Wireless Sensor Network Security Analytics
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This document outlines 10 goals for a wireless sensor network project, including developing routing algorithms, measuring energy consumption, validating and improving an existing energy consumption estimation model, proposing a new model, developing an energy-aware routing algorithm, implementing a configurable routing algorithm, and developing mathematical and fuzzy models to represent the wireless sensor network topology and routing.
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New method for route efficient energy calculations with mobile-sink for wirel...nooriasukmaningtyas Despite proposing a number of algorithms and protocols, especially those related to routing, for the purpose of reducing energy consumption in wireless sensor networks, which is one of the most important issues facing this type of network. In this research paper, energy consumption and cost are calculated taking into account energy consumption and the amount of data transferred to a thousand nodes through specific paths towards the mobile sink. The proposed model simulated by sending various amounts of data with specific path to know the energy consumption of each track and the network life time with 250, 500, and 1000 bits. Cost calculated using various weight for each track of these paths and the coefficient of movement time and path loss factor and others related to the transmission and receiving circuits. And finally, the results compared with a previous method it showed the efficiency of our method used and calculating 1000 nodes with various amount of bits to show the experimental results. Deep learning used to remember each and every path of each position or nearby to avoid calculation cost later.
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2nd fast.pptxLaxmanSundar1 The document proposes a Fast Fault Node Recovery algorithm to enhance the lifetime of a wireless sensor network when sensor nodes fail. The algorithm is based on rerouting using grade diffusion combined with a genetic algorithm. It aims to reduce the number of replaced sensor nodes and reuse more routing paths. Simulation results show the algorithm increases active nodes by up to 8.7 times, reduces data loss by 98.8%, and reduces energy consumption by 31.1%.
Mobile Networking and Mobile Ad Hoc Routing Protocol Modeling
Mobile Networking and Mobile Ad Hoc Routing Protocol ModelingIOSR Journals This document summarizes a research paper about modeling mobile ad hoc networks and routing protocols. It discusses modeling the network topology and connectivity between nodes. It also describes modeling the routing protocol instances running on each node. The document outlines different approaches to modeling the network, including explicitly modeling topology and transitions, parameterizing based on network properties, and developing a universal quantification model. It discusses techniques for coping with state explosion when modeling mobile ad hoc networks, such as symbolic representation, partial order reduction, and abstraction.
From shortest path to all-path the routing continuum theory and its applications
From shortest path to all-path the routing continuum theory and its applicationsNexgen Technology Ecruitment Solutions (ECS) is one of the leading Delhi based Software Development & HR Consulting Firm, which is assessed at the level of ISO 9001:2008 standard. ECS offers an awesome project and product based solutions to many customers around the globe.
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From shortest path to all-path the routing continuum theory and its applications
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A PROPOSAL TO IMPROVE SEP ROUTING PROTOCOL USING INSENSITIVE FUZZY C-MEANS IN...
A PROPOSAL TO IMPROVE SEP ROUTING PROTOCOL USING INSENSITIVE FUZZY C-MEANS IN...IJCNCJournal This document proposes improving the SEP routing protocol in wireless sensor networks by combining it with the Insensitive Fuzzy C-Means clustering algorithm. The SEP protocol is an existing heterogeneous routing protocol that increases network stability but has limitations. The proposed SEP-εFCM protocol selects cluster heads using εFCM clustering, which can create more balanced clusters and reduce energy consumption. Simulation results showed the SEP-εFCM protocol performed better than the original SEP protocol, with more remaining live nodes and energy over time.
Fo2510211029
Fo2510211029IJERA Editor This document summarizes a research paper that proposes an enhanced cross-layer protocol (ECLP) for wireless sensor networks. ECLP integrates medium access control and routing to improve energy efficiency and reduce latency. It uses an adaptive duty cycling scheme with adaptive timeouts and reservation requests. It also designs a tree-based energy-aware routing algorithm to prolong the network lifetime while minimizing control overhead for data delivery. Simulation results show ECLP outperforms other existing algorithms in terms of energy efficiency and latency.
Investigation of Ant Colony Optimization Algorithm for Efficient Energy Utili...
