Management In Wireless Sensor Networks Research Articles

Design of Data Management System for Remote ECG Monitoring

This paper presents a design schema about remote electrocardiograph (ECG) monitoring system. There are three parts in this system which include hardware detection system based on MSP430, Zigbee wireless sensor network and data management software system on PC. This paper mainly provides information for study and design of the data management software system using visual C++ program to realize immediate communication of medical monitoring. The data management software system will achieve many functions such as serial communication, real-time dynamic display of 12-lead ECG waveform and physiological parameter which include Heart Rate (HR).

Game-theoretic solutions through intelligent optimization for efficient resource management in wireless visual sensor networks

We propose a quality-driven cross-layer optimization scheme for wireless direct sequence code division multiple access (DS-CDMA) visual sensor networks (VSNs). The scheme takes into account the fact that different nodes image videos with varying amounts of motion and determines the source coding rate, channel coding rate, and power level for each node under constraints on the available bit rate and power. The objective is to maximize the quality of the video received by the centralized control unit (CCU) from each node. However, since increasing the power level of one node will lead to increased interference with the rest of the nodes, simultaneous maximization of the video qualities of all nodes is not possible. In fact, there are an infinite number of Pareto-optimal solutions. Thus, we propose the use of the Nash bargaining solution (NBS), which pinpoints one of the infinite Pareto-optimal solutions, based on the stipulation that the solution should satisfy four fairness axioms. The NBS results in a mixed-integer optimization problem, which is solved using the particle swarm optimization (PSO) algorithm. The presented experimental results demonstrate the advantages of the NBS compared with alternative optimization criteria.

A survey on architectures, protocols, applications, and management in wireless sensor networks

With the recent technological advances in wireless communications, integrated digital circuits, and micro electro mechanical systems (MEMS); development of wireless sensor networks has been enabled and become dramatically feasible. Wireless sensor networks (WSNs) are large networks made of a numerous number of sensor nodes with sensing, computation, and wireless communications capabilities. Many various routing, power management, and data dissemination protocols have been designed for wireless sensor networks (WSNs) dependent on both the network architecture and the applications that it is designed for. In this paper, we present the state of the art of wireless sensor networks' architecture and design features. Also, in this paper, we introduce recent work on routing protocols for WSNs and their design goals and challenges. Also, an overview of the application that WSNs assist in is presented. Finally, several open research questions of wireless sensor networks management and issues are suggested and put forward.

Wormhole Attack Behaviour in Monte-Carlo Localization for Mobile Sensor Networks

Localization is the basic requirement for network management in Wireless Sensor Networks as it helps nodes find their absolute position coordinates and in gathering information relevant to their locations. A localization algorithm has to be dynamic, scalable and should not impose high computation or communication overhead. The localization systems are also prone to attacks. We target a localization scheme for mobile sensor networks called Monte-Carlo Localization, which study its behavior under the most dangerous attack on localization called Wormhole Attack, also known as Collusion Attack and propose a modified algorithm that can help the localization system retain its accuracy level even in the presence of attacks. Our algorithm has communication cost almost equal to that of original localization algorithm (in this case MCL) in the absence of attacks.

A Study of Routing Path Decision Method Using Mobile Robot Based on Distance Between Sensor Nodes

We propose Robot Wireless Sensor Networks (RWSNs) management method for maintaining wireless communication connectivity for a mobile robot teleoperation with considering a distance between sensor nodes. Recent studies for reducing disaster damage focus on a disaster area information gathering in underground spaces. Since information gathering activities in such post disaster underground spaces present a high risk of personal injury by secondary disasters, a lot of rescue workers were injured or killed in the past. On basis of this background, gathering information by utilizing the mobile robot is discussed in wide area. However, maintaining wireless communication infrastructures for teleoperation of a mobile rescue robot in the post-disaster underground space by various reasons. Therefore we have been discussing the wireless communication infrastructures construction method for teleoperation of the rescue robot by utilizing the RWSN. In this paper, we evaluated the proposed method for changing routing path by utilizing the RWSN in field operation test in order to confirm the availability of performance of communication connectivity and the throughputs between End-to-End communications via constructed network.

