A framework for energy based performability models for wireless sensor networks

A novel idea of alternating node operations between Active and Sleep modes in Wireless Sensor Network (WSN) has successfully been used to save node power consumption. The idea which started off as a simple implementation of a timer in most protocols has been improved over the years to dynamically change with traffic conditions and the nature of application area. Recently, use of a second low power radio transceiver to triggered Active/Sleep modes has also been made. Active/Sleep operation modes have also been used to separately model and evaluate performance and availability of WSNs. The advancement in technology and continuous improvements of the existing protocols and application implementation demands continue to pose great challenges to the existing performance and availability models. In this study the need for integrating performance and availability studies of WSNs in the presence of both channel and node failures and repairs is investigated. A framework that outlines and characterizes key models required for integration of performance and availability of WSN is in turn outlined. Possible solution techniques for such models are also highlighted. Finally it is shown that the resulting models may be used to comparatively evaluate energy consumption of the existing motes and WSNs as well as deriving required performance measures

On the performance, availability and energy consumption modelling of clustered IoT systems

Wireless 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

On the performance, availability and energy consumption modelling of clustered IoT systems

Wireless 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

Modelling and performability evaluation of Wireless Sensor Networks

This thesis presents generic analytical models of homogeneous clustered Wireless Sensor Networks (WSNs) with a centrally located Cluster Head (CH) coordinating cluster communication with the sink directly or through other intermediate nodes. The focus is to integrate performance and availability studies of WSNs in the presence of sensor nodes and channel failures and repair/replacement. The main purpose is to enhance improvement of WSN Quality of Service (QoS). Other research works also considered in this thesis include modelling of packet arrival distribution at the CH and intermediate nodes, and modelling of energy consumption at the sensor nodes. An investigation and critical analysis of wireless sensor network architectures, energy conservation techniques and QoS requirements are performed in order to improve performance and availability of the network. Existing techniques used for performance evaluation of single and multi-server systems with several operative states are investigated and analysed in details. To begin with, existing approaches for independent (pure) performance modelling are critically analysed with highlights on merits and drawbacks. Similarly, pure availability modelling approaches are also analysed. Considering that pure performance models tend to be too optimistic and pure availability models are too conservative, performability, which is the integration of performance and availability studies is used for the evaluation of the WSN models developed in this study. Two-dimensional Markov state space representations of the systems are used for performability modelling. Following critical analysis of the existing solution techniques, spectral expansion method and system of simultaneous linear equations are developed and used to solving the proposed models. To validate the results obtained with the two techniques, a discrete event simulation tool is explored. In this research, open queuing networks are used to model the behaviour of the CH when subjected to streams of traffic from cluster nodes in addition to dynamics of operating in the various states. The research begins with a model of a CH with an infinite queue capacity subject to failures and repair/replacement. The model is developed progressively to consider bounded queue capacity systems, channel failures and sleep scheduling mechanisms for performability evaluation of WSNs. Using the developed models, various performance measures of the considered system including mean queue length, throughput, response time and blocking probability are evaluated. Finally, energy models considering mean power consumption in each of the possible operative states is developed. The resulting models are in turn employed for the evaluation of energy saving for the proposed case study model. Numerical solutions and discussions are presented for all the queuing models developed. Simulation is also performed in order to validate the accuracy of the results obtained. In order to address issues of performance and availability of WSNs, current research present independent performance and availability studies. The concerns resulting from such studies have therefore remained unresolved over the years hence persistence poor system performance. The novelty of this research is a proposed integrated performance and availability modelling approach for WSNs meant to address challenges of independent studies. In addition, a novel methodology for modelling and evaluation of power consumption is also offered. Proposed model results provide remarkable improvement on system performance and availability in addition to providing tools for further optimisation studies. A significant power saving is also observed from the proposed model results. In order to improve QoS for WSN, it is possible to improve the proposed models by incorporating priority queuing in a mixed traffic environment. A model of multi-server system is also appropriate for addressing traffic routing. It is also possible to extend the proposed energy model to consider other sleep scheduling mechanisms other than On-demand proposed herein. Analysis and classification of possible arrival distribution of WSN packets for various application environments would be a great idea for enabling robust scientific research

