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.
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++.
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%.
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.
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.
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.
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.
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.
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.
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++.
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%.
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.
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.
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.
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.
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.
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.
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.
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.
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
An Approach to Data Extraction and Visualisation for Wireless Sensor NetworksM H
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.
ON THE PERFORMANCE OF INTRUSION DETECTION SYSTEMS WITH HIDDEN MULTILAYER NEUR...IJCNCJournal
Deep learning applications, especially multilayer neural network models, result in network intrusion detection with high accuracy. This study proposes a model that combines a multilayer neural network with Dense Sparse Dense (DSD) multi-stage training to simultaneously improve the criteria related to the performance of intrusion detection systems on a comprehensive dataset UNSW-NB15. We conduct experiments on many neural network models such as Recurrent Neural Network (RNN), Long-Short Term Memory (LSTM), Gated Recurrent Unit (GRU), etc. to evaluate the combined efficiency with each model through many criteria such as accuracy, detection rate, false alarm rate, precision, and F1-Score.
Energy Conservation in Wireless Sensor Networks Using Cluster-Based ApproachIJRES Journal
In a wireless networking environment, the network is comprised of sensor nodes and backbones are subsets of sensors or actuators that suffice for performing basic data communication operations. They are applied for energy efficient broadcasting. In a broadcasting (also known as data dissemination) task, a message is to be sent from one node, which could be a sink or an actuator, to all the sensors or all the actuators in the network. The goal is to minimize the number of rebroadcasts while attempting to deliver messages to all sensors or actuators. Neighbor detection and route discovery algorithms that consider a realistic physical layer are described. An adaptive broadcasting protocol without parameters suitable for delay tolerant networks is further discussed. In existing solutions for minimal energy broadcasting problem, nodes can adjust their transmission powers. Wireless Sensor Networks (WSNs) are sets of many sensors that gather data and collaborate together. So, the procedures of broadcast or multicast are more important than traditional point-to-point communication in computer network. This paper focuses on broadcasting in structured WSNs. In such a kind, the procedure of network communications is easier than in unstructured WSNs. Thus, it will make an overview of Multi Point Relay (MPR) to show its weakness. Then define a cluster-based architecture for WSNs which is constructed using MPR. Next, provide a new broadcast algorithm based on the previous cluster architecture called 3B (Backbone Based Broadcasting). By the end, an illustration of 3B shows that it minimizes the energy consumption for accomplishing broadcast compared to MPR.
There are number of cluster based routing algorithms in mobile ad hoc networks. Since ad hoc networks are not accompanied by fixed access points, efficient routing is a must for such networks. Clustering approach is applied in mobile ad hoc network because clusters are more easily manageable and are more viable. It consists of segregating the given network into several reasonable clusters by using a clustering algorithm. By performing clustering we elect a worthy node from the cluster as the cluster head in such a way that we strive to reduce the management overheads and thus increasing the efficiency of routing. As for the fact that nodes in mobile ad hoc network have frequent host change and frequent topology change routing plays an important role for maintenance and backup mechanism to stabilize network performance. This paper aims to review the previous research papers and provide a survey on the various cluster based routing protocols in mobile ad hoc network. This paper presents analytical study of cluster based routing algorithms from literature. Index Terms— Ad- hoc networks, Cluster head, Clustering, Protocol, Route selection.
A QoI Based Energy Efficient Clustering for Dense Wireless Sensor Networkijassn
In a wireless sensor network Quality of Information (QoI), Energy Efficiency, Redundant data avoidance,
congestion control are the important metrics that affect the performance of wireless sensor network. As
many approaches were proposed to increase the performance of a wireless sensor network among them
clustering is one of the efficient approaches in sensor network. Many clustering algorithms concentrate
mainly on power Optimization like FSCH, LEACH, and EELBCRP. There is necessity of the above
metrics in wireless sensor network where nodes are densely deployed in a given network area. As the nodes
are deployed densely there is maximum possibility of nodes appear in the sensing region of other nodes. So
there exists an option that nodes have to send the information that is already reached the base station by its
own cluster members or by members of other clusters. This mechanism will affect the QoI, Energy factor
and congestion control of the wireless sensor networks. Even though clustering uses TDMA (Time Division
Multiple Access) for avoiding congestion control for intra clustering data transmission, but it may fail in
some critical situation. This paper proposed a energy efficient clustering which avoid data redundancy in a
dense sensor network until the network becomes sparse and hence uses the TDMA efficiently during high
density of the nodes.
The novel applications of sensor networks impose some requirements in wireless sensor network design. With the energy efficiency and lifetime awareness, the throughput and network delayalso required to support emerging applications of sensor networks. In this paper, we propose
throughput and network delay aware intra-cluster routing protocol. We introduce the back-up links in the intra-cluster communication path. The link throughput, communication delay, packet loss ratio, interference, residual energy and node distance are the considered factors in finding efficient path of data communication among the sensor nodes within the cluster. The
simulation result shows the higher throughput and lower average packet delay rate for the proposed routing protocol than the existing benchmarks. The proposed routing protocol also shows energy efficiency and lifetime awareness with better connectivity rate.
Wireless Sensor Networks are highly distributed self-organized systems. WSN have been deployed in various fields. Now a day, Topology issues have received more and more attentions in Wireless Sensor Networks (WSN). While WSN applications are normally optimized by the given underlying network topology, another trend is to optimize WSN by means of topology control. In this area, a number of approaches have been invested, like network connectivity based topology control, cooperating schemes, topology directed routing, sensor coverage based topology control. Most of the schemes have proven to be able to provide a better network monitoring and communication performance with prolonged system lifetime. In this survey paper, I provide a full view of the studies in this area.
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.
Mobile Data Gathering with Load Balanced Clustering and Dual Data Uploading i...1crore projects
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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.
Designing an opportunistic routing scheme for adaptive clustering in mobile a...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
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.
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.
