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Distributed Caching Algorithms for Content Distribution Networks
TLDR
This paper develops light-weight cooperative cache management algorithms aimed at maximizing the traffic volume served from cache and minimizing the bandwidth cost, and establishes that the performance of the proposed algorithms is guaranteed to be within a constant factor from the globally optimal performance.
Robust and flexible power-proportional storage
TLDR
Rabbit is a distributed file system that arranges its data-layout to provide ideal power-proportionality down to very low minimum number of powered-up nodes (enough to store a primary replica of available datasets).
On the inapproximability of M/G/K: why two moments of job size distribution are not enough
The M/G/K queueing system is one of the oldest models for multiserver systems and has been the topic of performance papers for almost half a century. However, even now, only coarse approximations
Sampling Strategies for Epidemic-Style Information Dissemination
TLDR
This paper identifies the minimum number of samplings needed to reach a target fraction of hosts, assuming global information about the host distribution over subnets is available and shows that this optimum can be achieved by a dynamic strategy, or, surprisingly, even by a static strategy, for which the sampling probabilities overSubnets are fixed.
Self-adaptive admission control policies for resource-sharing systems
TLDR
This paper abstracts resource sharing systems as a Processor Sharing server with state-dependent service rate and a First-Come-First-Served queue, and presents two traffic-oblivious dynamic admission control policies that adjust the MPL based on the instantaneous queue length while also taking into account the variability of the job size distribution.
On the Optimal Design of a Bipartite Matching Queueing System
TLDR
This work considers a multi-class multi-server queueing system and proposes a mixed-integer linear program (MILP) that can be used to find the set of matching topologies that define the Pareto frontier of reward-delay pairs.
On the Compatibility of Privacy and Fairness
TLDR
This work investigates whether privacy and fairness can be simultaneously achieved by a single classifier in several different models and gives an efficient algorithm for classification that maintains utility and satisfies both privacy and approximate fairness with high probability.
Stability of the bipartite matching model
TLDR
It is proved that the Stability of the bipartite model is implied by the stability of the associate fluid limits, and this result is used to establish maximal stability region for the FIFO matching policy.
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