Search results

The purpose of this paper is to propose a receding horizon control approach for the problem of locating unknown wireless sensor networks by using a mobile robot.

A control framework is used and consists of two levels: one is a decision level, while the other is a control level. In the decision level, a spatiotemporal probability occupancy grid method is used to give the possible positions of all nodes in sensor networks, where the posterior probability distributions of sensor nodes are estimated by capturing the transient signals. In the control level, a virtual robot is designed to move along the edge of obstacles such that the problem of obstacle avoidance can be transformed into a coordination problem of multiple robots. On the basis of the possible positions of sensor nodes and virtual robots, a receding horizon control approach is proposed to control mobile robots to locate sensor nodes, where a temporary target position method is utilized to avoid several special obstacles.

When the number of obstacles increases, the average localization errors between the actual locations and the estimated locations significantly increase.

The proposed control approach can guide the mobile robot to avoid obstacles and deal with the corresponding dynamical events so as to locate all sensor nodes for an unknown wireless network.

Wireless Multimedia Sensor Network (WMSN) is expected to be a key technology for future network. The multimodal information along with very low-cost availability of the camera sensor nodes is promoting the extensive use of audio, image and video in various real-time implementations. The purpose of this paper is to study various routing issues and the effect of mobility on existing solutions for the applications in future internet.

This paper conducts a survey of the various methodologies for routing and the vital issues in the design of routing protocols for WMSN, and it also discusses about the effect of mobility on various routing methodologies of WMSN. WMSN ubiquitously performs data acquisition, processing and routing for scalar and multimedia data in a mobile environment. The routing protocols should be adaptive in nature and should have a dynamic approach to service effectively for future network. Many authors proposed the mobility of sink to improve lifetime of the network. This paper discusses some effective approaches for the network where not only the sink node but also some of the sensor nodes are mobile.

During the survey, the performance and lifetime of the network are discussed, other parameters like delay, packet loss, energy consumption and simulators used for implementation are also discussed.

The techniques in this paper represent a considerable solution for mobility issues in future internet applications.

The importance of mobile services in our everyday life is growing while at the same time new interoperability issues arise due to hardware and software heterogeneity. Therefore, new architectural paradigms and models are needed to enhance software engineering methodologies with regard to platform independence and interoperability. This paper describes an UML pattern based approach for developing reconfigurable autonomous mobile services. Through the analysis of an mcommerce project, the relevance of our proposed architecture will be explained. Our focus lays on a generic reconfiguration mechanism based on profile matching from software modules. This profiling part will be further described and discussed. Finally, the applicability of our approach is investigated within a project about reconfigurable indoor navigation computers and a project about robot assisted sensor networks.

This paper aims to provide an acceptable level of security while taking into account limited capabilities of the sensors. This paper proposes a mobile approach to securing data exchanged by structured nodes in a cluster.

The approach is based on mobile nodes with significant calculation and energy resources that allow cryptographic key management and periodic rekeying. However, mobility in wireless sensor networks aims to increase the security and lifetime of the entire network. The technical methods used in this paper are based on cryptography elliptic curves and key management through a balanced binary tree.

To maintain the effectiveness of critical applications based on wireless sensor networks, a good level of nodes security must be ensured, taking into account their limited energy and computing. Collaboration between powerful mobile nodes provides better coverage and a good key management. Owing to the significant capabilities of the mobile nodes, they can be used to secure critical applications at the same time if needed in applications requiring difficult operations.

To compare the performance of the proposed approach with other mobile algorithms, the following metrics are focused on: the energy consumed by normal sensors and cluster heads, the number of packets exchanged during key installation, time to generate and distribute cryptographic keys and the memory used by the different sensors to store keys.

In particular, this paper aims to systematically analyze a few prominent wireless sensor network (WSN) clustering routing protocols and compare these different approaches according to the taxonomy and several significant metrics.

In this paper, the authors have summarized recent research results on data routing in sensor networks and classified the approaches into four main categories, namely, data-centric, hierarchical, location-based and quality of service (QoS)-aware, and the authors have discussed the effect of node placement strategies on the operation and performance of WSNs.

Performance-controlled planned networks, where placement and routing must be intertwined and everything from delays to throughput to energy requirements is well-defined and relevant, is an interesting subject of current and future research. Real-time, deadline guarantees and their relationship with routing, mac-layer, duty-cycles and other protocol stack issues are interesting issues that would benefit from further research.

Energy consumption has always been the most serious issue to consider while deploying wireless sensor networks (WSNs). Sensor nodes are limited in power, computational capacities and memory so reporting the occurrence of specific events, such as fire or flooding, as quickly as possible using minimal energy resources is definitely a challenging issue. The purpose of this paper is to propose a new, reactive and energy‐efficient scheme for reporting events. In this scheme, nodes that detect a certain event will organize themselves into a cluster, elect a clusterhead that will collect data from the cluster members, aggregate it and forward it to the mobile sink.

In order to evaluate the scheme, a new sensor node model was designed, where the network layer is implemented from scratch. This layer contains the state process model of the algorithm which was made available through a high‐fidelity process modeling methodology.

Simulation results show that a high‐event notification delivery ratio and a significant energy saving is achieved by deploying the proposed sensor node model; comparisons with existing methods show the efficiency of using the new scheme.

The new contribution in this paper is a novel, reactive and energy‐efficient scheme for reporting events over WSNs. The concept introduced in this paper will decrease energy consumption inside the network and, thus, improve its lifetime.

