Resource Constraints Of Wireless Sensor Networks Research Articles

Integrity assured multi-functional multi-application secure data aggregation in wireless sensor networks (IAMFMA-SDA)

Industrial revolutions and demand of novel applications drive the development of sensors which offer continuous monitoring of remote hostile areas by collecting accurate measurement of physical phenomena. Data aggregation is considered as one of the significant energy-saving mechanism of resource constraint Wireless Sensor Networks (WSNs) which reduces bandwidth consumption by eliminating redundant data. Novel applications demand WSN to provide information about the monitoring region in multiple aspects in large scale. To meet this requirement, different kinds of sensors of different parameters are deployed in the same region which in turn demands the aggregator node to integrate diverse data in a smooth and secure manner. Novelty in applications also requires Base station (BS) to apply multiple statistical functions. Hence, we propose to develop a novel secure cost-efficient data aggregation scheme based on asymmetric privacy homomorphism to aggregate data of multiple parameters and facilitate the BS to compute multiple functions in one round of data collection by providing elaborated view of monitoring region. To meet the claim of large scale WSN which requires dynamic change in size, vector-based data collection method is adopted in our proposed scheme. The security aspect is strengthened by allowing BS to verify the authenticity of source node and validity of data received. The performance of the system is analyzed in terms of computation and communication overhead using the mathematical model and simulation results.

Q-Learning based Routing Protocol to Enhance Network Lifetime in WSNs

In resource constraint Wireless Sensor Networks (WSNs), enhancement of network lifetime has been one of the significantly challenging issues for the researchers. Researchers have been exploiting machine learning techniques, in particular reinforcement learning, to achieve efficient solutions in the domain of WSN. The objective of this paper is to apply Q-learning, a reinforcement learning technique, to enhance the lifetime of the network, by developing distributed routing protocols. Q-learning is an attractive choice for routing due to its low computational requirements and additional memory demands. To facilitate an agent running at each node to take an optimal action, the approach considers node’s residual energy, hop length to sink and transmission power. The parameters, residual energy and hop length, are used to calculate the Q-value, which in turn is used to decide the optimal next-hop for routing. The proposed protocols’ performance is evaluated through NS3 simulations, and compared with AODV protocol in terms of network lifetime, throughput and end-to-end delay.

GCRP: Grid-cycle routing protocol for wireless sensor network with mobile sink

Energy conservation is a critical issue in resource constraint wireless sensor networks. Employing mobile sink to deliver the sensed data becomes pervasive approach to conserve sensors’ limited energy. However, mobile sink makes data delivery a hard nut to crack since nodes need to know its latest location. Providing sink’s latest location by traditional flooding, erode the energy conservation goal. In this paper, we propose a Grid-Cycle Routing Protocol (GCRP) with the aim of minimizing the overhead of updating the mobile sink’s latest location. In GCRP, sensor field is partitioned into grid of cells and for each cell a grid cell head (GCH) is elected. Cycles of four GCHs is formed. Cycle(s) involving border GCHs is called exterior cycle and said to belong to a region. Another cycle involving non-boundary GCHs is called interior cycle, connecting GCHs of different regions. When sink stays at one location, it updates the nearest GCH, which in turn updates the other GCHs through exterior and interior cycle. Moreover, we propose a set of sharing rules that govern GCHs when and with who share sink’s latest location information. The performance of GCRP is evaluated at different number of nodes and compared with existing work using NS-2.31.

A Framework and Classification for Fault Detection Approaches in Wireless Sensor Networks with an Energy Efficiency Perspective

Wireless Sensor Networks (WSNs) are more and more considered a key enabling technology for the realisation of the Internet of Things (IoT) vision. With the long term goal of designing fault-tolerant IoT systems, this paper proposes a fault detection framework for WSNs with the perspective of energy efficiency to facilitate the design of fault detection methods and the evaluation of their energy efficiency. Following the same design principle of the fault detection framework, the paper proposes a classification for fault detection approaches. The classification is applied to a number of fault detection approaches for the comparison of several characteristics, namely, energy efficiency, correlation model, evaluation method, and detection accuracy. The design guidelines given in this paper aim at providing an insight into better design of energy-efficient detection approaches in resource-constraint WSNs.

Toll Fraud Detection of VoIP Service Networks in Ubiquitous Computing Environments

Voice over Internet Protocol (VoIP) is an emerging communication service that has advanced in ubiquitous computing environments. Although VoIP is inexpensive and offers additional services, there has been little provision for attacks at the weak points. With the advances of Wireless Sensor Network (WSN) technologies, the risk is increasing. Due to the resource constraints of WSN, attacks have become easier, making protection of the network more difficult. In this work, we attempt to distinguish fraud call attacks as outliers from normal calls on the basis of call detail records. We adopted and applied a Local Outlier Factor (LOF) method on real call data, which include actual fraud call attacks. Our results show the outlier detection method can be effective in detecting fraud calls. Moreover, introducing two additional attributes related to fraud call characteristics enhanced the detection performance.