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
An Approach to Data Extraction and Visualisation for Wireless Sensor NetworksM H
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.
ON THE PERFORMANCE OF INTRUSION DETECTION SYSTEMS WITH HIDDEN MULTILAYER NEUR...IJCNCJournal
Deep learning applications, especially multilayer neural network models, result in network intrusion detection with high accuracy. This study proposes a model that combines a multilayer neural network with Dense Sparse Dense (DSD) multi-stage training to simultaneously improve the criteria related to the performance of intrusion detection systems on a comprehensive dataset UNSW-NB15. We conduct experiments on many neural network models such as Recurrent Neural Network (RNN), Long-Short Term Memory (LSTM), Gated Recurrent Unit (GRU), etc. to evaluate the combined efficiency with each model through many criteria such as accuracy, detection rate, false alarm rate, precision, and F1-Score.
Energy Conservation in Wireless Sensor Networks Using Cluster-Based ApproachIJRES Journal
In a wireless networking environment, the network is comprised of sensor nodes and backbones are subsets of sensors or actuators that suffice for performing basic data communication operations. They are applied for energy efficient broadcasting. In a broadcasting (also known as data dissemination) task, a message is to be sent from one node, which could be a sink or an actuator, to all the sensors or all the actuators in the network. The goal is to minimize the number of rebroadcasts while attempting to deliver messages to all sensors or actuators. Neighbor detection and route discovery algorithms that consider a realistic physical layer are described. An adaptive broadcasting protocol without parameters suitable for delay tolerant networks is further discussed. In existing solutions for minimal energy broadcasting problem, nodes can adjust their transmission powers. Wireless Sensor Networks (WSNs) are sets of many sensors that gather data and collaborate together. So, the procedures of broadcast or multicast are more important than traditional point-to-point communication in computer network. This paper focuses on broadcasting in structured WSNs. In such a kind, the procedure of network communications is easier than in unstructured WSNs. Thus, it will make an overview of Multi Point Relay (MPR) to show its weakness. Then define a cluster-based architecture for WSNs which is constructed using MPR. Next, provide a new broadcast algorithm based on the previous cluster architecture called 3B (Backbone Based Broadcasting). By the end, an illustration of 3B shows that it minimizes the energy consumption for accomplishing broadcast compared to MPR.
There are number of cluster based routing algorithms in mobile ad hoc networks. Since ad hoc networks are not accompanied by fixed access points, efficient routing is a must for such networks. Clustering approach is applied in mobile ad hoc network because clusters are more easily manageable and are more viable. It consists of segregating the given network into several reasonable clusters by using a clustering algorithm. By performing clustering we elect a worthy node from the cluster as the cluster head in such a way that we strive to reduce the management overheads and thus increasing the efficiency of routing. As for the fact that nodes in mobile ad hoc network have frequent host change and frequent topology change routing plays an important role for maintenance and backup mechanism to stabilize network performance. This paper aims to review the previous research papers and provide a survey on the various cluster based routing protocols in mobile ad hoc network. This paper presents analytical study of cluster based routing algorithms from literature. Index Terms— Ad- hoc networks, Cluster head, Clustering, Protocol, Route selection.
A QoI Based Energy Efficient Clustering for Dense Wireless Sensor Networkijassn
In a wireless sensor network Quality of Information (QoI), Energy Efficiency, Redundant data avoidance,
congestion control are the important metrics that affect the performance of wireless sensor network. As
many approaches were proposed to increase the performance of a wireless sensor network among them
clustering is one of the efficient approaches in sensor network. Many clustering algorithms concentrate
mainly on power Optimization like FSCH, LEACH, and EELBCRP. There is necessity of the above
metrics in wireless sensor network where nodes are densely deployed in a given network area. As the nodes
are deployed densely there is maximum possibility of nodes appear in the sensing region of other nodes. So
there exists an option that nodes have to send the information that is already reached the base station by its
own cluster members or by members of other clusters. This mechanism will affect the QoI, Energy factor
and congestion control of the wireless sensor networks. Even though clustering uses TDMA (Time Division
Multiple Access) for avoiding congestion control for intra clustering data transmission, but it may fail in
some critical situation. This paper proposed a energy efficient clustering which avoid data redundancy in a
dense sensor network until the network becomes sparse and hence uses the TDMA efficiently during high
density of the nodes.
The novel applications of sensor networks impose some requirements in wireless sensor network design. With the energy efficiency and lifetime awareness, the throughput and network delayalso required to support emerging applications of sensor networks. In this paper, we propose
throughput and network delay aware intra-cluster routing protocol. We introduce the back-up links in the intra-cluster communication path. The link throughput, communication delay, packet loss ratio, interference, residual energy and node distance are the considered factors in finding efficient path of data communication among the sensor nodes within the cluster. The
simulation result shows the higher throughput and lower average packet delay rate for the proposed routing protocol than the existing benchmarks. The proposed routing protocol also shows energy efficiency and lifetime awareness with better connectivity rate.
Wireless Sensor Networks are highly distributed self-organized systems. WSN have been deployed in various fields. Now a day, Topology issues have received more and more attentions in Wireless Sensor Networks (WSN). While WSN applications are normally optimized by the given underlying network topology, another trend is to optimize WSN by means of topology control. In this area, a number of approaches have been invested, like network connectivity based topology control, cooperating schemes, topology directed routing, sensor coverage based topology control. Most of the schemes have proven to be able to provide a better network monitoring and communication performance with prolonged system lifetime. In this survey paper, I provide a full view of the studies in this area.
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.
Mobile Data Gathering with Load Balanced Clustering and Dual Data Uploading i...1crore projects
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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.
