Advanced metering infrastructure Architecture

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.
Read:
1. https://sandyclassic.wordpress.com/2013/10/30/internet-of-things-iot-step-by-step-approach/
2. https://sandyclassic.wordpress.com/2014/01/08/the-owl-in-semantic-web-and-internet-of-things-iot/

This Article is in top most on google Search page on semantic web OWL and Internet of things.
SemanticWebOWLAndInternetOf Things
– Ontology  can be represented by OWL (Ontology Web Language) which is also refining and defining the agents used to search the personalized behavioural web for you(also called semantic web) Thus these agents understand you behaviour and help to find better recommendations and  search List in Semantic space.
OWL:
OWL2-structure2-800
– Semantic Web:
– Augmented Reality : is used in Gaming and multimedia application
(read Article link below)
Perceived Reality vs The augmented reality
Augmented reality is fuelled by ontology + perceived reality.
READ: How Augmented Reality transforming gamification of Software (like ERP)
https://sandyclassic.wordpress.com/2012/06/27/future-of-flex-flash-gamification-of-erp-enterprise-software-augmented-reality-on-mobile-apps-iptv/
– New age software development
https://sandyclassic.wordpress.com/2013/09/18/new-breed-of-app-development-is-here/
O
ntology can integrate many task into a Uniform task which were not possible Early.

Read Discussion On Reality Vs Actuality on Wikki link of Ontology
http://en.wikipedia.org/wiki/Ontology

This Is ongoing Article I going to complete the pieces with example and below topics
– CDI, Customer Data Integration (Single version of truth for a data Like
single person can be An Employee in Peoplesoft ERP, same person can be Customer in SAP CRM, Can be an represented in different way in  Oracle Financial. But when we develop reports on some parameters across functional areas then categorisation into a single entity can be achieved through CDI.
How this is linked to Ontology will explain further.
– MDM, Master data Management (Managing data (meta data)about data)
– Federated data management.
several Data Marts leading to a universal single data warehouse one design But in Data Federation the data from various data mart can be integrated virtually to create single view of Data from various disparate sources can also be used.
This relationship would be further expanded its not complete now..

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.
  • 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/

 

Architecture Difference between SAP Business Objects and IBM Cognos part1

Lets understand how Cognos product works internally

Most of BI product Architecture are almost similar internally.
BI Bus: Enterprise service Bus which surrounds all the services/servers which tool provide.
Typical ESB from Oracle BEA Aqualogic Stack engulfing many Web services looks like:
ESB_archNow you can compare this popular ESB with BI internal Architecture.
you can read more about ESB at : http://docs.oracle.com/cd/E13171_01/alsb/docs20/concepts/overview.html
Under 4 tier system: A client connects the Web server  (which is protected by firewall) using dispatcher. Dispatcher connects to Enterprise Service Bus (ESB) which surrounds all the application server services (Web services). ESB in case of cognos is Cognos BI Bus surrounds Web services Servers (like Report Server, Job server, Content Management server etc ). Mediation Layer Cognos BI Bus interacts with Non Java , C++ code which could not to converted or purposefully kept in C++ for may be more flexibility and speed
Cognos BI Bushttp://pic.dhe.ibm.com/infocenter/cbi/v10r1m1/index.jsp?topic=%2Fcom.ibm.swg.ba.cognos.crn_arch.10.1.1.doc%2Fc_arch_themulti-tierarchitecture.html

In case of SAP Business Objects (BO) ESB was not properly developed so an intermediate layer was created which works for interfacing between multiple servers like Job server, report server, page server etc. BO XI R2 came in pervius version was more in C++ to C++ to java bridge was created in ESB layer. Since Java was preferred language for coarse grain interoperability  provided by web services. Each server was developed using web services.
interaction between web server was routed through BI Bus.
BO-xi-r3.1-infrastructureIn latest version here u find a pipe connecting all components call Business Objects XI 3.1 Enterprise Infrastructure. Earlier version had different names. here you can see its connecting all server like Crystal report server, IFRS input file repository server( storing template of reports), OFRS Output file repository services, Program Job server(storing all programs which can be published on Portal (Infoview) ). This ESB does mediation between different server and achieves interoperability yet control of different components of products. This is in competitor product Cognos is called Cognos BI Bus.
http://bobi.blog.com/2013/06/02/sap-business-object-architecture-overview-and-comparatice-analysis/
For latest BO uses in memory product SAP HANA more about its competitors follow:
https://sandyclassic.wordpress.com/2011/11/04/architecture-and-sap-hana-vs-oracle-exadata-competitive-analysis/

In Micro-strategy there are two important server Intelligent server which creates cubes

More I will cover in later issues:
Oracle BI Architecture:
http://www.rittmanmead.com/2008/02/towards-a-future-oracle-bi-architecture/

Implementation OF BI system is not related to these product Architecture :
A  typical BI system under implementation haveing componets of ETL, BI, databases, Web server, app server, production server, test/development server looks like:
typical BI ArchtectureMore details: http://www.ibm.com/developerworks/patterns/bi/product-s390-web.html
Big Data Architecture:
From components perspective of ETL to BI implementation Aspect is little different
bigdata-scalein-architecture

Hadoop Architecture layers:
hadoop-architecturehttps://sandyclassic.wordpress.com/2011/10/19/hadoop-its-relation-to-new-architecture-enterprise-datawarehouse/
http://codemphasis.wordpress.com/2012/08/13/big-data-parallelism-and-hadoopbasics/

Just like UDDI registry is repository of Web

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/