Correlated survivability analysis model for manets

Mobile ad hoc networks (MANETs) rely on collective nodes effort which requires node to be in cooperative behavior to continuously offer network services. Furthermore, node in MANETs shows correlated node behavior due to topology changes, node misbehavior or security attacks in which poses a significant impact on network survivability. However, correlated node behavior is not reflected as one of the metric in analyzing network survivability with current survivability models. The models did not represent real life scenario with the assumption made on individual node behavior. This limitation resulted inaccuracy when analyzing network survivability. To overcome the limitation of current research, this thesis presents a new network survivability analysis model which captures correlated node behavior to depict node behavior in MANETs and proposed a way to minimize the impact of correlated node behavior. Firstly, before network survivability analysis is modeled, a better understanding of dynamic characteristics of node behavior and its correlated behavior need to be studied and modeled. In this thesis, a merging of semi Markov process and Susceptible-Infection-Remove (SIR) epidemic theory is proposed to stochastically model correlated node behavior. To capture correlated node behavior, correlated degree is proposed in the model as a new metric to measure the impact of network survivability under correlated node behavior. Correlated node behavior model leads to a better understanding and prediction of the critical condition and the speed of spreading correlated node behavior to entire network. Network survivability under correlated node behavior is analyzed based on statistical method of multivariate survival analysis in medical research. The modification of Cox Proportional Hazard regression model in particular correlated hazard function is proposed to analyze the probability of correlated node behavior and to determine variables that significantly influence network survivability. The result on regression analysis shows energy consumption and correlated degree are the most significant variables that influence network survivability. Furthermore, probability of network survivability also can be determined. A new algorithm of topology formation is proposed with correlated degree metric to mitigate the impact of correlated node behavior on network performances. The simulation result shows that, with the new algorithm, energy consumption in MANETs can be balance which prolong node life time and increase network survivability. In addition, new algorithm also prevents network topology from partitioning. With new survivability analysis model, the status of network can be precisely measured and countermeasure can be done earlier to prevent network disruption

Correlated Node Behavior Model based on Semi Markov Process for MANETS

This paper introduces a new model for node behavior namely Correlated Node Behavior Model which is an extension of Node Behavior Model. The model adopts semi Markov process in continuous time which clusters the node that has correlation. The key parameter of the process is determined by five probabilistic parameters based on the Markovian model. Computed from the transition probabilities of the semi-Markov process, the node correlation impact on network survivability and resilience can be measure quantitatively. From the result, the quantitative analysis of correlated node behavior on the survivability is obtained through mathematical description, and the effectiveness and rationality of the proposed model are verified through numerical analysis. The analytical results show that the effect from correlated failure nodes on network survivability is much severer than other misbehaviors.Comment: IJCSI Volume 9, Issue 1, January 201

Correlated Node Behavior Model based on Semi Markov Process for MANETS

This paper introduces a new model for node behavior namely Correlated Node Behavior Model which is an extension of Node Behavior Model. The model adopts semi Markov process in continuous time which clusters the node that has correlation. The key parameter of the process is determined by five probabilistic parameters based on the Markovian model. Computed from the transition probabilities of the semi-Markov process, the node correlation impact on network survivability and resilience can be measure quantitatively. From the result, the quantitative analysis of correlated node behavior on the survivability is obtained through mathematical description, and the effectiveness and rationality of the proposed model are verified through numerical analysis. The analytical results show that the effect from correlated failure nodes on network survivability is much severer than other misbehaviors

アドホックネットワークにおけるネットワーク生存性評価に関する研究

広島大学(Hiroshima University)博士(工学)Doctor of Engineeringdoctora

Integrated Social and Quality of Service Trust Management of Mobile Groups in Ad Hoc Networks

Abstract—We propose to combine social trust derived from social networks with quality-of-service (QoS) trust derived from communication networks to obtain a composite trust metric as a basis for evaluating trust of mobile nodes in mobile ad hoc network (MANET) environments. We develop a novel modelbased approach to identify the best protocol setting under which trust bias is minimized, that is, the peer-to-peer subjective trust as a result of executing our distributed trust management protocol is close to ground truth status over a wide range of operational and environment conditions with high resiliency to malicious attacks and misbehaving nodes. Keywords—trust management; mobile ad hoc networks; QoS trust; social trust; trust bias minimization. I

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

Methodologies for the analysis of value from delay-tolerant inter-satellite networking

In a world that is becoming increasingly connected, both in the sense of people and devices, it is of no surprise that users of the data enabled by satellites are exploring the potential brought about from a more connected Earth orbit environment. Lower data latency, higher revisit rates and higher volumes of information are the order of the day, and inter-connectivity is one of the ways in which this could be achieved. Within this dissertation, three main topics are investigated and built upon. First, the process of routing data through intermittently connected delay-tolerant networks is examined and a new routing protocol introduced, called Spae. The consideration of downstream resource limitations forms the heart of this novel approach which is shown to provide improvements in data routing that closely match that of a theoretically optimal scheme. Next, the value of inter-satellite networking is derived in such a way that removes the difficult task of costing the enabling inter-satellite link technology. Instead, value is defined as the price one should be willing to pay for the technology while retaining a mission value greater than its non-networking counterpart. This is achieved through the use of multi-attribute utility theory, trade-space analysis and system modelling, and demonstrated in two case studies. Finally, the effects of uncertainty in the form of sub-system failure are considered. Inter-satellite networking is shown to increase a system's resilience to failure through introduction of additional, partially failed states, made possible by data relay. The lifetime value of a system is then captured using a semi-analytical approach exploiting Markov chains, validated with a numerical Monte Carlo simulation approach. It is evident that while inter-satellite networking may offer more value in general, it does not necessarily result in a decrease in the loss of utility over the lifetime.In a world that is becoming increasingly connected, both in the sense of people and devices, it is of no surprise that users of the data enabled by satellites are exploring the potential brought about from a more connected Earth orbit environment. Lower data latency, higher revisit rates and higher volumes of information are the order of the day, and inter-connectivity is one of the ways in which this could be achieved. Within this dissertation, three main topics are investigated and built upon. First, the process of routing data through intermittently connected delay-tolerant networks is examined and a new routing protocol introduced, called Spae. The consideration of downstream resource limitations forms the heart of this novel approach which is shown to provide improvements in data routing that closely match that of a theoretically optimal scheme. Next, the value of inter-satellite networking is derived in such a way that removes the difficult task of costing the enabling inter-satellite link technology. Instead, value is defined as the price one should be willing to pay for the technology while retaining a mission value greater than its non-networking counterpart. This is achieved through the use of multi-attribute utility theory, trade-space analysis and system modelling, and demonstrated in two case studies. Finally, the effects of uncertainty in the form of sub-system failure are considered. Inter-satellite networking is shown to increase a system's resilience to failure through introduction of additional, partially failed states, made possible by data relay. The lifetime value of a system is then captured using a semi-analytical approach exploiting Markov chains, validated with a numerical Monte Carlo simulation approach. It is evident that while inter-satellite networking may offer more value in general, it does not necessarily result in a decrease in the loss of utility over the lifetime