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Multiphase displacement in porous media can be adjusted by micro/nanoparticle suspensions, which is widespread in many scientific and industrial contexts. Direct visualization of suspension flow dynamics and corresponding multiphase patterns is crucial to understanding displacement mechanisms and eventually optimizing these processes in geological, biological, chemical, and other engineering systems. However, suspension flow inside the opaque realistic porous media makes direct observation challenging. The advances in microfluidic experiments have provided us with alternative methods to observe suspension influence on the interface and multiphase flow behaviors at high temporal and spatial resolutions. Macroscale processes are controlled by microscale interfacial behaviors, which are affected by multiple physical factors, such as particle adsorption, capillarity, and hydrodynamics. These properties exerted on the suspension flow in porous media may lead to interesting interfacial phenomena and new displacement consequences. As an underpinning science, understanding and controlling the suspension transport process from interface to flow patterns in porous media is critical for a lower operating cost to improve resource production while reducing harmful emissions and other environmental impacts. This review summarizes the basic properties of different micro/nanoparticle suspensions and the state-of-the-art microfluidic techniques for displacement research activities in porous media. Various suspension transport behaviors and displacement mechanisms explored by microfluidic experiments are comprehensively reviewed. This review is expected to boost both experimental and theoretical understanding of suspension transport and interfacial interaction processes in porous media. It also brings forward the challenges and opportunities for future research in controlling complex fluid flow in porous media for diverse applications.

We report non-monotonic wettability effects on displacement efficiency in heterogeneous porous structures at the post-breakthrough stage, in contrast to the monotonic ones in homogeneous porous structures. Experiments on designed microfluidic chips show that there exists a critical wettability to attain the highest efficiency of displacement in the porous matrix structure combined with a preferential flow pathway, while a stronger wettability of the displacing fluid leads to a higher displacement efficiency on the same matrix structure only. The porous structure with or without a preferential flow pathway results in totally different topological characteristics of phase distribution during displacement. Pore-scale mechanisms are identified to elucidate the formation of this non-monotonic wettability rule: cooperative pore filling under weakly water-wet conditions yields the best displacement; corner flow under strongly water-wet conditions and Haines events under strongly oil-wet conditions decrease the displacement efficiency. The pore-scale findings may provide unique insights into the joint effects of both wettability and flow heterogeneity on fluid displacement in porous media.

Preferential flow in porous media is commonly encountered and decreases the multiphase displacement efficiency. Here, we synthesized microgel-in-oil in suspension and demonstrated that microgel-in-oil as a novel additive could present self-adaptive transport behavior and introduce a novel multiphase displacement mode for improving displacement efficiency in heterogeneous porous media.We investigated the microgel-in-oil formation process and characterized their morphology with fluorescence microscopy and Cryo-SEM. The suspension displacement performance in heterogeneous porous media was evaluated using a microfluidic chip containing a preferential flow pathway (PFP) and a parallel matrix region. The displacement results of microgel-in-oil were compared to plain microgel particles and analyzed from pore-scale particle transport behavior to macroscopic multiphase flow patterns.The results show that suspension with moderate microgel-in-oil yields the optimal displacement efficiency. Fewer microgel-in-oil cannot alter the flow direction, while too many microgel-in-oil would block the PFP region. The topological analysis identified that suspensions with moderate microgel-in-oil content could achieve the strongest sweeping and carrying abilities that contribute to the highest displacement efficiency. The synergistic transport of microgel-in-oil and plain microgel particles would result in local pressure fluctuations to divert displacing fluid from PFP into the matrix region, which explains the above flow behavior.

The next generation large-scale computing applications require network support for interactive visualization, computational steering and instrument control over wide-area networks. In particular, these applications require stable transport streams over wide-area networks, which are not adequately supported by current transport methods. We propose a new class of protocols capable of stabilizing a transport channel at a specified throughput level in the presence of random network dynamics based on the classical Robbins-Monro stochastic approximation approach. These protocols dynamically adjust the window size or sleep time at the source to achieve stable throughput at the destination. The target throughput typically corresponds to a small fraction of the available connection bandwidth. This approach yields provably probabilistically stable protocols as a consequence of carefully adjusted step sizes. The superior and robust stabilization performance of the proposed approach is extensively evaluated in a simulated environment and further verified through real-life implementations and deployments over both Internet and dedicated connections under disparate network conditions in comparison with existing transport methods.