Improving QOS using Artificial Neural Networks in Wireless Sensor Networks

The service provided by the Wireless Sensor Networks (WSN) should provide better quality as Quality of the network plays an important role in the improving the performance of the system. The dynamic topology and resource constraints of WSN are highly challenging in achieving QoS. Thus in this paper Quality of Service (QoS) is improved for some of the QoS parameters like packet loss and congestion. Categorization of nodes as qualified and unqualified is done using the parameters. The quality node then dynamically forms a network. A novel method to improve the QoS based on Artificial Neural Network (ANN) is used to train the unqualified nodes to make them as quality nodes. The structure of Artificial Neural Networks provides less complexity compared to other Computational Intelligence (CI) tools as wireless sensor networks are prone to many constraints like memory and energy it reduces the computation cost and time. Our Simulation results shows that the proposed system has better performance in improving the QoS by increasing the network lifetime and reducing the packet loss ratio.

Enhanced Ring Signatures Schemes for Privacy Preservation in Wireless Sensor Networks

Advancements in the domains of low-data-rate wireless networking and micro-electro-mechanical systems enabled the inception of a new networking domain, called wireless sensor network. These ad-hoc kind of networks have diversified applications in battlefield surveillance, disaster monitoring, intrusion detection etc. These networks consist plethora of sensor nodes which are severely resource constrained. As the application of the wireless sensor network is increasing, there is an emerging need for the security and privacy scheme which makes the network secure from various attacks and hide the ongoing activities in the network from a non-network entity. Privacy in wireless sensor network is yet a challenging domain to work on. Lot of work has been done to ensure privacy in the network. These relate to provide privacy in terms of the network entity and the privacy of the sensed information. Most of the solutions till date is based upon routing in the network layer, random walk based flooding, dummy data injection and cross layer solutions. Each of the schemes induce some overhead in the network. A light weight scheme is always desired for resource constraint wireless sensor networks. In this work we will propose a scheme which assures the privacy of the nodes in the network along with the privacy of the event generated in the network through a self organizing scheme. Through various simulation results the validity of our scheme among different network scenarios will be shown. We will also prove through graphical results that our proposed scheme enhances network lifetime quite satisfactorily.

Collaborative Lightweight Trust Management Scheme for Wireless Sensor Networks

The cooperative multi-hop communication in a remote infrastructureless networking environment poses a serious security threat for the design of wireless sensor networks (WSNs). Because of their vulnerability to attacks, the intrinsic and demanding assignment of WSNs is security. Earlier security solutions aimed at thwarting different types of malicious threats but failed to consider the resource constrained nature of sensor nodes. The stringent resource constraints of WSNs require a lightweight trust-based routing scheme. In this paper, we propose a collaborative lightweight trust-based (CLT) routing protocol for WSNs with minimal overhead in regard to memory and energy consumption. It does not use promiscuous mode of operation to monitor the neighboring nodes for trust derivation. CLT employs a novel trust counselor that monitors and warns the neighboring nodes whose trust falls below a warning threshold. The warning message alarms a sensor node to check and correct the packet forwarding behavior to improve its trust relationship with its neighbors. Theoretical analysis and simulation results of CLT protocol demonstrate higher packet delivery ratio, higher network lifetime, lower end-to-end delay, lower memory and energy consumption than the traditional and existing trust-based routing schemes.

A Multipath Routing Approach for Secure and Reliable Data Delivery in Wireless Sensor Networks

The severe resource constraints and challenging deployment environments of wireless sensor networks (WSNs) pose challenges for the security and reliability of data transmission for these networks. In this paper, we present and evaluate a secure and reliable routing mechanism offering different levels of security in an energy-efficient way for WSNs. Our approach uses node-disjoint routing and the selection mechanism of these paths depends on different application requirements in terms of security. The original data message is split into packets that are coded using Reed-Solomon (RS) codes and, to provide diverse levels of security, different number of fragments is encrypted related to the requested security level before being transmitted along independent node-disjoint paths. This technique makes encryption feasible for energy-constrained and delay-sensitive applications while still maintaining a robust security protection. We describe how to find the secure multipath, the number of these paths, and how to allocate fragments on each path seeking to enhance security and improve data reliability. Extensive analysis and performance evaluation show that data transmission security and reliability can be enhanced while respecting the resource constraints of WSNs.

