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My presentation at an interview


Google Finally Has a NEST to Hatch Internet of Things

Google Recent Acquisition of NEST which make Thermostat and Smoke detectors.
Very intelligent Decision:
As These are devices/Things which is present in almost every home. Once These are Enabled for Internet of Things (IoT). The Market can be quickly reached compared to new devices to penetrate consumer Homes.
As Other products it can correlate data with Gmail, social network , search and other data stored in data centre. AI/Machine Learning algorithm can be run over it to understand Consumer Behaviour , consumer Psychology.
New inputs room temperature, city temperature, room lights, intensity of lights to Algorithm can Achieve better targeting of advertisements and other meta data understanding.
Then There are IoT using IPV6.

Mathematical Modelling the Sensor Network


Modelling Wireless sensor network

Modelling Wireless sensor network

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.
  • 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)

3. Internet Of Things (IoT) and effects on other device ecosystem.
The Changing Landscape:

4. How application development changes with IoT, Bigdata, parallel computing, HPC High performance computing.


BPM, BPEL and Internet of things

Most initial components of Internet of Things comes from wireless sensor networks.
Internet of Things using TinyOS platform :
Then it has to Ubiquitous
Read for more detail:
Internet of things:
more details search on blog
Ubiquitous computing and BI
Ubiquitous computing  and ERP:
BPM and BPEL helps in aligning changing business process requirements. Any creating orchestrating business processes. creating workflow , business Rules and process Engine.
typical BPM components architecture looks like this:
BPM_Workflow_Service_Patternmore details:
When multiple devices interact the processes between them have to be orchestrated , easiest and best way to created interaction between devices and create rules is by creating workflow. Also workflow is What you see is What you Get (WYSIWYG). A Naive user can also diagrammatically drag and drop workflow components available in the panel and set rules. Which are quite similar to Business Rules. So Even BPM will become pervasive with internet of things.
Also programming multiple device interaction for complex task. the complexity can be reduced for programmer by using BPM using notation available in BPMN.
BPMN-CollectVotesA typical workflow of voting process depicted above:
Now similarly device workflow are captured and programmed using BPMN notation.
Recently IBM released Node.js pattern JavaScript for Internet of things over wireless sensor networks.
node-red-screenshotRead more detail:
you can clearly see device workflow above . Also this is how we set the filter rules to analyse filter data from the web using yahoo pipes
More details later sometime again: Happy reading 🙂