Automated Change Planning for Differential Update IT Systems with State Constraint

Nakanoya, Manabu; Kuroda, Takayuki; Kitano, Atsushi

doi:10.1109/edocw.2016.7584349

Cited by 2 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In contrast to those works, in our previous work [8]- [10], we chose state-space search for making it possible to explicitly deal with system states and easily taking global constraints (cf. [12]) into account.…”

Section: Related Workmentioning

confidence: 99%

“…We assume that our declarative system update tool uses high-level models to hide details of states, transitions and dependencies. For example, the component model [9], [10] is proposed, which consists of system components, connections between them, and property of them. In this model, the model encapsulates the details of components and connections, and are converted into a detailed model that corresponds to the state model.…”

Section: Modeling Systemsmentioning

confidence: 99%

See 1 more Smart Citation

Scalable State Space Search with Structural-Bottleneck Heuristics for Declarative IT System Update Automation

Kuwahara¹,

Kuroda²,

Nakanoya³

et al. 2019

IEICE Trans. Commun.

Self Cite

View full text Add to dashboard Cite

Takuya KUWAHARA †a) , Takayuki KURODA †b) , Manabu NAKANOYA †c) , Yutaka YAKUWA †d) , Nonmembers, and Hideyuki SHIMONISHI †e) , Member SUMMARY As IT systems, including network systems using SDN/NFV technologies, become large-scaled and complicated, the cost of system management also increases rapidly. Network operators have to maintain their workflow in constructing and consistently updating such complex systems, and thus these management tasks in generating system update plan are desired to be automated. Declarative system update with state space search is a promising approach to enable this automation, however, the current methods is not enough scalable to practical systems. In this paper, we propose a novel heuristic approach to greatly reduce computation time to solve system update procedure for practical systems. Our heuristics accounts for structural bottleneck of the system update and advance search to resolve bottlenecks of current system states. This paper includes the following contributions: (1) formal definition of a novel heuristic function specialized to system update for A* search algorithm, (2) proofs that our heuristic function is consistent, i.e., A* algorithm with our heuristics returns a correct optimal solution and can omit repeatedly expansion of nodes in search spaces, and (3) results of performance evaluation of our heuristics. We evaluate the proposed algorithm in two cases; upgrading running hypervisor and rolling update of running VMs. The results show that computation time to solve system update plan for a system with 100 VMs does not exceed several minutes, whereas the conventional algorithm is only applicable for a very small system.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Modeling Systemsmentioning

confidence: 99%