Spatial query processing in wireless sensor networks – A survey

Wireless sensor networks (WSN) are particularly useful for obtaining data concerning events limited to a well-defined geographic region, such as a disaster site or a malfunctioning subsection of a factory plant. Such applications typically use spatial queries, which are SQL-like queries where location constraints are imposed on the collected data. Further, spatial queries allow changing the set of nodes (the region of interest) at runtime. This work surveys spatial queries in WSN. Due to the particular energy and resource constraints of WSN, spatial queries are performed by mechanisms having several stages, each of them implemented using localized distributed algorithms. This article categorizes the existing strategies for each stage, in order to ease the understanding of the state of the art. Finally, we analyze the most recent works on spatial query processing, identifying which classes of algorithms are used on each stage.

Matrix-based memory efficient symmetric key generation and pre-distribution scheme for wireless sensor networks

As wireless sensor networks (WSN) have gained popularity due to their broader applications areas, so does the need for effective security mechanisms. Encryption can be used to protect data communication, but severe resource constraints in WSN make necessary key distribution very difficult. This study addresses the problem of key establishment in WSN using a key pre-distribution scheme. In this study, the authors have proposed a symmetric key generation and pre-distribution scheme, using a symmetric matrix and generator matrix of maximum rank distance (MRD) codes. Sensor nodes are divided into groups and some information is stored at each node to enable it to generate link keys. This node division substantially improves the memory required at each node, which is approximately equal to the group size. The proposed scheme also reduces the communication overhead to setup a link key. It requires only two messages to setup a link key between any two nodes. Furthermore this scheme also provides the highest level of network connectivity and scalability. Any two nodes in the network can establish a link key and new nodes can be added at any time without changing any information on previously deployed nodes.

Negative Binomial Distribution Based Reputation Direct Update for Wireless Sensor Networks

In the reputation modeling of wireless sensor networks (WSNs) many literatures have proposed creative reputation indirect update methods, such as reputation integration, discounting, aging to eliminate, and filtering malicious reputation information. However, few have discussed the reputation direct update. In this paper, based on sound statistical theories, a negative binominal distribution method in the reputation direct update for WSNs is proposed. Results show that the proposed method is more suitable and time-saving for the reputation update of the resource constraint WSNs and can improve the computation power efficiency as well.

Arresting Particle Hijack in Multitarget Tracking

Abstract Robust, lightweight, and distributed multitarget tracking in wireless sensor networks (WSN) is discussed. Sequential Monte Carlo or particle filter is an excellent stochastic technique for approximate state estimation using Bayesian algorithms. When targets move close to each other, the signal energies generated by them get overlapped. Solving multitarget tracking problem using independent particle filters suffers from many problems, including that the target with the best likelihood hijacks the particles of nearby targets. Even in joint tracking there is potential for particles to carry labels to wrong target position. This paper proposes a dynamic-Bayesian-network-based framework called ‘Particle Filter-Merger Modeled-Maximum a Posteriori’ (PF-MM-MAP). The framework explicitly models the signal overlap by introducing additional hidden states, thereby adding robustness to the tracking process. The implementation is distributed and lightweight, keeping in view the requirements and resource constraints of WSN.

Chowkidar

Wireless sensor network (WSN) testbeds are useful because they provide a way to test applications in an environment that makes it easy to deploy experiments, configure them statically or dynamically, and gather performance information. However, WSNs are typically composed of low-cost devices and tend to be unreliable, with failures a common phenomenon. Accurate knowledge of network health status, including nodes and links of each type, is critical for correctly configuring applications on WSN testbeds and for interpreting the data collected from them. In this article we present a stabilizing protocol, Chowkidar, that provides accurate and efficient network health monitoring in WSNs. Our approach adapts the well-known problem of message-passing rooted spanning tree construction and its use in propagation of information with feedback (PIF) for the case of a WSN. The Chowkidar protocol is initiated upon demand; that is, it does not involve ongoing maintenance, and it terminates with accurate results, including detection of failure and restart during the monitoring process. Chowkidar is distinguished from others in two important ways. Given the resource constraints of WSNs, it is message-efficient in that it uses only a few messages per node. Also, it tolerates ongoing node and link failure and node restart, in contrast to requiring that faults stop during convergence. We have implemented the Chowkidar protocol as part of enabling a network health status service that is tightly integrated with a remotely accessible wireless sensor network testbed, Kansei, at The Ohio State University. We present experimental results from this testbed that validate the correctness and performance of Chowkidar. We also report on initial experiences and lessons learnt from the integration of Chowkidar with Kansei, including feedback from both testbed users and administrators who have found Chowkidar to be a useful tool for improving the accuracy and efficiency of testbed experimentation and maintenance, and the need for well-defined policies to address issues such as minimizing interference with concurrently running experiments. Finally, we discuss extensions that enhance the functionality and usability of Chowkidar.