Ever since descartes introduced planar coordinate systems, visual representations of data have become a widely accepted way of describing scientific phenomena. Modern advances in measurement and instrumentation have required increasingly sophisticated visual representations, to ensure that scientists can quickly and accurately interpret increasingly complex data. Most recently, wireless sensor networks (WSNs) have emerged as a technology which is capable of collecting a vast amount of data over space and time. The sheer volume of the data makes it difficult to be interpreted by humans into meaningful insights. This presents a number of challenges for developers of visualisation techniques which seek to ``map'' the data sensed by a network. Visualisation techniques helps to turn large amounts of raw data into credible visual information such as graphs, charts, or maps, that can assist in understanding of the meaning of that data. In this paper we propose a map as a suitable data visualisation and extraction tool. We aim to develop an in-network distributed information extraction and visualisation service. Such a service would greatly simplify the production of higher-level information-rich representations suitable for informing other network services and the delivery of field information visualisation.
Map as a Service: A Framework for Visualising and Maximising Information Retu...M H
This paper presents a distributed information extraction and visualisation service, called the mapping service, for maximising information return from large-scale wireless sensor networks. Such a service would greatly simplify the production of higher-level, information-rich, representations suitable for informing other network services and the delivery of field information visualisations. The mapping service utilises a blend of inductive and deductive models to map sense data accurately using externally available knowledge. It utilises the special characteristics of the application domain to render visualisations in a map format that are a precise reflection of the concrete reality. This service is suitable for visualising an arbitrary number of sense modalities. It is capable of visualising from multiple independent types of the sense data to overcome the limitations of generating visualisations from a single type of sense modality. Furthermore, the mapping service responds dynamically to changes in the environmental conditions, which may affect the visualisation performance by continuously updating the application domain model in a distributed manner. Finally, a distributed self-adaptation function is proposed with the goal of saving more power and generating more accurate data visualisation. We conduct comprehensive experimentation to evaluate the performance of our mapping service and show that it achieves low communication overhead, produces maps of high fidelity, and further minimises the mapping predictive error dynamically through integrating the application domain model in the mapping service.
Information extraction from sensor networks using the Watershed transform alg...M H
Wireless sensor networks are an effective tool to provide fine resolution monitoring of the physical environment. Sensors generate continuous streams of data, which leads to several computational challenges. As sensor nodes become increasingly active devices, with more processing and communication resources, various methods of distributed data processing and sharing become feasible. The challenge is to extract information from the gathered sensory data with a specified level of accuracy in a timely and power-efficient approach. This paper presents a new solution to distributed information extraction that makes use of the morphological Watershed algorithm. The Watershed algorithm dynamically groups sensor nodes into homogeneous network segments with respect to their topological relationships and their sensing-states. This setting allows network programmers to manipulate groups of spatially distributed data streams instead of individual nodes. This is achieved by using network segments as programming abstractions on which various query processes can be executed. Aiming at this purpose, we present a reformulation of the global Watershed algorithm. The modified Watershed algorithm is fully asynchronous, where sensor nodes can autonomously process their local data in parallel and in collaboration with neighbouring nodes. Experimental evaluation shows that the presented solution is able to considerably reduce query resolution cost without scarifying the quality of the returned results. When compared to similar purpose schemes, such as “Logical Neighborhood”, the proposed approach reduces the total query resolution overhead by up to 57.5%, reduces the number of nodes involved in query resolution by up to 59%, and reduces the setup convergence time by up to 65.1%.
Interpolation Techniques for Building a Continuous Map from Discrete Wireless...M H
Wireless sensor networks (WSNs) typically gather data at a discrete number of locations. However, it is desirable to be able to design applications and reason about the data in more abstract forms than in points of data. By bestowing the ability to predict inter-node values upon the network, it is proposed that it will become possible to build applications that are unaware of the concrete reality of sparse data. This interpolation capability is realised as a service of the network. In this paper, the ‘map’ style of presentation has been identified as a suitable sense data visualisation format. Although map generation is essentially a problem of interpolation between points, a new WSN service, called the map generation service, which is based on a Shepard interpolation method, is presented. A modified Shepard method that aims to deal with the special characteristics of WSNs is proposed. It requires small storage, can be localised and integrates the information about the application domain to further reduce the map generation cost and improve the mapping accuracy. Flood management application is considered to demonstrate how MGS-generated maps can be used in various applications. Empirical analysis has shown that the map generation service is an accurate, a flexible and an efficient method.
An Overview of Information Extraction from Mobile Wireless Sensor NetworksM H
Information Extraction (IE) is a key research area within the field of Wireless Sensor Networks (WSNs). It has been characterised in a variety of ways, ranging from the description of its purposes, to reasonably abstract models of its processes and components. There has been only a handful of papers addressing IE over mobile WSNs directly, these dealt with individual mobility related problems as the need arises. This paper is presented as a tutorial that takes the reader from the point of identifying data about a dynamic (mobile) real world problem, relating the data back to the world from which it was collected, and finally discovering what is in the data. It covers the entire process with special emphasis on how to exploit mobility in maximising information return from a mobile WSN. We present some challenges introduced by mobility on the IE process as well as its effects on the quality of the extracted information. Finally, we identify future research directions facing the development of efficient IE approaches for WSNs in the presence of mobility.
An Overview and Classification of Approaches to Information Extraction in Wir...M H
Recent advances in wireless communication have made it possible to develop low-cost, and low power Wireless Sensor Networks (WSN). The WSN can be used for several application areas (e.g., habitat monitoring, forest fire detection, and health care). WSN Information Extraction (IE) techniques can be classified into four categories depending on the factors that drive data acquisition: event-driven, time-driven, query-based, and hybrid. This paper presents a survey of the state-of-the-art IE techniques in WSNs. The benefits and shortcomings of different IE approaches are presented as motivation for future work into automatic hybridisation and adaptation of IE mechanisms.
Information Extraction from Wireless Sensor Networks: System and ApproachesM H
Recent advances in wireless communication have made it possible to develop low-cost, and low power Wireless Sensor Networks (WSN). The WSN can be used for several application areas (e.g., habitat monitoring, forest fire detection, and health care). WSN Information Extraction (IE) techniques can be classified into four categories depending on the factors that drive data acquisition: event-driven, time-driven, query-based, and hybrid. This paper presents a survey of the state-of-the-art IE techniques in WSNs. The benefits and shortcomings of different IE approaches are presented as motivation for future work into automatic hybridization and adaptation of IE mechanisms.
Adaptive Routing in Wireless Sensor Networks: QoS Optimisation for Enhanced A...M H
One of the key challenges for research in wireless sensor networks is the development of routing protocols that provide application-specific service guarantees. This paper presents a new cluster-based Route Optimisation and Load-balancing protocol, called ROL, that uses various quality of service (QoS) metrics to meet application requirements. ROL combines several application requirements, specifically it attempts to provide an inclusive solution to prolong network life, provide timely message delivery and improve network robustness. It uses a combination of routing metrics that can be configured according to the priorities of user-level applications to improve overall network performance. To this end, an optimisation tool for balancing the communication resources for the constraints and priorities of user applications has been developed and Nutrient-flow-based Distributed Clustering (NDC), an algorithm for load balancing is proposed. NDC works seamlessly with any clustering algorithm to equalise, as far as possible, the diameter and the membership of clusters. This paper presents simulation results to show that ROL/NDC gives a higher network lifetime than other similar schemes, such Mires++. In simulation, ROL/NDC maintains a maximum of 7\% variation from the optimal cluster population, reduces the total number of set-up messages by up to 60%, reduces the end-to-end delay by up to 56%, and enhances the data delivery ratio by up to 0.98% compared to Mires++.
Algorithmic Construction of Optimal and Load Balanced Clusters in Wireless Se...M H
This paper proposes a clustering algorithm - Ba-lanced Minimum Radius Clustering (BMRC) - for use in large scale, distributed Wireless Sensor Networks (WSN). Cluster balancing is an intractable problem to solve in a distributed manner, and distribution is important, by reason of both avoiding specialised node vulnerability and minimising message overhead.The BMRC algorithm described here distributes several of the cluster balancing functions to the cluster-heads. In proposing this algorithm, several tentative claims have been made for it, namely that it is suitable for arbitrary number of cluster heads; that its pecifies a way to elect cluster heads and use them to create the local models; that it accomplishes optimal balanced clusters in distributed manner; that it is scalable and it uses the number-of-hops as a clustering parameter; that it is energy efficient. These claims were studied and verified by simulation.
