Maiter: An Asynchronous Graph Processing Framework for Delta-based Accumulative Iterative Computation

Myriad of graph-based algorithms in machine learning and data mining require parsing relational data iteratively. These algorithms are implemented in a large-scale distributed environment in order to scale to massive data sets. To accelerate these large-scale graph-based iterative computations, we propose delta-based accumulative iterative computation (DAIC). Different from traditional iterative computations, which iteratively update the result based on the result from the previous iteration, DAIC updates the result by accumulating the "changes" between iterations. By DAIC, we can process only the "changes" to avoid the negligible updates. Furthermore, we can perform DAIC asynchronously to bypass the high-cost synchronous barriers in heterogeneous distributed environments. Based on the DAIC model, we design and implement an asynchronous graph processing framework, Maiter. We evaluate Maiter on local cluster as well as on Amazon EC2 Cloud. The results show that Maiter achieves as much as 60x speedup over Hadoop and outperforms other state-of-the-art frameworks.Comment: ScienceCloud 2012, TKDE 201

Quantifying AS Path Inflation by Routing Policies

A route in the Internet may take a longer AS path than the shortest AS path due to routing policies. In this paper, we systematically analyze AS paths and quantify the extent to which routing policies inflate AS paths. The results show that AS path inflation in the Internet is more prevalent than expected. We first present the extent of AS path inflation observed from the RouteView and RIPE routing tables. We then employ three common routing policies to show the extent of AS path inflation. We find that No-Valley routing policy causes the least AS path inflation among the three routing policies. PreferCustomer-and-Peer-over-Provider policy causes the most AS path inflation. In addition, we find that single-homed stub ASes experience more path inflations than transit ASes and multi-homed ASes. The AS pairs with shortest AS path of 3 AS hops experience more path inflations than other AS pairs. Finally, we investigate the AS path inflation on the end-to-end path from end users to two popular content providers, Google and Comcast. Although the majority of the shortest AS paths from end users to the two providers consists of no more than three AS hops, the actual end-to-end paths that the traffic will take are longer than the shortest AS paths in many cases. Quantifying AS path inflation in the Internet has important implications on the extent of routing policies, traffic engineering performed on the Internet, and BGP convergence speed

Impact of autologous platelet-rich plasma therapy vs. hyaluronic acid on synovial fluid biomarkers in knee osteoarthritis: a randomized controlled clinical trial

ObjectiveObserve the effects of platelet-rich plasma (PRP) therapy on inflammatory cytokines in the synovial fluid of the knee joint of patients with KOA, and explore the effects of PRP intra-articular injection on the inflammation of the knee joint environment and the possible mechanism of action.MethodsSeventy patients were randomized to undergo three blinded weekly intra-articular injections of PRP or hyaluronic acid (HA). The concentrations of inflammatory cytokines, including interleukin (IL)-6, IL-1β, tumor necrosis factor (TNF)-α, IL-8, IL-17A, IL-17F, IL-4, IL-5, and IL-10, in the synovial fluid were evaluated before the intervention and 1 month after the third injection. The Western Ontario and McMaster University (WOMAC) and visual analog scale (VAS) scores were used to assess pain and functional status of the knee joints in both groups before the intervention, immediately post-intervention, and 1, 3, 6, and 12 months after the intervention.ResultsBaseline characteristics were similar in both groups with no statistical difference. The IL-6, IL-1β, TNF-α, IL-17A, and IL-10 levels in the synovial fluid of the observation group decreased significantly after, vs. before, the intervention (p < 0.05), whereas the IL-8, IL-17F, and IL-4 levels decreased (p > 0.05) and IL-5 levels increased (p > 0.05). There was no statistically significant difference between inflammatory cytokine levels in the synovial fluid of the samples from the control group before and after the intervention (p > 0.05). There were no statistically significant differences between the two groups immediately after intervention (p > 0.05). At 1, 3, 6, and 12 months after intervention, the WOMAC and VAS scores were significantly better in the observation group than in the control group (p < 0.05).ConclusionPlatelet plasma therapy can reduce the concentrations of inflammatory cytokines IL-6, IL-1β, TNF-α, IL-17A, and IL-10 in the synovial fluid of KOA patients, reduce the expression levels of IL-8, IL-17F, and IL-4, clear the pro-inflammatory factors, improve the inflammatory environment of the affected knee joint, and alleviate pain caused by inflammation. Thus, alleviating pain and improving knee function in patients with KOA

Efficient Inference of AS-Level Paths in the Internet

Abstract: Routing protocols maintain connectivity of Internet routers and hosts and determine the path that a packet traverses. Inferring Internet paths is critical for evaluating the performance of Internet applications and services, such as cloud services and content delivery. Unlike intra-domain routing protocols, which typically use the shortest paths, inte-domain routing protocol apply local policies for selecting routes/paths and propagating routing information. These routing policies are typically constrained by contractual commercial agreements between ASes. It is well-known that routing policies can impact the AS path that an AS may select for delivering a packet. Thus, the ability to infer the AS-level paths is critical to evaluate the impact of routing policies on the performance of Internet applications and services. In addition, inferring AS-level paths is also important for content providers, such as Google and Amazon, to determine routing policies to ensure small latency in delivering content. However, inferring AS-level paths is challenging. Internet path selection largely depends on routing policies, which in turn are determined independently by network administrators and are considered as confidential information. In this paper, we present three common routing policies in the Internet and formulate the problem of inferring routing policy conforming AS-level paths. We present efficient algorithms for inferring the Internet AS-level paths. The algorithms are proved to be optimal in terms of the ability of derive the policy-conforming AS-level paths. We further quantify the efficiency of these algorithms

Efficient Inference of AS-Level Paths in the Internet

Routing protocols maintain connectivity of Internet routers and hosts and determine the path that a packet traverses. Inferring Internet paths is critical for evaluating the performance of Internet applications and services, such as cloud services and content delivery. Unlike intra-domain routing protocols, which typically use the shortest paths, inte-domain routing protocol apply local policies for selecting routes/paths and propagating routing information. These routing policies are typically constrained by contractual commercial agreements between ASes. It is well-known that routing policies can impact the AS path that an AS may select for delivering a packet. Thus, the ability to infer the AS-level paths is critical to evaluate the impact of routing policies on the performance of Internet applications and services. In addition, inferring AS-level paths is also important for content providers, such as Google and Amazon, to determine routing policies to ensure small latency in delivering content. However, inferring AS-level paths is challenging. Internet path selection largely depends on routing policies, which in turn are determined independently by network administrators and are considered as confidential information. In this paper, we present three common routing policies in the Internet and formulate the problem of inferring routing policy conforming AS-level paths. We present efficient algorithms for inferring the Internet AS-level paths. The algorithms are proved to be optimal in terms of the ability of derive the policy-conforming AS-level paths. We further quantify the efficiency of these algorithms

C.: Priter: a distributed framework for prioritized iterative computations

Iterative computations are pervasive among data analysis applications in the cloud, including Web search, online social network analysis, recommendation systems, and so on. These cloud applications typically involve data sets of massive scale. Fast convergence of the iterative computation on the massive data set is essential for these applications. In this paper, we explore the opportunity for accelerating iterative computations and propose a distributed computing framework, PrIter, which enables fast iterative computation by providing the support of prioritized iteration. Instead of performing computations on all data records without discrimination, PrIter prioritizes the computations that help convergence the most, so that the convergence speed of iterative process is significantly improved. We evaluate PrIter on a local cluster of machines as well as on Amazon EC2 Cloud. The results show that PrIter achieves up to 50x speedup over Hadoop for a series of iterative algorithms