Next-generation eScience applications often generate large amounts of simulation or experimental data that must be shared and managed by collaborative organizations. Advanced networking technologies and services have been rapidly developed and deployed to facilitate the massive data transport necessary for such data sharing and collaboration. However, these technologies and services have not been fully utilized by application users mainly because their use typically requires significant domain knowledge and in many cases even their existence is not made aware to the public. We design and develop a Network-aware Data Movement Advisor (NADMA) utility to enable automated discovery of network and system resources and advise the user of efficient strategies for fast and successful data transfer. NADMA is primarily a client-end program that interacts with existing data/space management and discovery services such as Storage Resource Management, transport methods such as GridFTP, and network resource provisioning systems such as TeraPaths and OSCARS. NADMA acts as a route planner in a typical vehicle navigation system to provide the user a set of feasible route options along with performance estimations as well as specific steps and commands to authorize and execute data transfer. We demonstrate the efficacy of NADMA in several use cases based on its implementation and deployment in wide-area networks.

Supporting large-scale scientific workflows in distributed network environments and optimizing their performances are crucial to the success of collaborative scientific discovery. We develop a generic scientific workflow platform, referred to as SciFlow, which constitutes a flexible framework to facilitate the distributed execution and management of scientific workflows and incorporates a class of workflow mapping schemes to achieve optimal end-to-end performances. The functionalities of SciFlow are provided and its interactions with other tools or systems are enabled through web services for easy access over standard Internet protocols while being independent of different platforms and programming languages. The performance superiority of SciFlow over existing workflow mapping schemes and management systems is illustrated by extensive simulations and is further verified by large-scale experiments on real-life scientific workflows through effective system implementation and deployment in distributed network environments.

The traditional client-server architecture widely adopted on the Internet is not adequate to meet the increasing user loads and bandwidth demands in live streaming systems especially for multimedia content delivery. Peer-to-peer P2P) overlay networks provide excellent system scalability and high resource utilization, which make it an attractive solution to this problem. This paper considers a hybrid hierarchical P2P overlay network structure that consists of both super and normal peers. The media streaming architecture is built upon a tree structured network of super peers and the tree construction process has a significant impact on the overall system performance. We construct network cost models and formulate a Bandwidth Constrained Tree (BCT) construction problem, which aims at maximizing the number of peers that satisfy a specified bandwidth constraint. We prove that BCT is NP-complete and propose optimal algorithms in two special cases and a heuristic approach in a general case. The performance superiority of the proposed method is illustrated by an extensive set of experiments on simulated networks of various sizes in comparison with existing greedy and degree constrained algorithms.

Several research and production high-performance networks now provision multi-Gbps dedicated channels to support large data transfers in network-intensive applications. However, end users have not seen a corresponding increase in application throughput mainly because traditional end-to-end transport methods are not optimized for such connections. New congestion or flow control mechanisms are desirable to meet the challenges brought by dedicated connections to transport protocol design. The advent and proliferation of multi-core processors make it now possible to improve application throughput by providing multiple processing and networking resources to a single data transfer. Based on the existing PLUT method, we propose a new transport method, Para-PLUT, which utilizes multiple parallel UDP connections to take advantage of the full power of multicore processors for maximum aggregate goodput. We implement and test Para-PLUT in a local dedicated network testbed and the experimental results illustrate its superior performance over several existing methods.

The client-server architecture widely adopted on the Internet is not adequate to meet the ever-increasing user loads and bandwidth demands in live streaming systems especially for multimedia content delivery. Peer-to-peer (P2P) overlay networks provide excellent system scalability and high resource utilization, which make it an attractive solution to this problem. We consider a hybrid hierarchical P2P overlay network that consists of both super and normal peers to support live streaming applications. This architecture is built upon a tree-structured network of super peers, which organize normal peers into clusters. The tree construction process has a significant impact on the overall system performance. We formulate a specific type of problem, max-minTC, to maximize the minimum node throughput in tree construction, where the system's stream rate is optimized by constructing an efficient spanning tree among super peers. We present a decentralized approach where super peers run the same algorithm in parallel to derive a tree from an identical database describing the topology of the streaming system. This approach is able to quickly converge to a new tree upon the detection of any topological changes in super peers. The performance superiority of the proposed solution is illustrated by extensive simulations on a large set of simulated networks of various sizes from small to large scales in comparison with other methods.