Map as a Service: A Framework for Visualising and Maximising Information Retu...M H
This paper presents a distributed information extraction and visualisation service, called the mapping service, for maximising information return from large-scale wireless sensor networks. Such a service would greatly simplify the production of higher-level, information-rich, representations suitable for informing other network services and the delivery of field information visualisations. The mapping service utilises a blend of inductive and deductive models to map sense data accurately using externally available knowledge. It utilises the special characteristics of the application domain to render visualisations in a map format that are a precise reflection of the concrete reality. This service is suitable for visualising an arbitrary number of sense modalities. It is capable of visualising from multiple independent types of the sense data to overcome the limitations of generating visualisations from a single type of sense modality. Furthermore, the mapping service responds dynamically to changes in the environmental conditions, which may affect the visualisation performance by continuously updating the application domain model in a distributed manner. Finally, a distributed self-adaptation function is proposed with the goal of saving more power and generating more accurate data visualisation. We conduct comprehensive experimentation to evaluate the performance of our mapping service and show that it achieves low communication overhead, produces maps of high fidelity, and further minimises the mapping predictive error dynamically through integrating the application domain model in the mapping service.
Information extraction from sensor networks using the Watershed transform alg...M H
Wireless sensor networks are an effective tool to provide fine resolution monitoring of the physical environment. Sensors generate continuous streams of data, which leads to several computational challenges. As sensor nodes become increasingly active devices, with more processing and communication resources, various methods of distributed data processing and sharing become feasible. The challenge is to extract information from the gathered sensory data with a specified level of accuracy in a timely and power-efficient approach. This paper presents a new solution to distributed information extraction that makes use of the morphological Watershed algorithm. The Watershed algorithm dynamically groups sensor nodes into homogeneous network segments with respect to their topological relationships and their sensing-states. This setting allows network programmers to manipulate groups of spatially distributed data streams instead of individual nodes. This is achieved by using network segments as programming abstractions on which various query processes can be executed. Aiming at this purpose, we present a reformulation of the global Watershed algorithm. The modified Watershed algorithm is fully asynchronous, where sensor nodes can autonomously process their local data in parallel and in collaboration with neighbouring nodes. Experimental evaluation shows that the presented solution is able to considerably reduce query resolution cost without scarifying the quality of the returned results. When compared to similar purpose schemes, such as “Logical Neighborhood”, the proposed approach reduces the total query resolution overhead by up to 57.5%, reduces the number of nodes involved in query resolution by up to 59%, and reduces the setup convergence time by up to 65.1%.
Interpolation Techniques for Building a Continuous Map from Discrete Wireless...M H
Wireless sensor networks (WSNs) typically gather data at a discrete number of locations. However, it is desirable to be able to design applications and reason about the data in more abstract forms than in points of data. By bestowing the ability to predict inter-node values upon the network, it is proposed that it will become possible to build applications that are unaware of the concrete reality of sparse data. This interpolation capability is realised as a service of the network. In this paper, the ‘map’ style of presentation has been identified as a suitable sense data visualisation format. Although map generation is essentially a problem of interpolation between points, a new WSN service, called the map generation service, which is based on a Shepard interpolation method, is presented. A modified Shepard method that aims to deal with the special characteristics of WSNs is proposed. It requires small storage, can be localised and integrates the information about the application domain to further reduce the map generation cost and improve the mapping accuracy. Flood management application is considered to demonstrate how MGS-generated maps can be used in various applications. Empirical analysis has shown that the map generation service is an accurate, a flexible and an efficient method.
An Overview of Information Extraction from Mobile Wireless Sensor NetworksM H
Information Extraction (IE) is a key research area within the field of Wireless Sensor Networks (WSNs). It has been characterised in a variety of ways, ranging from the description of its purposes, to reasonably abstract models of its processes and components. There has been only a handful of papers addressing IE over mobile WSNs directly, these dealt with individual mobility related problems as the need arises. This paper is presented as a tutorial that takes the reader from the point of identifying data about a dynamic (mobile) real world problem, relating the data back to the world from which it was collected, and finally discovering what is in the data. It covers the entire process with special emphasis on how to exploit mobility in maximising information return from a mobile WSN. We present some challenges introduced by mobility on the IE process as well as its effects on the quality of the extracted information. Finally, we identify future research directions facing the development of efficient IE approaches for WSNs in the presence of mobility.
An Overview and Classification of Approaches to Information Extraction in Wir...M H
Recent advances in wireless communication have made it possible to develop low-cost, and low power Wireless Sensor Networks (WSN). The WSN can be used for several application areas (e.g., habitat monitoring, forest fire detection, and health care). WSN Information Extraction (IE) techniques can be classified into four categories depending on the factors that drive data acquisition: event-driven, time-driven, query-based, and hybrid. This paper presents a survey of the state-of-the-art IE techniques in WSNs. The benefits and shortcomings of different IE approaches are presented as motivation for future work into automatic hybridisation and adaptation of IE mechanisms.
Information Extraction from Wireless Sensor Networks: System and ApproachesM H
Recent advances in wireless communication have made it possible to develop low-cost, and low power Wireless Sensor Networks (WSN). The WSN can be used for several application areas (e.g., habitat monitoring, forest fire detection, and health care). WSN Information Extraction (IE) techniques can be classified into four categories depending on the factors that drive data acquisition: event-driven, time-driven, query-based, and hybrid. This paper presents a survey of the state-of-the-art IE techniques in WSNs. The benefits and shortcomings of different IE approaches are presented as motivation for future work into automatic hybridization and adaptation of IE mechanisms.
Adaptive Routing in Wireless Sensor Networks: QoS Optimisation for Enhanced A...M H
One of the key challenges for research in wireless sensor networks is the development of routing protocols that provide application-specific service guarantees. This paper presents a new cluster-based Route Optimisation and Load-balancing protocol, called ROL, that uses various quality of service (QoS) metrics to meet application requirements. ROL combines several application requirements, specifically it attempts to provide an inclusive solution to prolong network life, provide timely message delivery and improve network robustness. It uses a combination of routing metrics that can be configured according to the priorities of user-level applications to improve overall network performance. To this end, an optimisation tool for balancing the communication resources for the constraints and priorities of user applications has been developed and Nutrient-flow-based Distributed Clustering (NDC), an algorithm for load balancing is proposed. NDC works seamlessly with any clustering algorithm to equalise, as far as possible, the diameter and the membership of clusters. This paper presents simulation results to show that ROL/NDC gives a higher network lifetime than other similar schemes, such Mires++. In simulation, ROL/NDC maintains a maximum of 7\% variation from the optimal cluster population, reduces the total number of set-up messages by up to 60%, reduces the end-to-end delay by up to 56%, and enhances the data delivery ratio by up to 0.98% compared to Mires++.
Algorithmic Construction of Optimal and Load Balanced Clusters in Wireless Se...M H
This paper proposes a clustering algorithm - Ba-lanced Minimum Radius Clustering (BMRC) - for use in large scale, distributed Wireless Sensor Networks (WSN). Cluster balancing is an intractable problem to solve in a distributed manner, and distribution is important, by reason of both avoiding specialised node vulnerability and minimising message overhead.The BMRC algorithm described here distributes several of the cluster balancing functions to the cluster-heads. In proposing this algorithm, several tentative claims have been made for it, namely that it is suitable for arbitrary number of cluster heads; that its pecifies a way to elect cluster heads and use them to create the local models; that it accomplishes optimal balanced clusters in distributed manner; that it is scalable and it uses the number-of-hops as a clustering parameter; that it is energy efficient. These claims were studied and verified by simulation.
Simulation Issues in Wireless Sensor Networks: A SurveyM H
This paper presents a survey of simulation tools and systems for wireless sensor networks. Wireless sensor network modelling and simulation methodologies are presented for each system alongside judgments concerning their relative ease of use and accuracy. Finally, we propose a mixed-mode simulation methodology that integrates a simulated environment with real wireless sensor network testbed hardware in order to improve both the accuracy and scalability of results when evaluating different prototype designs and systems.
