ALFE: A replacement policy to cache elephant flows in the presence of mice flooding

Pan, Tian; Guo, Xiaoyu; Zhang, Chenhui; Meng, Weiyi; Liu, Bin

doi:10.1109/icc.2012.6364403

Cited by 15 publications

(5 citation statements)

References 7 publications

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“…5. The results verify the conclusion on the traffic mice and elephants, which are presented in [28]. Although there are many clusters, only several clusters occupy most of the traffic volumes.…”

Section: B Analysis Of Traffic Volumes Of Per Cluster Holdssupporting

confidence: 89%

MUCM: Multilevel User Cluster Mining Based on Behavior Profiles for Network Monitoring

Qin

Guan

Wang

et al. 2015

IEEE Systems Journal

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Mastering user's behavior character is important for efficient network management and security monitoring. In this paper, we develop a novel framework named as multilevel user cluster mining (MUCM) to measure user's behavior similarity under different network prefix levels. Focusing on aggregated traffic behavior under different network prefixes cannot only reduce the number of traffic flows but also reveal detailed patterns for a group of users sharing similar behaviors. First, we employ the bidirectional flow and bipartite graphs to model network traffic characteristics in large-scale networks. Four traffic features are then extracted to characterize the user's behavior profiles. Second, an efficient method with adjustable weight factors is employed to calculate the user's behavior similarity, and entropy gain is applied to select the weight factor adaptively. Using the behavior similarity metrics, a simple clustering algorithm based on k-means is employed to perform user clustering based on behavior profiles. Finally, we examine the applications of behavior clustering in profiling network traffic patterns and detecting anomalous behaviors. The efficiency of our methods is verified with extensive experiments using actual traffic traces collected from the northwest region center of China Education and Research Network (CERNET), and the cluster results can be used for flow control and traffic security monitoring.Index Terms-Behavior profiles, different prefix levels, regional flow model, user clustering.

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Section: B Analysis Of Traffic Volumes Of Per Cluster Holdssupporting

confidence: 89%

MUCM: Multilevel User Cluster Mining Based on Behavior Profiles for Network Monitoring

Qin

Guan

Wang

et al. 2015

IEEE Systems Journal

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“…Memory management techniques in traditional switch design can be extended to optimize the SDN switch design for rule storage in order to reduce memory usage and use the limited [65], [66]. Route aggregation or summarization can reduce the memory usage by aggregating several routing records with a common routing prefix to a single new routing record with the common prefix.…”

Section: A Switching Devicesmentioning

confidence: 99%

A Survey on Software-Defined Networking

Wei

Wen

Foh

et al. 2015

IEEE Commun. Surv. Tutorials

914

361

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Emerging mega-trends (e.g., mobile, social, cloud, and big data) in information and communication technologies (ICT) are commanding new challenges to future Internet, for which ubiquitous accessibility, high bandwidth, and dynamic management are crucial. However, traditional approaches based on manual configuration of proprietary devices are cumbersome and error-prone, and they cannot fully utilize the capability of physical network infrastructure. Recently, software-defined networking (SDN) has been touted as one of the most promising solutions for future Internet. SDN is characterized by its two distinguished features, including decoupling the control plane from the data plane and providing programmability for network application development. As a result, SDN is positioned to provide more efficient configuration, better performance, and higher flexibility to accommodate innovative network designs. This paper surveys latest developments in this active research area of SDN. We first present a generally accepted definition for SDN with the aforementioned two characteristic features and potential benefits of SDN. We then dwell on its three-layer architecture, including an infrastructure layer, a control layer, and an application layer, and substantiate each layer with existing research efforts and its related research areas. We follow that with an overview of the de facto SDN implementation (i.e., OpenFlow). Finally, we conclude this survey paper with some suggested open research challenges.

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“…However, the elephant flows (huge flows) over the network can be handled using an efficient cache mechanism to prevent the overflow of massive mice flows (tiny flows). Pan et al 144 computed a solution by designing an optimal flow cache policy named Adaptive Least Frequently Evicted (ALFE). The proposed approach is compared with the least recently used (LRU) cache placement policy and is tested over 1000 cache entries.…”

Section: Fault Tolerance In Iotmentioning

confidence: 99%

A comprehensive survey on software‐defined networking for smart communities

Chaudhary

Aujla

Kumar

et al. 2022

Int J Communication

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The need to provide services closer to the end-user proximity leads to the exchange of a large volume of data generated from the smart devices deployed at different geo-distributed sites. The massive amount of data generated from the smart devices need to be transmitted, analyzed, and processed. This requires seamless data exchanges among geo-separated nodes, which results in a considerable burden on the underlying network infrastructure and can degrade the performance of any implemented solution. Therefore, a dynamic, agile, and programmable network management paradigm is required. To handle the challenges mentioned above, software-defined networking (SDN) gained much attention from academia, researchers, and industrial sectors.Shifting the computational load from forwarding devices to a logically centralized controller is a dream of every network operator who wants to have complete control and global visibility of the network. Also, the concept of network functions virtualization (NFV) in SDN controller is required to increase resource utilization efficiency. Thus, in this paper, a comprehensive survey on SDN for various smart applications is presented. This survey covers the infrastructural details of SDN hardware and OpenFlow switches, controllers, simulation tools, programming languages, open issues, and challenges in SDN implementation with advanced technologies such as 5G and microservices. In addition, the challenges on the control plane and data plane are highlighted in detail, such as fault tolerance, routing, scheduling of flows, and energy consumption on OpenFlow switches. Finally, various open issues and challenges future scope of SDN are discussed and analyzed in the proposal.

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ALFE: A replacement policy to cache elephant flows in the presence of mice flooding

Cited by 15 publications

References 7 publications

MUCM: Multilevel User Cluster Mining Based on Behavior Profiles for Network Monitoring

MUCM: Multilevel User Cluster Mining Based on Behavior Profiles for Network Monitoring

A Survey on Software-Defined Networking

A comprehensive survey on software‐defined networking for smart communities

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