Genetic algorithm based dynamic combination of polyhedron structures against multiple link failures

Polyhedron protection realizes link protection by constructing a pre-assigned structure and allocates backup resources on a fixed polyhedron structure based on the maximum number of working resources. Taking into account both protection success rate and resource redundancy, this paper dynamically combines different polyhedron structures to allocate backup resources according to the link load, and proposes a genetic algorithm based dynamic combination of polyhedron structures(GA-DCPS) to reduce the resource consumption in the network while ensuring the protection success rate. GA-DCPS aims to minimize the consumption of wavelength resources, and uses the genetic strategy to find the polyhedron combination with the least redundancy to allocate backup resources while ensuring the success rate of service protection. Compared to using the fixed polyhedron structure with 1:m backup resource allocation, GA-DCPS can reduce resource redundancy by about 15% while ensuring complete protection against double-link failures.

Global Annual Mean Surface Air Temperature Anomalies and Their Link with Indian Summer Monsoon Failures

Analysis of the global mean annual temperature anomalies based on land and marine data for the last 88 years (1901-1988) of this century has been carried out with a view to find any relationship with failures in Indian summer monsoon rainfall. On the climatological scale (i.e. 30 years) it has been noticed that there is an abnormal increase in the frequency of drought years during epochs of global warming and cooling, while it is considerably less when global temperatures are near normal. Results are unchanged even when the data are filtered out for ENSO (El-Nino Southern Oscillation) effect.It has also been noticed that during warm and cold epochs in global temperatures the amount of summer monsoon rainfall decreases as compared to the rainfall during a normal temperature epoch.

Prediction of Link Failure in MANET-IoT Using Fuzzy Linear Regression

A Mobile Ad-hoc NETwork(MANET)contains numerous mobile nodes,and it forms a structure-less network associated with wireless links.But,the node movement is the key feature of MANETs;hence,the quick action of the nodes guides a link failure.This link failure creates more data packet drops that can cause a long time delay.As a result,measuring accurate link failure time is the key factor in the MANET.This paper presents a Fuzzy Linear Regression Method to measure Link Failure(FLRLF)and provide an optimal route in the MANET-Internet of Things(IoT).This work aims to predict link failure and improve routing efficiency in MANET.The Fuzzy Linear Regression Method(FLRM)measures the long lifespan link based on the link failure.The mobile node group is built by the Received Signal Strength(RSS).The Hill Climbing(HC)method selects the Group Leader(GL)based on node mobility,node degree and node energy.Additionally,it uses a Data Gathering node forward the infor-mation from GL to the sink node through multiple GL.The GL is identified by linking lifespan and energy using the Particle Swarm Optimization(PSO)algo-rithm.The simulation results demonstrate that the FLRLF approach increases the GL lifespan and minimizes the link failure time in the MANET.

Improving QoS Using Mobility-Based Optimized Multipath Routing Protocol in MANET

Mobile Ad-hoc Networks(MANETs)connect numerous nodes to communicate data from the sender node to the target node.Due to the lack of an infrastructure network,mobile nodes communicate through wireless without an access point.MANET does not have a centralized controller and has a dynamic network topology,which increases link failure and energy consumption resulting in excessive path delay,loss of Quality of service(QoS),and reduced throughput during data communication.Congestion is a significant problem when the QoS of the link carrying the data is degraded.Routing is one of the vital challenges of MANET due to the very dynamic and distributed nature of MANET.This article introduces a Mobility-Based Optimized Multipath Routing Protocol(MBOMRP)and an Efficient Reliable Link-State Transmission(ERLST)algorithm to overcome these problems.The proposed Mobility-Based Optimized Multipath Routing Protocol(MBOMRP)is utilized for route discovery and maintenance to efficiently avoid traffic and sleeping nodes.ERLST algorithm is used for efficient data transmission to increase QoS measurement parameters like throughput,Packet Delivery Ratio(PDR),and minimize the latency performance.The proposed MBOMRP-ERLST algorithm improves data communication network lifetime,avoids link failures,and provides efficient results compared with previous algorithms.