An Integrated Inductive-Deductive Framework for Data Mapping in Wireless Sens...M H
Wireless sensor networks (WSNs) havean intrinsic interdependency with the environments inwhich they operate. The part of the world with whichan application is concerned is defined as that applica-tion’sdomain.Thispaperadvocatesthatanapplicationdomain of a WSN can serve as a supplement to analysis,interpretation,andvisualisationmethodsandtools.Webelieve it is critical to elevate the capabilities of thedata mapping services proposed in [1] to make use of the special characteristics of an application domain. Inthis paper, we propose an adaptive Multi-DimensionalApplication Domain-driven (M-DAD) mapping frame-work that is suitable for mapping an arbitrary num-ber of sense modalities and is capable of utilising therelations between different modalities as well as otherparameters of the application domain to improve themapping performance. M-DAD starts with an initialuser defined model that is maintained and updatedthroughout the network lifetime. The experimentalresults demonstrate that M-DAD mapping frameworkperforms as well or better than mapping services with-out its extended capabilities.
Review on Clustering and Data Aggregation in Wireless Sensor NetworkEditor IJCATR
Wireless Sensor Network is a collection of various sensor nodes with sensing and communication capabilities. Clustering is the
process of grouping the set of objects so that the objects in the same group are similar to each other and different to objects in the other
group. The main goal of Data Aggregation is to collect and aggregate the data by maintaining the energy efficiency so that the network
lifetime can be increased. In this paper, I have presented a comprehensive review of various clustering routing protocols for WSN, their
advantages and limitation of clustering in WSN. A brief survey of Data Aggregation Algorithm is also outlined in this paper. Finally, I
summarize and conclude the paper with some future directions
In this presentation we review some of the research problems we address at EPFL in the area of sensor data management. At the level of infrastructure we have developed a middleware to seamlessly integrate, aggregate and analyze heterogeneous sensor data streams in real-time, a WIKI based repository supporting the cooperative management of the metadata associated with sensor deployments and cloud-based storage infrastructure. An important problem in managing sensor data is their efficient storage and transmission using compression techniques. To that end we apply model-based compression methods. For analyzing sensor data, we have developed methods to dynamically estimate the variability, which can be readily used for outlier detection, and to extract semantic features from GPS sensor data streams. We also investigate techniques for trading off between the accuracy of the sensor data obtained and the degree of privacy preservation that can be maintained.
The Sensor Data Management presentation was presented by Karl Aberer (Ecole Polytechnique Federale de Lausanne) at the PlanetData project Meeting on February 28 - March 4, 2011 in Innsbruck, Austria.
Data Centric Approach Based Protocol using Evolutionary Approach in WSNijsrd.com
The evolution of wireless communication and circuit technology has enabled the development of an infrastructure consists of sensing, computation and communication units that makes administrator capable to observe and react to a phenomena in a particular environment. In a Wireless Sensor Network (WSN), nodes are scattered densely in a large area. Sensor nodes can communicate with the sink node directly or through other nodes. Data transmission is the major issue in WSN. Each node has limited energy which is used in transmitting and receiving the data. Various routing protocols have been proposed to save the energy during the transmission of data. data centric approach based routing protocol which efficiently propagates information between sensor nodes in an energy constrained mode. This paper proposes a data centric routing Using evolutionary apporoach in WSN.The main objective of this protocol with evolutionary apporoach is to use artificial intelligence, to reduce the energy consumption by the nodes in transmitting and receiving the data. Implementation of Basic SEP, intelligence cluster routing and proposed protocols will be done using MATLAB.
A Review of Atypical Hierarchical Routing Protocols for Wireless Sensor Networksiosrjce
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
International Journal of Advanced Smart Sensor Network Systems ( IJASSN )ijassn
With the availability of low cost, short range sensor technology along with advances in wireless networking, sensor networks has become a hot topic of discussion. The International Journal of Advanced Smart Sensor Network Systems is an open access peer-reviewed journal which focuses on applied research and applications of sensor networks. While sensor networks provide ample opportunities to provide various services, its effective deployment in large scale is still challenging due to various factors. This journal provides a forum that impacts the development of high performance computing solutions to problems arising due to the complexities of sensor network systems. It also acts as a path to exchange novel ideas about impacts of sensor networks research.
Scheduling different types of packets, such as
real-time and non-real-time data packets, at sensor nodes with
resource constraints in Wireless Sensor Networks (WSN) is of
vital importance to reduce sensors’ energy consumptions and endto-end
data transmission delays. Most of the existing packetscheduling
mechanisms of WSN use First Come First Served
(FCFS), non pre-emptive priority and pre-emptive priority
scheduling algorithms. These algorithms incur a high processing
overhead and long end-to-end data transmission delay due to the
FCFS concept, starvation of high priority real-time data packets
due to the transmission of a large data packet in non pre-emptive
priority scheduling, starvation of non-real-time data packets due
to the probable continuous arrival of real-time data in preemptive
priority scheduling, and improper allocation of data
packets to queues in multilevel queue scheduling algorithms.
Moreover, these algorithms are not dynamic to the changing
requirements of WSN applications since their scheduling policies
are predetermined.
In the Advanced Multilevel Priority packet scheduling
scheme, each node except those at the last level has three levels of
priority queues. According to the priority of the packet and
availability of the queue, node will schedule the packet for
transmission. Due to separated queue availability, packet
transmission delay is reduced. Due to reduction in packet
transmission delay, node can goes into sleep mode as soon as
possible. And Expired packets are deleted at the particular node
at itself before reaching the base station, so that processing
burden on the node is reduced. Thus, energy of the node is saved.
Security based Clock Synchronization technique in Wireless Sensor Network for...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A Reliable Routing Technique for Wireless Sensor NetworksEditor IJCATR
Wireless Sensor Network (WSN) consists of very large number of sensor nodes which are deployed close to the area which
is to be monitored so as to sense various environmental conditions. WSN is a data-driven network which produces large amount of data
and also sensor nodes are energy-limited devices and their energy consumption is mainly associated with data routing. Therefore it is
necessary to perform redundant data aggregation so as to save energy. In this work data aggregation is achieved with the help of two key
approaches namely Clustering approach and In-network data aggregation. These two approaches help to save energy and thereby
increasing the lifetime of the network. The proposed work has some key features like reliable cluster formation, high data aggregation
rate, priority of packets, minimized overhead, multiple routes, reduced energy consumption which enhance the network lifetime. The
performance evaluation of the proposed approach is carried out using Network Simulator- version 2
An Integrated Distributed Clustering Algorithm for Large Scale WSN...................................................1
S. R. Boselin Prabhu, S. Sophia, S. Arthi and K. Vetriselvi
An Efficient Connection between Statistical Software and Database Management System ................... 1
Sunghae Jun
Pragmatic Approach to Component Based Software Metrics Based on Static Methods ......................... 1
S. Sagayaraj and M. Poovizhi
SDI System with Scalable Filtering of XML Documents for Mobile Clients ............................................... 1
Yi Yi Myint and Hninn Aye Thant
An Easy yet Effective Method for Detecting Spatial Domain LSB Steganography .................................... 1
Minati Mishra and Flt. Lt. Dr. M. C. Adhikary
Minimizing the Time of Detection of Large (Probably) Prime Numbers ................................................... 1
Dragan Vidakovic, Dusko Parezanovic and Zoran Vucetic
Design of ATL Rules for TransformingUML 2 Sequence Diagrams into Petri Nets..................................... 1
Elkamel Merah, Nabil Messaoudi, Dalal Bardou and Allaoua Chaoui
Data collection algorithm for wireless sensor networks using collaborative mo...IJECEIAES
The simplest approach to reduce network latency for data gathering in wireless sensor networks (WSN) is to use multiple mobile elements rather than a single mobile sink. However, the most challneging issues faced this approach are firstly the high network cost as a result of using large number of mobile elements. Secondly, it suffers from the difficulty of network partitioning to achieve an efficient load balancing among these mobile elements. In this study, a collaborative data collection algorithm (CDCA) is developed. Simulation results presented in this paper demonstrated that with this algorithm the latency is significantly reduced at small number of mobile elements. Furthermore, the performance of CDCA algorithm is compared with the Area Splitting Algorithm (ASA). Consequently, the CDCA showed superior performance in terms of network latency, load balancing, and the required number of mobile elements.