Designing an opportunistic routing scheme for adaptive clustering in mobile a...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Sensors are electromechanical devices that use magnetic
field for sensing
Velocity sensors for antilock brakes and stability control
Position sensors for static seat location
Eddy current sensors for flaw detection
Design and simulation of passive uhf rfid temperature sensor tag using 3 d em...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
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DESIGN ISSUES ON SOFTWARE ASPECTS AND SIMULATION TOOLS FOR WIRELESS SENSOR NE...IJNSA Journal
In this paper, various existing simulation environments for general purpose and specific purpose WSNs are discussed. The features of number of different sensor network simulators and operating systems are compared. We have presented an overview of the most commonly used operating systems that can be used in different approaches to address the common problems of WSNs. For different simulation environments there are different layer, components and protocols implemented so that it is difficult to compare them. When same protocol is simulated using two different simulators still each protocol implementation differs, since their functionality is exactly not the same. Selection of simulator is purely based on the application, since each simulator has a varied range of performance depending on application.
From Physical to Virtual Wireless Sensor Networks using Cloud Computing IJORCS
In the modern world, billions of physical sensors are used for various dedications: Environment Monitoring, Healthcare, Education, Defense, Manufacturing, Smart Home, Agriculture Precision and others. Nonetheless, they are frequently utilized by their own applications and thereby snubbing the significant possibilities of sharing the resources in order to ensure the availability and performance of physical sensors. This paper assumes that the immense power of the Cloud can only be fully exploited if it is impeccably integrated into our physical lives. The principal merit of this work is a novel architecture where users can share several types of physical sensors easily and consequently many new services can be provided via a virtualized structure that allows allocation of sensor resources to different users and applications under flexible usage scenarios within which users can easily collect, access, process, visualize, archive, share and search large amounts of sensor data from different applications. Moreover, an implementation has been achieved using Arduino-Atmega328 as hardware platform and Eucalyptus/Open Stack with Orchestra-Juju for Private Sensor Cloud. Then this private Cloud has been connected to some famous public clouds such as Amazon EC2, ThingSpeak, SensorCloud and Pachube. The testing was successful at 80%. The recommendation for future work would be to improve the effectiveness of virtual sensors by applying optimization techniques and other methods.
Performance Evaluation of Wireless Sensor Networks Communication Overhead and...ijtsrd
Powerful actors and resource constrained sensors are joined in wireless networks to form Wireless Sensor and Actor Networks WSANs . The lifespan of a sensor network may be effectively increased by clustering. The method of clustering involves breaking up sensor networks into smaller, more nimble groups of individuals with a cluster head. In hierarchically organised wireless sensor networks, clustering algorithms must choose the ideal number of clusters. In this study, we examine the effectiveness of cluster based wireless sensor networks for various wireless sensor network communication patterns WSNs . By utilising the self organizing map SOM based clustering approach, we concentrate on their performances in terms of Communication overhead and Energy consumption in WSN with varied velocities for the cluster based protocol. Mangukiya Hiteshkumar Bhupatbhai "Performance Evaluation of Wireless Sensor Networks' Communication Overhead and Energy Consumption using the Self-Organizing Map Method" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-6 , October 2022, URL: https://www.ijtsrd.com/papers/ijtsrd51936.pdf Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/51936/performance-evaluation-of-wireless-sensor-networks-communication-overhead-and-energy-consumption-using-the-selforganizing-map-method/mangukiya-hiteshkumar-bhupatbhai
Wireless Sensor Networks (WSNs) are used in many application fields, such as military,
healthcare, environment surveillance, etc. The WSN OS based on event-driven model doesn’t
support real-time and multi-task application types and the OSs based on thread-driven model
consume much energy because of frequent context switch. Due to the high-dense and largescale
deployment of sensor nodes, it is very difficult to collect sensor nodes to update their
software. Furthermore, the sensor nodes are vulnerable to security attacks because of the
characteristics of broadcast communication and unattended application. This paper presents a
task and resource self-adaptive embedded real-time microkernel, which proposes hybrid
programming model and offers a two-level scheduling strategy to support real-time multi-task
correspondingly. A communication scheme, which takes the “tuple” space and “IN/OUT”
primitives from “LINDA”, is proposed to support some collaborative and distributed tasks. In
addition, this kernel implements a run-time over-the-air updating mechanism and provides a
security policy to avoid the attacks and ensure the reliable operation of nodes. The performance
evaluation is proposed and the experiential results show this kernel is task-oriented and
resource-aware and can be used for the applications of event-driven and real-time multi-task.
TASK & RESOURCE SELF-ADAPTIVE EMBEDDED REAL-TIME OPERATING SYSTEM MICROKERNEL...cscpconf
Wireless Sensor Networks (WSNs) are used in many application fields, such as military,
healthcare, environment surveillance, etc. The WSN OS based on event-driven model doesn’t
support real-time and multi-task application types and the OSs based on thread-driven model
consume much energy because of frequent context switch. Due to the high-dense and largescale
deployment of sensor nodes, it is very difficult to collect sensor nodes to update their
software. Furthermore, the sensor nodes are vulnerable to security attacks because of the
characteristics of broadcast communication and unattended application. This paper presents a
task and resource self-adaptive embedded real-time microkernel, which proposes hybrid
programming model and offers a two-level scheduling strategy to support real-time multi-task
correspondingly. A communication scheme, which takes the “tuple” space and “IN/OUT”
primitives from “LINDA”, is proposed to support some collaborative and distributed tasks. In
addition, this kernel implements a run-time over-the-air updating mechanism and provides a
security policy to avoid the attacks and ensure the reliable operation of nodes. The performance
evaluation is proposed and the experiential results show this kernel is task-oriented and
resource-aware and can be used for the applications of event-driven and real-time multi-task.
The European Space Agency (ESA) uses an engine to perform tests in the Ground Segment infrastructure, specially the Operational Simulator. This engine uses many different tools to ensure the development of regression testing infrastructure and these tests perform black-box testing to the C++ simulator implementation. VST (VisionSpace Technologies) is one of the companies that provides these services to ESA and they need a tool to infer automatically tests from the existing C++ code, instead of writing manually scripts to perform tests. With this motivation in mind, this paper explores automatic testing approaches and tools in order to propose a system that satisfies VST needs.
