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COMP 410 Update March 13, 2015.

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Presentation on theme: "COMP 410 Update March 13, 2015."— Presentation transcript:

1 COMP 410 Update March 13, 2015

2 Meeting Agenda Risk Mitigation and Timeline Prototype 0 Demonstration
Prototype 1 Design Questions & Logistical Discussion

3 There’s a hurricane People need water, food, and medicine The city has shelters that people are going to for relief How does the city use its food banks, hospitals, weather information, and relief trucks to distribute resources to those shelters?

4 We connect these resources so that truck drivers know where to send food, food banks know when they will receive more inventory, and city leadership knows the status of these systems and can route according to weather and road conditions Finally the city is back on its feet and city managers want to look back at how decisions were made to modify emergency response protocols for future disasters. First we solved the immediate problem then learned from those decisions to help us in the future

5 The Core Issues From Last Meeting: High Volumes of Data Disconnections
Different Kinds of Devices New: 4. Human Interaction Heterogeneous Data Sources = Different Kinds of Devices

6 Solutions High Volumes of Data Disconnections
Large Scale Data Aggregation Historical Data Storage Disconnections Dynamic Network Topology Robust Connections This is priority order Dynamic Network Topology Framework Scalability Large Scale Data Aggregation Historical Data Storage Robust Connections System Diagnostics UX/UI

7 Solutions Different Kinds of Devices Human Interaction
Framework Scalability Human Interaction System Diagnostics UX/UI

8 Feature Priority Dynamic Network Topology Framework Scalability
Large Scale Data Aggregation Historical Data Storage Robust Connections System Diagnostics UX/UI Feature encompasses each of the solutions previously mentioned

9 Dynamic Network Topology
New devices can be connected to existing infrastructure Business Value Easy to add new devices without reconfiguring entire network Smoothly handle reconnection after intentional disconnection EX for business gains Take prototype 0, we want to monitor another door. Currently would have to shutdown all devices, and bring back up. We want to be able to just connect the new devices to the already running network Intentional disconnect – when the monitor disconnects from the alarm after sending photo Estimated Completion Currently in progress Team of 2-3 people one week

10 Dynamic Network Topology
Challenges Current Component Framework model typically static Mention that we are currently working on implementing a solution – defer technical questions to Matt

11 Framework Scalability
Integration of a cloud platform with the Framework Business Gains Support high volumes of data Perform high performance computations Testing through integration with the cloud (we are using Azure) Estimated Completion Currently in progress (Team of 2) Infrastructure built in Prototype 1 Stress testing in Prototype 2

12 Framework Scalability
Challenges Running Framework on cloud platform Need cloud platform because we have limited devices – won’t be able to test scalability until this is complete

13 Large Scale Data Aggregation
High Bandwidth, few devices, fluctuating heterogeneous data Business Gains Stress tests the system to handle lots of incoming data Proves Framework can synthesize and interpret lots of data Chose high bandwidth, few devices because the resources available to us as far as devices is currently limited (we have laptops that have a set amount of computing power), but we can create high bandwidth through data simulation, azure instances, etc. Timeframe – consistently work throughout rest of class. 2 weeks for first portion, 2 weeks for second Estimated Completion Dedicate a team of 3-4 people for rest of semester Infrastructure in Prototype 1, extensive use in Prototype 2 Potential Setback Areas Testing will cause extensive strain on our system Remaining Questions: What technologies will show this off? Where will it be incorporated in the use case?

14 Large Scale Data Aggregation
Challenges Simulating massive amounts of heterogeneous data is slow Designing tests that follow real world situations Find bottlenecks and thresholds for the system Improving system to maximize data flow Not hard to break the system with an overflow of data. The challenge - How will we scale back and find bottlenecks and thresholds for our system to find where to improve?

15 Historical Data Storage
Store and access data using a Database Business Gains Analyze information after an event to help future predictions Works as a data source for large scale data aggregation Considering NoSQL - good for storing data that doesn’t have clear format, heterogeneous kinds of data, don’t know how clean everything will be, faster & easier to set-up Estimated Completion Team of 2 about a week Integrate in Prototype 1

16 Historical Data Storage
Challenges Creating meaningful, readable data Combining data storage with cloud services Considering NoSQL - good for storing data that doesn’t have clear format, heterogeneous kinds of data, don’t know how clean everything will be, faster & easier to set-up Estimated Completion Team of 2 about a week Integrate in Prototype 1

17 Robust Connections Handle unexpected disconnection of components
Business Gains Devices are able to reconnect after unexpected disconnection Bypass the reconnection process of installing a new device EX WiFi drops’ Estimated Completion Team of 2-3 people a week Will be demoed in Prototype 2

18 Robust Connections Challenges Networking can be unpredictable
Designing sufficient testing of unexpected disconnections EX WiFi drops’ Estimated Completion Team of 2-3 people a week Will be demoed in Prototype 2

19 System Diagnostics Ability to log performance of the system
Business Gain Internal – We can know what happens when connections fail External – Customers will be able to monitor their system and make adjustments as necessary Estimated Completion Continual development throughout the project Member of data storage team over course of semester

20 System Diagnostics Challenges Monitoring the system during runtime
Determining the right type of information to log Synthesizing information for system improvements

21 UX/UI How customers will use the Framework Business Gains
Currently have a User Manual on SharePoint UI for application in demo Business Gains Easily use Framework to create applications Displaying and interacting with aggregated data Estimated Completion Already in progress Continual development throughout semester

22 UX/UI Challenges Ensuring that documentation is clear and understandable Displaying data for humans to interpret and respond to changes Point 1: We wrote the system, so it makes a lot of sense. Want to make sure anyone not involved in the process can read and understand documentation and then use it to create an application

23 Implementation Timeline

24 Prototype 0 Demo

25

26 Prototype 0 Connects devices with different protocols
Interacts with WunderBar and Kinect through adapters Transfers and interprets data sent between devices Transfers photos intermittently from Collector to Monitor Sends alerts from Monitor to Admin Aggregates and analyzes data Stores pictures in local storage Analyzes pictures’ timestamps Different protocols being blue tooth (already translated into TCP up to the cloud) TCP/IP, disconnection protocols (intermittent, always connect, abrupt disconnect) Data aggregation & analysis -> timestamp, aggegration = pictures

27 High-Level Framework Design
Application Layer, a.k.a. Business Logic Communication Protocol Storage Protocol 3rd Party Device Adapter

28

29 Prototype 1 Design

30 Prototype 1 Interact with cloud services for data analysis
Now that components are connected, we want to make sure we can use the data effectively Aggregate data from multiple sources Added complexity to the flow of information Introduce new components to the network without reconfiguring Demonstrating the extensibility of the Framework PROTOTYPE 1 - hurricane/disaster situation (disconnection) gracefully handles disconnection; saves data (see below) (data safety) keeps information in a buffer when disconnect (third party support) nodes can connect to third party stuff IoT devices (data aggregation) probably store data on the cloud (data analysis) probably analysis nodes (scalability) interaction with the cloud Features solved in this prototype are either hi-pri, or easy to solve along the way. 

31 Basic Idea

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35 Basic Idea

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