Model Problem: Znn.com

by Shang-Wen Cheng and Bradley Schmerl.

Description

Based on real sites like cnn.com and RockyMountainNews.com, Znn.com is a news service that serves multimedia news content to its customers. Architecturally, Znn.com is a web-based client-server system that conforms to an N-tier style. As illustrated in the figure below, Znn.com uses a load balancer to balance requests across a pool of replicated servers, the size of which is dynamically adjusted to balance server utilization against service response time. A set of client processes (represented by the C component) makes stateless content requests to one of the servers. Let us assume we can monitor the system for information such as server load and the bandwidth of server-client connections. Assume further that we can modify the system, for instance, to add more servers to the pool or to change the quality of the content. We want to add self-adaptation capabilities that will take advantage of the monitored system and adapt the system to fulfill Znn.com objectives.

ZnnCom

The business objectives at Znn.com are to serve news content to its customers within a reasonable response time range while keeping the cost of the server pool within its operating budget. From time to time, due to highly popular events, Znn.com experiences spikes in news requests that it cannot serve adequately, even at maximum pool size. To prevent unacceptable latencies, Znn.com opts to serve minimalist textual content during such peak times in lieu of providing its customers zero service. The Znn.com system administrators (sys-admins) adapt the system using two actions: adjust the server pool size or switch content mode. When the system comes under high load, the sys-admins may increase the server pool size until a cost-determined maximum is reached, at which point the sys-admin would switch the servers to serve textual content. If the system load drops, the sys-admin may switch the servers back to multimedia mode to make customers happy in combination with reducing the pool size to reduce operating cost.

The adaptation decision is determined by observations of overall average response time versus server load. Specifically, four adaptations are possible, and the choice depends not only on the conditions of the system, but also on business objectives:

  1. Switch the server content mode from multimedia to textual
  2. Switch the server content mode from textual to multimedia
  3. Increment the server pool size, and 
  4. Decrement the server pool size

We want to help Znn.com automate system management to adjust the server pool size vs. switch content between multimedia and textual modes. In reality, a news site like cnn.com already supports some level of automated adaptation. However, automating decisions that trade off multiple objectives to adapt a system is still unsupported in most systems today. For instance, while automating adaptations on performance concerns is possible (e.g., load balancing), it is much harder to do so for potentially conflicting qualities such as performance and security. This work is an important step in that direction: to allow automation of adaptations that must strike a balance between multiple objectives.

Relevance: Slashdot Effect

The motivation for the Znn.com instantiation comes from an Internet phenomenon known as the Slashdot effect, where an otherwise low-traffic website, shortly after being featured on slashdot.org, gets inundated with visitors for a period of time, anywhere from a few hours to a couple days [Ter04]. Now a common term, it describes a similar phenomenon where a website experiences a sudden, unanticipated rise in requests due to a popular event (or sometimes, anticipated, but not to the scale observed), for example, breaking news or superbowl craze [Wik08d]. To illustrate a few instances, on the morning of August 17, 2006, a break in the JonBenet Ramsey case resulted in a local news website, rockymountainnews.com, being swamped by news readers. Browsing the site at 10:18 AM took more than 2 minutes to retrieve a blank page with only the local weather showing in the corner. On September 4, 2006, the shocking death of Steve “Crocodile Hunter” Irwin caused the Australian Broadcasting Corp website to be temporarily shut down; similarly, numerous other news sites groaned to a halt. Of note is that Australian Broadcasting Corp’s site resumed a few hours later with a low-bandwidth format to cope with the high traffic [Tai06]. A more problematic, revenue-losing case arises when an e-commerce site is shut down by the Slashdot-like effect, as exemplified by Wal-Mart’s shopping site on Black Friday 2006, which remained inaccessible into the afternoon after the initial morning rush [San06, Sch06]. The Australian Broadcasting Corp illustrates the present coping mechanism of most website administrators to the Slashdot effect. When they first notice a sudden rise in visit requests, they make a decision to temporarily shut down the site for manual reconfiguration, where usually entails resorting to lower fidelity content. In extreme cases, the site might temporarily shut down or simply post a notice to “visit later.” There are a number of disadvantages with this scheme:

  • The problem may not be discovered in time;
  • The manual process means slower response time;
  • The chosen solution may be suboptimal; and
  • It may result in a potential loss of confidence, revenue, or future business.

An ideal approach would be to achieve site adaptation automatically, and our aim is to demonstrate such self-adaptation with the Znn.com instantiation. It is worth noting that a few modern systems with sophisticated infrastructures, such as Google Gmail, have equipped themselves with similar but limited adaptation capabilities, for example, to instruct its users to “reload in a few seconds” when it detects a sudden peak or other underlying connectivity issues to its servers.

Adaptation Challenges

A typical news content service such as Znn.com needs to serve content to its customers within a reasonable response time range while keeping the cost of the server pool within a certain operating budget. In normal operating circumstances, the appropriate trade-offs can be made at design-time. However, from time to time, due to highly popular events, Znn.com experiences spikes in news requests that are not within the originally designed parameters. This means that it cannot serve the clients adequately (i.e., clients will not receive content in a timely manner). To the client, the site will appear to be down, and customers will go elsewhere, resulting in lost revenue.

The challenge for self-adaptation is to be able to still provide content at these peak times. There are several ways to deal with this, such as serving minimalist content, increasing the number of servers serving content, redirecting to alternative sites, choosing to prioritize serving clients to paying customers.

In this exemplar, there are currently three runtime parameters than can be adjusted to adapt the system dynamically:

  • Performance
  • Cost
  • Content Fidelity

Znn System Download and Setup

Znn can be set up by a virtual machine model for deployment. The Open Virtualization Archive file contains a base Debian system and all the web, configuration, and script files for Znn to run the various aspects of Znn.

The ZNN Exemplar system at GitHub

Solutions

  • Rainbow
    The Rainbow solution to self-adaptation uses architecture-based techniques combined with control and utility theories. The observed properties of an executing system are reflected in an architecture model. Leveraging existing work on architectural analyses, the architecture model enables automatic reasoning about appropriate changes to the target system to improve quality-of-service, using utility theory to analyze trade-offs across the quality dimensions. The changes are effected in the system, and the effects re-observed in a closed-loop of control.

Related Problems

No related exemplars so far.

References

to be completed.