Real World Testbeds Emulation for Mobile Ad-hoc NetworksKishan Patel
It focuses on creating an original computer environment, which can be time-consuming and difficult to achieve, and also it is very costly because of its ability to maintain a closer connection to the authenticity object.
Analysis and assessment software for multi-user collaborative cognitive radi...IJECEIAES
Computer simulations are without a doubt a useful methodology that allows to explore research queries and develop prototypes at lower costs and timeframes than those required in hardware processes. The simulation tools used in cognitive radio networks (CRN) are undergoing an active process. Currently, there is no stable simulator that enables to characterize every element of the cognitive cycle and the available tools are a framework for discrete-event software. This work presents the spectral mobility simulator in CRN called “App MultiColl-DCRN”, developed with MATLAB’s app designer. In contrast with other frameworks, the simulator uses real spectral occupancy data and simultaneously analyzes features regarding spectral mobility, decision-making, multi-user access, collaborative scenarios and decentralized architectures. Performance metrics include bandwidth, throughput level, number of failed handoffs, number of total handoffs, number of handoffs with interference, number of anticipated handoffs and number of perfect handoffs. The assessment of the simulator involves three scenarios: the first and second scenarios present a collaborative structure using the multi-criteria optimization and compromise solution (VIKOR) decision-making model and the naïve Bayes prediction technique respectively. The third scenario presents a multi-user structure and uses simple additive weighting (SAW) as a decision-making technique. The present development represents a contribution in the cognitive radio network field since there is currently no software with the same features.
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.
CSP as a Domain-Specific Language Embedded in Python and JythonM H
Recently, much discussion has taken place within the Python programming community on how best to support concurrent programming. This paper describes a new Python library, python-csp, which implements synchronous, message-passing concurrency based on Hoare’s Communicating Sequential Processes. Although other CSP libraries have been written for Python, python-csp has a number of novel features. The library is implemented both as an object hierarchy and as a domain-specific language, meaning that programmers can compose processes and guards using infix operators, similar to the original CSP syntax. The language design is intended to be idiomatic Python and is therefore quite different to other CSP libraries. python-csp targets the CPython interpreter and has variants which reify CSP process as Python threads and operating system processes. An equivalent library targets the Jython interpreter, where CSP processes are reified as Java threads. jython-csp also has Java wrappers which allow the library to be used from pure Java programs. We describe these aspects of python-csp, together with performance benchmarks and a formal analysis of channel synchronisation and choice, using the model checker SPIN.
Modelling Clustering of Wireless Sensor Networks with Synchronised Hyperedge ...M H
This paper proposes Synchronised Hyperedge Replacement (SHR) as a suitable modelling framework for Wireless Sensor Networks (WSNs). SHR facilitates explicit modelling of WSNs applications environmental conditions (that significantly affect applications performance) while providing a sufficiently high level of abstraction for the specification of the underling coordination mechanisms. Because it is an intractable problem to solve in distributed manner, and distribution is important, we propose a new Nutrient-flow-based Distributed Clustering (NDC) algorithm to be used as a working example. The key contribution of this work is to demonstrate that SHR is sufficiently expressive to describe WSNs algorithms and their behaviour at a suitable level of abstraction to allow onward analysis.
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.
Enhancing Student Learning Experience and Satisfaction Using Virtual Learning...M H
The paper presents a project that aims to enhance students experiences and satisfaction through the use of a Virtual Learning Environment. Particularly, it aims at developing a blended learning community to support diverse student population, including students with special learning needs. This project focuses on the teaching/learning aspects of students experiences and satisfaction. Other aspects are geared towards use by student support staff and those whose main responsibility is technical or system administration support. Various methods were used to measure the success of the project and its implementation. Evaluation results show a significant increase in student satisfaction and enhanced progression rate.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
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Simulation Issues in Wireless Sensor Networks: A Survey
1. SENSORCOMM 2012 : The Sixth International Conference on Sensor Technologies and Applications
Simulation Issues in Wireless Sensor Networks: A Survey
Abdelrahman Abuarqoub, Fayez Al-Fayez, Tariq Alsboui, Mohammad Hammoudeh, Andrew Nisbet
School of Computing, Mathematics and Digital Technology
Manchester Metropolitan University
Manchester, UK
f.a.alfayez@gmail.com{A.Abuarqoub, M.Hammoudeh, T.Alsboui, A.Nisbet}@mmu.ac.uk
Abstract—This paper presents a survey of simulation tools Kurkowski et al. [4]. Yet, 53% of the authors used
and systems for wireless sensor networks. Wireless sensor simulation in their research. Apart from the self-developed
network modelling and simulation methodologies are simulators, there are a few widely used network simulators
presented for each system alongside judgments concerning including NS-2 [5] , OPNET [6], MATLAB [7], IFAS [8],
their relative ease of use and accuracy. Finally, we propose
a mixed-mode simulation methodology that integrates a
and OMNet++ [9]. Figure 1 shows the simulator usage
simulated environment with real wireless sensor network following a survey of simulation based papers in
testbed hardware in order to improve both the accuracy and SENSORCOMM 2011 conference. Simulation of ad hoc
scalability of results when evaluating different prototype wireless capabilities for WSNs have been addressed by
designs and systems. extending existing simulators, or specifically building new
ones, such as NS-3 [10]. The latter class of simulators
Keywords-Wireless Sensor Networks; Simulation tools; mostly focus on protocols and algorithms for layers of the
Survey; Testbeds; Mix-mode simulation. network stack, but they do not directly support WSNs.
