4,812 research outputs found
Distributed Object Tracking Using a Cluster-Based Kalman Filter in Wireless Camera Networks
Local data aggregation is an effective means to save sensor node energy and prolong the lifespan of wireless sensor networks. However, when a sensor network is used to track moving objects, the task of local data aggregation in the network presents a new set of challenges, such as the necessity to estimate, usually in real time, the constantly changing state of the target based on information acquired by the nodes at different time instants. To address these issues, we propose a distributed object tracking system which employs a cluster-based Kalman filter in a network of wireless cameras. When a target is detected, cameras that can observe the same target interact with one another to form a cluster and elect a cluster head. Local measurements of the target acquired by members of the cluster are sent to the cluster head, which then estimates the target position via Kalman filtering and periodically transmits this information to a base station. The underlying clustering protocol allows the current state and uncertainty of the target position to be easily handed off among clusters as the object is being tracked. This allows Kalman filter-based object tracking to be carried out in a distributed manner. An extended Kalman filter is necessary since measurements acquired by the cameras are related to the actual position of the target by nonlinear transformations. In addition, in order to take into consideration the time uncertainty in the measurements acquired by the different cameras, it is necessary to introduce nonlinearity in the system dynamics. Our object tracking protocol requires the transmission of significantly fewer messages than a centralized tracker that naively transmits all of the local measurements to the base station. It is also more accurate than a decentralized tracker that employs linear interpolation for local data aggregation. Besides, the protocol is able to perform real-time estimation because our implementation takes into consideration the sparsit- - y of the matrices involved in the problem. The experimental results show that our distributed object tracking protocol is able to achieve tracking accuracy comparable to the centralized tracking method, while requiring a significantly smaller number of message transmissions in the network
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications
Wireless sensor networks monitor dynamic environments that change rapidly
over time. This dynamic behavior is either caused by external factors or
initiated by the system designers themselves. To adapt to such conditions,
sensor networks often adopt machine learning techniques to eliminate the need
for unnecessary redesign. Machine learning also inspires many practical
solutions that maximize resource utilization and prolong the lifespan of the
network. In this paper, we present an extensive literature review over the
period 2002-2013 of machine learning methods that were used to address common
issues in wireless sensor networks (WSNs). The advantages and disadvantages of
each proposed algorithm are evaluated against the corresponding problem. We
also provide a comparative guide to aid WSN designers in developing suitable
machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial
Improving energy efficiency in wireless sensor networks through scheduling and routing
This paper is about the wireless sensor network in environmental monitoring
applications. A Wireless Sensor Network consists of many sensor nodes and a
base station. The number and type of sensor nodes and the design protocols for
any wireless sensor network is application specific. The sensor data in this
application may be light intensity, temperature, pressure, humidity and their
variations .Clustering and routing are the two areas which are given more
attention in this paper.Comment: 7 Pages, 2 Figures and 1 Tabl
AM-DisCNT: Angular Multi-hop DIStance based Circular Network Transmission Protocol for WSNs
The nodes in wireless sensor networks (WSNs) contain limited energy
resources, which are needed to transmit data to base station (BS). Routing
protocols are designed to reduce the energy consumption. Clustering algorithms
are best in this aspect. Such clustering algorithms increase the stability and
lifetime of the network. However, every routing protocol is not suitable for
heterogeneous environments. AM-DisCNT is proposed and evaluated as a new energy
efficient protocol for wireless sensor networks. AM-DisCNT uses circular
deployment for even consumption of energy in entire wireless sensor network.
Cluster-head selection is on the basis of energy. Highest energy node becomes
CH for that round. Energy is again compared in the next round to check the
highest energy node of that round. The simulation results show that AM-DisCNT
performs better than the existing heterogeneous protocols on the basis of
network lifetime, throughput and stability of the system.Comment: IEEE 8th International Conference on Broadband and Wireless
Computing, Communication and Applications (BWCCA'13), Compiegne, Franc
Multimedia Content Distribution in Hybrid Wireless Networks using Weighted Clustering
Fixed infrastructured networks naturally support centralized approaches for
group management and information provisioning. Contrary to infrastructured
networks, in multi-hop ad-hoc networks each node acts as a router as well as
sender and receiver. Some applications, however, requires hierarchical
arrangements that-for practical reasons-has to be done locally and
self-organized. An additional challenge is to deal with mobility that causes
permanent network partitioning and re-organizations. Technically, these
problems can be tackled by providing additional uplinks to a backbone network,
which can be used to access resources in the Internet as well as to inter-link
multiple ad-hoc network partitions, creating a hybrid wireless network. In this
paper, we present a prototypically implemented hybrid wireless network system
optimized for multimedia content distribution. To efficiently manage the ad-hoc
communicating devices a weighted clustering algorithm is introduced. The
proposed localized algorithm deals with mobility, but does not require
geographical information or distances.Comment: 2nd ACM Workshop on Wireless Multimedia Networking and Performance
Modeling 2006 (ISBN 1-59593-485
Hierarchical Design Based Intrusion Detection System For Wireless Ad hoc Network
In recent years, wireless ad hoc sensor network becomes popular both in civil
and military jobs. However, security is one of the significant challenges for
sensor network because of their deployment in open and unprotected environment.
As cryptographic mechanism is not enough to protect sensor network from
external attacks, intrusion detection system needs to be introduced. Though
intrusion prevention mechanism is one of the major and efficient methods
against attacks, but there might be some attacks for which prevention method is
not known. Besides preventing the system from some known attacks, intrusion
detection system gather necessary information related to attack technique and
help in the development of intrusion prevention system. In addition to
reviewing the present attacks available in wireless sensor network this paper
examines the current efforts to intrusion detection system against wireless
sensor network. In this paper we propose a hierarchical architectural design
based intrusion detection system that fits the current demands and restrictions
of wireless ad hoc sensor network. In this proposed intrusion detection system
architecture we followed clustering mechanism to build a four level
hierarchical network which enhances network scalability to large geographical
area and use both anomaly and misuse detection techniques for intrusion
detection. We introduce policy based detection mechanism as well as intrusion
response together with GSM cell concept for intrusion detection architecture.Comment: 16 pages, International Journal of Network Security & Its
Applications (IJNSA), Vol.2, No.3, July 2010. arXiv admin note: text overlap
with arXiv:1111.1933 by other author
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