245 research outputs found
A Model-driven Engineering Framework to Support an Architecture-Driven Development and Analysis of WSNs
No full textAn Effective Forest Fire Data-set for Heterogeneous Wireless Multimedia Sensor Networks
No full textForest fire images for deep learning
Effective Forest Fire Detection Data-set for Heterogeneous Wireless Multimedia Sensor Networks
No full textForest fire images for deep learning
A model-driven engineering framework for architecting and analysing Wireless Sensor Networks
No full textA Wireless Sensor Network (WSN) is composed of distributed sensors with limited processing capabilities and energy restrictions. These unique attributes pose new challenges amongst which prolonging the WSN lifetime is one of the most important. Challenges are often tackled by a code-and-fix process that relies on low-level hardware and software information
On the performance, availability and energy consumption modelling of clustered IoT systems
No full textWireless sensor networks (WSNs) form a large part of the ecosystem of the Internet of Things (IoT), hence they have numerous application domains with varying performance and availability requirements. Limited resources that include processing capability, queue capacity, and available energy in addition to frequent node and link failures degrade the performance and availability of these networks. In an attempt to efficiently utilise the limited resources and to maintain the reliable network with efficient data transmission; it is common to select a clustering approach, where a cluster head is selected among the diverse IoT devices. This study presents the stochastic performance as well as the energy evaluation model for WSNs that have both node and link failures. The model developed considers an integrated performance and availability approach. Various duty cycling schemes within the medium-access control of the WSNs are also considered to incorporate the impact of sleeping/idle states that are presented using analytical modeling. The results presented using the proposed analytical models show the effects of factors such as failures, various queue capacities and system scalability. The analytical results presented are in very good agreement with simulation results and also present an important fact that the proposed models are very useful for identification of thresholds between WSN system characteristics
Effects of IDSs on the WSNs Lifetime: Evidence of the Need of New Approaches
No full textA Wireless Sensor Network (WSN) consists of spatially distributed autonomous sensors that monitor environmental data such as temperature, humidity, light, speed and sound. WSNs pose new security challenges because of their unattended nature and limited resources. Although prevention measures such as encryption and firewalls have been successfully applied, the attacker can physically access the node and modify it. Intrusion Detection Systems (IDSs) are a second line of defence that can be used to mitigate this problem. Building IDSs for WSNs is a new challenge because of the limited resources of the WSN nodes. IDS solutions for sensor networks should try to minimise the use of battery of the sensor nodes in order to prolong the network lifetime. In this paper we analyse different solutions that have been proposed for intrusion detection in wireless sensor networks. More specifically we analyse the impact of popular intrusion detection systems on the life time of the WSNs. Our study is quite general since we consider IDSs that are distributed on the sensor nodes and continuously monitor the networks for evidence of attacks. We also consider IDSs that are event triggered, which means that they require agreement between nodes when a suspicious activity is detected. The agreement is used to detect the attack and isolate the attacker. We analyse the effects of IDSs on battery life. The results show that, popular oral message algorithm of Byzantine generals problem should be considered for small scale WSNs because of the overhead introduced in terms of messages exchanged for decision. We conclude our paper with properties and recommendations for IDSs working for WSNs and some future works
Path Loss Effect on Energy Consumption in a WSN
No full textEnergy consumption of nodes is a crucial factor that constrains the networks life time for Wireless Sensor Networks (WSNs). WSNs are composed of small sensors equipped with low-power devices, and have limited battery power supply. The main concern in existing architectural and optimisation studies is to prolong the network lifetime. The lifetime of the sensor nodes is affected by different components such as the microprocessor, the sensing module and the wireless transmitter/receiver. The existing works mainly consider these components to decide on best deployment, topology, protocols and so on. Recent studies have also considered the monitoring and evaluation of the path loss caused by environmental factors. Path loss is always considered in isolation from the higher layers such as application and network. It is necessary to combine path loss computations used in physical layer, with information from upper layers such as application layer for a more realistic evaluation. In this paper, a simulation-based study is presented that uses path-loss model and application layer information in order to predict the network lifetime. Physical environment is considered as well. We show that when path-loss is introduced, increasing the transmission power is needed to reduce the amount of packets lost. This presents a tradeoff between the residual energy and the successful transmission rate when more realistic settings are employed for simulation. It is a challenging task to optimise the transmission power of WSNs, in presence of path loss, because although increasing the transmission power reduces the residual energy, it also reduces the number of retransmissions required
Performability Modelling and Analysis of Clustered Wireless Sensor Networks with Limited Storage CapacitiesInternet and Distributed Computing Systems
No full textWireless Sensor Network (WSN) technology has seen an increasing demand for use in various application areas including multimedia sensor networks, smart agriculture and industrial automation. The applications demand for optimum results are dictated by the complexity of their deployment environment, hence the need for improved performance, availability and reliability. Packet loss due to limited memory capacity has become a major drawback in some areas of WSN applications like Multimedia Wireless Sensor Networks (WMSN). Most of the existing studies consider performance and availability evaluation separately. Considering systems for pure performance evaluation may cause overestimation of systems ability to perform. On the other hand focussing only on the availability may be too conservative since various levels of performance are not considered. In this paper, we propose an analytical modelling approach for bounded WSN queues where cluster-tree architecture is considered and integrated performance and availability measures analysed in the presence of failures, repairs/replacement and restoration. Open queuing network is used to model the behaviour of the cluster head as an M/M/1/L queuing system and using spectral expansion method, the system is solved and validated against simulation results. Both analytical and simulation results presented are in good agreement and are further used to analyse the trade-off between the arrival rate and buffer size for optimum performance and availability
Network Experience Scheduling and Routing Approach for Big Data Transmission in the Internet of Things
No full textThe recent developments in the Internet of Things related technologies have caused a shift towards smart applications such as smart cities, smart homes, smart education systems, e-health, and online applications to run businesses. These, in turn, have introduced significant additional loads to the existing network infrastructures. In addition, these applications use big data and require relatively short response times. In this paper, we are introducing a new scheduling and routing approach to enhance the end user experience, and utilize the network resources by providing improved transmission speed for the big data applications. The approach considers the source and destination requirements in terms of data size, expected delay, link load, and link capacity. Extensive simulations are performed, and the results obtained show the efficiency of our approach against other competitive approaches in terms of in-network delay, network throughput, and dropped packets
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