Investigation of Ant Colony Optimization Algorithm for Efficient Energy Utili...IJCNCJournal Maintaining the energy conservation is considered as an important approach to increase the lifetime of WSN. In fact, an energy reduction mechanism is considered as the main concept to enhance the lifespan of the network. In this paper, the performance analysis/evaluation of optimization technique, specifically, Ant Colony Optimization (ACO) and modified ACO (m-ACO) in the routing method are investigated. This network analysis is done by 100 iterations and differentiated with 50, 75 and 100 numbers of nodes. Finally, experimental results illustrate that the performance of m-ACO algorithm obtained the obvious performance, which is comparatively better than ACO algorithm, because it improves the routing efficiency by pheromone evaporation control and energy threshold value. It demonstrates that m-ACO algorithm gives better results than ACO in terms of throughput (1.41%), transmission delay (1.43%), packet delivery ratio (1.41%), energy consumption (2.05%), and the packet loss (9.70%). The convergence rate is analysed for ACO and m-ACO algorithms with respect to 100 number of iterations for WSNs.
Investigation of Ant Colony Optimization Algorithm for Efficient Energy Utili...
Investigation of Ant Colony Optimization Algorithm for Efficient Energy Utili...IJCNCJournal Maintaining the energy conservation is considered as an important approach to increase the lifetime of WSN. In fact, an energy reduction mechanism is considered asthe main concept to enhance the lifespan of the network. In this paper, the performance analysis/evaluation of optimization technique, specifically, Ant Colony Optimization (ACO) and modified ACO (m-ACO) in the routing method are investigated. This network analysis is done by 100 iterations and differentiated with 50, 75 and 100 numbers of nodes. Finally, experimental results illustrate that the performance of m-ACO algorithm obtained the obvious performance,which is comparatively better than ACO algorithm, because it improves the routing efficiency by pheromone evaporation control and energy threshold value. It demonstrates that m-ACO algorithm gives better results than ACO in terms of throughput (1.41%), transmission delay (1.43%), packet delivery ratio (1.41%), energy consumption (2.05%), and the packet loss (9.70%). The convergence rate is analysed for ACO and m-ACO algorithms with respect to 100 number of iterations for WSNs.
An Adaptive Routing Algorithm for Communication Networks using Back Pressure...
An Adaptive Routing Algorithm for Communication Networks using Back Pressure...IJMER The basic idea of backpressure techniques is to prioritize transmissions over links that have
the highest queue differentials. Backpressure method effectively makes packets flow through the network
as though pulled by gravity towards the destination end, which has the smallest queue size of zero. Under
high traffic conditions, this method works very well, and backpressure is able to fully utilize the available
network resources in a highly dynamic fashion. Under low traffic conditions, however, because many
other hosts may also have a small or zero queue size, there is inefficiency in terms of an increase in
delay, as packets may loop or take a long time to make their way to the destination end. In this paper we
use the concept of shadow queues. Each node has to maintain some counters, called as shadow queues,
per destination. This is very similar to the idea of maintaining a routing table (for routing purpose) per
destination. Using the concept of shadow queues, we partially decouple routing and the scheduling. A
shadow network is maintained to update a probabilistic routing table that packets use upon arrival at a
node. The same shadow network, with back-pressure technique, is used to activate transmissions between
nodes. The routing algorithm is designed to minimize the average number of hops used by the packets in
the network. This idea, along with the scheduling and routing decoupling, leads to delay reduction
compared with the traditional back-pressure algorithm
Hybrid networking and distribution 
Hybrid networking and distribution vivek pratap singh This document outlines a study on implementing a hybrid routing protocol for wireless sensor networks. It discusses the problems with purely proactive or reactive routing protocols and the motivation for a hybrid approach. The document outlines the objectives to implement OLSR and AODV protocols, design a framework to allow them to work together, and test their performance. Preliminary results show the individual protocols working correctly in simulation. The future work involves combining the protocols in the framework and further evaluating the hybrid protocol's performance and efficiency.
