Analytic models for the latency and steady-state throughput of TCP Tahoe, Reno, and SACK

Continuing the process of improvements made to TCP through the addition of new algorithms in Tahoe and Reno, TCP SACK aims to provide robustness to TCP in the presence of multiple losses from the same window. In this paper we present analytic models to estimate the latency and steady-state throughput of TCP Tahoe, Reno, and SACK and validate our models using both simulations and TCP traces collected from the Internet. In addition to being the first models for the latency of finite Tahoe and SACK flows, our model for the latency of TCP Reno gives a more accurate estimation of the transfer times than existing models. The improved accuracy is partly due to a more accurate modeling of the timeouts, evolution of cwnd during slow start and the delayed ACK timer. Our models also show that, under the losses introduced by the droptail queues which dominate most routers in the Internet, current implementations of SACK can fail to provide adequate protection against timeouts and a loss of roughly more than half the packets in a round will lead to timeouts. We also show that with independent losses SACK performs better than Tahoe and Reno and, as losses become correlated, Tahoe can outperform both Reno and SACK.     

Performance and buffering requirements of Internet protocols overATM ABR and UBR services

ATM networks are quickly being adopted as backbones over various parts of the Internet. This article studies the dynamics and performance of the TCP/IP protocol over the ABR and UBR services of ATM networks. Specifically the buffering requirements in the ATM switches as well as the ATM edge devices. It is shown that with a good switch algorithm, ABR pushes congestion to the edges of the ATM network while UBR leaves it inside the ATM portion. As a result, the switch ABR buffer requirement for zero-packet-loss high-throughput TCP transmission is a sublinear function of the number of TCP connections     

Weak state versus strong state: an analysis of a probabilistic state mechanism for dynamic networks

Network protocols coordinate their decision making using information about entities in remote locations. Such information is provided by state entries. To remain valid, the state information needs to be refreshed via control messages. When it refers to a dynamic entity, the state has to be refreshed at a high rate to prevent it from becoming stale. In capacity constrained networks, this may deteriorate the overall performance of the network. The concept of weak state has been proposed as a remedy to this problem in the context of routing in mobile ad-hoc networks. Weak state is characterized by probabilistic semantics and local refreshes as opposed to strong state that is interpreted as absolute truth. A measure of the probability that the state remains valid, i.e. confidence, accompanies the state. The confidence is decayed in time to adapt to dynamism and to capture the uncertainty in the state information. This way, weak state remains valid without explicit state refresh messages. We evaluate the consistency of weak state and strong state using two notions of distortion. Pure distortion measures the average difference between the actual value of the entity and the value that is provided by the remote state. Informed distortion captures both this difference and the effect of confidence value on state consistency. Using a mathematical analysis and simulations, we show that weak state reduces the distortion values when it provides information about highly dynamic entities and/or it is utilized for protocols that is required to incur a low amount of overhead.     

Optimization of inoculum to substrate ratio for bio-energy generation in co-digestion of tannery solid wastes

The inoculum to substrate (I/S) ratio is an important factor which influences the anaerobic digestion process. In this study, the effect of different I/S ratios on the performance of co-digestion of fleshings along with mixture of sludge generated during treatment of tannery wastewater was investigated. The parameters studied were biogas generation, volatile solids reduction, volatile fatty acid (VFA) production, and the stability of the digestion process based on VFA to alkalinity ratio was evaluated for various I/S ratios. Economical significance of I/S ratio as related to the volume of the anaerobic digester and the potential benefit of bio-energy generated are discussed in detail.     

Effect of ozonation and ultrasonication pretreatment processes on co-digestion of tannery solid wastes

Studies were carried out by the application of ozonation and ultrasonication as pretreatment processes on primary and secondary sludge generated during treatment of tannery wastewater to enhance the soluble chemical oxygen demand (SCOD). Further, co-digestion (simultaneous digestion of two or more substrates) studies were carried out in batch reactors using the fleshings (a solid waste generated during the processing of raw hides or skins into finished leather) along with the primary and the secondary sludge wherein biogas generation was compared with and without pre-treated sludge using ozone and ultrasonication processes, respectively. It was found that, application of pretreatment processes enhanced biogas generation by 45% in the case of ozone pre-treated sludge and 53% by ultrasonication processes, respectively, in conjunction with the fleshings. However, considering the optimum contact time required, application of ultrasonication as a pretreatment process was found to be the most appropriate and viable process to enhance the SCOD. This pretreatment process has the potential for implementation in tanneries using the shortest possible ultrasonication time to minimize energy cost when compared with ozonation time.     

