Scalable service migration in autonomic network environments
Scalable service migration in autonomic network environments
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DOI：
10.1109/jsac.2010.100109
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发表时间：
2010
影响因子：
16.4
通讯作者：
K. Oikonomou;I. Stavrakakis
中科院分区：
文献类型：
--
作者：
K. Oikonomou;I. Stavrakakis
服务放置是通信网络中的一个关键问题，因为它决定了用户服务需求得到支持的效率。这个问题传统上是通过制定和解决需要全局知识的大型优化问题来解决的，并且在网络变化的情况下不断地重新计算解决方案。这种方法不适用于大规模和动态的网络环境。在本文中，确定服务设施的最佳位置的问题被重新审视，并以一种既可扩展又能处理网络动态的方式来解决。特别是，服务迁移是基于本地信息的，它使服务设施能够在相邻节点之间移动到更具通信成本效益的位置。分析表明，本文提出的迁移策略能够以降低服务提供成本的方式在相邻节点之间移动服务设施，并且在某些条件下，服务设施达到最优（成本最小化）位置，并在环境不变的情况下锁定在那里；随着网络条件的变化，迁移过程会自动恢复，从而在一定条件下自然地响应网络的动态性。这项工作的分析结果也得到了模拟结果的支持，这些结果进一步阐明了拟议政策的行为和有效性。
Service placement is a key problem in communication networks as it determines how efficiently the user service demands are supported. This problem has been traditionally approached through the formulation and resolution of large optimization problems requiring global knowledge and a continuous recalculation of the solution in case of network changes. Such approaches are not suitable for large-scale and dynamic network environments. In this paper, the problem of determining the optimal location of a service facility is revisited and addressed in a way that is both scalable and deals inherently with network dynamicity. In particular, service migration which enables service facilities to move between neighbor nodes towards more communication cost-effective positions, is based on local information. The migration policies proposed in this work are analytically shown to be capable of moving a service facility between neighbor nodes in a way that the cost of service provision is reduced and - under certain conditions - the service facility reaches the optimal (cost minimizing) location, and locks in there as long as the environment does not change; as network conditions change, the migration process is automatically resumed, thus, naturally responding to network dynamicity under certain conditions. The analytical findings of this work are also supported by simulation results that shed some additional light on the behavior and effectiveness of the proposed policies.