Workload-aware request routing in cloud data center using software-defined networking

  title={Workload-aware request routing in cloud data center using software-defined networking},
  author={Haitao Yuan and Jing Bi and Bo Hu Li},
  journal={Journal of Systems Engineering and Electronics},
  • Haitao Yuan, J. Bi, B. Li
  • Published 20 March 2015
  • Computer Science
  • Journal of Systems Engineering and Electronics
Large latency of applications will bring revenue loss to cloud infrastructure providers in cloud data center. The ex- isting controllers of software-defined networking architecture can fetch and process traffic information in network. Therefore, the controllers can only optimize the network latency of applications. However, the serving latency of applications is also an important factor in delivered user-experience for arrival requests. Unintel- ligent request routing will cause large serving… 

WARM: Workload-Aware Multi-Application Task Scheduling for Revenue Maximization in SDN-Based Cloud Data Center

A workload-aware revenue maximization approach to maximize the revenue from a data center provider’s perspective is presented and the results show that WARM yields the best schedules that not only increase the revenue but also reduce the round-trip time of tasks for all applications.

Revenue-sensitive scheduling of multi-application tasks in software-defined cloud

Simulation based on real-life task data demonstrates that compared with several current algorithms, RSMT can produce the efficient schedules that increase the cloud provider's revenue and decrease round trip time of multi-application tasks.

Ferrying vehicular data in cloud through software defined networking

  • P. SahooY. Yunhasnawa
  • Computer Science
    2016 IEEE 12th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)
  • 2016
Data transmission time is computed when vehicular data is transmitted to the cloud though the road side units and OpenFlow switches in a Software Defined Network (SDN).

Migration and Integration Strategy of Virtual Machines in Cloud Data Center Based on HPGA

By combining the advantages of FFD and PGA, this paper improves the utilization of the resources of the entire cloud data center, reduces energy consumption, and prevents the occurrence of computing “hot spots”.

Software-Defined Networking for Internet of Things: A Survey

A comprehensive survey of different SDN-based technologies, which are useful to fulfill the requirements of IoT, from different networking aspects—edge, access, core, and data center networking.

Security Challenges in Software Engineering for the Cloud: A Systematic Review

A systematic review of articles in the area of software engineering security challenges on the cloud examines articles that were published between 2014 and 2019, and includes cloud models of service delivery, access control, harm detection, and integrity.

Review and Analysis of Information Security Issues in Data Exchange and Management of a Virtualized Environment of Remote Data Processing Centers

The article deals with issues related to information security when exchanging data and managing a virtualized environment of remote data processing centers. As of today, it has become clear, that



Improving the Scalability of Data Center Networks with Traffic-aware Virtual Machine Placement

This paper designs a two-tier approximate algorithm that efficiently solves the VM placement problem for very large problem sizes and shows a significant performance improvement compared to existing general methods that do not take advantage of traffic patterns and data center network characteristics.

DR2: Dynamic Request Routing for Tolerating Latency Variability in Online Cloud Applications

This paper proposes a dynamic request routing framework, DR2, by taking full advantage of redundant components in the clouds to tolerate latency variability, and finds that many functionally-equivalent components have been already deployed redundant for load balancing and fault tolerance, thus resulting in low additional overhead for DR2.

Schedule first, manage later: Network-aware load balancing

This work proposes a novel scheme that incurs no communication overhead between the users and the servers upon job arrival, thus removing any scheduling overhead from the job's critical path, and shows that this scheme improves the expected queuing overhead over traditional schemes by a factor of 9 (or more) under various load conditions.

The Impact of Virtualization on Network Performance of Amazon EC2 Data Center

The results show that even though the data center network is lightly utilized, virtualization can still cause significant throughput instability and abnormal delay variations.

Traffic engineering in software defined networks

It is shown how to leverage the centralized controller to get significant improvements in network utilization as well as to reduce packet losses and delays and it is shown that these improvements are possible even in cases where there is only a partial deployment of SDN capability in a network.

CARPO: Correlation-aware power optimization in data center networks

CARPO is a correlation-aware power optimization algorithm that dynamically consolidates traffic flows onto a small set of links and switches in a DCN and then shuts down unused network devices for energy savings and integrates traffic consolidation with link rate adaptation for maximized energy savings.

Dynamic Provisioning Modeling for Virtualized Multi-tier Applications in Cloud Data Center

A novel dynamic provisioning technique for a cluster-based virtualized multi-tier application that employ a flexible hybrid queueing model to determine the number of virtual machines at each tier in a virtualized application is presented.

Achieving high utilization with software-driven WAN

A novel technique is developed that leverages a small amount of scratch capacity on links to apply updates in a provably congestion-free manner, without making any assumptions about the order and timing of updates at individual switches.

Network traffic characteristics of data centers in the wild

An empirical study of the network traffic in 10 data centers belonging to three different categories, including university, enterprise campus, and cloud data centers, which includes not only data centers employed by large online service providers offering Internet-facing applications but also data centers used to host data-intensive (MapReduce style) applications.

Longer Is Better: Exploiting Path Diversity in Data Center Networks

This paper presents the Baatdaat flow scheduling algorithm which uses spare DC network capacity to mitigate the performance degradation of heavily utilized links and achieves close to optimal Traffic Engineering by reducing network-wide maximum link utilization by up to 18% over Equal-Cost Multi-Path (ECMP) routing.