This paper aims to provide prolonging network lifetime and optimizing energy consumption in mobile wireless sensor networks (MWSNs). Forming clusters of mobile nodes is a great task owing to their dynamic nature. Such clustering has to be performed with a higher consumption of energy. Perhaps sensor nodes might be supplied with batteries that cannot be recharged or replaced while in the field of operation. One optimistic approach to handle the issue of energy consumption is an efficient way of cluster organization using the particle swarm optimization (PSO) technique.

In this paper two improved versions of centralized PSO, namely, unequal clustering PSO (UC-PSO) and hybrid K-means clustering PSO (KC-PSO), are proposed, with a focus of achieving various aspects of clustering parameters such as energy consumption, network lifetime and packet delivery ratio to achieve energy-efficient and reliable communication in MWSNs.

Theoretical analysis and simulation results show that improved PSO algorithms provide a balanced energy consumption among the cluster heads and increase the network lifetime effectively.

In this work, each sensor node transmits and receives packets at same energy level only. In this work, focus was on centralized clustering only.

To validate the proposed swarm optimization algorithm, a simulation-based performance analysis has been carried out using NS-2. In each scenario, a given number of sensors are randomly deployed and performed in a monitored area. In this work, simulations were carried out in a 100 × 100 m² network consisting 200 nodes by using a network simulator under various parameters. The coordinate of base station is assumed to be 50 × 175. The energy consumption due to communication is calculated using the first-order radio model. It is considered that all nodes have batteries with initial energy of 2 J, and the sensing range is fixed at 20 m. The transmission range of each node is up to 25 m and node mobility is set to 10 m/s.

This proposed work utilizes the swarm behaviors and targets the improvement of mobile nodes’ lifetime and energy consumption.

PSO algorithms have been implemented for dynamic sensor nodes, which optimize the clustering and CH selection in MWSNs. A new fitness function is evaluated to improve the network lifetime, energy consumption, cluster formation, packet transmissions and cluster head selection.

This paper aims to provide a prolonging network lifetime and optimizing energy consumption in mobile wireless sensor networks (MWSNs). MWSNs have characteristics of dynamic topology due to the factors such as energy consumption and node movement that lead to create a problem in lifetime of the sensor network. Node clustering in wireless sensor networks (WSNs) helps in extending the network life time by reducing the nodes’ communication energy and balancing their remaining energy. It is necessary to have an effective clustering algorithm for adapting the topology changes and improve the network lifetime.

This work consists of two centralized dynamic genetic algorithm-constructed algorithms for achieving the objective in MWSNs. The first algorithm is based on improved Unequal Clustering-Genetic Algorithm, and the second algorithm is Hybrid K-means Clustering-Genetic Algorithm.

Simulation results show that improved genetic centralized clustering algorithm helps to find the good cluster configuration and number of cluster heads to limit the node energy consumption and enhance network lifetime.

In this work, each node transmits and receives packets at the same energy level throughout the solution. The proposed approach was implemented in centralized clustering only.

The main reason for the research efforts and rapid development of MWSNs occupies a broad range of circumstances in military operations.

The research highly gains impacts toward mobile-based applications.

A new fitness function is proposed to improve the network lifetime, energy consumption and packet transmissions of MWSNs.

The paper aims to investigate performance benefits associated with adopting a mobile wireless sensor network (WSN). Sensor nodes are generally energy constrained due to the latter being acquired from onboard battery cells. If one or more sensor nodes fail, possible coverage holes may be created which could invariantly lead to a reduced network lifetime. The paper proposes that instead of rendering the entire WSN inoperative, sensor nodes should physically change position within the region of interest thus adaptively altering the WSN topology with a view of recovering from failures. This type of motion will be referred to as “self healing”.

This paper presents a mobility scheme based on Bayesian networks for predictive reasoning (BayesMob) which is essentially a distributed self healing algorithm for coordinating physical relocation of sensor nodes. Using the algorithm, sensor nodes can predict the performance of the WSN in terms of coverage given that the node moves in a given direction. The evidence for this hypothesis is acquired from local neighborhood information.

The paper compares BayesMob with an alternative algorithm – Coverage Fidelity Algorithm – and shows that BayesMob maintains a higher level WSN coverage for a greater percentage of failures, thus increasing the useful lifetime of the WSN.

The physical relocation of sensor nodes will incur energy overhead, therefore the tradeoffs between all application criteria should be investigated before implementation.

This paper presents a Bayesian network based motion coordination algorithm for WSN which repairs coverage holes caused by energy exhaustion and/or abrupt node failures.

Programming Sensor Networks currently is a subtle task not because of enormous amount of code but due to inherent limitations of embedded hardware like the power, memory, network bandwidth and clock speed. In addition, there are very few programming abstractions and standards available which lead to close coupling between the application code and the embedded OS requiring understanding of low‐level primitives during implementation. A Middleware can provide glue code between the applications and the heterogeneity of devices by providing optimized set of services for autonomously managing the resources and functionality of wireless nodes in a distributed wireless sensor network. This paper presents an autonomous middleware framework for low power distributed wireless sensor networks that support adaptive sensor functionality, context aware communications, clustering, quality of service and faulttolerance. Finally an application on how to use the autonomous middleware is illustrated on the Envelope System Research Apparatus (ESRA).