arXiv subjects

Yuquan Shan

Publications and source records attributed to Yuquan Shan.

6 recordsLinked to original sources

arXiv2018

Scheduling Distributed Resources in Heterogeneous Private Clouds

We first consider the static problem of allocating resources to ( i.e. , scheduling) multiple distributed application framework s, possibly with different priorities and server preferences , in a private cloud with heterogeneous servers. Several fai r scheduling mechanisms have been proposed for this purpose. We extend pr ior results on max-min and proportional fair scheduling to t his constrained multiresource and multiserver case for generi c fair scheduling criteria. The task efficiencies (a metric r elated to proportional fairness) of max-min fair allocations found b y progressive filling are compared by illustrative examples . They show that "server specific" fairness criteria and those that are b ased on residual (unreserved) resources are more efficient.

cs.PF↗

arXiv2018

Heterogeneous MacroTasking (HeMT) for Parallel Processing in the Public Cloud

Using tiny, equal-sized tasks (Homogeneous microTasking, HomT) has long been regarded an effective way of load balancing in parallel computing systems. When combined with nodes pulling in work upon becoming idle, HomT has the desirable property of automatically adapting its load distribution to the processing capacities of participating nodes - more powerful nodes finish their work sooner and, therefore, pull in additional work faster. As a result, HomT is deemed especially desirable in settings with heterogeneous (and possibly possessing dynamically changing) processing capacities. However, HomT does have additional scheduling and I/O overheads that might make this load balancing scheme costly in some scenarios. In this paper, we first analyze these advantages and disadvantages of HomT. We then propose an alternative load balancing scheme - Heterogeneous MacroTasking (HeMT) - wherein workload is intentionally partitioned according to nodes' processing capacity. Our goal is to study when HeMT is able to overcome the performance disadvantages of HomT. We implement a prototype of HeMT within the Apache Spark application framework with complementary enhancements to the Apache Mesos cluster manager. Spark's built-in scheduler, when parameterized appropriately, implements HomT. Our experimental results show that HeMT out-performs HomT when accurate workload-specific estimates of nodes' processing capacities are learned. As representative results, Spark with HeMT offers about 10% better average completion times for realistic data processing workloads over the default system.

cs.PF↗

arXiv2018

Moving-target Defense against Botnet Reconnaissance and an Adversarial Coupon-Collection Model

We consider a cloud based multiserver system consisting of a set of replica application servers behind a set of proxy (indirection) servers which interact directly with clients over the Internet. We study a proactive moving-target defense to thwart a DDoS attacker's reconnaissance phase and consequently reduce the attack's impact. The defense is effectively a moving-target (motag) technique in which the proxies dynamically change. The system is evaluated using an AWS prototype of HTTP redirection and by numerical evaluations of an adversarial coupon-collector mathematical model, the latter allowing larger-scale extrapolations.

cs.CR↗

arXiv2018

Online Scheduling of Spark Workloads with Mesos using Different Fair Allocation Algorithms

In the following, we present example illustrative and experimental results comparing fair schedulers allocating resources from multiple servers to distributed application frameworks. Resources are allocated so that at least one resource is exhausted in every server. Schedulers considered include DRF (DRFH) and Best-Fit DRF (BF-DRF), TSF, and PS-DSF. We also consider server selection under Randomized Round Robin (RRR) and based on their residual (unreserved) resources. In the following, we consider cases with frameworks of equal priority and without server-preference constraints. We first give typical results of a illustrative numerical study and then give typical results of a study involving Spark workloads on Mesos which we have modified and open-sourced to prototype different schedulers.

cs.PF↗

arXiv2017

Numerical Evaluation of Cloud-Side Shuffling Defenses against DDoS Attacks on Proxied Multiserver Systems

We consider a cloud based multiserver system, that may be cloud based, consisting of a set of replica application servers behind a set of proxy (indirection) servers which interact directly with clients over the Internet. We address cloud-side proactive and reactive defenses to combat DDoS attacks that may target this system. DDoS attacks are endemic with some notable attacks occurring just this past fall. Volumetric attacks may target proxies while "low volume" attacks may target replicas. After reviewing existing and proposed defenses, such as changing proxy IP addresses (a "moving target" technique to combat the reconnaissance phase of the botnet) and fission of overloaded servers, we focus on evaluation of defenses based on shuffling client-to-server assignments that can be both proactive and reactive to a DDoS attack. Our evaluations are based on a binomial distribution model that well agrees with simulations and preliminary experiments on a prototype that is also described.

cs.CR↗

arXiv2014

Generation bidding game with flexible demand

For a simple model of price-responsive demand, we consider a deregulated electricity marketplace wherein the grid (ISO, retailer-distributor) accepts bids per-unit supply from generators (simplified herein neither to consider start-up/ramp-up expenses nor day-ahead or shorter-term load following) which are then averaged (by supply allocations via an economic dispatch) to a common "clearing" price borne by customers (irrespective of variations in transmission/distribution or generation prices), i.e., the ISO does not compensate generators based on their marginal costs. Rather, the ISO provides sufficient information for generators to sensibly adjust their bids. Notwithstanding our idealizations, the dispatch dynamics are complex. For a simple benchmark power system, we find a price-symmetric Nash equilibrium through numerical experiments.

cs.GT↗