Ruiying Li

Deployment-Based Lifetime Optimization Model for Homogeneous Wireless Sensor Network under Retransmission

Sensor-deployment-based lifetime optimization is one of the most effective methods used to prolong the lifetime of Wireless Sensor Network (WSN) by reducing the distance-sensitive energy consumption. In this paper, data retransmission, a major consumption factor that is usually neglected in the previous work, is considered. For a homogeneous WSN, monitoring a circular target area with a centered base station, a sensor deployment model based on regular hexagonal grids is analyzed. To maximize the WSN lifetime, optimization models for both uniform and non-uniform deployment schemes are proposed by constraining on coverage, connectivity and success transmission rate. Based on the data transmission analysis in a data gathering cycle, the WSN lifetime in the model can be obtained through quantifying the energy consumption at each sensor location. The results of case studies show that it is meaningful to consider data retransmission in the lifetime optimization. In particular, our investigations indicate that, with the same lifetime requirement, the number of sensors needed in a non-uniform topology is much less than that in a uniform one. Finally, compared with a random scheme, simulation results further verify the advantage of our deployment model.

Modeling and simulation for network transmission time reliability

As the high redundancy of network equipments and paths, connection reliability is no longer the most important parameter for networks. According to network function, this paper advances transmission time reliability as a common parameter to describe network congestion. It is defined to be the probability that networks will transmit material, energy or information timely when used under specified operating conditions. To evaluate this parameter, this paper presents four models, including structure model, routing model, service mechanism model and application model. Structure model is built to describe network topology; routing model and service mechanism model are used to express network operation mechanism; and application model is set up to generate network traffic. This paper also provides simulation flow and reliability evaluation method. Finally, the backbone of CERNET (china education and research network) is studied as a case, and the result shows that this modeling & simulation method is quite effectively. The contributions of this paper are: (1)A common network parameter, transmission time reliability, is advanced to describe network congestion, and it was only used for transportation systems before. (2)A modeling and simulation technology is expressed to evaluate the network transmission time reliability. Network operation mechanism which is covered in this method is not considered before.

A sensor deployment optimization model of the wireless sensor networks under retransmission

Wireless sensor networks (WSN) are widely applied in the supervisory control of the agriculture, biology, transportation, military and many other fields. An excellent node deployment strategy can largely reduce the energy consumption and optimize the lifetime of WSN. In this paper, a new node deployment model based on regular hexagon grids is proposed for a homogeneous flat WSN. Both the data transmission and energy consumption of each sensor in a data gathering cycle are analyzed based on energy consumption models, a routing algorithm, a retransmission model and a sleep/wakeup mechanism. Two optimization models for uniform and non-uniform sensor deployment schemes are proposed to minimize the energy consumption under the constraints of connectivity and coverage requirements. The results of our case studies show that when retransmission is considered, there are much less nodes and initial energy needed in the deployment of the WSN.

The applicability of traditional sampling techniques in the measurement of LAN availability

The net flow is increased gradually with the rapid development of Internet, therefore it is impossible and unaffordable to capture and analysis every packet in network measure. Many scholars have developed variety of packet sampling techniques. However, the parameters researched were not about network availability, and the difference among applications was not considered. In this paper, the conception of network availability based on different applications was explained. The influence of using different traditional sampling techniques, including simple random sampling, periodic sampling and systematic sampling, were discussed by experiments based on three typical protocols in LAN. Finally, the applicable network sampling techniques for availability based on different protocols were recommended.

The method of network reliability and availability simulation based on Monte Carlo

Reliability and availability have always been important characteristics of systems but become even more critical and complex issues on networks. Due to the high complexity of accurate calculation methods, simulation methods for network reliability and availability evaluation have been a popular area of research, and received significant attention. In this paper the network topology model, the failure driven simulation method and the reliability and availability statistical algorithms are put forward, and then the network reliability and availability simulation flow based on the Monte Carlo method was designed. This simulation method can be used to calculate the reliability and availability of a network whose nodes and links may be failure. Two repair policies, immediate repair and delay repair, are provided to choose. Finally, the backbone of CERNET (China Education and Research Network) is taken as an example and the simulation results are analyzed.

A Comprehensive Analysis Method for System Resilience Considering Plasticity

Resilience is generally described as the ability of a system to absorb disturbance and to recover rapidly back to its original state. However, the system may not recover thoroughly after every interruption. This paper defines resilient limit and system plasticity, and proposes an analysis method for system resilience considering plasticity, which provides a comprehensive evaluation for both resilience and plasticity of systems suffering from performance degradation. The resilience and plasticity of an airborne GPS/INS navigation system is then analyzed to illustrate the effectiveness of our method.

The layered index method for network reliability analysis

This paper proposed the layered index method for network reliability analysis through the study of the current network reliability research, as well as the existing problems. This paper first analyzed the required function, the stated condition, the specified period of the network reliability definition, then discussed the calculation of the application reliability based on individual application, finally proposed the methodology of reliability analysis considering the relationship among different applications. The contribution of this paper is: (i) the function, the condition, and the period in network reliability analysis were exemplified; (ii) the network reliability was analyzed based on the different applications; (iii) a parameter system for network reliability evaluation was constructed; (iv) an example of computer network was given which show the steps of using this method.

Reliability testing technology for computer network applications

Computer network reliability testing is an important technology for network reliability evaluation. Focused on reliability testing for computer network applications, the testing profile building method, the sample selection method, the failure criterions setting method and the index evaluation method are researched. Finally, the testing process is explained with a testing case.

Maximum flow-based resilience analysis: From component to system

Resilience, the ability to withstand disruptions and recover quickly, must be considered during system design because any disruption of the system may cause considerable loss, including economic and societal. This work develops analytic maximum flow-based resilience models for series and parallel systems using Zobel’s resilience measure. The two analytic models can be used to evaluate quantitatively and compare the resilience of the systems with the corresponding performance structures. For systems with identical components, the resilience of the parallel system increases with increasing number of components, while the resilience remains constant in the series system. A Monte Carlo-based simulation method is also provided to verify the correctness of our analytic resilience models and to analyze the resilience of networked systems based on that of components. A road network example is used to illustrate the analysis process, and the resilience comparison among networks with different topologies but the same components indicates that a system with redundant performance is usually more resilient than one without redundant performance. However, not all redundant capacities of components can improve the system resilience, the effectiveness of the capacity redundancy depends on where the redundant capacity is located.

Lifetime optimisation for linear wireless sensor networks under retransmission

The lifetime of wireless sensor networks WSN is strongly affected by the energy consumption, which is partly attributed to retransmission. In this paper, the energy consumption of a linear WSN is analysed based on basic energy consumption models and a retransmission model. Optimisation models are proposed with the objective of maximising WSN lifetime under the coverage and success transmission rate constraints. In particular, for traditional uniform and non-uniform sensor deployment problems without considering the sleep/wakeup mechanism, the number of sensors and their distances are optimised. Moreover, for a linear WSN with a sleep/wakeup mechanism, a sensor deployment scheme is developed by optimally assigning sensors to fixed locations. The genetic algorithm and the generalised reduced gradient method are applied to solve these problems. Our case studies illustrate that the lifetime of WSN with and without retransmission are different, and it is important to consider retransmission in WSN lifetime optimisation.