A cognitive framework for WSN based on weighted cognitive maps and Q-learning

Due to the rising popularity of Wireless Sensor Networks (WSN), there has been an increasing demand for more challenging applications. Generally speaking, such applications demand the support of Quality of Service (QoS) constraints and often multiple conflicting objectives. To address these requirements, network management becomes a critical task. However, single layer and cross-layer techniques will probably not be sufficient. Fortunately, cognitive techniques have shown great potential in improving network performance and achieving the end-to-end goals. In this paper, cognitive solutions for resource management in WSN are proposed to address the needs of challenging applications. The solutions proposed include a reasoning machine designed for the first time using the mathematical tool known as Weighted Cognitive Maps (WCM), and a learning protocol designed using the Q-learning algorithm. The WCM has powerful inference properties and can model complex systems using their underlying causal relationships. Thus, it can consider multiple conflicting objectives with low complexity. On the other hand, the learning protocol uses Q-learning to build a knowledge base that is used to enhance the performance of the WCM reasoning machine and address the end-to-end goals of the applications directly. Extensive computer simulations are used to evaluate the performance of the cognitive framework. The results show that it can efficiently consider multiple conflicting goals and constraints, thus outperforming its state-of-the-art counterparts.

Energy-efficient Secure Directed Diffusion Protocol for Wireless Sensor Networks

In wireless sensor networks, it is crucial to design and employ energy-efficient communication protocols, since nodes are battery-powered and thus their lifetimes are limited. Such constraints combined with a great number of applications used in these networks, pose many challenges (limited energy, low security…) to the design and management of wireless sensor networks. These challenges necessitate a great attention. In this paper, we present a new version of Directed Diffusion routing protocol which provides both security and energy efficiency together in wireless sensor networks.

Energy-Efficient Skycube Query Processing in Wireless Sensor Networks

With the wide application of wireless sensor network in many domains of the national economy, more and more researchers pay attentions to data management of wireless sensor network. As the main means of multi-decision and data mining, skyline query in wireless sensor network gradually becomes a focus of the researches. Resent years, skycube, an important variation of skyline query, has been deeply discussed, but due to the special properties of wireless sensor network, existing approaches could not be directly applied into the sensor environment. In this paper, skycube query in wireless sensor network is further researched and a new skycube query algorithm based on extended skyline (SCAES) is proposed in certain environment, and a new threshold skycube query algorithm based on threshold extended skyline (p-SCAES) is proposed in uncertain environment. SCAES algorithm shifts the necessary data from the network based on extended skyline and filters the data that do not belong to skycube. p-SCAES brings in the probability threshold mechanism to decrease the data transmission. Therefore, the number of data transmission in both SCAES and p-SCAES is reduced as a consequence. The experimental results show that both SCAES and p-SCAES could greatly reduce the data transmission no matter in certain or uncertain environments, while calculating the correct skycube of the network, and prolong the life span of the wireless sensor network. DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.3705

An Ontology-Based Context Model for Wireless Sensor Network (WSN) Management in the Internet of Things

Wireless sensor networks (WSNs) are an enabling technology of context-aware systems. The Internet of Things (IoT), which has attracted much attention in recent years, is an emerging paradigm where everyday objects and spaces are made context-aware and interconnected through heterogeneous networks on a global scale. However, the IoT system can suffer from poor performances when its underlying networks are not optimized. In this paper, an ontology model for representing and facilitating context sharing between network entities in WSNs is proposed for the first time. The context model aims to enable optimal context-aware management of WSNs in IoT, which will also harness the rich context knowledge of IoT systems.

A Wireless Sensor Network Service Management Strategy

Wireless sensor networks with highly dynamic characteristics and limited resources, this paper presents a simple service management Strategy. It realizes service deployment management across different clusters, the request and the response of wireless sensor is simple that based on the protocol data format of XML WSNXML between the clusters. It provides an effective method for the management of shared resources of wireless sensor network and service expansion and realizes service release and deployment management difficulties between various wireless sensor network management based on different management cluster.

