An important concern for current IaaS cloud providers is to be falsely accused by cloud users for the response delays of their applications running on the cloud. Since cloud computing brings an additional virtualization layer between guest-OS and hardware resources, the relationship between the performance of an application and its resource consumption becomes obscure. Only monitoring resource consumption (e.g., CPU, memory, disk I/O and so on) is often inadequate to detect the QoS degradation of a deployed application, not to mention resolving cloud users' QoS complaints. In this paper, we introduce a novel single-view performance visualization technique for a cloud platform to monitor the response delays of all the on-line applications running on it. Our technique sniffs network packets from a network switch in the platform and analyzes their flow to estimate the response time of each application. An important merit of this approach is the easy installation into a cloud platform. Concretely, our approach only requires changing the configuration of a network switch to enable port mirroring. To detect and visualize the response delay of each application in a single view, we convert the absolute response time of each application to a comparable value of delay degree ("delay ratio") which shows how serious the response delays compared to its baseline. The baseline is the service time of each application, which we estimate from the distribution of observed response times (service time + waiting time) by adopting an exponentially modified Gaussian (EMG) distribution fitting with an outlier elimination. We validate our approach through extensive experiments of a representative on-line application benchmark (RUBBoS). The results show high repeatability of the service time estimation (the standard deviation of 40 trials is 0.11). The results also show that our performance monitoring technique is able to accurately visualize response delays even when a training set of response times has a heavy-tailed distribution.

Input/output (I/O) devices such as a graphics processing unit and a solid-state drive are inserted into I/O slots of a host in data center platforms. With this sort of configuration the I/O devices are used exclusively by the host with resultant inefficient resource usage. In addition, the maximum number of I/O devices that can be assigned to each host is limited by the number of its I/O slots. This paper proposes a method to solve the resource usage inefficiency and assignment limitation by disaggregating I/O devices from hosts. An I/O device accommodated in a device pool is interconnected with multiple hosts by a standard Ethernet and can be flexibly assigned to one of them. Introducing assignment flexibility of I/O devices among hosts improves the resource usage efficiency and enables as many I/O devices as desired being assigned to each host. The authors further propose a method that enables an I/O device to be simultaneously shared among multiple hosts and multiple I/O packets to be aggregated into an Ethernet frame to suppress the performance overhead of the device disaggregation. Evaluation results showed that I/O devices that are compliant to PCI Express are shared with the overhead up to 27 percent.

Presents a conference poster that covers the following topics: bridge chip; PCIe switch; Ethernet; seamless disaggregated computer; and data center.

In this paper, we propose a simplified multi-path aggregation scheme, Ethernet with flow label for multi-path, called EFL-MP. There are several aggregation schemes, such as link aggregation and multi-path TCP, for multi-path load balancing. However, link aggregation does not distribute a single flow into multiple paths due to its MAC address based flow dispatch. In addition, the multipath TCP scheme is not suitable for implementing into hardware because of the implementation complexity caused by the management of the two stages of sequence number (SEQ) (i.e., the SEQ assigned to a path and the SEQ assigned to the flow); thus it fails to provide high throughput and short latency. To maximize data transfer throughput and minimize latency, we employed a single-stage sequence number scheme with a reorder-buffer-usage-based retransmission activating algorithm. Simulation results show that EFL-MP provides high throughput and short latency despite its simple scheme, and its throughput and its latency suit to use for interconnection transport. In addition, we demonstrate that our proposed retransmission activating algorithm activates retransmission due to packet losses earlier than the conventional timer-based retransmission activating algorithm.