[Eecs-news-links] FW: CIS Colloquium, Faculty Candidate - Tuesday, June 7, 2016 @ 3:30pm in 220 Deschutes Hall

Batten, Tina tina.batten at oregonstate.edu
Mon Jun 6 08:44:14 PDT 2016

-----Original Message-----
From: Adriane Bolliger [mailto:adriane at cs.uoregon.edu] 
Sent: Monday, June 06, 2016 8:30 AM
To: colloquia at cs.uoregon.edu; dept at cs.uoregon.edu; grads-mail at cs.uoregon.edu
Subject: CIS Colloquium, Faculty Candidate - Tuesday, June 7, 2016 @ 3:30pm in 220 Deschutes Hall

*** Please note that this talk take place on TUESDAY, June 7 ***


Optimizing Cloud Resource Allocation and Reconfiguration

Lei Jiao 
Nokia Bell Labs, Ireland


Resource allocation and reconfiguration is fundamental in cloud computing, and becomes more challenging as cloud services and architectures continue to evolve wit​h ​complexities. In the service aspect, online social networks are popular, and allocating storage for users​' data over multiple clouds needs to address the interconnection of users,​ ​the master-slave data replication, the conflicting requirements of different objectives, as well as the diversity of multi-cloud data access policies. In the architecture aspect, the​ ​emerging edge-core tiered structure of distributed clouds complicates the allocation of resources such as virtual machines and servers, due to the reconfiguration cost associated​ ​to changing resource allocation decisions over time, the often unpredictable service demands and resource prices, as well as the heterogeneity of resources.

In this talk, I will introduce our work on exploiting optimization to solve these two problems​,​ while addressing all the aforementioned challenges. The first problem is a large-scale​ ​combinatorial optimization problem regarding social network data placement over clouds, potentially with multiple system objectives such as carbon footprint, latency, and​ ​inter-​cloud traffic. We propose to decompose it into two sub-problems of placing master data replicas and slave data replicas respectively, where we leverage the graph cuts technique​ ​to solve the master placement problem, use a greedy method to place the slaves, and solve the two sub-problems alternately in multiple rounds. The second problem is an online​ ​optimization problem regarding cloud and network resource allocation over time ​to process dynamic workloads ​in a tiered infrastructure, where a resource allocation decision needs to be​ ​made on the fly without knowing the entire inputs over the time horizon. With​ no​ knowledge of future inputs, we leverage the regularization technique to design an online algorithm​ ​that decomposes the original problem by constructing a series of sub-problems solvable at each corresponding time slot, with provable worst-case​ ​performance​ ​guarantee​s​. Experiments with real-world data traces confirm that our approaches have substantial advantages over the state of the arts.


Lei​ Jiao is a post-doctoral ​​researcher​ at Nokia Bell Labs in Dublin, Ireland​. ​​His research interests are broadly in theories and algorithms (e.g.,​ ​optimization, control, game​ ​theory), with a focus on modeling, analyzing, and solving real-world problems in distributed and networked systems.​ ​His research appeared in conferences such as IEEE INFOCOM, ICNP, IPDPS, and in journals such as IEEE/ACM Transactions on Networking. He was also a recipient of the Best Paper Award in IEEE LANMAN 2013. He​ received ​the​ Ph.D.​ ​degree in computer science from University of ​​Gö​ttingen in G​ö​ttingen, Germany in 2014. ​Prior to ​his Ph.D. study, ​he​ was a ​​researcher​ ​at IBM Research in Beijing, China.

DATE:	Tuesday, June 7, 2016 
TIME:	3:30 p.m. talk, refreshments following talk
PLACE:	220 Deschutes Hall (Colloquium Room), University of Oregon

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