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Articles by Jianling Sun
Total Records ( 4 ) for Jianling Sun
  Jian Wang , Jianling Sun , xinyu Wang and Hang Chen
  Process allocation for load distribution can improve system performance by utilizing resources efficiently. For primary-backup based fault tolerant system, a classic load-balancing process allocation method (two-stage allocation algorithm) has been proposed that can balance the load before as well as after faults occurrence. But two-stage allocation algorithm has bad scalability since its load-balancing performance reduces dramatically when each primary process is duplicated more than once (i.e., has more than one backup process). In this study, we present an improved algorithm named RSA (R-Stage Allocation algorithm) that can have the load better balanced no matter how many backup processes each primary process owns; Simulations are also used to compare the proposed algorithm with the two-stage allocation algorithm and the experimental results show that when extending to replicated R-Resilient processes, RSA has significantly better load distribution performance than two-stage allocation algorithm.
  Xinyu Wang , Xiaohu Yang , Jianling Sun and Zhengong Cai
  Once software is in production, maintenance works are inevitable e.g., bug fixes, requirement changes, etc. During the long-term software maintenance, documents become gradually inconsistent with the system and the source code becomes the most reliable source for design recovery. Currently there exist many approaches to identify component from source code, which adopt different component metrics and clustering algorithms. However, these approaches are not satisfying in the precision and efficiency. This study proposes a new component extraction approach based on 0 metrics and hierarchical clustering algorithm, which greatly improves the precision and efficiency.
  Chao Huang , Jianling Sun , Xinyu Wang and Yuanjie Si
  In this study, we propose the redundancy and inconsistency checking algorithms to support the policy management of systems employing role based access control model. Present method is based on the formal definition of the policy redundancy and policy inconsistency. Via constructing the role graph, we analyze the redundancy and inconsistency one by one. According to the features of each type of redundancy and inconsistency, present algorithm checks all the possible violations and generates the related policy elements to help the security administrator to amend the policy afterwards. The performance test demonstrates that the approach is efficient enough for practical usage. Present approach could guarantee the conciseness as well as consistency of the access control policy, at same time reduce the burden of access control administration significantly.
  Shuai Zhang , Jianling Sun , Yuanhong Shen , Yixi Chen and Aleksander J. Kavs
  Many approaches have been proposed for performance optimization of centralized services composition. However, with the prevalence of web services, services orchestration evolves from intra-enterprise integration to cross-enterprise integration and involves multiple networks. In such environment, the centralized orchestration suffers from several performance and reliability issues due to the limitation of centralized execution engine and the network conditions. In this paper, we try to optimize the performance of composite services in enterprise environment by adjusting the deployment location of component services. First, we propose a decentralized orchestration model for multiple networks environment. Based on this model, we propose the concept called service interaction strength, which is denoted by the data interaction between component services in a composite service as well as the importance of composite service itself. Then we design an objective function for all composition services with overall minimum cross domains service interaction costs and thus reduce the response latency and increase the performance of composite services. At last we introduce a mixed repair genetic algorithm to get the optimized deployment plans for all component services. Experimental results on simulation prototype show the optimization effectiveness of our approach and the performance of algorithm itself is also acceptable.
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