Energy Efficient Multipath Routing For Mobile Ad Hoc Networks
Energy Efficient Multipath Routing For Mobile Ad Hoc NetworksZac Darcy Energy consumption is a significant issue in ad hoc networks since mobile nodes are battery powered. In
order to prolong the lifetime of ad hoc networks, it is the most critical issue to minimize the energy
consumption of nodes. In this paper, we propose an energy efficient multipath routing protocol for
choosing energy efficient path. This system also considers transmission power of nodes and residual energy
as energy metrics in order to maximize the network lifetime and to reduce energy consumption of mobile
nodes. The objective of our proposed system is to find an optimal route based on two energy metrics while
choosing a route to transfer data packets. This system is implemented by using NS-2.34. Simulation results
show that the proposed routing protocol with transmission power and residual energy control mode can
extend the life-span of network and can achieve higher performance when compared to traditional ad-hoc
on-demand multipath distance vector (AOMDV) routing protocol.
Energy Efficient Multipath Routing For Mobile Ad Hoc Networks
Energy Efficient Multipath Routing For Mobile Ad Hoc NetworksZac Darcy Energy consumption is a significant issue in ad hoc networks since mobile nodes are battery powered. In
order to prolong the lifetime of ad hoc networks, it is the most critical issue to minimize the energy
consumption of nodes. In this paper, we propose an energy efficient multipath routing protocol for
choosing energy efficient path. This system also considers transmission power of nodes and residual energy
as energy metrics in order to maximize the network lifetime and to reduce energy consumption of mobile
nodes. The objective of our proposed system is to find an optimal route based on two energy metrics while
choosing a route to transfer data packets. This system is implemented by using NS-2.34. Simulation results
show that the proposed routing protocol with transmission power and residual energy control mode can
extend the life-span of network and can achieve higher performance when compared to traditional ad-hoc
on-demand multipath distance vector (AOMDV) routing protocol.
Energy Efficient Multipath Routing For Mobile Ad Hoc Networks
Energy Efficient Multipath Routing For Mobile Ad Hoc NetworksZac Darcy Energy consumption is a significant issue in ad hoc networks since mobile nodes are battery powered. In
order to prolong the lifetime of ad hoc networks, it is the most critical issue to minimize the energy
consumption of nodes. In this paper, we propose an energy efficient multipath routing protocol for
choosing energy efficient path. This system also considers transmission power of nodes and residual energy
as energy metrics in order to maximize the network lifetime and to reduce energy consumption of mobile
nodes. The objective of our proposed system is to find an optimal route based on two energy metrics while
choosing a route to transfer data packets. This system is implemented by using NS-2.34. Simulation results
show that the proposed routing protocol with transmission power and residual energy control mode can
extend the life-span of network and can achieve higher performance when compared to traditional ad-hoc
on-demand multipath distance vector (AOMDV) routing protocol.
A scalable and power efficient solution for routing in mobile ad hoc network ...
A scalable and power efficient solution for routing in mobile ad hoc network ...ijmnct This document summarizes a research paper that proposes a scalable and power-efficient routing solution for mobile ad hoc networks (MANETs). The paper describes a cluster-based MANET architecture and develops a graph theoretic routing algorithm that finds paths from source to destination nodes using routes with minimum cumulative degree. Simulation results show that the algorithm provides efficient routing paths even as the number of nodes increases, and uses multi-hop connectivity to transmit packets using minimum power irrespective of the number of nodes in the network. The algorithm is shown to be scalable and power efficient compared to other routing methods.
Comparative analysis of the performance of various active queue management te...
Comparative analysis of the performance of various active queue management te...IJECEIAES This paper demonstrates the robustness of active queue management techniques to varying load, link capacity and propagation delay in a wireless environment. The performances of four standard controllers used in Transmission Control Protocol/Active Queue Management (TCP/AQM) systems were compared. The active queue management controllers were the Fixed-Parameter Proportional Integral (PI), Random Early Detection (RED), Self-Tuning Regulator (STR) and the Model Predictive Control (MPC). The robustness of the congestion control algorithm of each technique was documented by simulating the varying conditions using MATLAB® and Simulink® software. From the results obtained, the MPC controller gives the best result in terms of response time and controllability in a wireless network with varying link capacity and propagation delay. Thus, the MPC controller is the best bet when adaptive algorithms are to be employed in a wireless network environment. The MPC controller can also be recommended for heterogeneous networks where the network load cannot be estimated.
