Table 8 Data management concerns for big data software systems
From: Software architectures for big data: a systematic literature review
Motivation | Domain, Subdomain | Citation # | Details (explanation, data size, sensor type) |
|---|---|---|---|
Supporting Analytics Process | Industrial applications, Environmental Sustainability | 41 | Sensor types: temperature, pressure, velocity I. Decision making for the coordination and optimization (lifecycle management) |
Social media, Web Data Warehousing, Social Data Storage and Analytics | 39 | A query language at the level of SQL, parallel runtime querying, various query sizes, continuous data ingestion… 100 nodes 5 gb - > 500 gb 100 nodes 12 tb - > 1.2 pb | |
Improving Efficiency | Health, Brain and Health Monitoring System | 1 | Improvement of the fusion and the analysis of the big data (>2gb in ~ 70 s) |
Other, Trace Analyzer | 33 | To optimize the workload and investigate the usage pattern via the analysis of the monitoring data | |
Industrial Applications, Electric Power Industry | 42 | To improve the efficiency and safety of the power systems while keeping the flexibility and availability on demand Sensors: occupancy sensor | |
Other, Hive Alternative | 39 | Performance improvement up to 30 times with higher scalability and availability | |
Healthcare, Interconnection of Healthcare Platforms | 26 | Improve the processing performance, having a resilient cloud storage and indexes for unstructured data and metadata for efficient search | |
Industrial Applications, Automotive Industry | 17 | Facilitated cloud services, cost and performance improvement, scalability on demand ● Data size may exceed 17 Eb per year | |
Industrial Applications, Environmental Sustainability | 3 | Focused on integration considering design optimization and exploration. Models in size of 50GB in size (3D, encoded, compressed, in diverse formats) | |
Industrial Applications, Environmental Sustainability | 41 | Improvement of the decision-making procedures for coordination and optimization II. Sensors: temperature, pressure, velocity | |
Improving Real-time Processing | Smart Cities, Network Security | 35 | Optimal responses in real time Latency sensitive applications with fog computing |
Social Media, Social Network Analysis | 14 | Social data processing in real time. | |
Smart Cities, Traffic State Assessment | 40 | Real-time traffic situation prediction III. 5gb per day | |
Reduce development costs | Financial Services, Banking | 25 | Cost reduction keeping the required level of flexibility and scalability |
Social media, Semantic-based Heterogeneous Multimedia Retrieval | 12 | Heterogenous multimedia data, low cost store and retrieval IV. 10 machines, 10 processors, 20 GB memory, 10 disks and 10 slave data modes | |
Smart cities, surveillance systems | 24 | Optimizing the number of camera sensors ● Up to 100 gb ● Microwave sensor, boundary/non-boundary camera sensor | |
Smart Cities, Smart Grid | 34 | Efficiency of energy usage and minimization of pollution via managing traffic and the city | |
Smart Cities, Smart City Experiment Testbed | 9 | Testbed with a wireless network topology, reliable data transmission and battery lifetime. Processing both real time and historical data: 50 GB data, 112 sensor nodes, 9 different sensor types. | |
New Kinds of Services | Scientific Platforms, Scientific Platform for the Cloud | 4 | Scientific applications are designed and deployed to the cloud. Generic infrastructure, web interface, post processing and plotting, monitoring real time V. Use of big machines (An r3.8, 32 vCPUs and 244GB of RAM) |
Smart cities, Smart City Experiment Testbed | 5 | Architecture for collection of sensor-based data in the context of the IoT. VI. 2gb per year for one sensor (Scenarios with 150–200 GB) VII. 1 measurement per second VIII. Sonar/temperature sensors | |
Smart Cities, Smart Grid | 34 | Enable new kind of services, data accuracy data to assist decision making ● Social sensors (twitter, blogs etc.) ● Smart home sensors (18 sensor measurement per second, citywide 360,000 measurements per second) | |
Industrial Applications, Electric Power Industry | 6 | Data analysis and statistics functions for specific tasks and services such as time series. Performance evaluation with certain evaluation metrics. | |
Healthcare, Brain and Health Monitoring System | 7 | Smart monitoring services. Brain monitoring and models for accurate diagnosis, personalized service modules. | |
Data Management and Orchestration | Social Media, Public Opinion Monitoring | 15 | Flexible, knowledge-worker driven iterative exploration, rapid integration |
Social media, Travel Advising | 8 | Achieving, strategic control, continuous big data value delivery for WBS. ● Various systems from 90 TB to 1 PB |