This paper considers a hybrid hierarchical P2P overlay network structure that consists of both super and normal peers. The media streaming architecture is built upon a tree-structured network of super peers and the tree construction process has a significant impact on the overall system performance. We build network cost models and formulate a specific type of problem to maximize the minimum node throughput in Tree Construction (max-minTC), which aims at optimizing the system's stream rate by constructing an efficient spanning tree among super peers. We consider two scenarios: (i) When the overlay network has an arbitrary topology, we prove max-minTC to be NP-complete by reducing from the Degree Constrained Spanning Tree problem and propose an efficient heuristic algorithm. The performance superiority of the proposed algorithm is justified by experimental results collected by a live media streaming system deployed in real networks and is also illustrated by extensive simulations performed on a large set of simulated networks of various sizes from small to large scales in comparison with other methods, (ii) When the topology of the overlay network is complete, we rigorously prove that the same heuristic algorithm yields an optimal solution.

Peer-to-peer (P2P) overlay networks provide a highly effective and scalable solution to live media streaming systems that require the collective use of massively distributed network resources. A P2P media streaming architecture is typically built completely or partially upon a tree-structured network topology and the process of tree construction has a significant impact on the overall system performance. We build network cost models and formulate a specific type of topology construction problem, Maximum Average Bandwidth Spanning Tree (MABST), which aims at optimizing the system's average stream rate. We prove that MABST is NP-complete by reducing from Hamiltonian Path problem and propose an efficient heuristic algorithm. The performance superiority of the proposed algorithm is justified by experimental results using a live media streaming system deployed in real networks and is also illustrated by an extensive set of simulations on simulated networks of various sizes in comparison with other methods based on a degree constraint or a greedy strategy.

Several research and production high-performance networks now provision multi-Gbps dedicated channels to meet the demands of large data transfers in network-intensive applications. However, end users have not seen corresponding increase in application throughput mainly because (i) the existence of high-bandwidth links has shifted the congestion from the network to end hosts, and (ii) such congestion is not well handled by TCP's Additive Increase and Multiplicative Decrease algorithm. Particularly, due to the sharing with unknown background workloads, the data receiver oftentimes lacks sufficient system resources to process the arriving packets, hence leading to significant packet drops at the end system. This paper proposes a UDP-based transport method that incorporates a performance-adaptive flow control mechanism to regulate the activities of both the sender and receiver in response to system dynamics to achieve high throughput. We construct a mathematical model for the socket receive buffer and data receiving process, and employ a profiling-based method to estimate the initial receiving bottleneck rate, which is dynamically adjusted and sent back to the sender for source rate control. The sending rate is stabilized at the estimated bottleneck rate based on a stochastic approximation algorithm. We test the proposed method on a local dedicated connection and the experimental results illustrate its superior performance over existing methods.

Several research and production networks now provide multiple Gbps dedicated connections to meet the demands of large data transfers over wide-area networks. End users, however, have not been able to see corresponding increase in application goodputs mainly because (i) such rates have pushed the bottleneck from the network to the end system, and (ii) the traditional transport methods are not optimized for handling host dynamics. Due to the sharing with unknown background workloads, the data receiver oftentimes lacks sufficient system resources to process packets arriving from high-speed dedicated links, therefore leading to significant packet drops at the end system. We propose a rigorous design approach for a new class of transport protocols that explicitly account for the dynamics of the running environment to maximize application goodputs over dedicated connections. The control strategy of the proposed transport method combines two aspects: (i) the receiving bottleneck rate is predicted based on performance modeling, and (ii) the sending rate is stabilized at the estimated bottleneck rate based on stochastic approximation. We test the proposed method on a local dedicated connection and the experimental results illustrate its superior performance over existing methods.

Several research and production networks now provide multiple Gbps dedicated connections to meet the demands of large data transfers over wide-area networks. Application throughputs, however, were not able to match these rates because the traditional transport methods have not been optimized for such connections. We propose a transport method based on stochastic approximation methods that: (a) stabilizes the source rate for peak utilization of connection bandwidth, and (b) adapts the acknowledgment interval to maximize the goodput at the receiver. We show the asymptotic stability and convergence of this method in maximizing the throughput over dedicated connections under fairly general conditions. Extensive experimental results indicate the effectiveness of this transport method in achieving file transfer throughputs that closely match iperf bandwidth measurements on dedicated connections of several thousand miles over UltraScience Net and ESnet, and also illustrate its superior performance on a local dedicated connection in comparison with existing methods.