Mathematical Modelling of Wireless Sensor Network

 

Wireless Sensor Network Security Analytics – presentation

find link of my presentation by searching on google itself
google : ” Wireless Sensor Network Security Analytics ”

TopSearchWirelessSensorSecurityAnalytics2

 

Link below
https://sandyclassic.wordpress.com/2014/03/07/wireless-security-analytics-approach/

2 New Routing algorithm for ad-hoc routing wireless sensor network, mathematical modelling for wireless sensor network 4 models for over all system and 2 models for energy measurement of wireless sensor network
Project Goal:

  • 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 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.
  • 9. 1.3 WSN SECURITY
  • 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.
    2. WSN and BPEL and Internet Of Things (IoT)
    https://sandyclassic.wordpress.com/2013/10/06/bpm-bpel-and-internet-of-things/3. Internet Of Things (IoT) and effects on other device ecosystem.
    The Changing Landscape:
    https://sandyclassic.wordpress.com/2013/10/01/internet-of-things/

    4. How application development changes with IoT, Bigdata, parallel computing, HPC High performance computing.
    https://sandyclassic.wordpress.com/2013/09/18/new-breed-of-app-development-is-here/

    5. Landslide detection and mpact reduction using wireless sensor network.
    https://sandyclassic.wordpress.com/2013/06/23/landslide-detection-impact-reduction-using-wireless-sensor-network

    6. Mathematical modelling Energy Wireless sensor Network.
    https://sandyclassic.wordpress.com/2014/02/04/mathematical-modelling-energy-security-of-wireless-sensor-network/

    Topic Topics Wireless sensor network Security Analytic, Wireless Security Analytics,Security QA metrics

Interview presentation is topmost search on slideshare and google

Top Search On Google:

TopSearchAdvanced metering infrastructure Architecture Analytics

Top Search on SlideShare.com just search (Advanced meter architecture analytics).

Top Search on SlideShare.com Advanced meter architecture analytics

And you reach
https://sandyclassic.wordpress.com/2014/04/03/advanced-metering-infrastructure-architecture/

Advanced metering infrastructure Architecture

My presentation at an interview

 

Mathematical Modelling Energy Security Wireless sensor network- part 2

1. Go through the Slides about Modelling the Wireless sensor Network and Internet of Things

  • 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 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.
  • 9. 1.3 WSN SECURITY
  • 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.

2. WSN and BPEL and Internet Of Things (IoT)
https://sandyclassic.wordpress.com/2013/10/06/bpm-bpel-and-internet-of-things/

3. Internet Of Things (IoT) and effects on other device ecosystem.
The Changing Landscape:
https://sandyclassic.wordpress.com/2013/10/01/internet-of-things/

4. How application development changes with IoT, Bigdata, parallel computing, HPC High performance computing.
https://sandyclassic.wordpress.com/2013/09/18/new-breed-of-app-development-is-here/

5. Landslide detection and mpact reduction using wireless sensor network.
https://sandyclassic.wordpress.com/2013/06/23/landslide-detection-impact-reduction-using-wireless-sensor-network

6. Mathematical modelling Energy Wireless sensor Network.
https://sandyclassic.wordpress.com/2014/02/04/mathematical-modelling-energy-security-of-wireless-sensor-network/


Telecom Technology Stack – Part 2 Strategy ( Oracle Stack + CRM for ARPU)