I. INTRODUCTION
A successful large-scale Wireless Sensor Network
(WSN) deployment necessitates that the design concepts
are checked before they are optimised for a specific
hardware platform. Developing, testing, and evaluating
network protocols and supporting architectures and
services for WSNs can be undertaken through test-beds or
simulation. Whilst test-beds are extremely valuable,
implementing such test-beds is not always viable because Figure 1. Simulator usage results from a survey of simulation based
papers in SENSORCOMM 2011.
it is difficult to adapt a large number of nodes in order to
study the different factors of concern. The substantial cost Recently, several simulation tools have appeared to
of deploying and maintaining large-scale WSNs and the specifically address WSNs, varying from extensions of
time needed for setting up the network for experimental existing tools to application specific simulators. Although
goals makes simulation invaluable in developing reliable these tools have some collective objectives, they obviously
and portable WSNs applications. differ in design goals, architecture, and applications
In WSNs, simulation provides a cost effective method abstraction level. In the next section, we review some of
of assessing the appropriateness of systems before the important WSNs simulation tools and explore their
deployment. It can, for example, help assess the scalability characteristics.
of algorithms free of the constraints of a hardware The rest of the paper is organised as follows: In
platform. Furthermore, simulators can be used to simplify Section II, the most popular WSNs simulators are outlined
the software development process for a particular WSN and their strengths and weaknesses are discussed.
application. For instance, TOSSIM [1] utilises the Section III, presents our views about the future of WSNs
component based architecture of TinyOS [2] and provides testing and evaluation methods. Section IV concludes the
a hardware resource abstraction layer that enables the paper.
simulation of TinyOS applications which can then be
ported directly to a hardware platform without further II. WSNS NETWORK SIMULATION TOOLS
modifications.
A. SensorSim
Simulation is hence the research tool of choice for the
majority of the mobile ad hoc network community. An SensorSim [11] builds on the NS-2 simulator providing
examination of research papers published in additional capabilities for modelling WSNs. The main
SENSORCOMM 2011 [3] reveals a significant increase in features of this platform are: power and communication
using real testbeds compared to the study published by protocol models; sensing channel and sensor models;
scenario generation; and support for hybrid simulations.
Copyright (c) IARIA, 2012. ISBN: 978-1-61208-207-3 222
2. SENSORCOMM 2012 : The Sixth International Conference on Sensor Technologies and Applications
The public release of the SensorSim suite of tools was simulation of a heterogeneous collection of sensor nodes
withdrawn due to its unfinished nature and the inability of and a dynamic network topology. TOSSF suffers from
authors to provide the needed level of support. potentially long test-debug cycles because it does not
Georgia Tech SensorSimII [12] is written in a modular provide a scripting framework for experimentation.
style, where sensor nodes are organised into three Although it enables development of custom environmental
components: application, network, and link. The work in models, the absence of a scripting framework requires
SensorSimII may be divided into two areas: the simulator those models to be compiled into the simulation
core and the visualisation tools. The simulator core framework. Given that both of these simulators are tightly
coupled with TinyOS, they may be unsuitable for early
essentially manages an array of independent sensor nodes
prototyping, or developing portable WSN applications.
throughout time. The visualisation tools provide views of
both individual node state and communication traffic D. GloMoSim
between nodes. GloMoSim [16] is a scalable simulation environment
Both SensorSim projects are open source and free to for wireless and wired network systems. Its parallel
use. However, the simulators are limited in their realism discrete-event design distinguishes it from most other
because (apart from SensorSim's power modules) neither sensor network simulators. Though it is a general network
simulator considers the limited resources of sensor nodes
simulator, GloMoSim currently supports protocols
such as memory, and real-time computational capability.
designed purely for wireless networks. GloMoSim is built
Moreover, it is not always required by the WSN to validate
the functional correctness and/or, to provide performance using a layered approach similar to the seven layer
guarantees. SensorSim simulates the complete WSN network architecture of the OSI model. It uses standard
protocol stack, although this can be regarded as overkill APIs between different simulation layers to allow rapid
and adding unnecessary complexity as this is not required integration of models developed at different layers,
in order to simulate the expected behaviour. This makes possibly by different users.
the SensorSim platform complex and difficult to use. As in NS-2, GloMoSim uses an object-oriented
approach, however for scalability purposes; each object is
B. TOSSIM responsible for running one layer in the protocol stack of
There are platforms specifically designed to simulate every node. This design strategy helps to divide the
WSNs, such as TOSSIM [1] which is a part of the TinyOS overhead management of a large-scale network.
development efforts [2]. TOSSIM is a discrete-event GloMoSim has been found to be effective for simulating
simulator for TinyOS applications [13]. It aims to assist IP networks, but it is not capable of simulating sensor
TinyOS application development and debugging by networks accurately [17]. Moreover, GloMoSim does not
compiling applications into the TOSSIM framework, support phenomena occurring outside of the simulation
which runs on a PC instead of compiling them for a mote. environment, all events must be gathered from
Using the TOSSIM framework, programs can be directly neighbouring nodes in the network. Finally, GloMoSim
targeted to motes without modification. This gives users a stopped releasing updates in 2000 and released a
bigger margin to debug, test, and analyse algorithms in a commercial product called QualNet.
controlled and repeatable environment. In TOSSIM, all
E. Qualnet
nodes share the exact same code image, simulated at bit
granularity, and assuming static node connectivity is Qualnet is a commercial network simulator tool
known in advance. Therefore, TOSSIM is more of a released by Scalable Network Technologies [18] that is
TinyOS emulator than a general WSN simulator. It derived from GloMoSim. Qualnet significantly extends the
focuses on simulating TinyOS rather than simulating the set of models and protocols supported by GloMoSim. It
real world. This has the advantage that the developed also provides a comprehensive set of advanced wireless
algorithms can be tested on a target platform. However, modules and user-friendly tools for building scenarios and
this may place some restrictions of the target platform on analysing simulation results. Qualnet is a discrete-event
the simulation. TOSSIM is not always the right simulation simulator, as such, it is event driven and time aware. It
solution; like any simulation, it makes several assumptions uses a layered architecture that is run by each node. When
about the target hardware platform, focusing on making a protocol resides in a particular layer at one node, the
some behaviour accurate while simplifying others [1]. packets are passed down crossing the remaining layers at
TOSSIM can be used as a tool for absolute evaluation of the sending node, across the network, and then up to the
some causes of the behaviour observed in real-world protocol stack at the receiving node. Qualnet has a
network deployments. modular design and an intuitive GUI that make it easy to
use to learn and modify.