Survivability modeling for cyber-physical systems subject to data corruption

Cyber-physical critical infrastructures are created when traditional physical infrastructure is supplemented with advanced monitoring, control, computing, and communication capability. More intelligent decision support and improved efficacy, dependability, and security are expected. Quantitative models and evaluation methods are required for determining the extent to which a cyber-physical infrastructure improves on its physical predecessors. It is essential that these models reflect both cyber and physical aspects of operation and failure. In this dissertation, we propose quantitative models for dependability attributes, in particular, survivability, of cyber-physical systems. Any malfunction or security breach, whether cyber or physical, that causes the system operation to depart from specifications will affect these dependability attributes. Our focus is on data corruption, which compromises decision support -- the fundamental role played by cyber infrastructure. The first research contribution of this work is a Petri net model for information exchange in cyber-physical systems, which facilitates i) evaluation of the extent of data corruption at a given time, and ii) illuminates the service degradation caused by propagation of corrupt data through the cyber infrastructure. In the second research contribution, we propose metrics and an evaluation method for survivability, which captures the extent of functionality retained by a system after a disruptive event. We illustrate the application of our methods through case studies on smart grids, intelligent water distribution networks, and intelligent transportation systems. Data, cyber infrastructure, and intelligent control are part and parcel of nearly every critical infrastructure that underpins daily life in developed countries. Our work provides means for quantifying and predicting the service degradation caused when cyber infrastructure fails to serve its intended purpose. It can also serve as the foundation for efforts to fortify critical systems and mitigate inevitable failures --Abstract, page iii

Improving Packet Analysis in Wireless Sensor Network using Bit Rate Classifier

Remote sensor system (WSN) has risen as a promising innovation. Despite the fact that WSN is a promising innovation, there is still a lot of extra research required before it ?nally turns into a developed innovation. An extensive variety of WSN applications have been proposed, for example, living space checking, natural perceptions and estimating frameworks, wellbeing observing, and so on. In these applications, numerous low power and cheap sensor hubs are sent in an unlimited space to coordinate as a system. This paper assesses the impact of utilization of bit rate investigation on bundle approaching to the switch in the remote sensor system. The fundamental point is to accomplish an effective remote sensor system which ought to be not any more defenseless to parcel misfortune. Alternate parameters are deferral, throughput, bundle conveyance proportion, jitter and vitality. The calculation minimizes the postponement that may happen because of high activity rate by utilizing bit rate classifier in this way enhancing the throughput and different parameters

Packet arrival analysis in wireless sensor networks

Distributed sensor networks have been discussed for more than 30 years, but the vision of Wireless Sensor Networks (WSNs) has been brought into reality only by the rapid advancements in the areas of sensor design, information technologies, and wireless networks that have paved the way for the proliferation of WSNs. The unique characteristics of sensor networks introduce new challenges, amongst which prolonging the sensor lifetime is the most important. WSNs have seen a tremendous growth in various application areas including health care, environmental monitoring, security, and military purposes despite prominent performance and availability challenges. Clustering plays an important role in enhancement of the life span and scalability of the network, in such applications. Although researchers continue to address these grand challenges, the type of distributions for arrivals at the cluster head and intermediary routing nodes is still an interesting area of investigation. Modelling the behaviour of the networks becomes essential for estimating the performance metrics and further lead to decisions for improving the network performance, hence highlighting the importance of identifying the type of inter-arrival distributions at the cluster head. In this paper, we present extensive discussions on the assumptions of exponential distributions in WSNs, and present numerical results based on Q-Q plots for estimating the arrival distributions. The work is further extended to understand the impact of end-to-end delay and its effect on inter-arrival time distributions, based on the type of medium access control used in WSNs. Future work is also presented on the grounds that such comparisons based on simple eye checks are insufficient. Since in many cases such plots may lead to incorrect conclusions, demanding the necessity for validating the types of distributions. Statistical analysis is necessary to estimate and validate the empirical distributions of the arrivals in WSNs

Packet arrival analysis in wireless sensor networks

Distributed sensor networks have been discussed for more than 30 years, but the vision of Wireless Sensor Networks (WSNs) has been brought into reality only by the rapid advancements in the areas of sensor design, information technologies, and wireless networks that have paved the way for the proliferation of WSNs. The unique characteristics of sensor networks introduce new challenges, amongst which prolonging the sensor lifetime is the most important. WSNs have seen a tremendous growth in various application areas including health care, environmental monitoring, security, and military purposes despite prominent performance and availability challenges. Clustering plays an important role in enhancement of the life span and scalability of the network, in such applications. Although researchers continue to address these grand challenges, the type of distributions for arrivals at the cluster head and intermediary routing nodes is still an interesting area of investigation. Modelling the behaviour of the networks becomes essential for estimating the performance metrics and further lead to decisions for improving the network performance, hence highlighting the importance of identifying the type of inter-arrival distributions at the cluster head. In this paper, we present extensive discussions on the assumptions of exponential distributions in WSNs, and present numerical results based on Q-Q plots for estimating the arrival distributions. The work is further extended to understand the impact of end-to-end delay and its effect on inter-arrival time distributions, based on the type of medium access control used in WSNs. Future work is also presented on the grounds that such comparisons based on simple eye checks are insufficient. Since in many cases such plots may lead to incorrect conclusions, demanding the necessity for validating the types of distributions. Statistical analysis is necessary to estimate and validate the empirical distributions of the arrivals in WSNs