Wentao Han

ImmortalGraph: A System for Storage and Analysis of Temporal Graphs

Temporal graphs that capture graph changes over time are attracting increasing interest from research communities, for functions such as understanding temporal characteristics of social interactions on a time-evolving social graph. ImmortalGraph is a storage and execution engine designed and optimized specifically for temporal graphs. Locality is at the center of ImmortalGraph’s design: temporal graphs are carefully laid out in both persistent storage and memory, taking into account data locality in both time and graph-structure dimensions. ImmortalGraph introduces the notion of locality-aware batch scheduling in computation, so that common “bulk” operations on temporal graphs are scheduled to maximize the benefit of in-memory data locality. The design of ImmortalGraph explores an interesting interplay among locality, parallelism, and incremental computation in supporting common mining tasks on temporal graphs. The result is a high-performance temporal-graph system that is up to 5 times more efficient than existing database solutions for graph queries. The locality optimizations in ImmortalGraph offer up to an order of magnitude speedup for temporal iterative graph mining compared to a straightforward application of existing graph engines on a series of snapshots.

Weibo, and a Tale of Two Worlds

Weibo is the Twitter counterpart in China that has attracted hundreds of millions of users. We crawled an almost complete Weibo user network that contains 222 million users and 27 billion links in 2013. This paper analyzes the structural properties of this network, and compares it with a Twitter user network. The topological properties we studied include the degree distributions, reciprocity, clustering coefficient, PageRank centrality, and degree assortativity. We find that Weibo users have a higher diversity index, higher Gini index, but a lower reciprocity and clustering coefficient for most of the nodes. A surprising observation is that the reciprocity of Weibo is only about a quarter of the reciprocity of the Twitter user network. We also show that Weibo adoption rate correlates with economic development positively, and Weibo network can be used to quantify the connections between provinces and regions in China. In particular, point-wise mutual information is shown to be accurate in quantifying the strength of connections.

How OpenMP applications get more benefit from many-core era

With the approaching of the many-core era, it becomes more and more difficult for a single OpenMP application to efficiently utilize all the available processor cores. On the other hand, the available cores become more than necessary for some applications. We believe executing multiple OpenMP applications concurrently will be a common usage model in the future. In this model, how threads are scheduled on the cores are important as cores are asymmetric. We have designed and implemented a prototype scheduler, SWOMPS, to help schedule the threads of all the concurrent applications system-widely. The scheduler makes its decision based on underlying hardware configuration as well as the hints of scheduling preference of each application provided by users. Experiment evaluation shows SWOMPS is quite efficient in improving the performance. With the help of SWOMPS, we compared exclusive running one application and concurrent running multiple applications in term of system throughput and individual application performance. In various experimental comparisons, concurrent execution outperforms in throughput, meanwhile the performance slowdown of individual applications in concurrent execution is reasonable.

A comparative analysis on Weibo and Twitter

Weibo is the Twitter counterpart in China that has attracted hundreds of millions of users. We crawled an almost complete Weibo user network that contains 222 million users and 27 billion links in 2013. This paper analyzes the structural properties of this network, and compares it with a Twitter user network. The topological properties we studied include the degree distributions, connected components, distance distributions, reciprocity, clustering coefficient, PageRank centrality, and degree assortativity. We find that Weibo users have a higher diversity index, higher Gini index, but a lower reciprocity and clustering coefficient for most of the nodes. A surprising observation is that the reciprocity of Weibo is only about a quarter of the reciprocity of the Twitter user network. We also show that Weibo adoption rate correlates with economic development positively, and Weibo network can be used to quantify the connections between provinces and regions in China. In particular, point-wise mutual information is shown to be accurate in quantifying the strength of connections. We developed an interactive analyzing software framework for this study, and released the data and code online.

Acolyte: an in-memory social network query system

WISE 2012 Challenge provides a data set crawled from Sina Weibo, which consists of hundreds of millions of anonymized following relationships and microblogs. In the performance track, 19 typical queries on the data set are given. Most of the queries are to get the top n users or microblogs which have the largest statistical numbers of some features during a specific period. The solution should focus on both throughput and latency in the execution of these queries. In this report, we present Acolyte, which is an in-memory query system that can solve the performance track efficiently.

SMILE: streaming management of applications and data for mobile terminals

With the rapid growth of the mobile phone industry in recent years, consumer habits in using mobile applications have changed significantly. Mobile clients have replaced desktop computers as primary internet access devices. However, mobile phones have limited battery life, low processing power, and limited storage capacities. As mobile devices are easily lost or damaged, better data management schemes are also required. In this paper, a streamed application and data management system based on transparent computing technology is proposed to support more secure, better managed mobile phones. Experimental results show that the proposed system is a feasible and efficient solution for future mobile computing applications.