Wireless Security Analytics- Approach

How To model wireless security mathematically. (its topmost search in Google Type(Wireless Sensor network Security Analytics) Result:
TopMostSearchWirelessSensorNetworkSecurityAnalyticsRead:

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/

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/


On TinyOS if Motelist is not working

first diagnose using.

=========================================================
diagnose using command
$ dmesg -s
you can see messages what is causing problem.

—————————————————————————–

For motelist not working download motelist source code.  

googlecode+ tinyos+motelist
http://tinyos-main.googlecode.com/svn/trunk/tools/platforms/msp430/motelist/motelist-linux.in

Check the mount structure for
As from previous version 8 of last image to Ubuntu 12.4 the directory structure is changed little bit  hence last version directory required should be copied to new directories
check $mount all mount structure
then if there is duplicate unmount using $umount
$sudo mount –bind /dev/bus /proc/bus
dev structure should be copied to /proc

then download Google(motelist code perl)
open editor copy paste code in editor
$nano or gedit (program name ).pl

Execute the perl code $ perl
$ perl (program name).pl

BPM and its influence on Cloud: Infrastructure as service

Cisco, Microsoft and Neapp Jointly produced a system called opalis (Workflow) in 2012.

Data centre System process interactions can be configured depending on user need on Opalis and rules can be set up for those interactions. Read previous blog more about BPM and internet of things:

https://sandyclassic.wordpress.com/2013/10/06/bpm-bpel-and-internet-of-things/
Opalis, Which essentially provide a workflow to dynamically create,monitor,deploy a Machine instance , allocate OS instance, (just like in Nebula, or Eucalyptus ) and User also can request (specific machine with RAM, CPU, storage space).
Microsoft provide all OS /software instance, Neapp provide SAN or and storage required on , Cisco provide Server , Nexus switches boxes.
http://technet.microsoft.com/en-us/systemcenter/hh913943.aspx
I
ts integrated with Microsoft SCMM System centre Manager (used to creating private cloud on Microsoft technologies and a single User Interface to administer whole
Orchestration are discussed in previous blog in case of opalis its architecture llooks like this
opalis_orchestrationRead: http://technet.microsoft.com/en-gb/library/hh420377.aspx
Read: opalis blog
http://blogs.technet.com/b/opalis/

Read: http://contoso.se/blog/?p=1665

If all exist then they can be configured using BPM workflow of opalis for a user.

Internet of things New Paradigm Shift in Computing

Paradigm shift in Computing Industry over period of time:

Mainframe–> Personal Computer, (PC based Application software ) –> Web Computing (Web servers, Internet, web application) –> devices (Mobile/ Mobility )/IP TV , notebook /ipad —>
For next shift there lot of possibility Like surface computing might eliminate Screen requirement or Ipad/laptop requirement, IP TV interacting with human interactions with gesture to camera , and devices projecting screen on any surface. Many devices which are coming in the industry would certainly require Ubiquitous Access. And All devices will have agent to take informed decisions (Like once fridge know milk is empty it could connect to internet and ask your access to credit card or confirmation (workflow software configured) it can order retailer.(So like Internet of Things)
So Internet of things is not only these devices that will interact with other home system, devices but also get data with wired or wireless sensors inside Home.
more about it can be read at : https://sandyclassic.wordpress.com/2013/05/03/classifying-ubiquitious-data-images-into-emotion-for-target-advertisement-campaign/

Read: https://sandyclassic.wordpress.com/2012/10/28/ubiquity-the-most-crucial-challenge-in-business-intelligence/

New age application development :
https://sandyclassic.wordpress.com/2013/09/18/new-breed-of-app-development-is-here/

CMS are integrated with SIP servers for PSTN phone to Digital phone and Softphone conversion. More details:
https://sandyclassic.wordpress.com/2013/09/22/approach-to-best-collaboration-management-system/

All these will increase focus on the development Internet of Things with sensor network generating huge video,audio, image and text data collected from sensor has to move ubiquitous from one system to another. For this to happen internet infrastructure will be utilized using cluster computing of Hadoop, Hive, HBase. for data analysis and storage. When sensor nodes , devices , Home appliances access and interact with this data ubiquitously  at same time interact , under transaction using internet infrastructure Possibility of Internet of things is only conclusion it can derive.
Read more on hadoop: https://sandyclassic.wordpress.com/2011/10/19/hadoop-its-relation-to-new-architecture-enterprise-datawarehouse/