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Simulation Issues in Wireless Sensor Networks: A SurveyM H
This paper presents a survey of simulation tools and systems for wireless sensor networks. Wireless sensor network modelling and simulation methodologies are presented for each system alongside judgments concerning their relative ease of use and accuracy. Finally, we propose a mixed-mode simulation methodology that integrates a simulated environment with real wireless sensor network testbed hardware in order to improve both the accuracy and scalability of results when evaluating different prototype designs and systems.
An Integrated Inductive-Deductive Framework for Data Mapping in Wireless Sens...M H
Wireless sensor networks (WSNs) havean intrinsic interdependency with the environments inwhich they operate. The part of the world with whichan application is concerned is defined as that applica-tion’sdomain.Thispaperadvocatesthatanapplicationdomain of a WSN can serve as a supplement to analysis,interpretation,andvisualisationmethodsandtools.Webelieve it is critical to elevate the capabilities of thedata mapping services proposed in [1] to make use of the special characteristics of an application domain. Inthis paper, we propose an adaptive Multi-DimensionalApplication Domain-driven (M-DAD) mapping frame-work that is suitable for mapping an arbitrary num-ber of sense modalities and is capable of utilising therelations between different modalities as well as otherparameters of the application domain to improve themapping performance. M-DAD starts with an initialuser defined model that is maintained and updatedthroughout the network lifetime. The experimentalresults demonstrate that M-DAD mapping frameworkperforms as well or better than mapping services with-out its extended capabilities.
Review on Clustering and Data Aggregation in Wireless Sensor NetworkEditor IJCATR
Wireless Sensor Network is a collection of various sensor nodes with sensing and communication capabilities. Clustering is the
process of grouping the set of objects so that the objects in the same group are similar to each other and different to objects in the other
group. The main goal of Data Aggregation is to collect and aggregate the data by maintaining the energy efficiency so that the network
lifetime can be increased. In this paper, I have presented a comprehensive review of various clustering routing protocols for WSN, their
advantages and limitation of clustering in WSN. A brief survey of Data Aggregation Algorithm is also outlined in this paper. Finally, I
summarize and conclude the paper with some future directions
In this presentation we review some of the research problems we address at EPFL in the area of sensor data management. At the level of infrastructure we have developed a middleware to seamlessly integrate, aggregate and analyze heterogeneous sensor data streams in real-time, a WIKI based repository supporting the cooperative management of the metadata associated with sensor deployments and cloud-based storage infrastructure. An important problem in managing sensor data is their efficient storage and transmission using compression techniques. To that end we apply model-based compression methods. For analyzing sensor data, we have developed methods to dynamically estimate the variability, which can be readily used for outlier detection, and to extract semantic features from GPS sensor data streams. We also investigate techniques for trading off between the accuracy of the sensor data obtained and the degree of privacy preservation that can be maintained.
The Sensor Data Management presentation was presented by Karl Aberer (Ecole Polytechnique Federale de Lausanne) at the PlanetData project Meeting on February 28 - March 4, 2011 in Innsbruck, Austria.
Data Centric Approach Based Protocol using Evolutionary Approach in WSNijsrd.com
The evolution of wireless communication and circuit technology has enabled the development of an infrastructure consists of sensing, computation and communication units that makes administrator capable to observe and react to a phenomena in a particular environment. In a Wireless Sensor Network (WSN), nodes are scattered densely in a large area. Sensor nodes can communicate with the sink node directly or through other nodes. Data transmission is the major issue in WSN. Each node has limited energy which is used in transmitting and receiving the data. Various routing protocols have been proposed to save the energy during the transmission of data. data centric approach based routing protocol which efficiently propagates information between sensor nodes in an energy constrained mode. This paper proposes a data centric routing Using evolutionary apporoach in WSN.The main objective of this protocol with evolutionary apporoach is to use artificial intelligence, to reduce the energy consumption by the nodes in transmitting and receiving the data. Implementation of Basic SEP, intelligence cluster routing and proposed protocols will be done using MATLAB.
A Review of Atypical Hierarchical Routing Protocols for Wireless Sensor Networksiosrjce
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
International Journal of Advanced Smart Sensor Network Systems ( IJASSN )ijassn
With the availability of low cost, short range sensor technology along with advances in wireless networking, sensor networks has become a hot topic of discussion. The International Journal of Advanced Smart Sensor Network Systems is an open access peer-reviewed journal which focuses on applied research and applications of sensor networks. While sensor networks provide ample opportunities to provide various services, its effective deployment in large scale is still challenging due to various factors. This journal provides a forum that impacts the development of high performance computing solutions to problems arising due to the complexities of sensor network systems. It also acts as a path to exchange novel ideas about impacts of sensor networks research.
Scheduling different types of packets, such as
real-time and non-real-time data packets, at sensor nodes with
resource constraints in Wireless Sensor Networks (WSN) is of
vital importance to reduce sensors’ energy consumptions and endto-end
data transmission delays. Most of the existing packetscheduling
mechanisms of WSN use First Come First Served
(FCFS), non pre-emptive priority and pre-emptive priority
scheduling algorithms. These algorithms incur a high processing
overhead and long end-to-end data transmission delay due to the
FCFS concept, starvation of high priority real-time data packets
due to the transmission of a large data packet in non pre-emptive
priority scheduling, starvation of non-real-time data packets due
to the probable continuous arrival of real-time data in preemptive
priority scheduling, and improper allocation of data
packets to queues in multilevel queue scheduling algorithms.
Moreover, these algorithms are not dynamic to the changing
requirements of WSN applications since their scheduling policies
are predetermined.
In the Advanced Multilevel Priority packet scheduling
scheme, each node except those at the last level has three levels of
priority queues. According to the priority of the packet and
availability of the queue, node will schedule the packet for
transmission. Due to separated queue availability, packet
transmission delay is reduced. Due to reduction in packet
transmission delay, node can goes into sleep mode as soon as
possible. And Expired packets are deleted at the particular node
at itself before reaching the base station, so that processing
burden on the node is reduced. Thus, energy of the node is saved.
Security based Clock Synchronization technique in Wireless Sensor Network for...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A Reliable Routing Technique for Wireless Sensor NetworksEditor IJCATR
Wireless Sensor Network (WSN) consists of very large number of sensor nodes which are deployed close to the area which
is to be monitored so as to sense various environmental conditions. WSN is a data-driven network which produces large amount of data
and also sensor nodes are energy-limited devices and their energy consumption is mainly associated with data routing. Therefore it is
necessary to perform redundant data aggregation so as to save energy. In this work data aggregation is achieved with the help of two key
approaches namely Clustering approach and In-network data aggregation. These two approaches help to save energy and thereby
increasing the lifetime of the network. The proposed work has some key features like reliable cluster formation, high data aggregation
rate, priority of packets, minimized overhead, multiple routes, reduced energy consumption which enhance the network lifetime. The
performance evaluation of the proposed approach is carried out using Network Simulator- version 2
An Integrated Distributed Clustering Algorithm for Large Scale WSN...................................................1
S. R. Boselin Prabhu, S. Sophia, S. Arthi and K. Vetriselvi
An Efficient Connection between Statistical Software and Database Management System ................... 1
Sunghae Jun
Pragmatic Approach to Component Based Software Metrics Based on Static Methods ......................... 1
S. Sagayaraj and M. Poovizhi
SDI System with Scalable Filtering of XML Documents for Mobile Clients ............................................... 1
Yi Yi Myint and Hninn Aye Thant
An Easy yet Effective Method for Detecting Spatial Domain LSB Steganography .................................... 1
Minati Mishra and Flt. Lt. Dr. M. C. Adhikary
Minimizing the Time of Detection of Large (Probably) Prime Numbers ................................................... 1
Dragan Vidakovic, Dusko Parezanovic and Zoran Vucetic
Design of ATL Rules for TransformingUML 2 Sequence Diagrams into Petri Nets..................................... 1
Elkamel Merah, Nabil Messaoudi, Dalal Bardou and Allaoua Chaoui
Data collection algorithm for wireless sensor networks using collaborative mo...IJECEIAES
The simplest approach to reduce network latency for data gathering in wireless sensor networks (WSN) is to use multiple mobile elements rather than a single mobile sink. However, the most challneging issues faced this approach are firstly the high network cost as a result of using large number of mobile elements. Secondly, it suffers from the difficulty of network partitioning to achieve an efficient load balancing among these mobile elements. In this study, a collaborative data collection algorithm (CDCA) is developed. Simulation results presented in this paper demonstrated that with this algorithm the latency is significantly reduced at small number of mobile elements. Furthermore, the performance of CDCA algorithm is compared with the Area Splitting Algorithm (ASA). Consequently, the CDCA showed superior performance in terms of network latency, load balancing, and the required number of mobile elements.