Adaptive routing for dynamic on body wireless
Adaptive routing for dynamic on body wirelessjpstudcorner HEAD OFFICE (CHENNAI):
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Wireless Sensor Network Security Analytics
- 1. 10 PROJECT GOALS 1. Routing algorithm: SPIN,CTP. 2. Measure energy consumed 3. Validate PPECEM Model 4. Improve in existing model for efficiency, reliability, availability.
- 2. 10 PROJECT GOALS 5. New Model: ERAECEM Efficiency Reliability Availability Energy consumption Estimation Model. 6. ERAQP BASED on ERAECEM Model for WSN a new energy aware routing algorithm (ERAQP)
- 3. 10 PROJECT GOALS 7. Configurable Routing Algorithm Approach Proposed on WSN motes utilizing user defined QoS parameters 8. Model for WSN: Leader-Follower Model, Directed Diffusion Model
- 4. 10 PROJECT GOALS 9. Fuzzy routing Algorithm Motes represent 10. Fuzzy Information Neural Network representation of Wireless Sensor Network.
- 5. MOTIVATION
- 6. 1.1 SPIN
- 7. 1.2 CTP Collection tree protocol
- 8. 2 ENERGY MEASUREMENT Agilent 33522B Waveform Generator was used to measure the Current and voltage graph . The Graph measurement were then converted to numerical power Power= Voltage X current = V X I. The Power consumed during motes routing on SPIN and CTP then taken into is added up to give power consumption and values are applied to PPECEM.
- 10. 3.1COST OF SECURITY Cost of security In WSN can only be estimated by looking at extra burden of secure algorithm and security of Energy Consumption as the Energy is key driver or critical resource in design of WSN. As design is completely dominated by size of battery supplying power to mote.
- 11. 3.2 PPECEM QCPU = PCPU * TCPU = PCPU * (BEnc * TBEnc + BDec * TBDec +BMac * TBMac + TRadioActive) Eq.2)
- 12. 4 ERA Efficiency = Ptr X Prc X Pcry … (Eq.2) Reliability = Rnode1 = FtrX FrcX Fcy Availability= TFNode1 = Ftr+ Frc+Fcry
- 13. 5. IMPROVE EXISTING . ERA = fed Efficiency of Energy Model: QEff=QCPU X Eff (improvement #1 in Zang model)
- 14. ERAECEM Etotal = Average(Eff + R +A)= (E+R+A)/3 Efficiency of Energy Model: QEff=QCPU X Etotal (improvement #1 in Zang model)
- 15. 6 ERAQP Efficiency ,Reliability, Availability QoS prioritized routing Algorithm ERA ranked and routing based Ranking Cost on Dijesktra to find most suitable path
- 16. 7.CONFIG. ROUTING q1, q2, q3 as QoS parameter algorithm rank Motes/nodes based on combined score of these parameters. Based on this we rank we apply Dijesktra algorithm to arrive at least path or elect Cluster head to node. Thus q1, q2, q3 can be added, deleted.
- 17. 8 MATHEMATICAL MODEL Leader Follower EACH node share defined diffusion rate given by slider control on UI which tells quantity it is diffusing with its neighbors.Since it’s a directed graph so Node B gives data towards Node A while traffic from A towards B may be non-existent Directed Diffusion Mathematical model represent diffusion of quantity towards a directed network. Helps to understand topology, density and stability of network and a starting point for designing complex , realistic Network Model.
- 18. 9 FUZZY ROUTING Fuzzy set A {MoteA, p(A)) Where, p(A) is probability Of Data Usage Or Percentage Load in Fraction Compared With Global Load
- 19. 10 FUZZY TOPOLOGY Based on this Utilization p(A) nodes can be ranked in ascending order to find most data dwarfed node at the top. Then We can apply Dijkstra's algorithm on the network to find best route based on weight on each node represented by Rank.