Survivability evaluation for networks carrying complex traffic flows

The capability of a system to fulfill its mission promptly in the presence of attacks,failures,or accidents is one of the qualitative definitions of survivability.In this paper,we propose a model for survivability quantification,which is acceptable for networks carrying complex traffic flows.Complex network traffic is considered as general multi-rate,heterogeneous traffic,where the individual bandwidth demands may aggregate in complex,nonlinear ways.Blocking probability is the chosen measure for survivability analysis.We study an arbitrary topology and some other known topologies for the network.Independent and dependent failure scenarios as well as deterministic and random traffic models are investigated.Finally,we provide survivability evaluation results for different network configurations.The results show that by using about 50%of the link capacity in networks with a relatively high number of links,the blocking probability remains near zero in the case of a limited number of failures.

Attitude control of multi-spacecraft systems on SO(3)with stochastic links failure

In this paper,for Multi-Spacecraft System(MSS)with a directed communication topology link and a static virtual leader,a controller is proposed to realize attitude consensus and attitude stabilization with stochastic links failure and actuator saturation.First,an MSS attitude error model suitable for a directed topology link and with a static virtual leader based on SO(3)is derived,which considers that the attitude error on SO(3)cannot be defined based on algebraic subtraction.Then,we design a controller to realize the MSS on SO(3)with attitude consensus and attitude stabilization under stochastic links failure and actuator saturation.Finally,the simulation results of a multi-spacecraft system with stochastic links failure and a static virtual leader spacecraft are demonstrated to illustrate the efficiency of the attitude controller.

A fully distributed robust optimal control approach for air-conditioning systems considering uncertainties of communication link in IoT-enabled building automation systems

Internet of Things(IoT)technologies are increasingly implemented in buildings as the cost-effective smart sens-ing infrastructure of building automation systems(BASs).They are also dispersed computing resources for novel distributed optimal control approaches.However,wireless communication networks are critical to fulfill these tasks with the performance influenced by inherent uncertainties in networks,e.g.,unpredictable occurrence of link failures.Centralized and hierarchical distributed approaches are vulnerable against link failure,while the robustness of fully distributed approaches depends on the algorithms adopted.This study therefore proposes a fully distributed robust optimal control approach for air-conditioning systems considering uncertainties of com-munication link in IoT-enabled BASs.The distributed algorithm is adopted that agents know their out-neighbors only.Agents directly coordinate with the connected neighbors for global optimization.Tests are conducted to test and validate the proposed approach by comparing with existing approaches,i.e.,the centralized,the hierarchical distributed and the fully distributed approaches.Results show that different approaches are vulnerable against to uncertainties of communication link to different extents.The proposed approach always guarantees the optimal control performance under normal conditions and conditions with link failures,verifying its high robustness.It also has low computation complexity and high optimization efficiency,thus applicable on IoT-enabled BASs.

Multifault diagnosis in WSN using a hybrid metaheuristic trained neural network

Wireless sensor networks are susceptible to failures of nodes and links due to various physical or computational reasons.Some physical reasons include a very high temperature,a heavy load over a node,and heavy rain.Computational reasons could be a third-party intrusive attack,communication conflicts,or congestion.Automated fault diagnosis has been a well-studied problem in the research community.In this paper,we present an automated fault diagnosis model that can diagnose multiple types of faults in the category of hard faults and soft faults.Our proposed model implements a feed-forward neural network trained with a hybrid metaheuristic algorithm that combines the principles of exploration and exploitation of the search space.The proposed methodology consists of different phases,such as a clustering phase,a fault detection and classification phase,and a decision and diagnosis phase.The implemented methodology can diagnose composite faults,such as hard permanent,soft permanent,intermittent,and transient faults for sensor nodes as well as for links.The proposed implementation can also classify different types of faulty behavior for both sensor nodes and links in the network.We present the obtained theoretical results and computational complexity of the implemented model for this particular study on automated fault diagnosis.The performance of the model is evaluated using simulations and experiments conducted using indoor and outdoor testbeds.

Shared p-cycles design for dual link failure restorability in optical WDM networks

Pre-configured cycles （p-cycles） can attain high capacity efficiency and fast protection switching times in wavelength division multiplexing （WDM） networks. This article proposes the weighted straddling link algorithm（WSLA） for generating a subset of all cycles that can guarantee 100% restorability in case of dual link failure, and give an integer linear programming（1LP） formulation that solves the shared p-cycles design problem minimizing the total spare capacities. Numerical result shows that our method can achieve 100% dual link failure restorability with acceptable spare capacity. The larger standard deviation of demand set and the larger node degree network, the better the shared p-cycles scheme performs.