Part 1 read: https://sandyclassic.wordpress.com/2013/10/26/telecom-technology-stack/
The Enhanced Telecom Operation Map in short e-TOM does gives complete landsacpe of software products used by a Telecom Vendor.
EtomLevel0                                              Level Zero e-TOM software landscape.
More detail : read previous blog
Complementary read: http://en.wikipedia.org/wiki/Enhanced_Telecom_Operations_Map
Two major category its is divided into are Operational support software OSS and BSS Business support software. (Read Last article for more detail)
https://sandyclassic.wordpress.com/2013/10/26/telecom-technology-stack/
Oracle has been trying to build a complete stack of OSS and BSS bundled into one product offering by acquiring company like acquisition of Portal in 2006 for billing acquisition of
http://en.wikipedia.org/wiki/Portal_Software
Covergin : Telecom Service Borker
Oracle Communication Stack                                   Oracle Communication Stack
Watch complete list of acquisitions:
http://en.wikipedia.org/wiki/List_of_acquisitions_by_Oracle
Software Based Communication Stack is also being defined by Open Management Group OMG which maintains specifications for UML, CORBA (http://www.omg.org/spec/CORBA/) and other IDL . Can read Complete list of Specification maintained by OMG at http://www.omg.org/spec/
In OSS Activation and in BSS mediation,Billing are most important components.
Want to be Profitable focus on CRM Analytics:
Telecom services Company profitability is dependent on:
These days to mantain Good ARPU (Average Revenue per User) , CRM is most critical.
As tailoring of plans and greater understanding of consumer behaviour can be achieved By studying Data of customer inside CRM.
CRM Customer Relationship management Software were first set of ERP module Which Went trough reversal in Approach. While in ERP an ERP analyst feeds data of customer (high probability of data errors) in CRM its self service Automation. CRM provided user itself access to forms were data can be entered.
Do you remember When you take vodaphone card seller tells you do not forgot to enter your details in portal you will get extra top-up free. its same self service automation which generates forms and take data to CRM system.So not only less work on data entry and thus errors , wrong bills sometimes due to that Also Wrong targeted offering by vendors which defeats the purpose itself. So CRM is very crucial.

Changes in CRM ecosystem?
CRM were first set of software to embrace open source with products like SugarCRM based on PHP and LAMP technology. Why?
Reasoning: CRM is one set of ERP module which is required by not only small scale vendor , but also SMB (small and medium sector enterprises) as well Large vendors. Usually unlike other modules like we say SAP financials (it was hard earlier for small vendor not only to purchase but many of its sub module will remain redundant or Such details are not required by SME vendors). So Many applications vendor started adding feature for SME CRM requirements. From this born out SugarCRM completely PHP based.

Siebel dominated CRM market as focused vendor for Only CRM not other  module.
Highly customizable like ERP and integrated with products for data management like informatica, data stage , BI Business Objects or Sieble for reporting.

CRM were first set of software to enter into cloud why?
precisely same reason spelt out above. Also benefits of pay per use is more for small vendor turning its capital Expenditure CAPEX into operating Expenditure OPEX.
For SME also CAPEX to OPEX make more sense rather than blocking money in Expensive software buying , maintenance and implementation.
Cloud based SalesForce CRM was Hot technology in cloud made perfect sense last 3-4 yrs.
To That Extent that one of oracle develop conference did had inaugural address from Salesforce CEO Marc Benioff.
See this News: http://www.salesforce.com/ca/company/news-press/press-releases/2010/09/100913.jsp

The Presence in Every Basket Strategy
But in next 2011 conference since cloud tech was hot this was matter of speculations Whether  Marc Benioff will speak or not? in Oracle Develop. Any how Ellison had investment in both the companies.It was like P&G marketing strategy.
If you are high income group I have soap X for you.
if you are medium income group I have soap Y for you.
if you are low income group I have soap Z for you.
So Every segment was coverded.
Oracle Already present in non-cloud CRM by Oracle CRM and acquisition Oracle peoplesoft CRM, Oracle Siebel CRM had invesment in Cloud CRM Salesforce CRM.
CRM Analytics
CRM data which is most crucial is Churn Analysis will show where customer is moving.
Showing Number of customer moving out of particular plan can help in improving retention in plan or improve plan.You can find which assets are moving by turnover ratios and offer discounts on not moving to monetise assets holding up money circulation.
Market basket analysis will show the Number of baskets in which customer can be grouped use this for targeted plan for each group/basket.Segmenting depends on number of variable related to consumer and market conditions like inflection point. Using analytic we can simulate to test hypothesis, variance, trends, Extrapolate data based on induced conditions, predictive analytics can further refine trends and predict success factors.