C. TOSSF
F. OPNET
TOSSF [14] is a simulation framework that compiles a
TinyOS application into the SWAN [15] simulation OPNET [19] is a further discrete event, object
framework. It can be viewed as an improvement over oriented, general purpose network simulator. The engine
TOSSIM with a primary focus on scalability. It allows of OPNET is a finite state machine model in combination
Copyright (c) IARIA, 2012. ISBN: 978-1-61208-207-3 223
3. SENSORCOMM 2012 : The Sixth International Conference on Sensor Technologies and Applications
with an analytical model. It uses a hierarchical model to platforms. The next step in the development cycle
define each characteristic of the system. The top hierarchy following the simulation is data replay. In this model,
level contains the network model, where the topology is EmStar uses data collected from actual sensors in order to
designed. The second level defines the data flow models. run its simulation. Leading directly from this, Emstar uses
The third level is the process editor, which handles the half-simulation methodology similar to SensorSim's,
control flow models defined in the second level. Finally, a where the software is running on a host machine and
parameter editor is included to support the three higher interfacing with a real physical communication channels.
levels. The hierarchical models result in event queues for The final step in the development cycle is deployment.
a discrete event simulation engine and a set of entities that EmStar combines many of the features of other WSNs
handle the events. Each entity represents a node which simulators. Its component based design allows for fair
consists of a finite state machine which processes the scalability. Moreover, each aspect of the network can be
events during simulation. logically fine-tuned due to its development cycle design.
Unlike NS-2 and GloMoSim, OPNET supports Because it targets a particular platform, many protocols
modelling sensor-specific hardware, such as physical-link are already available to be used. At the deployment step
transceivers and antennas. It also enables users to define in the development cycle, only the configuration files
custom packet formats. An attractive feature of OPNET is have to be designed. This potentially adds constraints on
its capability of recording a large set of user defined the user as they must either ensure that the hardware
results. Furthermore, the GUI (Graphical User Interface), configuration being used matches the existing
along with the considerable amount of documentation and configuration file, or they must write their own files.
study cases that come along with the license are another The main goal of Emstar is to reduce design
attractive feature of the simulator. This GUI interface can complexity, enabling work to be shared and reused, and to
also be used to model, graph, and animate the resulting simplify and accelerate the design of new sensor network
output. The network operator is provided with editors that applications. While not as efficient and fast as other
are required to simplify the different levels of modelling. frameworks like TOSSIM, Emstar provides a simple
Though model parameters can be changed, the simulation environmental model and network medium in which to
accuracy is influenced because OPNET is not open source design, develop and deploy heterogeneous sensor network
software. Similar to NS-2, the object-oriented design of applications. When used as a migration platform from
OPNET causes scalability problems. It does not have a code to real sensor environment, the environment model
may be sufficient for most developers. Another drawback
high number of protocols publicly available possibly
of Emstar is that the simulator supports only the code for
because of source code licensing constraints. Finally, the types of nodes that it is designed to work with.
OPNET is only available in commercial form.
The second class of simulators are application-oriented H. SENS
simulators, including EmStar [20], SENS [21], J-Sim [22], SENS [21] is a customisable component-based
Shawn [23], and Dingo [24]. simulator for WSN applications. It consists of
G. EmStar interchangeable and extensible components for
applications, network communication, and the physical
EmStar [20] is a component based, discrete-event
environment. In SENS, each node is partitioned into four
framework that offers a range of run-time environments,
main components: application, simulates the software
from pure simulation, distributed deployment on
application of the sensor node; network, handles incoming
iPAQs [25], to a hybrid simulation mode similar to
and outgoing packets; physical, reads sensed information;
SensorSim. Emstar supports the use of simulation in the
and environment, network propagation characteristics.
early stages of design and development by providing a
Multiple different component implementations offer
range of simulated sensor network components, including
varying degrees of realism. For example, users can choose
radios, which provide the same interfaces as actual
between various application-specific environments with
components. It supports hybrid mode with some actual
different signal propagation characteristics. As in
components and some simulated components, and full
TOSSIM, SENS source code can be ported directly into
native mode with no simulated components. As in
actual sensor nodes, enabling application portability.
TOSSIM, EmStar uses the same source code that runs at
Moreover, it provides a power module for development of
each of these levels to run on actual sensors. Amongst
dependable applications.
other simulators, such as TOSSIM, EmStar provides an
SENS defines three network models that can be used.
option to interface with actual hardware while running a
The first successfully forwards packets to all neighbours,
simulation. EmStar is compatible with two different types
the second delivers with a chance of loss based on a fixed
of node hardware. It can be used to develop software for
probability, and the third considers the chance of collision
Mica2 motes [26] and it also offers support for
at each node. The physical component includes the non-
developing software for iPAQ based microservers. The
network hardware for the sensor such as the power,
development cycle is the same for both hardware
sensors, and actuators. At a lower level, the environment
Copyright (c) IARIA, 2012. ISBN: 978-1-61208-207-3 224
4. SENSORCOMM 2012 : The Sixth International Conference on Sensor Technologies and Applications
component models the physical phenomena and the communicates using the same protocols that would be
layout. The layout model includes different types of deployed on a physical node. Sensors are modelled using a
surfaces, each affecting radio and sound propagation in a pool of concurrent, communicating threads. Individual
different way. sensors are able to: (1) Gather and process data from a
SENS is less customisable than many other model environment; (2) Locate and communicate with
simulators, providing no chance to alter the MAC their nearest neighbours; (3) Determine whether they are
protocol, along with other low level network protocols. operating correctly and act accordingly to alter the
SENS uses one of the most sophisticated environmental network topology in case of faulty nodes being detected.