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A Comparative Analysis for Hybrid Routing Protocol for Wireless Sensor NetworksIJERA Editor
Wireless Sensor Networks (WSNs) consist of smallnodes with sensing, computation and wireless
communicationscapabilities. These sensor networks interconnect a several othernodes when established in large
and this opens up severaltechnical challenges and immense application possibilities.These wireless sensor
networks communicate using multi-hopwireless communications, regular ad hoc routing techniquescannot be
directly applied to sensor networks domain due tothe limited processing power and the finite power available
toeach sensor nodes hence recent advances in wireless sensornetworks have developed many protocols
depending on theapplication and network architecture and are specificallydesigned for sensor networks where
energy awareness is anessential consideration. This paper presents routingprotocols for sensor networks and
compares the routingprotocols that are presently of increasing importance.
In this paper, we propose Hybrid Routing Protocol whichcombines the merits of proactive and reactive approach
andovercome their demerits.
ENERGY EFFICIENT MULTIHOP QUALITY PATH BASED DATA COLLECTION IN WIRELESS SENS...Editor IJMTER
In recent years there has been an increased focus on the use of sensor networks to sense and measure
the environment. This leads to a wide variety of theoretical and practical issues on appropriate protocols for data
sensing and transfer. Recent work shows sink mobility can improve the energy efficiency in wireless sensor
networks (WSNs). However, data delivery latency often increases due to the speed limit of mobile sink. Most of
them exploit mobility to address the problem of data collection in WSNs. The WSNs with MS (mobile Sink) and
provide a comprehensive taxonomy of their architectures, based on the role of the MS. An overview of the data
collection process in such a scenario, and identify the corresponding issues and challenges. A protocol named
weighted rendezvous planning (WRP) which is a heuristic method that finds a near-optimal traveling tour that
minimizes the energy consumption of sensor nodes. Focus on the path selection problem in delay-guaranteed
sensor networks with a path-constrained mobile sink. Concentrate an efficient data collection scheme, which
simultaneously improves the total amount of data and reduces the energy consumption. The optimal path is chosen
to meet the requirement on delay as well as minimize the energy consumption of entire network. Predictable sink
mobility is exploited to improve energy efficiency of sensor networks.
Time Orient Multi Attribute Sensor Selection Technique For Data Collection In...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
A Review Study on Shortest Path in WSN to detect the Abnormal Packet for savi...Editor IJMTER
The main motive of this research is to study energy-efficient data-gathering mechanisms to
abnormal packet data for saving the energy. To detect the abnormal packet irregularities is useful for
saving energy, as well as for management of network, because the patterns found can be used for
both decision making in applications and system performance tuning. Node distribution in WSNs is
either deterministic or self-organizing and application dependant. The sensor nodes in WSNs have
minimum energy and they use their energy for communication and sensing.
A COST EFFECTIVE COMPRESSIVE DATA AGGREGATION TECHNIQUE FOR WIRELESS SENSOR N...ijasuc
In wireless sensor network (WSN) there are two main problems in employing conventional compression
techniques. The compression performance depends on the organization of the routes for a larger extent.
The efficiency of an in-network data compression scheme is not solely determined by the compression
ratio, but also depends on the computational and communication overheads. In Compressive Data
Aggregation technique, data is gathered at some intermediate node where its size is reduced by applying
compression technique without losing any information of complete data. In our previous work, we have
developed an adaptive traffic aware aggregation technique in which the aggregation technique can be
changed into structured and structure-free adaptively, depending on the load status of the traffic. In this
paper, as an extension to our previous work, we provide a cost effective compressive data gathering
technique to enhance the traffic load, by using structured data aggregation scheme. We also design a
technique that effectively reduces the computation and communication costs involved in the compressive
data gathering process. The use of compressive data gathering process provides a compressed sensor
reading to reduce global data traffic and distributes energy consumption evenly to prolong the network
lifetime. By simulation results, we show that our proposed technique improves the delivery ratio while
reducing the energy and delay
An Efficient Approach for Data Gathering and Sharing with Inter Node Communi...cscpconf
In today’s era Wireless sensor networks (WSNs) have emerged as a solution for a wide range of
applications. Most of the traditional WSN architectures consist of static nodes which are densely deployed
over a sensing area. Recently, several WSN architectures based on mobile elements (MEs) have been
proposed. Most of them exploit mobility to address the problem of data collection in WSNs. The common
drawback among them is to data sharing between interconnected nodes. In this paper we propose an
Efficient Approach for Data Gathering and Sharing with Inter Node Communication in Mobile-Sink. Our
algorithm is divided into seven parts: Registration Phase, Authentication Phase, Request and Reply Phase,
Setup Phase, Setup Phase (NN), Data Gathering, and Forwarding to Sink. Our approach provides an
efficient way to handle data in between the intercommunication nodes. By the above approach we can
access the data from the node which is not in the list, by sharing the data from the node which is
approachable to the desired node. For accessing and sharing we need some security so that the data can
be shared between authenticated nodes. For this we use two way security approach one for the accessing
node and other for the sharing.
SYSTEMS USING WIRELESS SENSOR NETWORKS FOR BIG DATACSEIJJournal
Wireless sensor networks are continually developing in the big data world and are widely employed in
many aspects of life. In the monitoring region, the WSN gathers, analyses, and sends information about the
detected item. In recent years, WSN has also made important strides in the management of critical data
protection, traffic monitoring, and climate - change detection. The rich big data contributors known as
wireless sensor networks provide a significant amount of data from numerous sensor nodes in large-scale
networks (WSNs), which are among the numerous potential datasets. However, unlike traditional wireless
networks, suffer from significant constraints in communication and data dependability due to the cluster’s
constraints. This paper gives a detailed assessment of cutting-edge research on using WSN into large data
systems Potential network and effective deployment and scientific problems are presented and discussed in
the context of the study topics and aim. Finally, unresolved issues are addressed in order to discuss
interesting future research possibilities.
Systems using Wireless Sensor Networks for Big Datacivejjour
Wireless sensor networks are continually developing in the big data world and are widely employed in
many aspects of life. In the monitoring region, the WSN gathers, analyses, and sends information about the
detected item. In recent years, WSN has also made important strides in the management of critical data
protection, traffic monitoring, and climate - change detection. The rich big data contributors known as
wireless sensor networks provide a significant amount of data from numerous sensor nodes in large-scale
networks (WSNs), which are among the numerous potential datasets. However, unlike traditional wireless
networks, suffer from significant constraints in communication and data dependability due to the cluster’s
constraints. This paper gives a detailed assessment of cutting-edge research on using WSN into large data
systems Potential network and effective deployment and scientific problems are presented and discussed in
the context of the study topics and aim. Finally, unresolved issues are addressed in order to discuss
interesting future research possibilities.
Systems using Wireless Sensor Networks for Big DataCSEIJJournal
Wireless sensor networks are continually developing in the big data world and are widely employed in
many aspects of life. In the monitoring region, the WSN gathers, analyses, and sends information about the
detected item. In recent years, WSN has also made important strides in the management of critical data
protection, traffic monitoring, and climate - change detection. The rich big data contributors known as
wireless sensor networks provide a significant amount of data from numerous sensor nodes in large-scale
networks (WSNs), which are among the numerous potential datasets. However, unlike traditional wireless
networks, suffer from significant constraints in communication and data dependability due to the cluster’s
constraints. This paper gives a detailed assessment of cutting-edge research on using WSN into large data
systems Potential network and effective deployment and scientific problems are presented and discussed in
the context of the study topics and aim. Finally, unresolved issues are addressed in order to discuss
interesting future research possibilities.
An Overview of Information Extraction from Mobile Wireless Sensor Networkspowera10
Information Extraction (IE) is a key research area within the field of Wireless Sensor Networks (WSNs). It has been characterised in a variety of ways, ranging from the description of its purposes, to reasonably abstract mod- els of its processes and components. There has been only a handful of papers addressing IE over mobile WSNs directly, these dealt with individual mobility related problems as the need arises. This paper is presented as a tutorial that takes the reader from the point of identifying data about a dynamic (mobile) real world problem, relating the data back to the world from which it was collected, and finally discovering what is in the data. It covers the entire process with special emphasis on how to exploit mobility in maximising information re- turn from a mobile WSN. We present some challenges introduced by mobility on the IE process as well as its effects on the quality of the extracted information. Finally, we identify future research directions facing the development of efficient IE approaches for WSNs in the presence of mobility.
