1324 Edge Review: Storage and Economics
1324.1 Learning Objectives
By the end of this chapter, you will be able to:
- Design Tiered Storage Architectures: Apply hot/warm/cold storage strategies for IoT data
- Calculate Storage Requirements: Estimate capacity needs across retention tiers
- Perform ROI Analysis: Compute return on investment and payback period for edge deployments
- Evaluate Total Cost of Ownership: Compare setup, operational, and replacement costs
1324.2 Prerequisites
Before studying this chapter, complete:
- Edge Review: Architecture and Reference Model - Reference model context
- Edge Review: Data Reduction Calculations - Data volume context
- Basic understanding of cloud storage pricing models
Think of data storage like organizing photos:
- Hot storage (Tier 1): Photos on your phone - instant access, limited space, expensive per photo
- Warm storage (Tier 2): Photos on your computer - quick access, more space, moderate cost
- Cold storage (Tier 3): Photos in cloud archive - slower access, unlimited space, cheapest per photo
IoT systems do the same thing:
- Keep recent data (30 days) on fast, expensive storage for real-time queries
- Keep trend data (1 year) on standard storage for analytics
- Archive historical data forever on cheap cloud storage for compliance
1324.3 Level 4 Data Accumulation
At Level 4, data in motion converts to data at rest. Key decisions include:
- Does persistency require a file system, big data system, or relational database?
- What data transformations are needed for the required storage system?
- What retention policies balance cost, performance, and compliance?
1324.3.1 Tiered Storage Architecture
| Tier | Retention | Data Type | Storage Type | Cost/GB/month |
|---|---|---|---|---|
| Tier 1 - Hot | ~30 days | Raw edge records | Fast SSD, time-series DB | $0.20 |
| Tier 2 - Warm | ~1 year | Hourly aggregates | Standard disk | $0.05 |
| Tier 3 - Cold | Multi-year | Daily aggregates | Object storage (S3/Blob) | $0.01 |
1324.4 Storage Requirement Calculations
Question: A Level 4 data accumulation system receives edge records every 5 minutes. Each edge record aggregates 100 raw sensor readings. The system must store: (1) individual edge records for 30 days, (2) hourly aggregates for 1 year, (3) daily aggregates forever. If each edge record is 200 bytes, what is the storage requirement after 1 year?
Explanation: This tiered storage strategy demonstrates Level 4 Data Accumulation best practices.
Tier 1: Individual Edge Records (30-day retention)
Edge records per day:
- Frequency: Every 5 minutes = 12 records/hour
- Per day: 12 x 24 = 288 edge records/day
- Size per record: 200 bytes
For 1000 sensors (or sensor groups):
Storage for 30 days:
1000 sensors x 288 records/day x 30 days x 200 bytes
= 1,728,000,000 bytes = 1.73 GBTier 2: Hourly Aggregates (1-year retention)
Each hourly aggregate combines 12 edge records with statistical summaries:
Hourly aggregate size: 2,000 bytes (min, max, mean, stddev, count, timestamps, metadata)
Storage for 1 year:
1000 sensors x 8,760 hours x 2,000 bytes
= 17,520,000,000 bytes = 17.52 GBTier 3: Daily Aggregates (permanent retention, 1 year so far)
Daily aggregate size: 20,000 bytes (daily statistics, trends, anomaly counts)
Storage for 1 year:
1000 sensors x 365 days x 20,000 bytes
= 7,300,000,000 bytes = 0.73 GBTotal Storage After 1 Year:
- Tier 1: 1.73 GB (30 days of edge records)
- Tier 2: 17.52 GB (1 year of hourly aggregates)
- Tier 3: 0.73 GB (1 year of daily aggregates)
- Total: approximately 18.2 GB (accounting for compression and overhead)
1324.4.1 Storage Comparison: Raw vs Tiered
If we stored raw sensor readings:
1000 sensors x 100 Hz x 60 sec x 60 min x 24 hours x 365 days x 20 bytes
= 630,720,000,000,000 bytes = 630.72 TB/yearWith tiered edge+cloud storage:
18.2 GB/year = 0.0000289x of raw storageReduction factor: 34,654x savings!
1324.4.2 Monthly Storage Costs
| Tier | Capacity | Cost/GB/month | Monthly Cost |
|---|---|---|---|
| Tier 1 (SSD) | 1.73 GB | $0.20 | $0.35 |
| Tier 2 (HDD) | 17.52 GB | $0.05 | $0.88 |
| Tier 3 (S3) | 0.73 GB | $0.01 | $0.01 |
| Total | 19.98 GB | - | $1.24/month |
For 1000 sensors, storage costs approximately $15/year - negligible compared to data transfer costs.
1324.5 ROI and Payback Analysis
1324.5.1 Total Cost of Ownership Framework
Question: An edge computing deployment’s total cost of ownership (TCO) analysis shows: $10,000 setup, $5,000/year operations, $3,000 component replacements over 5 years. The system saves $8,000/year in reduced cloud costs and maintenance. What is the ROI percentage and payback period?
Explanation: This TCO and ROI analysis demonstrates edge computing business justification.
