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An enhanced DSM model for computation offloading
- Source :
- PerCom
- Publication Year :
- 2017
- Publisher :
- IEEE, 2017.
-
Abstract
- The distributed shared memory (DSM)-based computation offloading scheme allows collaborative multiple threads to dynamically migrate and execute across a mobile device and computing nodes. Despite this strong advantage, it misses a significant portion of the potential performance gain because the traditional DSM model is suboptimal for computation offloading. This paper proposes an enhanced DSM model that aims to enable multiple computing nodes to efficiently and reliably offload concurrent multiple threads from a mobile device. To achieve this design goal, we propose the following novel schemes: a) selective object tracking minimizes the set of objects to be monitored by the DSM layer; b) lock-thread repartitioning dynamically relocates threads and locks in order to reduce remote lock acquisitions and inter-node synchronizations; and c) thread-state checkpointing protects the data and context upon unexpected system failures. We implemented METEOR, which is a prototype based on the proposed schemes, and evaluated it with diverse applications. The evaluation showed that METEOR, with four computing nodes, improved the performance by up to 109% and reduced energy consumption by up to 52% in comparison with the previous DSM-based offloading scheme.
- Subjects :
- Distributed shared memory
Record locking
business.industry
Computer science
Distributed computing
020206 networking & telecommunications
Context (language use)
02 engineering and technology
Instruction set
Video tracking
Embedded system
Scalability
0202 electrical engineering, electronic engineering, information engineering
Computation offloading
020201 artificial intelligence & image processing
business
Mobile device
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2017 IEEE International Conference on Pervasive Computing and Communications (PerCom)
- Accession number :
- edsair.doi...........9b754e9bbce315ba84cd627952694fc3