Nodes may be configured differently to simulate a
models and implements the use of sensors well. However,
heterogeneous sensor network. Dingo comes with a set of
the only measurable phenomenon is sound.
application level routing packages including simple multi-
I. J-Sim hop flooding, MuMHR [28] and LEACH [29].
J-Sim [22] is a component-based discrete event Dingo features a significant improvement in the
simulator built in Java and modelled after NS-2. The simulation performance by giving the option to split the
design of this simulator aims at solving many of the visualisation from the simulation. It provides tools for the
shortcomings of comparable object-oriented simulators simulation and deployment of high-level, Python code on
like NS-2. J-Sim uses the concept of components instead real sensor networks. For example, Dingo-boom provides
of the concept of having an object for each individual a two-way interface between MoteIV's Boomerang class
node. J-Sim uses three top level components: the target motes and Dingo. Dingo-top is another tool which is used
node which produces stimuli, the sensor node that reacts to dump network topology data to a text file and generate
to the stimuli, and the sink node which is the ultimate a graphical representation of that topology. Furthermore,
destination for stimuli reporting. Each component is Dingo has several features in the form of plugins. These
broken into parts and modelled differently within the can be activated/deactivated on the plugin menu.
simulator; this eases the use of different protocols in As with SensorSimII, Dingo provides an extensible
different simulation runs. visualisation framework that aims at easing the life for
J-Sim claim has several advantages over NS-2 and sensor network debugging, assessment, and understanding
other simulators. First its component based architecture of the software by visualising the sensor network
scales better than the object oriented model used by NS-2 topology, the individual node state, and the transmission
and other simulators. Second, J-Sim has an improved of the sensed data. Dingo comes with an interface
energy model and the ability to simulate the use of between the simulation environment and different
sensors for phenomena detection. Like SensorSim, there hardware platforms, for example the Gumstix [30]
is support for using the simulation code for real hardware platform. Also, Dingo allows mixed-mode simulation
sensors. However, J-Sim is comparatively complicated to using a combination of real and simulated nodes. In
use. While no more complicated than NS-2, the latter Dingo, nodes have the ability to obtain their sensed data
simulator is more popular and accepted in the sensor from a database or graphical objects like maps; this
network research community and more community improves the fidelity of simulations as it makes it possible
support is available, therefore, more people are keen to to check the simulation results against the real data.
spend the time to learn how to use it. Dingo focuses on the protocols and algorithms for
Though it is scalable, J-Sim has a set of inefficiencies. higher layers of network state but it does not directly
First, there is unnecessary overhead in the support sensor networks at the physical layer. It has major
intercommunication model. The second problem is drawbacks which limit its functionality. Most of these
inherited by most sensor networks simulators that are built drawbacks are due to the incomplete nature of the tool.
on top of general purpose simulators, 802.11 is the only These drawbacks are: (1) The lack for Media Access
MAC protocol that can be used in J-Sim. Finally, Java is Control or MAC layer, communications to be handled by
possibly less efficient than many other languages. point-to-point systems. (2) No collision management
procedure, partly due to the absence of the MAC layer.
J. Dingo
Dingo [27] provides a workbench for prototyping K. NS-3
algorithms for WSNs taking a top-down design NS-2 [31] is an object-oriented discrete event
methodology. Having no target platform means the full simulator targeted at networking research. It is an open
functionality of a programming language can be used. This source network simulator originally designed for wired,
eases the design process as prototype algorithms can be IP networks. The NS-2 simulation environment offered
tested before optimisation for the target platform. Dingo great flexibility in studying the characteristics of WSNs
consists of a fixed API, with customisable internals. It has because it includes flexible extensions for WSNs. NS-2
a simple graphical user interface and a set of base classes, has a number of limitations: (1) It puts some restrictions
which are extended by the user to create simulation. Each on the customisation of packet formats, energy models,
simulated sensor node runs in its own thread and
MAC protocols, and the sensing hardware models, which
Copyright (c) IARIA, 2012. ISBN: 978-1-61208-207-3 225
5. SENSORCOMM 2012 : The Sixth International Conference on Sensor Technologies and Applications
limits its flexibility; (2), the lack of an application model and follow different approaches to investigate different
makes it ineffective in environments that require problems. The variety of existing simulation tools has led
interaction between applications and the network to accuracy and authenticity issues that concern even the
protocols. (3) It does not run real hardware code; (4) It best simulators available today. Such issues also make it
has been built by many developers and contains several even more difficult to replicate and compare evaluation
inherent known and unknown bugs. (5) It does not scale results from competing simulation systems. Simulation
well for WSNs due to its object-oriented design; (6) Using drawbacks also include the lack of visualisation tools,
C++ code and oTcl scripts makes it difficult to use. GUI's, poor documentation, absence of examples,
To overcome the above drawbacks the improved NS-3 amongst others.