Relation to cloud here 3V have actually now became 5V variability and value new 2V +addition to existing 3V Volume, variety and velocity being old 3V.                                  Read more: https://sandyclassic.wordpress.com/2013/07/02/data-warehousing-business-intelligence-and-cloud-computing/

External links for reference: http://www.sap.com/index.epx
http://www.oracle.comhttp://www.tibco.com/,http://spotfire.tibco.com/,
http://scn.sap.com/thread/1228659
S
AP XI: http://help.sap.com/saphelp_nw04/helpdata/en/9b/821140d72dc442e10000000a1550b0/content.htm

Oracle Web centre: http://www.oracle.com/technetwork/middleware/webcenter/suite/overview/index.html

CMS: http://www.joomla.org/,http://www.liferay.com/http://www-03.ibm.com/software/products/us/en/filecontmana/
Hadoop: http://hadoop.apache.org/

Map reduce: http://hadoop.apache.org/docs/stable/mapred_tutorial.html
f
acebook API: https://developers.facebook.com/docs/reference/apis/
L
inkedin API: http://developer.linkedin.com/apis
T
witter API: https://dev.twitter.com/

PC\Laptop will never be dead although new platform emerge: Analysis of Microsoft Strategy

PC / laptop may be dead or it will become centre piece of interaction of all devices at home.
Now as internet of things evolve or semantic agents start searching  web for you and customize search for you.
There will more than 100 devices like fan , cooler, heater, washing machine , each room sensor etc in your home as Home computing/smart city emerges platform like Zigbee, personal area network become more visible. PC will become like server controlling/configuring/updating/debugging all these devices at home.
This is in response to this news I am writing:
that Microsoft is trying to keep PC as device of choice.
http://www.bloomberg.com/news/2013-09-19/microsoft-ceo-says-working-to-keep-pc-device-of-choice-.html
Some places where low computation and mobilty is required smartphone and tablet may take up market which they already have but still PC/laptop will have its own market as it will become Home server of choice.
At end of day you want to come back home and sink all your devices to server which is Laptop with max processing power to do it fast.

Strategies For Software Services/product Companies next decade

 

 

 

These requirement are going to stay for next decade:Strategy-Small1Where can Software services/product firms lay emphasis for next stage of development. Or the areas which will see maximum amount of work coming in future..

Or What areas of knowledge should software companies develop manpower on:
1. Game development and Gamification:
https://sandyclassic.wordpress.com/2012/06/27/future-of-flex-flash-gamification-of-erp-enterprise-software-augmented-reality-on-mobile-apps-iptv/

read: https://sandyclassic.wordpress.com/2013/09/16/new-age-enterprise-resource-planning-systems/

2-7. Each of the Seven areas in development:
https://sandyclassic.wordpress.com/2013/09/18/new-breed-of-app-development-is-here/

read: https://sandyclassic.wordpress.com/2013/09/20/next-generation-application-developement/

As you read you realize software which can take advantage of multiple processor available on the devices None of sotware present in market today is written to take advantage of this fact. It may be possible an new language may come up to take benefit of this fact of we can still use old java/C++ threads more offen or we can distribute load on server by more specific COM/ DCOM or Distributed Common Request broker Architecture CORBA to processor level at server.. We have virtual switches and VM ware or Zen virtualisation which can exploit maximum benefit from it.
8. More virtualised network stack: this I wrote 2 yrs back still valid to quote here:
https://sandyclassic.wordpress.com/2012/07/16/cloud-innovation-heating-up-network-protocol-stack-and-telecom-stack/

private and public cloud new API will emerge: https://sandyclassic.wordpress.com/2011/10/20/infrastructure-as-service-iaas-offerings-and-tools-in-market-trends/

9. from SDLC V model to Agile and now to lean Agile ..use of six sigma to control process is just one part of mathematics being used for quality control but there would be new data model which will be tested based to mathematical modelling like probability distributions new model industry specific models would keep emerging.
like how for security project how security user stories are plugged into model
https://sandyclassic.wordpress.com/2013/01/05/agile-project-management-for-security-project/
or read https://sandyclassic.wordpress.com/2012/11/12/do-we-really-need-uml-today/

10.  BI would be Everyware:
https://sandyclassic.wordpress.com/2013/09/20/next-generation-application-developement/
parallelism , map reduce algorithm and cloud
https://sandyclassic.wordpress.com/2011/10/19/hadoop-its-relation-to-new-architecture-enterprise-datawarehouse/