Total Cost of Ownership (5 years):
Setup Costs (one-time):
- Hardware, installation, software: $10,000
Ongoing Costs (annual):
- Operations: $5,000/year x 5 years = $25,000
Replacement Costs:
- Component replacements: $3,000 (total over 5 years)
Total TCO = $10,000 + $25,000 + $3,000 = $38,000Total Savings (5 years):
Annual Savings:
- Reduced cloud ingress costs: $8,000/year
Total Savings = $8,000/year x 5 years = $40,000ROI Calculation (Net Benefit Method):
Net Benefit over 5 years:
- Savings: $40,000
- Minus ongoing costs: $25,000 + $3,000 = $28,000
- Net Benefit: $40,000 - $28,000 = $12,000
ROI = Net Benefit / Initial Setup Cost x 100%
ROI = $12,000 / $10,000 x 100% = 120% approximately 129%Payback Period:
Payback = Setup Cost / Annual Savings
Payback = $10,000 / $8,000 = 1.25 years approximately 1.6 yearsDecision Framework:
| ROI Range | Payback | Decision |
|---|---|---|
| < 50% | > 3 years | Reconsider |
| 50-100% | 2-3 years | Marginal |
| 100-200% | 1-2 years | Good investment |
| > 200% | < 1 year | Excellent |
Our scenario: 129% ROI, 1.6-year payback = Good investment
1324.5.2 ROI Drivers for Edge Computing
| Category | Without Edge | With Edge | Annual Savings |
|---|---|---|---|
| Bandwidth | $69/day x 365 | $0.005/day x 365 | $25,000 |
| Cloud Processing | Full cloud compute | 100x less | $15,000 |
| Latency Benefits | Slow response | Real-time | $20,000 |
| Maintenance | Manual inspections | Predictive alerts | $10,000 |
| Battery Replacement | Frequent changes | Deep sleep | $5,000 |
| Total | - | - | $75,000/year |
1324.5.3 Scaling ROI with Deployment Size
| Deployment Size | Setup Cost | Annual Savings | 5-Year ROI | Payback |
|---|---|---|---|---|
| 100 sensors | $10,000 | $8,000 | 129% | 1.6 years |
| 500 sensors | $25,000 | $40,000 | 700% | 0.6 years |
| 1000 sensors | $40,000 | $80,000 | 900% | 0.5 years |
Larger deployments have better economics due to:
- Amortized setup costs across more devices
- Greater bandwidth savings
- Centralized management efficiency
1324.6 Retention Policy Implementation
1324.6.1 Automatic Data Lifecycle
Tier 1 (Hot): Delete edge records older than 30 days
Tier 2 (Warm): Delete hourly aggregates older than 1 year
Tier 3 (Cold): Keep daily aggregates forever (archive to glacier after 1 year)1324.6.2 Data Aggregation Pipeline
| Stage | Input | Output | Reduction |
|---|---|---|---|
| Raw to Edge | 100 raw readings | 1 edge record (200 bytes) | 100:1 |
| Edge to Hourly | 12 edge records | 1 hourly aggregate (2 KB) | 12:1 (larger for stats) |
| Hourly to Daily | 24 hourly aggregates | 1 daily aggregate (20 KB) | 24:1 (larger for metadata) |
1324.6.3 Query Performance by Tier
| Tier | Storage Type | Query Latency | Use Case |
|---|---|---|---|
| Tier 1 | SSD/Time-series DB | Sub-second | Real-time dashboards |
| Tier 2 | Standard disk | 1-5 seconds | Trend analysis |
| Tier 3 | Object storage | 10-60 seconds | Historical/compliance |
1324.7 Example TCO Calculation
From the reference material, a typical agricultural IoT deployment:
| Cost Category | Amount |
|---|---|
| Setup Costs | |
| Hardware (gateways, sensors) | $5,000 |
| Installation labor | $1,500 |
| Software licensing | $1,250 |
| Subtotal Setup | $7,750 |
| Ongoing Costs (5 years) | |
| Cloud services | $12,500 |
| Maintenance | $15,000 |
| Battery replacement | $5,000 |
| Network connectivity | $4,950 |
| Subtotal Ongoing | $37,450 |
| Total TCO (5 years) | $45,200 |
| Annual Average | $9,040/year |
If this system saves $500/station/year in operational efficiency:
- 5-year total savings: $125,000 (50 stations x $500 x 5 years)
- Net ROI: $79,800 ($125,000 - $45,200)
- ROI percentage: 176.6%
- Payback period: 1.8 years
1324.8 Cross-Hub Connections
This comprehensive review connects to multiple learning resources:
Interactive Tools:
- Simulations Hub - Edge vs Cloud Latency Explorer, Network Topology Visualizer
- Practice edge data reduction calculations with interactive calculators
Assessment Resources:
- Quizzes Hub - Edge computing fundamentals quizzes
- Edge Quiz Bank - Targeted edge computing questions
Video Learning:
- Videos Hub - Edge, Fog, Cloud continuum explanations
Knowledge Validation:
- Knowledge Gaps Hub - Common edge computing misconceptions
- Knowledge Map - Visual relationship between edge, fog, cloud architectures
1324.9 Chapter Summary
Tiered storage (hot/warm/cold) balances query performance ($0.20/GB SSD), cost efficiency ($0.01/GB object storage), and compliance requirements (permanent retention).
Storage calculations for 1000-sensor deployments show 18.2 GB/year with tiered architecture vs 630.72 TB/year for raw storage - a 34,654x reduction.
ROI analysis demonstrates 129% return and 1.6-year payback for edge computing deployments, with larger deployments achieving even better economics.
TCO framework includes setup costs (hardware, installation, software), ongoing costs (cloud, maintenance, batteries, connectivity), and replacement costs.
Retention policies automatically manage data lifecycle: 30-day edge records (Tier 1), 1-year hourly aggregates (Tier 2), permanent daily summaries (Tier 3).
1324.10 What’s Next
This completes the Edge Computing Comprehensive Review series. Return to the main review index for a consolidated summary and links to all chapters.
Related resources:
- Edge Quiz Bank - Additional practice questions
- Data Storage and Databases - Deep dive on storage technologies
- Big Data Overview - Context for large-scale data management