Data Aggregation Routing Protocols in Wireless Sensor Networks : A TaxonomyIJCNCJournal
Routing in Wireless Sensor Network (WSN) aims to interconnect sensor nodes via single or multi-hop
paths. The routes are established to forward data packets from sensor nodes to the sink. Establishing a
single path to report each data packet results in increasing energy consumption in WSN, hence, data
aggregation routing is used to combine data packets and consequently reduce the number of transmissions.
This reduces the routing overhead by eliminating redundant and meaningless data. There are two models
for data aggregation routing in WSN: mobile agent and client/server. This paper describes data
aggregation routing and classifies then the routing protocols according to the network architecture and
routing models. The key issues of the data aggregation routing models (client/server and mobile agent) are
highlighted and discussed.
Design Issues and Applications of Wireless Sensor Networkijtsrd
Efficient design and implementation of wireless sensor networks has become a hot area of research in recent years, due to the vast potential of sensor networks to enable applications that connect the physical world to the virtual world. By networking large numbers of tiny sensor nodes, it is possible to obtain data about physical phenomena that was difficult or impossible to obtain in more conventional ways. In future as advances in micro-fabrication technology allow the cost of manufacturing sensor nodes to continue to drop, increasing deployments of wireless sensor networks are expected, with the networks eventually growing to large numbers of nodes.Potential applications for such large-scale wireless sensor networks exist in a variety of fields, including medical monitoring, environmental monitoring, surveillance, home security, military operations, and industrial machine monitoring etc. G. Swarnalatha | R. Srilalitha"Design Issues and Applications of Wireless Sensor Network" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-6 , October 2017, URL: http://www.ijtsrd.com/papers/ijtsrd4688.pdf http://www.ijtsrd.com/engineering/computer-engineering/4688/design-issues-and-applications-of-wireless-sensor-network/g-swarnalatha
Characterization of directed diffusion protocol in wireless sensor networkijwmn
Wireless sensor network (WSN) has enormous applications in many places for monitoring the environments
of importance. Sensor nodes are capable of sensing, computing, and communicating. These sensor nodes
are energy constraint and operated by batteries. Since energy consumption is an important issue of WSN,
there have been many energy-efficient protocols proposed for the WSN. Directed diffusion (DD) is a datacentric
protocol that focuses on the energy efficiency of the networks. Since the first proposal of DD
protocol by Deborah, there have been various versions of DD protocols proposed by many scientists across
the globe. These upgraded versions of DD protocols add on various features to the original DD protocol
such as energy, scalability, network lifetime, security, reliability, and mobility. In this paper, we discuss
and classify various characteristics of themost populardirected diffusion protocols that have been proposed
over couple of years.
Building Programming Abstractions for Wireless Sensor Networks Using Watershe...M H
The availability and quality of information extracted from Wireless Sensor Networks (WSNs) revolutionised a wide range of application areas. The success of any WSN application is, nonetheless, determined by the ability to retrieve information with the required level of accuracy, within specified time constraints, and with minimum resource utilisation. This paper presents a new approach to localised information extraction that utilises the Watershed segmentation algorithm to dynamically group nodes into segments, which can be used as programming abstractions upon which different query operations can be performed. Watershed results in a set of well delimited areas, such that the number of necessary operations (communication and computation) to answer a query are minimised. This paper presents a fully asynchronous Watershed implementation, where nodes can compute their local data in parallel and independently from one another. The preliminary experimental results demonstrate that the proposed approach is able to significantly reduce the query processing cost and time without involving any loss of efficiency.
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Experimental Applications of Mapping Services in Wireless Sensor NetworksM H
Wireless sensor networks typically gather data at a number of locations. However, it is desirable to be able to design applications and reason about the data in more abstract forms than points of data. This paper examines one way in which this can be done. By bestowing the ability to predict inter-node values upon the network, it is proposed that it will become possible to build applications that are unaware of the concrete reality of sparse data. This interpolation capability is realised as a service of the network. We present an implementation of this service and discuss its merits and shortcomings. Additionally, we present an initial application of the service in the form of isopleth generation. That is, the delineation of contours of constant parameter value. Finally, we discuss the improvements required to create more sophisticated applications and services and examine the benefits these improvements would bring.
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Modelling Clustering of Wireless Sensor Networks with Synchronised Hyperedge ...M H
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Pennies from Heaven: a retrospective on the use of wireless sensor networks f...M H
Wireless sensor networks are finding many applications in terrestrial sensing. It seems natural to propose their use for planetary exploration. A previous study (the Mars daisy) has put forward a scenario using thousands of millimeter scale wireless sensor nodes to undertake a complete survey of an area of a planet. This paper revisits that scenario, in the light of some of the discussions surrounding its presentation. The practicality of some of the ideas put forward is examined again, and an updated design sketched out. It is concluded that the updated design could be produced using currently available technology.
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An Approach to Data Extraction and Visualisation for Wireless Sensor Networks
1. An Approach to Data Extraction and Visualisation
for Wireless Sensor Networks
Mohammad Hammoudeh, Robert Newman, Sarah Mount
School of Computing and IT
University of Wolverhampton
Wolverhampton, UK
Email: {m.h.h, r.newman, s.mount}@wlv.ac.uk
Abstract—Ever since Descartes introduced planar coordinate geographic map to enable observer to view the data for a
systems, visual representations of data have become a widely ac- specific area.
cepted way of describing scientific phenomena. Modern advances
This paper is organised as follows. Section 2 discusses
in measurement and instrumentation have required increasingly
sophisticated visual representations, to ensure that scientists can the related work. Section 3 presents the characteristics of the
quickly and accurately interpret increasingly complex data. Most sense data. In Section 4, we discuss visualisation challenges in
recently, wireless sensor networks (WSNs) have emerged as a WSNs. In Section 5 we introduce the benefits of visualisation
technology which is capable of collecting a vast amount of data of sense data. In Section 6 we discuss the advantages of map
over space and time. The sheer volume of the data makes it dif-
data format. We present the implementation of the mapping
ficult to be interpreted by humans into meaningful insights. This
presents a number of challenges for developers of visualisation services in Section 7. We also evaluate the performance of the
techniques which seek to “map” the data sensed by a network. proposed mapping service in Section 8. And we conclude the
Visualisation techniques helps to turn large amounts of raw data work in Section 9.
into credible visual information such as graphs, charts, or maps,
that can assist in understanding of the meaning of that data.
In this paper we propose a map as a suitable data visualisation II. R ELATED W ORK
and extraction tool. We aim to develop an in-network distributed
information extraction and visualisation service. Such a service Within the WSN field, mapping applications found in the lit-
would greatly simplify the production of higher-level information- erature are ultimately concerned with the problem of mapping
rich representations suitable for informing other network services measurements onto a model of the environment. Hellerstein et
and the delivery of field information visualisation. al. [2] propose to construct isobar maps in sensor networks.
They show how in-network merging of isobars could help re-
I. I NTRODUCTION duce the amount of communication. Furthermore, [3] proposes
The main objective of a wireless sensor network (WSN) an efficient data-collection scheme, and the building of contour
is to provide users with access to the information of interest maps, for event monitoring and network-wide diagnosis, in
from data gathered by spatially distributed sensors. In real- centralised networks. Solutions such as Distributed Mapping
world applications, WSNs are often deployed in a high density have been proposed to the general mapping domain [2]. How-
to ensure a full coverage of the monitored phenomena. These ever, many solutions are limited to particular applications and
networks are expected to generate an excessive amount of data. constrained with unreliable assumptions. The grid alignment
As the sensor network scales in size, so does the amount of in [2], for example, is one such assumption.
sensed data which is required to be collected by the network, In the wider literature, mapping was sought as a useful tool
processed, and presented to the user. The data produced and in respect to network diagnosis and monitoring [3], power
the form in which they are structured varies widely. Scientists management [4], and jammed-area detections [5]. For instance,
need tools to reconcile these differences. Human interpretation contour maps were found to be an effective solution to the
of this data will require extensive use of visualisation tools. pattern matching problem that works for limited resources
Using scientific visualisation techniques can help to make networks [6]. As opposed to resolving these types of isolated
meaningful visualisation possible in many aspects of data concerns, in the work proposed here the WSN is expected not
understanding and analysis. Data visualisation is becoming only to produce map type responses to queries but also to
increasingly important in WSNs as it enables end-users to best make use of the data supporting the maps for more effective
utilise the data collected by the sensor network. routing, further intelligent data aggregation and information
In this paper we propose a map as a suitable visualisa- extraction, power scheduling and other network processes.
tion and data extraction tool for WSNs. A map is a visual These are examples of specific instances of the mapping
representation of an area, although most commonly used to problem and, as such, motivate the development of a generic
depict geography, maps may represent any space, real or distributed, in-network mapping framework, furthering the
imagined, without regard to context or scale such as weather area of research by moving beyond the limitations of the
data distribution mapping [1]. It could be overlaid over a centralised approaches.