simulator [10] was developed. NS-3 supports simulation To solve the dilemma of having an accurate but
and emulation. It is totally written in C++, while users scalable and low-cost prototyping solution, we suggest the
can use python scripts to define simulations. Hence, use of mixed-mode simulation as an effective midrange
transferring NS-2 implementation to NS-3 require manual solution. Mixed-mode simulation is the integration of a
intervention. Besides the scalability and performance simulated environment and a real testbed to improve both
improvements, simulation nodes have the ability to the accuracy and scalability of testing results. In other
support multiple radio interfaces and multiple channels. words, the mixed-mode simulation enables the simulation
Furthermore, NS-3 supports a real-time schedule that of algorithms partially in software and partially in a real
makes it possible to interact with a real systems [10]. For hardware WSN testbed. A small number of simulation
example, a real network device can emit and receive NS-3 tools like NS-3 and Dingo already support this mode of
generated packets. simulation. This simulation mode allows researchers to
L. Shawn compare the results of running the same algorithm in both
simulation and on physical sensor hardware; the
Shawn is an open source discrete event simulator for comparison allows the inclusion or the modelling of more
WSNs. It is written in C++ and can be run in Linux/Unix realistic conditions in the simulation environment. A
and Windows environments. Shawn aims to simulate
flexible mixed-mode simulator should support integration
large- scale WSNs, where physically accurate simulations
fail. The idea behind Shawn is to use abstract models to of heterogeneous sensor devices. Also, the simulation-
simulate the affects of a phenomenon rather than the testbed interaction remains a challenging task that needs
phenomenon itself [23]. Users of Shawn can adapt the to be addressed. For instance, the authors of Dingo
simulation to their needs by selecting the application describe in [33] a new Python library that implements
preferred behaviour. The authors claim that Shawn synchronous message-passing concurrency to improve
provides a high abstraction level that hides a lot of the coordination between many hosts.
simulation details. Users are given full access to the Yet, the choice of a suitable simulator is a difficult
communication graph, which allows them to decision. There is no 'best' simulator; each simulator has
observe nodes and their data [23]. However, there are specific features that work well in certain circumstances.
some limitation in Shawn, for instance: Visualization The selection of a simulator depends mostly on the
output is not supported, MAC module is not extent, and algorithmic feature to be evaluated. High level simulators
also users need to do much programming [32]. like NS-2 gives an estimation about the applications and
some middleware behaviour. Mid-level simulators, e.g.
III. DISCUSSION
OMNET, provides more information about the physical
Generally, real WSNs testbeds provide a more layer components that are simulated without giving too
accurate, realistic, and replicable validation mechanism much details. Low-level simulators provide accurate bit
for algorithms and protocols. However, the cost of level estimations of the hardware as well as software
deployment and maintenance of large-scale testbeds limits performance. Regardless of the simulator, any
their applicability. Moreover, the wide variety of simulations will always have weaknesses either due to
available sensor hardware can make it rather difficult to non-realistic assumptions or modelling errors that may be
replicate any results produced by real testbeds. Besides, present in the algorithm itself. Therefore, developing
in some applications, where dangerous conditions are formal methods, e.g. using graph theory [34], to verify the
being studied, e.g. chemical pollution, a real testbed is an correctness of new algorithms and protocols is also part of
unwanted choice. Out of these restrictions came the need the testing or evaluation research.
for simulation as a tool for validating and testing Table 1 summarise and compares the reviewed
algorithms/protocols. As shown in Section II, simulation simulation tools.
tools are widely available and used by WSNs researchers.
However, most of the existing simulators are incomplete
Copyright (c) IARIA, 2012. ISBN: 978-1-61208-207-3 226
6. SENSORCOMM 2012 : The Sixth International Conference on Sensor Technologies and Applications
TABLE 1. SUMMARY ABOUT REVIEWED SIMULATION TOOLS
General or
Programming Open
Simulators GUI Specific Main Features Limitations
Language Source
Simulator
-Power and communication protocol -Limited in SensorSim project realism
models Sensing channel and sensor -Consider limited resources of sensor
Specifically
nodes.
SensorSim C++ No designed Yes models -Simulates the complete WSN protocol
for WSNs -Scenario generation stack
-Support for hybrid simulations
-Can be targeted to motes without
-Makes several assumptions about the
Specifically modification
target hardware platform
TOSSIM C++ Yes designed Yes -Nodes share the exact same code image
for WSNs -Focusing on making some behaviour
-The developed algorithms can be tested
accurate while simplifying others
on a target platform
Specifically -Primary focus on scalability
TOSSF C++ Yes designed Yes -Support heterogeneous nodes and -Long test-debug cycles
for WSNs dynamic topology
-Supports protocols designed purely for
-Not scapable of simulating sensor
wireless networks
networks accurately
GloMoSim C/Parsec Yes General Yes -Built using a layered approach.
-does not support phenomena occurring
-Uses standard APIs between different
outside of the simulation environmen
simulation layers.
Comm- -Comprehensive set of advanced wireless
Qualnet C/C++ Yes General - The annual license is expensive
ercial modules and user-friendly tools
-Uses a hierarchical model to define each
Comm- characteristic of the system
OPNET C/C++ Yes General - scalability problems
ercial -Capability of recording a large set of user
defined results
-Supports hybrid mode
-Provides an option to interface with
Specifically
actual hardware while running a -Supports only the code for the types of
EmStar C Yes designed Yes
simulation nodes that it is designed to work with
for WSNs
-Compatible with two different types of
node hardware
Specifically
-Multiple different component -Less customisable
SENS C++ No designed Yes
implementations -Only measurable phenomenon is sound
for WSNs
-Ability to simulate the use of sensors for
Specifically -Comparatively complicated to use
phenomena detection
J-Sim Java Yes designed Yes -Unnecessary overhead in the
-Support for using the simulation code for
for WSNs intercommunication model
real hardware sensors
-Full functionality of a programming -Does not directly support sensor
Specifically
language can be used networks at the physical layer
Dingo Python Yes designed Yes
-Option to split the visualisation from the -Incomplete nature of the tool
for WSNs
simulation
- Some restrictions on the
-Supports simulation and emulation
customisation.
-Supports a real-time schedule
NS-3 C++ No General Yes -Lack of an application model
-Ability to support multiple radio
-Does not run real hardware code
interfaces and multiple channels
-Does not scale well for WSNs
-Able to simulate large- scale WSNs
Specifically -Does not support visualization output
-Ability of selecting the application
Shawn C++ No designed Yes -MAC module is not extent
preferred behaviour
for WSNs -Lots of programing is required
-Full access to the communication graph
Copyright (c) IARIA, 2012. ISBN: 978-1-61208-207-3 227
7. SENSORCOMM 2012 : The Sixth International Conference on Sensor Technologies and Applications
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