Latest Articles

## On the Endurance of the d-Choices Garbage Collection Algorithm for Flash-Based SSDs

Garbage collection (GC) algorithms for flash-based solid-state drives (SSDs) have a profound impact on its performance and many studies have focused... (more)

##### NEWS

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (ToMPECS) is a new ACM journal that publishes refereed articles on all aspects of the modeling, analysis, and performance evaluation of computing and communication systems.

The target areas for the application of these performance evaluation methodologies are broad, and include traditional areas such as computer networks, computer systems, storage systems, telecommunication networks, and Web-based systems, as well as new areas such as data centers, green computing/communications, energy grid networks, and on-line social networks.

Issues of the journal will be published on a quarterly basis, appearing both in print form and in the ACM Digital Library.

##### Forthcoming Articles
Packet Clustering Introduced by Routers: Modeling, Analysis and Experiments

In this paper, we investigate routers inherent variation on packet processing time and its effect on interpacket delay and packet clustering.We propose a simple pipeline model incorporating the inherent variation, and two metrics, one to measure packet clustering and one to quantify inherent variation. To isolate the effect of the inherent variation, we begin our analysis with no cross traffic and step through setups where the input streams have different data rate, packet size and go through different number of hops. We show that a homogeneous input stream with a sufficiently large interpacket gap will emerge at the routers output with interpacket delays that are negative correlated with adjacent values and have symmetrical distributions. We show that for smaller interpacket gaps, the change in packet clustering is smaller. It is also shown that the degree of packet clustering could in fact decrease for a clustered input. We generalize our results by adding cross traffic. All the results predicted by the model are validated with experiments with real routers. We also discussed several factors that can affect the inherent variation as well as some potential applications of this study.

Scheduling for Optimal File Transfer Delay using Chunked Random Linear Network Coding Broadcast

We study the broadcast transmission of a single file to an arbitrary number of receivers using Random Linear Network Coding (RLNC) in a network with unreliable channels. Due to the increased computational complexity of the decoding process (especially for large files) we apply chunked RLNC (i.e. RLNC is applied within non-overlapping subsets of the file). In our work we show the optimality of the Least Received (LR) batch scheduling policy with regards to the expected file transfer completion time. The $LR$ policy strives to keep the receiver queues balanced. This is done by transmitting packets (corresponding to \textit{encoded} batches) that are needed by the receivers with the shortest queues of successfully received packets. Furthermore, we provide formulas for the expected time for the file transmission to all receivers using the LR batch scheduling policy and the minimum achievable coding window size in the case of a pre-defined delay constraint. Moreover, we evaluate through simulations a modification of the LR policy in a more realistic system setting with reduced feedback from the receivers. Finally, we provide an initial analysis and further modifications to the $LR$ policy for time-correlated channels and asymmetric channels.

Generalization of LRU Cache Replacement Policy with Applications to Video Streaming

Caching plays a crucial role in networking systems to reduce the load on the network and has become an ubiquitous functionality available at each router. One of the commonly used mechanisms, Least Recently Used (LRU), works well for identical file sizes. However, for asymmetric file sizes, the performance deteriorates. This paper proposes an adaptation to LRU strategy, called gLRU, where the file is sub-divided into equal-sized chunks. In this strategy, a chunk of the newly requested file is added in the cache, and a chunk of the least-recently-used file is removed from the cache. Even though approximate analysis for the hit rate has been studied for LRU, the analysis does not extend to gLRU since the metric of interest is no longer the hit rate as the cache has partial files. This paper provides a novel approximation analysis for this policy where the cache may have partial file contents. The approximation approach is validated by simulations. Further, gLRU outperforms LRU strategy for Zipf file popularity distribution and censored Pareto file size distribution for the file download times. Video streaming applications can further use the partial cache contents to help the stall durations significantly, and the numerical results indicate significant improvements (29\%) in stall durations using the gLRU strategy as compared to the LRU strategy.

A New Framework for Evaluating Straggler Detection Mechanisms in MapReduce