Name
Abstract | ||
|---|---|---|
Optimizing the deployment of software in a cloud environment is one approach for maximizing system Quality-of-Service (QoS) and minimizing total cost. A traditional challenge to this optimization is the large amount of benchmarking required to optimize even simplistic cloud systems. This paper introduces $$\\hbox {C}^2$$C2RAM, an new approach to enable rapid, optimized deployment of software onto a cloud environment by substantially reducing the number of benchmarks required. $$\\hbox {C}^2$$C2RAM continues to perform some benchmarking, and therefore its predictions of application QoS metrics, such as throughput and latency, are very accurate. Our results show a maximum difference of 1.06 % between $$\\hbox {C}^2$$C2RAM predicted QoS and empirically measured QoS. Moreover, $$\\hbox {C}^2$$C2RAM can be provided with QoS requirements for each software in the system, and will ensure that each requirement is met before presenting a deployment plan. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s10515-016-0191-0 | Autom. Softw. Eng. |
Keywords | Field | DocType |
Automated software deployment,QoS performance,Resource allocation and optimization,Bin packing | Software deployment,Computer science,Latency (engineering),Quality of service,Theoretical computer science,Software,Throughput,Bin packing problem,Benchmarking,Distributed computing,Embedded system,Cloud computing | Journal |
Volume | Issue | ISSN |
24 | 1 | 0928-8910 |
Citations | PageRank | References |
3 | 0.40 | 42 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu Sun | 1 | 63 | 10.64 |
| Jules White | 2 | 152 | 13.93 |
| Bo Li | 3 | 971 | 111.71 |
| Michael Walker | 4 | 21 | 1.57 |
| Hamilton A. Turner | 5 | 102 | 6.95 |