2. III. C HARACTERISTICS OF S ENSE DATA the pattern falls into one of two categories: regular, when data
is gathered from sensing nodes which are deployed on a grid;
Data acquired from a WSN is imperfect in nature. This irregular, when sensing nodes are deployed randomly, many
imperfect nature of data is due to physical constraints on sensor network data belongs to the irregular patterns category.
node deployment and data collection, noisy environment, It is sometimes necessary to know the data density besides
device measurement errors, among other factors. Moreover, their distribution. The network density is defined as the number
data collected by different sensors may have various qualities of nodes per unit area.
depending on physical characteristics such as distance from
sensed phenomena, node modality, or noise model of individ- IV. W HY VISUALISATION OF S ENSE DATA IS
ual sensors [7]. C HALLENGING
In densely deployed WSNs, sensor readings are usually Visualisation of sensor network data is challenging. The
highly correlated in the space domain [8]. Additionally, the large amount of data collected from deployed sensor networks
nature of the physical phenomenon contains the temporal arrives in “bursty” mode. This makes it difficult to process all
correlation between each sensor node successive readings. the data in a timely manner so that it can be used as an input
Data gathered from a WSN is often characterised by its to visualisation systems [12]. Furthermore, most scientific
significant redundancy. Many sensor networks are densely visualisation techniques require data to include connectivity
deployed with high node redundancy to deal with node failure information, which is not provided by a scattered data set.
based connectivity and coverage problems. However, dense Hence, highly efficient visualisation schemes operating di-
deployment causes neighbouring sensor nodes to have highly rectly on raw scattered data are necessary [13].
overlapping sensing regions. Consequently, it is likely that In large-scale WSN it is a non-trivial task to visualise the
multiple nodes often detect and communicate data packets observed phenomena given the problems of sparse, inaccurate,
about common phenomena. This is due to the fact that each high density, and irregularly distributed data, in addition to the
node observes the physical region of overlap independent of its limited physical resources. Therefore, we aim to define meth-
neighbours. Data aggregation techniques aim at reducing re- ods suitable for real-time visualisation and analysis suitable
dundant data transmissions. Although data aggregation results for sensor network data. This includes the specification of a
in fewer transmissions, however, they introduce considerable modular scattered data interpolation package for implementing
amount of delays on delivering the data to its final destination. suitable interactive viewers for time-varying data.
Data from nearer sources may have to be held back at an Practically, a point measured on a surface represents the
intermediate node in order to be aggregated with data coming environment conditions over an area of a certain size, hence
from sources that are farther away. In addition, within such net- it should be possible to generate a complete view of the
works, delays may be caused by hop-by-hop retransmission, observation field of a WSN using a discrete set of observation
scheduled data communication, queueing delays, propagation points. Depending on the desired degree of accuracy and
through the environment, and other factors. fidelity, the sampling interval over an unknown surface is
In many WSNs application areas, such as medical or defined. The problem is to define how to adequately represent
surveillance applications, the accuracy of acquired data is the observed phenomena by a limited number of elevation
often crucial. However, sensed data is often inaccurate and points, that is, what sampling interval to use with an unknown
erroneous [9]. This inaccuracy may be a result of faulty sensor surface? To select between different sampling strategies when
readings, internal errors in sensor nodes, network delays, data is acquired from a sensor network many factors must be
among other reason. The deployment of a larger number considered including: application, level of accuracy, the nature
of sensor nodes provides potential for greater accuracy in of the sampled data, the nature of monitored environment,
the information gathered. The ability to effectively increase nodes distribution, and density. Data acquisition strategy is of
the sensing quality without necessarily increasing data trans- high importance in sensor networks and is directly related to
missions will increase the reliability of the information for routing and single node capabilities. When sampled data is to
the end user application. Some schemes such as [10], trade visualise a certain observed phenomena results are good as the
data accuracy for energy efficiency, which typically increase sample [11].
with the amount of data transmissions. Data aggregation also In WSNs, it is increasingly becoming important to have a
increases the level of gathered data accuracy and exploits data live picture of the changing environmental variables. This can
redundancy to compensate node failures [10], [9]. Depending be achieved if data about the phenomenon is sampled at a
on the accuracy bounds required for a specific application, a suitable rate. In live data representation applications, where a
node may need to communicate some of its information to client is interested in the current picture of the environment,
the sink that is incorporated in the model so that the accuracy it is important to collect readings from the network at a rate
bounds are met. close as possible to the rate of change of the monitored envi-
Another characteristic of sampled sense data is the distribu- ronmental variable. In other applications, such as temperature
tion of sampled source data. The distribution of data is usually and pressure monitoring, when the measured phenomena is
specified in terms of location and pattern [11]. The location changing linearly over time and space, the sampling rate can
is specified in terms of Cartesian coordinates (x, y, z), while be reduced so that node resources are used effectively.
3. V. B ENEFITS OF S ENSE DATA VISUALISATION of the data attributes in a real-world map in ways that would
be intuitive and easy to talk and reason about. A map is
Data visualisation in WSNs has the ability to bridge the
intuitive and easy to understand as it provides an interface for
gap between the physical and logical worlds, by using the
visualising dynamic data from sensor net. It provides a higher-
gathered information from the physical world and communi-
level information-rich representation which was found suitable
cating that information to the end-user in compact and often
for informing other network services and the delivery of field
easy to understand way. Data visualisation helps to deal with
information visualisation. This information-rich representation
this flood of information, integrating the human in the data
satisfies the various requirements for the sensor network
analysis process. The main advantages of the application of
system end users. The map gives a low cost interface used
visualisation techniques in wireless sensor networks are:
to target queries for generating detailed maps from a subset
1) Visualisation could help in managing the huge amount of the sensors in the network.
of data coming from a sensor network. Visual data Maps are effective to understand spatial distribution of
exploration can easily deal with large, highly non- environmental features, since humans can use their natural
homogeneous and noisy amount of data. interpretation capabilities to understand colours, patterns, and
2) Maximisation of useful information return. Visualisation spatial relevance. The human interpretation capabilities sug-
is a fundamental tool to communicate information in a gest the importance of expression methods such as how to
compact and easy to understand way. It allows the user represent spatial data on a map. Maps can be either static
to gain insight into the data, drawing conclusions and or dynamic and allow data representation on two-dimensional
directly interacting with the data. Visualisation not only or tree-dimensional space. They allow the user to infer the
helps to answer questions that user has, but it elicits actual sizes of and distance between objects. The unique
questions that he did not even think of before. visualisation and analysis benefits offered by maps make them
3) Interactive visualisations benefit from dynamic queries more visually communicative, they imply the distributions and
which are a valuable tool to explore data. states; provide information about spatial patterns; and imply
4) More reliable information than possible from individ- the association of diverse phenomena. The users can zoom
ual sources. Although individual devices have limited in or zoom out respectively meaning showing more or less
resources, the true value of the sensor network systems details. Finally, representations such as maps allow to extract
comes from the emergent behaviour that arises when information that can not be obtained by looking at sensor
data from many places in the system is combined into readings separately and are more efficient to compute in both
a meaningful presentation [14]. The bandwidth of data time and energy. For instance, maps may capture trends or
transferred in a picture is much bigger than having a correlations among sense data and missing data, where there
human look at log files or textual data. is no operating sensor, can be interpolated using these spatial
5) Detection of higher-order relationships between different and temporal correlations among sensor readings.