Uncertainty quantification via bayesian inference using sequential monte carlo methods for CO2 adsorption process

This work presents the uncertainty quantification, which includes parametric inference along with uncertainty propagation, for CO₂ adsorption in a hollow fiber sorbent, a complex dynamic chemical process. Parametric inference via Bayesian approach is performed using Sequential Monte Carlo, a completely parallel algorithm, and the predictions are obtained by propagating the posterior distribution through the model. The presence of residual variability in the observed data and model inadequacy often present a significant challenge in performing the parametric inference. In this work, residual variability in the observed data is handled by three different approaches: (a) by performing inference with isolated data sets, (b) by increasing the uncertainty in model parameters, and finally, (c) by using a model discrepancy term to account for the uncertainty. The pros and cons of each of the three approaches are illustrated along with the predicted distributions of CO₂ breakthrough capacity for a scaled‐up process. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3352–3368, 2016     

DTN routing using explicit and probabilistic routing table states

Routing in communication networks involves the indirection from a persistent name (ID) to a locator. The locator specifies how packets are delivered to a destination with a particular ID. Such a mapping is provided by a routing table entry, i.e. state. In a DTN, it is hard to maintain routing state because intermittent connectivity prevents protocols from refreshing states when they become inaccurate. In prior work, per-destination state mostly corresponds to utilities, where a high utility value about a destination implies that the probability to encounter the destination for the node maintaining the state is high. This approach depends on a particular mobility pattern in which nodes that met frequently in the past are likely to encounter in the future. In this paper, we use the concept of weak state that does not rely on external messages to remain valid (Acer et al. in MobiCom ’07: proceedings of the 13th annual ACM international conference on mobile computing and networking, pp 290–301, 2007). Our weak state realization provides probabilistic yet explicit information about where the destination is located. We build Weak State Routing protocol for Delay Tolerant Networks (WSR-D) that exploits the direction of node mobility in forwarding. It provides an osmosis mechanism to disseminate the state information to the network. With osmosis, a node has consistent information about a portion of the nodes that are located in regions relevant to its direction of mobility. Through simulations, we show that WSR-D achieves a higher delivery ratio with smaller average delay, and reduces the number of message transfers in comparison to Spray & Wait (Spyropoulos et al. in Proceedings of ACM SIGCOMM 2005 workshops: conference on computer communications, pp 252–259, 2005) and Spray & Focus (Spyropoulos et al. in IEEE/ACM Trans Netw, 16(1):77–90, 2008), a stateless and a utility based protocol, respectively.     

Using directionality in mobile routing

The increased usage of directional methods of communications has prompted research into leveraging directionality in every layer of the network stack. In this paper, we explore the use of directionality in layer 3 to facilitate routing in highly mobile environments. We introduce Mobile Orthogonal Rendezvous Routing Protocol (MORRP) for mobile ad-hoc networks (MANETs). MORRP is a lightweight, but scalable routing protocol utilizing directional communications (such as directional antennas or free-space-optical transceivers) to relax information requirements such as coordinate space embedding, node localization, and mobility. This relaxation is done by introducing a novel concept called the directional routing table (DRT) which maps a set-of-IDs to each interface direction to provide probabilistic routing information based on interface direction. We show that MORRP achieves connectivity with high probability even in highly mobile environments while maintaining only probabilistic information about destinations. Additionally, we compare MORRP with various proactive, reactive, and position-based routing protocols using single omni-directional interfaces and multiple directional interfaces and show that MORRP gains over 10–14 × additional goodput vs. traditional protocols and 15–20% additional goodput vs. traditional protocols using multiple interfaces. MORRP scales well without imposing DHT-like graph structures (eg: trees, rings, torus etc). We also show that high connectivity can be achieved without the need to frequently disseminate node position resulting increased scalability even in highly mobile environments.     

Nanoparticle ordering by dewetting of Co on SiO2

Most metals on SiO₂ have a finite contact angle and are therefore subject to dewetting during thermal processing. The resulting dewetting morphology is determined primarily by nucleation and growth or instabilities. The dewetting mechanism implies a disordered spatial arrangement for homogeneous nucleation, but an ordered one for instabilities such as spinodal decomposition. Here, we show that the morphology of laser-melted ultrathin Co film (4-nm thick) can be attributed to dewetting via an instability. Dewetting leads to breakup of the continuous Co film into nanoparticles with a monomodal size distribution with an average particle diameter of 75 nm±23 nm. These nanoparticles have short-range order (SRO) of 130 nm in their separation. This result has important implications for nanomanufacturing with a robust spacing or size selection of nanoparticles in addition to spatial ordering.