Browsing by Author "Lu, Sung-Jer"

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EagleEye: Towards Mandatory Security Monitoring in Virtualized Datacenter Environment
(2013)
Wu, Yu-Sung
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Sun, Pei-Keng
;
Huang, Chun-Chi
;
Lu, Sung-Jer
;
Lai, Syu-Fang
Virtualized datacenter (VDC) has become a popular approach to large-scale system consolidation and the enabling technology for infrastructure-as-a-service cloud computing. The consolidation inevitably aggregates the security threats once faced by individual systems towards a VDC, and a VDC operator should remain vigilant of the threats at all times. We envision the need for on-demand mandatory security monitoring of critical guest systems as a means to track and deter security threats that could jeopardize the operation of a VDC. Unfortunately, existing VDC security monitoring mechanisms all require pre-installed guest components to operate. The security monitoring would either be up to the discretion of individual tenants or require costly direct management of guest systems by the VDC operator. We propose the EagleEye approach for on-demand mandatory security monitoring in VDC environment, which does not depend on pre-installed guest components. We implement a prototype on-access anti-virus monitor to demonstrate the feasibility of the EagleEye approach. We also identify challenges particular to this approach, and provide a set of solutions meant to strengthen future research in this area.
Network Performance Bottleneck Detection and Maximum Network Throughput Estimation for Datacenter Applications
(2016)
Ngai, Patrick
;
Lu, Sung-Jer
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Wu, Yu-Sung
;
Lim, Wei-Sheng
;
Lin, Tung-Yueh
For applications deployed in third-party datacenter environments to attain cost-effective performance, it requires precise provisioning of hardware resources such as assigning appropriate network bandwidth to an application. However, it is not always clear how much resource should be assigned to an application. In this work, we propose NBD (Network performance Bottleneck Detector) to detect the network bandwidth requirement of a datacenter application. NBD is fully transparent and does not require modification of applications. It correctly reports the required bandwidth of an application even when the preset network bandwidth is far below the required bandwidth. NBD employs a novel technique called network flow distortion for the estimation of application network bandwidth requirement. The evaluation results indicate that NBD is effective and only incurs mild performance overhead.