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.     

Maximizing network utilization with max–min fairness in wireless sensor networks

The state-of-the-art for optimal data-gathering in wireless sensor networks is to use additive increase algorithms to achieve fair rate allocation while implicity trying to maximize network utilization. For the quantification of the problem we present a receiver capacity model to capture the interference existing in a wireless network. We also provide empirical evidence to motivate the applicability of this model to a real CSMA based wireless network. Using this model, we explicitly formulate the problem of maximizing the network utilization subject to a max–min fair rate allocation constraint in the form of two coupled linear programs. We first show how the max–min rate can be computed efficiently for a given network. We then adopt a dual-based approach to maximize the network utilization. The analysis of the dual shows the sub-optimality of previously proposed additive increase algorithms with respect to bandwidth efficiency. Although in theory a dual-based sub-gradient search algorithm can take a long time to converge, we find empirically that setting all shadow prices to an equal and small constant value, results in near-optimal solutions within one iteration (within 2% of the optimum in 99.65% of the cases). This results in a fast heuristic distributed algorithm that has a nice intuitive explanation—rates are allocated sequentially after rank ordering flows based on the number of downstream receivers whose bandwidth they consume. We also investigate the near optimal performance of this heuristic by comparing the rank ordering of the source rates obtained from the heuristic to the solutions obtained by solving the linear program.

Non-interference topology scheme in wireless sensor networks

A novel topology scheme, cell with multiple mobile sinks method (CMMSM), is proposed in this article for the collection of information and for the environment monitoring in wireless sensor networks. The system consists of many static sensors, scattered in a large scale sensing field and multiple mobile sinks, cruising among the clusters. Conservation of energy and simplification of protocol are important design considerations in this scheme. The noninterference topology scheme largely simplifies the full-distributed communication protocol with the ability of collision avoidance and random routing. The total number of cluster heads in such a topology was analyzed, and then an approximate evaluation of the total energy consumption in one round was carried out. Simulation results show that CMMSM can save considerable energy and obtain higher throughput than low-energy adaptive clustering hierarchy (LEACH) and geographical adaptive fidelity (GAF).     

A novel mathematical model for coverage in wireless sensor network

1 Introduction With the development of the sensor, wireless communication, and computer science, many researches have been focused on the development of a novel wireless network named wireless Ad-hoc sensor networks. This network can be defined as a network that can be self-organized in Ad-hoc fashion. This includes many sensor nodes and its objective is to sense, collect, and process the information collected by the individual sensor nodes via their cooperation [2]. Because of its high pract…     

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.     

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.     

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…     

Locomotion trajectory with cooperative metrics in wireless sensor networks

Detection coverage control is one of the most important topics in the intrusion detection problem of wireless sensor networks (WSN). However, its converse, i.e., to design an object locomotion trajectory in WSN, has not received enough attention. This article proposes a heuristic algorithm, namely, the security & speed (SS) algorithm, to depict such a trajectory that takes into consideration both security and speed. The merit of the SS algorithm is its topology independency. When compared with traditional algorithms, the SS algorithm approaches the optimal trajectory better, and enjoys considerably lower computational load, and a better and adjustable tradeoff between trajectory security and speed.     

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…     

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.     

Clustering and multi-hop routing with power control in wireless sensor networks

Clustering routing protocols excel in several aspects of wireless sensor networks (WSNs). This article proposes a clustering and multihop routing protocol (CMRP). In CMRP, a node independently makes its decision to compete for becoming a cluster head or join a cluster, according to its residual energy and average broadcast power of all its neighbors. To minimize the power consumption of the cluster head, CMRP sends the data in a power-aware multihop manner to the base station (BS) through a quasi-fixed route (QFR). In addition, CMRP presents a transmission power control algorithm with dynamic intercluster neighbor position estimation (DCNPE) to save energy. Simulation results show that the performance of CMRP is better than the hybrid, energy-efficient, distributed clustering approach (HEED). In the best case, CMRP increases the sensor network lifetime by 150.2%.     

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.     

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.     

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.     

AEETC—adaptive energy-efficient timing control in wireless networks with network coding

Energy is a scarce resource in wireless networks. Network coding has been proposed recently as a means to reduce the number of transmissions and energy consumption. In this paper, we introduce timing control into network coding to further enhance its performance. It is found that when bandwidth is sufficient, the extra delay introduced by waiting for additional data to perform network coding will increase the number of codings without affecting system throughput. Both delay and throughput suffers when bandwidth is insufficient. An adaptive energy-efficient timing control algorithm called AEETC is proposed which can automatically adjust local node’s transmission behavior on the basis of the network traffic conditions. Simulation results demonstrate that AEETC increases network coding by 7% to 60% for light network load and is able to provide good performance in terms of delay, throughput and the number of successful codings.     

Pascal’s triangle-based range-free localization for anisotropic wireless networks

This paper introduces a Pascal’s triangle model to draw the potential locations and their probabilities for a normal node given the hop counts to the anchors according to the extent of detour of the shortest paths. Based on our proposed model, a Pascal’s triangle-based localization (PTL) algorithm using local connectivity information is presented for anisotropic wireless networks with a small number of anchors. The superiority of the PTL algorithm has been validated over the state-of-the-art algorithms through MATLAB simulations. We have shown that compared to the other algorithms, the PTL algorithm achieves higher localization accuracy with even fewer anchors. We have also validated the performance of the PTL algorithm in a real environment.     

Efficient cluster head selection using Naïve Bayes classifier for wireless sensor networks

Data mining and approaches based on it have always been of approaches that have been considered in solving problems in the field of computer, but on some issues, this approach has been neglected. The area of wireless sensor networks and specifically the issue of optimal determining of the cluster head node are of these issues. To solve the problem of optimal determining of the cluster head node, Naïve Bayes that is the subset of data mining techniques is used in this paper. The results obtained after simulation of the presented algorithm show that the efficiency of this algorithm is significantly higher compared with other approaches that have so far been used to solve this problem, and thus it can be said that using this algorithm will lead to improved outcomes of solving this problem.     

Range-free wireless sensor networks localization based on?hop-count quantization

Localization is one of the most important research issues in Wireless Sensor Networks (WSNs). Recently, hop-count-based localization has been proposed as a cost-effective alternative to many expensive hardware-based localization algorithms. The basic idea of many hop-count-based localization algorithms is to seek a transformation from hop-count information to distance (e.g. DV-hop algorithm of Niculescu and Nath in Global Telecommunications Conference, vol.?5, pp.?2926?C2931, 2001) or location (e.g. MDS algorithm of Shang et al. in International Symposium on Mobile Ad Hoc Networking and Computing, pp.?201?C212, 2003) information. Traditionally, hop-counts between any pair of nodes can only take on integer value regardless of relative positions of nodes in the hop. We argue that by partitioning a node??s one-hop neighbor set into three disjoint subsets according to their hop-count values, the integer hop-count can be transformed into a real number accordingly. The transformed real number hop-count is then a more accurate representation of a node??s relative position than an integer-valued hop-count. In this paper, we present a novel algorithm termed HCQ (hop-count quantization) to perform such transformation. We then use the transformed real number hop-count to solve WSNs localization problems based on the MDS (multidimensional scaling) method. Simulation results show that the performance of the MDS algorithm using the real number hop-count outperforms those which use integer hop-count values.     

Analytical general results for handoff dwell time distribution in wireless networks

1 Introduction The calling dwell time characteristic is critical for the user network planning and deployment, e.g., global system for mobile communications (GSM), as well as the next generation wireless multimedia networks, such as, the currently standar…