Research on the Storage Management of Wireless Sensor Networks Based on Query Algorithm

For the research of a query algorithm which is suitable for large-scale wireless sensor network should consider the energy consumption of nodes and the storage consumption of nodes. Through the simulation experiment of this algorithm can make the user adjust the merger rate according to the specific situation of network and the query, so as to ensure that the multiple queries in the processing are not affected by the limited cyber source.

A Service-Oriented Wireless Sensor Network Management Strategy and it's Implementation

Wireless sensor networks with highly dynamic characteristics and limited resources, this paper presents a simple service level management protocol. It realizes service deployment management across different clusters, the request and the response of wireless sensor is simple that based on the protocol data format of XML WSNXML between the clusters. It provides an effective method for the management of shared resources of wireless sensor network and service expansion and realizes service release and deployment management difficulties between various wireless sensor network management based on different management cluster.

An optimized and power savings protocol for mobility energy-aware in wireless sensor networks

Mobility management in Wireless Sensor Networks (WSNs) is a complex problem that must be taken into account in all layers of the protocol stack. But this mobility becomes very challenging at the MAC level in order to do not degrade the energy efficiency between sensor nodes that are in communication. However, among medium access protocols, sampling protocols reflect better the dynamics of such scenarios. Nevertheless, the main problem, of such protocols, remains the management of collisions and idle listening between nodes. Previous approaches like B-MAC and X-MAC, based on sampling protocols present some shortcomings. Therefore, we address the mobility issue of WSNs that use as medium access sampling protocols. Firstly, we propose a mobile access solution based on the X-MAC protocol which remains a reference protocol. This protocol, called MoX-MAC, incorporates different mechanisms that enables to mitigate the energy consumption of mobile sensor nodes. Furthermore, we extend our former work (Ba et al. in Proc. of IEEE WMNC, 2011) by evaluating the lifetime of static nodes with respect to MoX-MAC protocol, as well determine the degree of depletion of static nodes due to the presence of mobile nodes.

A new self-diagnosing approach based on petri nets and correlation graphs for fault management in wireless sensor networks

In most fault-detection algorithms in wireless sensor networks (WSNs), each sensor compares its data with the data of neighboring nodes. The majority of comparative methods will not work properly if more than half of the neighboring nodes of a sensor are faulty. Moreover, such comparative methods are unable to detect common mode failures (CMFs). Hence, having noticed the deficiencies of the existing comparative methods and as a reaction against such problems, we introduced a novel self-diagnosing approach to reduce the effect of neighboring node's data in determining the status of nodes so that a sensor's status will be determined independently of any comparisons. A sensor will be deemed to be fault-free if its components and the inner links between the components are flawless. In this paper, the behaviors of the components of a sensor are independently analyzed by means of the proposed model based on Petri nets and the links of the sensor's components are investigated by means of the correlation graph. In addition, the authors extended and generalized the proposed method to all the nodes of a network and evaluated their operation. Simulation results showed that the modeling implemented by the HPSim tool can cover both permanent and transient faults accurately. Moreover, using the correlation graph and Pearson correlation coefficient helped us to gain confidence in the correctness of the inner links between the components of a sensor. Evaluation of the results indicated that the statistical results from the QI Macros tool were substantially similar to those from HPSim and Matlab tools. Furthermore, simulations results demonstrated that the detection accuracy and false alarm rate of the proposed method is acceptable even when the fault probability of each sensor is generally to be high. As a result, using these mechanisms leads to the development of the self-diagnosing capability in the sensors of a WSN.

Adaptive Duty Cycle Control with Queue Management in Wireless Sensor Networks

This paper proposes a control-based approach to the duty cycle adaptation for wireless sensor networks. The proposed method controls the duty cycle through the queue management to achieve high-performance under variable traffic rates. To have energy efficiency while minimizing the delay, we design a feedback controller, which adapts the sleep time to the traffic change dynamically by constraining the queue length at a predetermined value. In addition, we propose an efficient synchronization scheme using an active pattern, which represents the active time slot schedule for synchronization among sensor nodes, without affecting neighboring schedules. Based on the control theory, we analyze the adaptation behavior of the proposed controller and demonstrate system stability. The simulation results show that the proposed method outperforms existing schemes by achieving more power savings while minimizing the delay.

