Network Coding in Heterogeneous Multicore IoT Nodes with DAG Scheduling of Parallel Matrix Block Operations
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
Random linear network coding (RLNC) has the potential to improve the performance of current and future Internet of Things (IoT) communication systems, but is computationally demanding due to matrix multiplications and inversions. Some single-core RLNC implementations achieve already sufficient coding speeds for contemporary multimedia streaming formats. However, advances in multimedia streaming formats and IoT applications will require the exploitation of heterogeneous multicore architectures, which are becoming common for a wide range of IoT nodes, including smartphones. In this paper, we introduce and evaluate efficient RLNC computing strategies for IoT node architectures, including the emerging heterogeneous big.LITTLE multicore architectures with multiple big (fast) cores and multiple LITTLE (slow) cores. In contrast to existing RLNC implementation strategies, we build on and adapt highly optimized dense matrix operations from the high performance computing field to RLNC on heterogeneous multicore IoT nodes. Our approach includes the optimization of RLNC matrix operations through optimized operations on matrix blocks with single instruction multiple data instructions. We schedule block operations on the heterogeneous cores through a directed acyclic graph that avoids artificial synchronization points while ensuring the data dependencies. We examine priority scheduling according to the number of outgoing dependencies of a task and data locality of cached blocks. Our extensive measurements with several heterogeneous big.LITTLE multicore IoT node and smartphone processor boards demonstrate higher RLNC encoding and decoding throughputs than existing approaches. Moreover, our measurements indicate that the utilization of more cores decreases energy consumption, which is an important goal for IoT nodes.
Details
Original language | English |
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Article number | 7926320 |
Pages (from-to) | 917-933 |
Number of pages | 17 |
Journal | IEEE internet of things journal |
Volume | 4 |
Issue number | 4 |
Publication status | Published - Aug 2017 |
Peer-reviewed | Yes |
External IDs
ORCID | /0000-0001-8469-9573/work/161891272 |
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Keywords
Sustainable Development Goals
ASJC Scopus subject areas
Keywords
- Directed acyclic graph (DAG), heterogeneous multicore architecture, Internet of Things (IoT) node, matrix inversion, matrix multiplication, parallel computing, random linear network coding (RLNC), smartphone