a survey of computation offloading for mobile systems
TRANSCRIPT
A Survey of Computation Offloading for Mobile Systems
Karthik Kumar, Jibang Liu
Yung-Hsiang Lu , Bharat Bhargava
Presented by
Zhipeng Yang (Scar)
Csci 8980 : Mobile Cloud Computing
Introduction1
Technology 2
Analysis3
Future 4
Summary5
Demand
Limitation
• Processors
• Storage
• Bandwidths
• Battery
• ……
•
• Object Recognition
• Real-Time
Translation
• Video Processing
• HD Games
• ……
•
Client/Server --- A thin client ALWAYS migrates computation to a server.
Multiprocessor Systems & Grid Computation --- For load balancing; Migrate for
the SAME environment.
SETI@home --- THOUSANDS of users.
Solution --- Offloading
Computation Offloading is different.
Computation Offloading: PARTLY migrate to (maybe) DIFFERENT
for (maybe) a SINGLE user.
• Feasibility (prior to 2000) --- Mainly due to low bandwidths.
• Decision (in early 2000s) --- Algorithms, for better performance & saving energy.
Parameters: Bandwidths, server speeds, memory, server loads, size of
data to be sent,
Solution: Partitioning programs & predicting parametric variations.
• Infrastructures (in late 2000s) --- Virtualization, bandwidths, etc.
• VMs Isolation & Protections Granularities
Development over the last 15 years
Classification Factors
• Why to offload
Performance
Save energy
• When to decide offloading
Static
Dynamic
• What mobile systems use offloading
Laptops, PDAs, Robots, Sensors
• Type of applications
Multimedia, gaming, calculators, text editors, predictors
• Infrastructures for offloading
Grid and cloud computing
Chroma
(Method)
CuckooMAUI
JIT-Cloudlet
CloneCloud
Comet(Thread)
(VM, Overlay)
Weblet(Component)
Sharing-based(Application)
(Task, Compact Discription)
(Method, Manually)
(Thread, Static)
Introduction1
Technology 2
Analysis3
Future 4
Summary5
Enabling technologies for computation offloading
(paper counts, obtained from IEEE Xplore)
Two significant enablers
1. Wireless networks & mobile agents
• Wireless networks --- WiFi
• Mobile agents
Kotz et al. --- Agent TCL (Tcl, Java, and Scheme)
Wong et al. --- Concordia (Java)
Joseph et al. --- Rover (toolkit,)
--- Migrate computation, platform-independent
2. Virtualization (when?) & cloud computing
• 1960s lost popularity during the 1980s and early 1990s
• Why we use it again?
Under utilization
Security
Operational cost
• Advantages: Multitasking, utilization and flexibility
Introduction1
Technology 2
Analysis3
Future 4
Summary5
Two main goals of offloading
• Improve performance
• Save energy
Performance
sm the speed of the mobile system
ss the speed of the server
w the amount of computation that can’t be migrated
di the size of data need to be sent
B the bandwidth
How does the inequality hold?
Large w & small di
Energy
pm the power on the mobile system
pm the power required to send data form mobile system over the network
pm the power required to wait for the result
sm the speed of the mobile system
ss the speed of the server
w the amount of computation that can’t be migrated
di the size of data need to be sent
B the bandwidth
How does the inequality hold?
Classification criteria here
• When to decide offloading & How are tasks identified for offloading
Static
Dynamic
• How are tasks identified for offloading
• Type of applications
Multimedia, gaming, calculators, text editors, predictors
• What mobile systems use offloading
Laptops, PDAs, Robots, Sensors
• Static, low overhead & need accurate prediction
Prediction algorithms: probabilistic prediction, history-based
prediction, fuzzy control
• Dynamic, flexible & high overhead with monitors
Prediction (Bayesian scheme) + monitors
Static &Dynamic
Identification
• Various algorithms for partition.
• E.g., Communication should be taken in to account.
Size of a vertex indicates the amount of computation
Width of an edge indicates the amount of data to be sent
Applications & Systems
Applications & Systems
Infrastructures
• Inter-operability, different networks, systems and capabilities
• Mobility and fault tolerance, handle failures
• Privacy & Security, for user’s confidential data
• Context awareness, user’s location and context
Introduction1
Technology 2
Analysis3
Future 4
Summary5
Two important trends
• Sensor deployment, not for computation but for data collection
and protection
• Growth in smartphones
• More requirements on mobile system.
Recognition, real-time translation, data management etc.
• Massive growth in mobile data in both types and volumes
Images, audios, videos etc.
• The capacities of the devices will be unlikely to grow at the
same pace.
Processors, storage, bandwidths, battery etc.
Introduction1
Technology 2
Analysis3
Future 4
Summary5
Summary
• What was done in this paper.
Background in details
Enabler technology
Simplified formula with extended example
Statistics from a lot of papers
Simple analysis about future trend
• Some comments.
Most of the issues above are simplified for readers
Easy to understand but not accurate, e.g. formula
More deep comparisons are needed for algorithms
Data sources are limited
Thank you