TY - JOUR
T1 - Smart community edge
T2 - Stream processing edge computing node for smart community services
AU - Abeysiriwardhana, W. A.Shanaka P.
AU - Wijekoon, Janaka L.
AU - Nishi, Hiroaki
N1 - Funding Information:
This study summarized the architecture and performance of the proposed SCE using DPDK, Hyperscan, and Docker technologies. The proposed SCE employs MSASCA and container technology to support multiple smart community services at the edge. SCE allowed MSASCA content to be directly transferred to services without network packet processing at the service containers. The SCE MSASCA achieved a throughput of 1–10 Gbps with 4 –16 CPU cores in conventional hardware systems. In addition, the SCE proposed a distributed rule change method for the Hyperscan library to change regular expression without affecting network flow. The SCE achieved a 10 Gbps ASCA throughput for 100 accumulated rules, which allowed more than ten rules per service. In addition, the proposed dictionary change method needs less than 0.3 ms to execute, and does not affect the performance of SPL network flows. SCE supported eight similar services while providing a 500 Mbps MSASCA content bandwidth for each service, where each service can support 5000 sensors with a 100 kbps bandwidth. Additionally, the total maximum delay of the SCE is maintained at less than 1 ms, allowing delay-sensitive services to operate at SCE nodes. Therefore, SCE shows adequate performance and applicability in smart community networks for supporting multiple IoT services at the network edge using MSASCA. Acknowledgment This work was supported by JST CREST Grant Number JPMJCR19K1, and the commissioned research by National Institute of Information and Communications Technology (NICT, Grant Number 22004), JAPAN. The authors would like to thank Keio University Doctorate Student Grant-in-Aid Program.
Publisher Copyright:
© 2020 The Institute of Electrical Engineers of Japan.
PY - 2020/9/1
Y1 - 2020/9/1
N2 - A smart community utilizes information technology to interconnect and manage community infrastructures. Smart community networks should support a large number of Internet of Things (IoT) devices in community infrastructures to provide services such as smart grids and health monitoring systems. In comparison to cloud-based solutions, smart community services can be deployed in the edge computing area to reduce service latency and to encapsulate private and local information. Furthermore, smart community services can leverage network virtualization technologies to support IoT network services at the edge. A service-oriented container-based solution that processes data streams from IoT sensors using conventional hardware will improve the compatibility and latency of these virtualized network services at the edge. To this end, a software-based edge computing node, namely, the smart community edge (SCE), was proposed to develop a platform for smart community services. SCE supports data-tapping applications, especially for IoT devices, and has a stream processing feature with a comparatively shorter processing delay. This tapping and processing function was named multi-service authorized stream content analysis. SCE captures network stream data and enables service applications using shared memory buffers for a shorter processing delay. SCE supports services as Docker containers to provide remote deployment, service compatibility, and service isolation. SCE allows IoT services to run at the edge through conventional hardware devices, thus, reducing the service latency for delay-sensitive services, which approximately require to sustain latency less than 10 ms. The proposed SCE achieves 10 Gbps bandwidth with a 16 core server when compared to the f-stack library with a 5 Gbps bandwidth. SCE deployment on conventional hardware devices shows its capability of operating at 1-10 Gbps line rates to support up to eight services at 500 Mbps data bandwidth per service, while keeping the overall latency below 1 ms. Therefore, SCE provides a platform for delay-sensitive IoT services at the network edge.
AB - A smart community utilizes information technology to interconnect and manage community infrastructures. Smart community networks should support a large number of Internet of Things (IoT) devices in community infrastructures to provide services such as smart grids and health monitoring systems. In comparison to cloud-based solutions, smart community services can be deployed in the edge computing area to reduce service latency and to encapsulate private and local information. Furthermore, smart community services can leverage network virtualization technologies to support IoT network services at the edge. A service-oriented container-based solution that processes data streams from IoT sensors using conventional hardware will improve the compatibility and latency of these virtualized network services at the edge. To this end, a software-based edge computing node, namely, the smart community edge (SCE), was proposed to develop a platform for smart community services. SCE supports data-tapping applications, especially for IoT devices, and has a stream processing feature with a comparatively shorter processing delay. This tapping and processing function was named multi-service authorized stream content analysis. SCE captures network stream data and enables service applications using shared memory buffers for a shorter processing delay. SCE supports services as Docker containers to provide remote deployment, service compatibility, and service isolation. SCE allows IoT services to run at the edge through conventional hardware devices, thus, reducing the service latency for delay-sensitive services, which approximately require to sustain latency less than 10 ms. The proposed SCE achieves 10 Gbps bandwidth with a 16 core server when compared to the f-stack library with a 5 Gbps bandwidth. SCE deployment on conventional hardware devices shows its capability of operating at 1-10 Gbps line rates to support up to eight services at 500 Mbps data bandwidth per service, while keeping the overall latency below 1 ms. Therefore, SCE provides a platform for delay-sensitive IoT services at the network edge.
KW - Docker services
KW - IoT services
KW - Smart community
KW - Stream processing
UR - http://www.scopus.com/inward/record.url?scp=85094157917&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85094157917&partnerID=8YFLogxK
U2 - 10.1541/ieejeiss.140.1030
DO - 10.1541/ieejeiss.140.1030
M3 - Article
AN - SCOPUS:85094157917
SN - 0385-4221
VL - 140
SP - 1030
EP - 1039
JO - IEEJ Transactions on Electronics, Information and Systems
JF - IEEJ Transactions on Electronics, Information and Systems
IS - 9
ER -
