fail or go out to deal with events, and thus, the sensors covered by the missing actors could be not to be reachable in time. This introduces the necessity of actor redeployment. In this paper, we study the problems of redeploying actors to maximize the number of sensors able to be covered by actors and to maximize the decrease of the residual distances of sensors, respectively. Both problems are shown to be NP-complete. Additionally, we prove that the greedy algorithm for each problem has an approximation ratio of 2. Simulations show that the greedy algorithm for each problem performs well.     

Energy efficient TDMA-based MAC protocol associated with GAF for wireless sensor networks

The design of media access control (MAC) protocol for wireless sensor networks (WSNs) with the idea of cross layer attracts more and more attention. People can improve the MAC protocol by obtaining certain information regarding the network layer and physical layer. This article synthesizes and optimizes certain cross-layer protocols which have existed. On the basis of the routing, topology information in the network layer, and transmission power information in the physical layer, the time slot assignment algorithm has been improved in the MAC layer. By using geographical adaptive fidelity algorithm (GAF) to divide the grids, controlling of transmission power and scheduling the work/sleep duty cycle for sensor nodes, a new MAC protocol has been proposed to decrease energy consumption and enlarge the lifetime of WSNs. Simulation results show that the MAC protocol functions well.     

The λMAC framework: redefining MAC protocols for wireless sensor networks

Most current WSN MAC protocol implementations have multiple tasks to perform—deciding on correct timing, sending of packets, sending of acknowledgements, etc. However, as much of this is common to all MAC protocols, there is duplication of functionality, which leads to larger MAC protocol code size and therefore increasing numbers of bugs. Additionally, extensions to the basic functionality must be separately implemented in each MAC protocol. In this paper, we look at a different way to design a MAC protocol, focusing on the providing of interfaces which can be used to implement the common functionality separately. This leaves the core of the MAC protocol, determining only when to send, which is substantially different for each protocol. We also look at some examples of MAC extensions that this approach enables. We demonstrate a working implementation of these principles as an implementation of B-MAC for TinyOS, and compare it with the standard TinyOS B-MAC implementation. We show a 35% smaller code size, with the same overall functionality but increased extensibility, and while maintaining similar performance. We also present results and experiences from using the same framework to implement T-MAC, LMAC, and Crankshaft. All are demonstrated with data from real-world experience using our 24 node testbed.     

Looking for network functionalities’ extension by avoiding energy-compromised hotspots in wireless sensor networks

The vast literature on the wireless sensor research community contains many valuable proposals for managing energy consumption, the most important factor that determines sensors’ lifetime. Interesting researches have been facing this requirement by focusing on the extension of the entire network lifetime: either by switching between node states (active, sleep) or by using energy-efficient routing. We argue that a better extension of the network lifetime can be obtained if an efficient combination of management mechanisms can be performed at the energy of each single sensor and at the load distribution over the network. Considering these two accuracy levels (i.e., node and network), this paper presents a new approach that uses cost functions to choose energy-efficient routes. In particular, by making different energy considerations at a node level, our approach distributes routing load, avoiding, thus, energy-compromised hotspots that may cause network disconnections. The proposed cost functions have completely decentralized and adaptive behavior and take into consideration the end-to-end energy consumption, the remaining energy of nodes, and the number of transmissions a node can make before its energy depletion. Our simulation results show that, though slightly increasing path lengths from sensor to sink nodes, some proposed cost functions (1) improve significantly the network lifetime for different neighborhood density degrees, while (2) preserving network connectivity for a longer period of time.     

Protocol for the application of cooperative MIMO based on clustering in sparse wireless sensor networks

Wireless sensor networks (WSN) using cooperative multiple-input multiple-output (MIMO) communication are effective tools to collect data in several environments. However, how to apply cooperative MIMO in WSN remains a critical challenge, especially in sparse WSN. In this article, a novel clustering scheme is proposed for the application of cooperative MIMO in sparse WSN by extending the traditional low-energy adaptive clustering hierarchy (LEACH) protocol. This clustering scheme solves the problem that the cluster heads (CH) cannot find enough secondary cluster heads (SCH), which are used to cooperate and inform multiple-antenna transmitters with CHs. On the basis of this protocol, the overall energy consumption of the networks model is developed, and the optimal number of CHs is obtained. The simulation results show that this protocol is feasible for the sparse WSN. The simulation results also illustrate that this protocol provides significant energy efficiencies, even after allowing for additional overheads.     

Joint scheduling and routing using space–time graphs for TDM wireless mesh networks

This paper presents a novel algorithm for joint routing and scheduling in TDM wireless mesh networks. We introduce a new construct, called a “space–time graph,” which incorporates the spatial and temporal aspects of routing in one structure by replicating a spatial network connectivity graph in layers along the time dimension. The power of the space–time graph lies in the fact that a path from one node to another in it specifies both a physical route in space as well as a schedule in time for a message. Hence the complicated and intractable problem of routing and scheduling reduces to the relatively simpler problem of determining shortest paths in a graph. Through simulations we show that a simply greedy algorithm on the space–time graph outperforms two state-of-the-art methods in terms of time taken to successfully transmit a set of messages from their sources to their destinations.     

Robust encryption method based on AES-CBC using elliptic curves Diffie–Hellman to secure data in wireless sensor networks

Wireless Networks - Secure data is a foremost topic in wireless sensor networks since data are transmitted through wireless channels where attackers may get access to critical information....     

Efficient fault-tolerant routing in IoT wireless sensor networks based on path graph flow modeling with Marchenko–Pastur distribution (EFT-PMD)

Wireless Networks - In the internet of things (IoT) based wireless sensor network (WSN), the nodes are scattered to segregate the rapt data in the relevant field of application. In general, sensor...