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| Content Provider | ACM Digital Library |
|---|---|
| Author | Gu, Lin Hong, Ke Yang, Shuo |
| Abstract | In the recent decade, datacenters have emerged to play an increasingly important role in cloud-based computing systems. It is shown that wireless sensor networks (sensornets) can provide fine-grained measurement and flexible coverage for the datacenter platform, and help achieve better control and energy efficiency [1]-[3]. In these applications, sensor nodes are only passive information receivers, and the use has so far been limited to auxiliary functions as an intelligent replacement of the traditional wired and embedded sensors. We argue that the combined computational and networking capability of a sensor network enables it to interact with server clusters in a much more sophisticated way and perform essential functions in the datacenter system. We design a technology to incorporating the sensornet as a core part of the datacenter system and improve datacenter management and operations. The sensornet can be easily deployed in a cluster, with sensor nodes attached in an ad hoc manner to the compute servers, and provide key system functions including reprogramming, supplementary authentication, and network signaling. The datacenter administrator can manage a large number of servers through the multihop sensor network, verify the participating servers to be legitimate entities within the datacenter, and improve performance through a low-bandwidth but intelligent wireless network. Our initial results have shown that the system eliminates some of the security problems present in current LAN network based datacenter management system; and that the sensornet provides good physical authentication function without introducing long delays in cluster-wide operations. |
| File Format | |
| ISBN | 9780769546957 |
| DOI | 10.1109/ICCPS.2012.52 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2012-04-17 |
| Access Restriction | Subscribed |
| Content Type | Text |
| Resource Type | Article |
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