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Cooperative group provisioning with latency guarantees in multi-cloud deployments
Yaw S., Howard E., Mumey B., Wittie M. ACM SIGCOMM Computer Communication Review45 (3):4-11,2015.Type:Article
Date Reviewed: Apr 8 2016

Uninterrupted online user experiences in augmented reality, online gaming, video chatting, and real-time language translation applications require innovative networking approaches. This paper addresses the issue of scheduling the least cost paths in terms of latency.

The authors introduce “the cooperative group provisioning (CGP) problem and show it is NP-hard to approximate within a constant factor.” They develop two algorithms that deal with the CGP. The greedy-k algorithm schedules the least cost path, and the greedy-k churn algorithm removes the offline clients and schedules a new timeslot. For multicast considerations in the greedy-k algorithm, the existing nodes and edges between clients and data centers remain unchanged; however, they modify input graphs and add new intermediate nodes to all inter-data center links. Thus, the authors separate the link into two sublinks, one with no cost and one with the old latency value.

The authors evaluate the effectiveness of the greedy algorithms on networks configured with connectivity and pricing models from Amazon, Microsoft, and Rackspace cloud providers. They randomly sample user locations and relative population sizes of the 100 most populous US cities. The authors simulate the groups of clients for gaming applications with a latency threshold of 80 ms, a group size of 12, and a session duration of 10 minutes. Further, for the groups of clients for video chat applications, they simulate with a latency threshold of 200 ms, a group size of 10, and a session duration that is exponentially distributed. The authors found similar results of churn simulations on the video chat and game groups.

The authors provide liberty in choosing parameters other than latency and total link cost in determining paths and also in using any other shortest path algorithm, which makes this paper worth reading. They further claim that the greedy algorithms can control multicast traffic and reduce latency, which makes them cost effective.

Reviewer:  Lalit Saxena Review #: CR144309 (1606-0404)
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