Redundancy Management of Multipath Routing for Intrusion Tolerance in Heterogeneous Wireless Sensor Networks

In this paper we propose redundancy management of heterogeneous wireless sensor networks (HWSNs), utilizing multipath routing to answer user queries in the presence of unreliable and malicious nodes. The key concept of our redundancy management is to exploit the tradeoff between energy consumption vs. the gain in reliability, timeliness, and security to maximize the system useful lifetime. We formulate the tradeoff as an optimization problem for dynamically determining the best redundancy level to apply to multipath routing for intrusion tolerance so that the query response success probability is maximized while prolonging the useful lifetime. Furthermore, we consider this optimization problem for the case in which a voting-based distributed intrusion detection algorithm is applied to detect and evict malicious nodes in a HWSN. We develop a novel probability model to analyze the best redundancy level in terms of path redundancy and source redundancy, as well as the best intrusion detection settings in terms of the number of voters and the intrusion invocation interval under which the lifetime of a HWSN is maximized. We then apply the analysis results obtained to the design of a dynamic redundancy management algorithm to identify and apply the best design parameter settings at runtime in response to environment changes, to maximize the HWSN lifetime.

A new key predistribution scheme for general and grid-group deployment of wireless sensor networks

Key predistribution for wireless sensor networks has been a challenging field of research because stringent resource constraints make the key predistribution schemes difficult to implement. Despite this, key predistribution scheme is regarded as the best option for key management in wireless sensor networks. Here, the authors have proposed a new key predistribution scheme. This scheme exhibits better performance than existing schemes of its kind. Moreover, our scheme ensures constant time of key establishment between two nodes. We provide some bounds on the resiliency of this scheme. Next, we use this new key predistribution scheme in a grid-group deployment of sensor nodes. The entire deployment zone is broken into square regions. The sensor nodes falling within a single square region can communicate directly. Sensor nodes belonging to different square regions can communicate by means of special nodes deployed in each of the square region. We measure the resiliency in terms of fraction of links disconnected as well as fraction of nodes and regions disconnected. We show that our key predistribution scheme when applied to grid-group deployment performs better than standard models in existence.

Key-insulated encryption based group key management for wireless sensor network

The key exposure problem is a practical threat for many security applications. In wireless sensor networks (WSNs), keys could be compromised easily due to its limited hardware protections. A secure group key management scheme is responsible for secure distributing group keys among valid nodes of the group. Based on the key-insulated encryption (KIE), we propose a group key management scheme (KIE-GKMS), which integrates the pair-wise key pre-distribution for WSN. The KIE-GKMS scheme updates group keys dynamically when adding or removing nodes. Moreover, the security analysis proves that the KIE-GKMS scheme not only obtains the semantic security, but also provides the forward and backward security. Finally, the theoretical analysis shows that the KIE-GKMS scheme has constant performance on both communication and storage costs in sensor nodes.

Property management in wireless sensor networks with overcomplete radon bases

This article presents a scalable algorithm for managing property information about moving objects tracked by a sensor network. Property information is obtained via distributed sensor observations, but will be corrupted when objects mix up with each other. The association between properties and objects then becomes ambiguous. We build a novel representation framework, exploiting an overcomplete Radon basis dictionary to model property uncertainty in such circumstances. By making use of the combinatorial structure of the basis design and sparse representations we can efficiently approximate the underlying probability distribution of the association between target properties and tracks, overcoming the exponential space that would otherwise be required. Based on the proposed theories, we design a fully distributed algorithm on wireless sensor networks. We conduct comparative simulations and the results validate the effectiveness of our approach.

Load-Balanced Clustering Algorithm With Distributed Self-Organization for Wireless Sensor Networks

Wireless sensor networks (WSNs) are composed of a large number of inexpensive power-constrained wireless sensor nodes, which detect and monitor physical parameters around them through self-organization. Utilizing clustering algorithms to form a hierarchical network topology is a common method of implementing network management and data aggregation in WSNs. Assuming that the residual energy of nodes follows the random distribution, we propose a load-balanced clustering algorithm for WSNs on the basis of their distance and density distribution, making it essentially different from the previous clustering algorithms. Simulated tests indicate that the new algorithm can build more balanceable clustering structure and enhance the network life cycle.