توضیحات
ABSTRACT
Software Defined Networking (SDN) is a revolutionary network architecture that separates out network control functions from the underlying equipment and is an increasingly trend to help enterprises build more manageable data centers where big data processing emerges as an important part of applications. To concurrently process large-scale data, MapReduce with an open source implementation named Hadoop is proposed. In practical
Hadoop systems one kind of issue that vitally impacts the overall performance is know as the NP-complete minimum make span1 problem. One main solution is to assign tasks on data local nodes to avoid link occupation since network bandwidth is a scarce resource. Many methodologies for enhancing data locality are proposed such as the HDS [1] and state-of-the-art scheduler BAR [2]. However, all of them either ignore allocating tasks in a global view or disregard available bandwidth as the basis for scheduling. In this paper we propose a heuristic bandwidth-aware
task scheduler BASS to combine Hadoop with SDN. It is not only able to guarantee data locality in a global view but also can efficiently assign tasks in an optimized way. Both examples and experiments demonstrate that BASS has the best performance in terms of job completion time. To our knowledge, BASS is the first to exploit talent of SDN for big data processing and we believe it points out a new trend for large-scale data processing
INTRODUCTION
Software Defined Networking (SDN)2 is a revolutionary network architecture that separates out network control functions from the underlying equipment and deploys them centrally on the controller, where OpenFlow is the standard interface. With SDN, applications can treat the network as a logical entity which makes enterprises and carriers gain unprecedented programmability, automation and network control. In addition, SDN also provides a set of APIs to simplify the implementation of common network services such as routing, multicast, security, access control, bandwidth management, quality of service (QoS) and storage optimization etc [3]. As a result, SDN creates amounts of opportunities to help enterprises build more deterministic, innovative, manageable and high scalable data centers that extend beyond private enterprise networks to public IT resources, which makes implementing OpenFlow based SDN data centers become a new developing trend nowadays. At the same time, big data
Year : 2014
Publisher : apache
By : Peng Qin, Bin Dai, Benxiong Huang and Guan Xu
File Information : English Language / 8 Page /Size : 276 K
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سال : 2014
ناشر : apache
کاری از : Peng Qin, Bin Dai, Benxiong Huang and Guan Xu
اطلاعات فایل : زبان انگلیسی /8 صفحه / حجم : 276 K
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