sensors. Relationships become apparent. Sometimes they
are completely hidden without visualisation. VII. M APPING S ERVICES FOR WSN S
6) More efficient data and information representation. Vi- Leading directly from Section VI which shows the use-
sualisation reduces analysis and response times. Going fulness of visualising sense data in a map format, we in-
through thousands of line of points data is slower than vestigate the development of methods for map construction
looking at a few graphs of the same data. It is a valuable and maintenance services within a WSN, focusing on service
tool to communicate information in a compact and often cost, complexity, computational load, storage, communication
easy to understand way. requirements, robustness to packet loss, nodes failures, and
7) Visual data examination does not require deep under- network density.
standing of complex mathematical or statistical algo- We propose a new network service: map generation. Map
rithms. Visualisation techniques provide a qualitative generation is essentially a problem of interpolation from sparse
overview useful for further quantitative analysis [15]. and irregular points. This service allows the production of
It definitely reduces analysis and response times. maps of arbitrary level of detail upon requests injected into
the network by the user, or pre-programmed as responses
VI. S ENSE DATA V ISUALISATION : M APS
to network events. The service should be entirely based on
Visual formats, such as maps, can be easily understood by in-network processing and would be applied to flat, com-
people possibly from different communities, thus allow them putationally homogeneous networks. Given a set of known
to derive conclusions based on substantial understanding of data points representing the nodes’ perception of a given
the available data. This understanding gained from maps fulfils measurable parameter of the phenomenon, what is the most
the ultimate goal of sensor network deployments which is not likely complete and continuous map of that parameter? In the
only to gather the data from the spatially distributed sensor work proposed here the WSN is expected not only to produce
nodes, but also convey and translate the data for scientists to map type responses to queries but also to make use of the
analyse and study. Visualisation of data collected from a sensor data supporting the maps for more effective routing, further
network in a map format is one way to display the distribution intelligent data aggregation and information extraction, power
4. instance, if the current cluster-head decides to hand its role to
the backup node, it notifies the respective node and forwards
to it necessary information, such as the backup nodes list, to
avoid a complete cluster set-up phase.
The role of In-network Processing module is to process raw
data received from various cluster-head nodes in the network.
It applies filtering on all the received data to reduce redun-
dancy resulting from overlapping cluster coverage. Moreover,
the In-network Processing module manages incremental up-
date messages and merges them into single transaction. Also,
it defines two interfaces for the Interpolation and Application
modules through which it provides access to the cached data
in a suitable format.
All mapping applications use the Interpolation module as
a building block to generate maps. The Interpolation module
provides access to the In-network Processing module to obtain
the available mapping or update data. In this paper, we use
Shepard interpolation algorithm [18]. Shepard interpolation
is simple and intuitive. It is suitable for large-scale wireless
Figure 1. Architecture of the distributed in-network mapping service. sensor networks because it reduces communication overhead
by only considering data points which are significant for the
interpolation results. Shepard defines a continuous function
scheduling and other network processes. Just as clustering, where the weighted average of data is inversely proportional
routing and aggregation allow for more sophisticated and to the distance from the interpolated location. This method
efficient use of the network resources, a mapping service exploits the intuitive sense that things that are close to each
would support other network services and make many more other are more likely to be similar. Shepard’s expression for
applications possible with little extra effort. globally modelling a surface is:
The proposed implementation of the distributed mapping
service contains four modules as seen in Figure 1: Application, ⎧ N
Interpolation, In-network Processing and Routing. ⎪
⎨ (di )−u zi if di = 0 for all Di (u > 0)
The Routing module is an essential module responsible for f1 (P ) = (1)
⎪ i=1
⎩
data communication. Routing proved to be a key issue as the zi if di = 0 for some Di
research developed. In this paper, we use a hierarchical routing
algorithm called MuMHR [16]. The defined routing procedure where di is the standard distance metric from an interpola-
builds the hierarchy and establishes the path between sensing tion point P to the point numbered i in the N known points
nodes and their respective cluster-head to enable data trans- set and zi is the known value at point i. The exponent u is
missions. MuMHR is an improvement over LEACH [17]. It used to control the smoothness of the interpolation. As the
relaxes some of the assumptions made by LEACH such as the distance between interpolation location P and the measured
single hop communication. The main objective of MuMHR sample point Di increases, the weight of that sampled point
protocol is to provide substantially energy-efficient and robust will decrease exponentially. As P approaches a data point
communication. The energy efficiency is achieved by load bal- Di , di tends to zero and the ith terms in both the numerator
ancing at two levels: (1) at the network level, which involves and denominator exceeds all bounds while other terms remain
traffic multiplexing over multiple paths; (2) at the cluster level, bounded.
introducing rotation of the cluster-heads every given interval of Finally, the Application module contains the user defined
time. This prevents energy depletion resulting from constantly applications such as path-finding or isopleths maps. The
using the same path for transmission or particular nodes being application module also has direct access to the In-network
cluster-heads for a long duration. The multi-path feature is not Processing module to get raw data if required. Figure 1 show
only used for load balancing but also when path failures occur. the mapping service architecture and interaction between its
When a path fails, an alternative path can be immediately used four modules.
which allows the protocol to dynamically adapt to failures
without delays or degradation in the quality of service. At the VIII. E XPERIMENTAL E VALUATION
cluster set-up time, one or more nodes are chosen as cluster- The efficiency of the proposed mapping service in terms of
head backup node(s). Backup cluster-head node substitute for the quality of the produced map was demonstrated using the
the cluster-head in some failure cases or when the current following experiment that simulates distributed execution on
cluster-head decides to reduce its participation in the protocol a real life data-set. As an example of the quality obtainable,
if its energy level approaches a certain threshold value. For and what might be expected from a sensor network the
5. following maps, derived from a series presented by Clarke and
Swaze [19], are presented. The maps generated by the mapping
service are compared to original Fe map taken from [19].
This algorithm was implemented using a mapping API with
an in-house simulation software “Dingo” [20] which is a fork
of the “SenSor” project [21]. It has proven that it is not only
easy to use, but also powerful enough to model and simulate
the behaviour of the mapping service at various design stages.
It provides an easy way to develop system models, enabling
users to quickly manipulate hardware elements and achieve
the desired results without having to build a full hardware
prototype.
Figure 2 is derived directly from [19] and shows distribution
of iron minerals around Cuprite, Nevada. This map represents Figure 2. Fe distribution around Cuprite, NV [19].
an area 2km on a side, and provides a very detailed account
of the mineral distribution in that area. This image has been
used as the basis for a simulation of the results that might
be expected from a sensor network, sensing for evidence of
the same chemicals. Using the Dingo simulator, a network
of sensors were randomly distributed over the 2km square,
and the values of the image in Figure 3 used as the output
of each sensing device at that point. The simulated sensor
network was programmed to produce a map, using the Shepard
interpolation method. The interpolated map of iron minerals
generated by the mapping service is clearly of poorer quality
than the original which could have been obtained using an
orbiting image spectrometer. However, the interpolated terrain
is clearly similar to the real surface. Determining exactly how
close the similarity is, and what the algorithmic limits to the
accuracy of the representation, is a problem we are currently Figure 3. Interpolated map of Fe distribution around Cuprite, NV produced
using 3000 sensor nodes.
investigating. Consider, though, that the information used to
reconstruct the surface in Figures 2 is just 3000 points, while
the original is recorded by the satellite spectroscopy which is simple to develop, and challenges that need to be met before
a hard target to hit. The satellite spatial resolution is about
such a service is feasible. Finally, we examine the applicability
17 meters pixel spacing. Taking the position of the nodes into
of Shepard interpolation in the reconstruction of a parameter
account as extra information, the reconstruction is built using map from sparsely sampled data.
less than 3% of the original data.
This paper is not the result of a completed project, but
To highlight this potential use of an in-network mapping the exposition of the start of one. We feel that this area of
service, we present an implementation of isopleths generation. research is pertinent to modern wireless sensor networks, and
The results of generating isopleths based on this data are in this paper we have taken initial steps towards exploring it.
shown in Figures 4 and 5. These contours were generated The problems and challenges described in Section 4 are the
in the 0.4 to 1.2 micron spectral region and a threshold of 1. opportunities we intend to take and the lines we intend to
Compared to the isopleths based on the actual Fe distribution follow.
map shown in Figure 4, it is visually evident that the isopleths
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