IDMaps: a global internet host distance estimation service
IEEE/ACM Transactions on Networking (TON)
Vivaldi: a decentralized network coordinate system
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Estimating network proximity and latency
ACM SIGCOMM Computer Communication Review
Local Graph Partitioning using PageRank Vectors
FOCS '06 Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science
A General Framework for Agglomerative Hierarchical Clustering Algorithms
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Smartsockets: solving the connectivity problems in grid computing
Proceedings of the 16th international symposium on High performance distributed computing
Visualizing community detection in opportunistic networks
Proceedings of the second ACM workshop on Challenged networks
Graph-Theoretical Methods for Detecting and Describing Gestalt Clusters
IEEE Transactions on Computers
Distributed community detection in delay tolerant networks
Proceedings of 2nd ACM/IEEE international workshop on Mobility in the evolving internet architecture
Hierarchical Agglomerative Clustering with Ordering Constraints
WKDD '10 Proceedings of the 2010 Third International Conference on Knowledge Discovery and Data Mining
Empirical comparison of algorithms for network community detection
Proceedings of the 19th international conference on World wide web
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Cloud computing is a big paradigm shift of computing mechanism. It provides high scalability and elasticity with a range of on-demand services. We can execute a variety of distributed applications on cloud's virtual machines (computing nodes). In a distributed application, virtual machine nodes need to communicate and coordinate with each other. This type of coordination requires that the inter-node latency should be minimal to improve the performance. But in the case of nodes belonging to different clusters of the same cloud or in a multi-cloud environment, there can be a problem of higher network latency. So it becomes more difficult to decide, which node(s) to choose for the distributed application execution, to keep inter-node latency at minimum. In this paper, we propose a solution for this problem. We propose a model for the grouping of nodes with respect to network latency. The application scheduling is done on the basis of network latency. This model is a part of our proposed Cloud Scheduler module, which helps the scheduler in scheduling decisions on the basis of different criteria. Network latency and resultant node grouping on the basis of this latency is one of those criteria. The main essence of the paper is that our proposed latency grouping algorithm not only has no additional network traffic overheads for algorithm computation but also works well with incomplete latency information and performs intelligent grouping on the basis of latency. This paper addresses an important problem in cloud computing, which is locating communicating virtual machines for minimum latency between them and group them with respect to inter-node latency.