We seek in this work to supply and conserve power for wearable resistive sensors by inductive coupling. A proof-of-concept experiment shows that through a pair of coils the core is able to deliver power and capture the resistance load at the remote sensor, achieving powering and communicating the state of the sensor simultaneously.

This study developed an elastic wristband called Polyband for profiling the unique deformation of the skin and muscles around the wrist during hand gestures through resistance measurements. A proof-of-concept design was demonstrated to recognize a simple set of gestures with 92.9% accuracy.

Latency is a major issue towards practical use of augmented reality (AR) in mobile apps such as navigation and gaming. A string of work has appeared recently, proposing to offload a part of the AR-related processing pipeline to the edge [8]. One pitfall in these studies is the (simplified) assumption about the network delay. As a reality check and to gather insights to realize AR in real time, we seek in this work a better understanding of how a popular AR game, Pokémon Go, delivers its data in situ.

We propose a cross-domain image-based 3D shape retrieval method, which learns a joint embedding space for natural images and 3D shapes in an end-to-end manner. The similarities between images and 3D shapes can be computed as the distances in this embedding space. To better encode a 3D shape, we propose a new feature aggregation method, Cross-View Convolution (CVC), which models a 3D shape as a sequence of rendered views. For bridging the gaps between images and 3D shapes, we propose a Cross-Domain Triplet Neural Network (CDTNN) that incorporates an adaptation layer to match the features from different domains better and can be trained end-to-end. In addition, we speed up the triplet training process by presenting a new fast cross-domain triplet neural network architecture. We evaluate our method on a new image to 3D shape dataset for category-level retrieval and ObjectNet3D for instance-level retrieval. Experimental results demonstrate that our method outperforms the state-of-the-art approaches in terms of retrieval performance. We also provide in-depth analysis of various design choices to further reduce the memory storage and computational cost.

Alcohol dependence is a chronic disorder associated with severe harm in multiple areas, and relapsing is easy, despite treatment. This study proposes SoberDiary, a phone-based support system that enables alcohol-dependent patients to self-monitor and -manage their own alcohol behavior, and remain sober in their daily lives. We tested SoberDiary in a real-life 12-week user study involving 27 clinical patients. The quantitative and qualitative results revealed that SoberDiary helped patients self-monitor and -manage their alcohol-use behavior, and reduced their total alcohol consumption as well as the number of heavy drinking days. Compared with patients who received standard treatment alone, this study demonstrated SoberDiary successfully complemented current alcohol treatment in reducing patients' alcoholic cravings and dropout rate over 3-month study period. Follow-up interviews further revealed the sophisticated use practices and value of SoberDiary.

To facilitate the collection of patient biosignals, designing extensible sensing devices in which sensor management is simplified is essential. This paper presents BioScope, an extensible sensing system that facilitates collecting data used in nursing assessments. We conducted experiments to demonstrate the potential of the system. The results obtained in this study can be applied in improving the design, thus enabling BioScope to facilitate data collection in numerous potential applications.

The effective end-to-end transport of delay-sensitive voice data has long been a problem in multimedia networking. One of the major issues is determining the sending rate of real-time VoIP streams such that the user experience is maximized per unit network resource consumed. A particularly interesting complication that remains to be addressed is that the available bandwidth is often dynamic. Thus, it is unclear whether a marginal increase warrants better user experience. If a user naively tunes the sending rate to the optimum at any given opportunity, the user experience could fluctuate. To investigate the effects of magnitude and frequency of rate changes on user experience, we recruited 127 human participants to systematically score emulated Skype calls with different combinations of rate changes, including varying magnitude and frequency of rate changes. Results show that: 1) the rate change frequency affects the user experience on a logarithmic scale, echoing Weber-Fechner's Law; 2) the effect of rate change magnitude depends on how users perceive the quality difference; and 3) this study derives a closed-form model of user perception for rate changes for Skype calls.

As Skype has become popular and a profitable business, the long-standing problem of how to deliver Skype calls deserves a serious revisit from an economic viewpoint. This study proposes a rate control mechanism for Skype calls that satisfies more users and satisfies users more than the greedy-naïve mechanism, as well as the mechanism implemented in Skype.

This study presents several extensions to our previous work on the PipeProbe system, a mobile sensor system for identifying the spatial topology of hidden water pipelines (i.e., non-moldable pipes such as copper and PVC) behind walls or under floors [Lai et al. 2010]. The PipeProbe system works by dropping a tiny wireless sensor capsule into the source of a water pipeline. As the PipeProbe capsule traverses the pipelines, it gathers and transmits pressure and angular velocity readings. Through spatiotemporal analysis of these sensor readings, the proposed algorithm locates all turning points in the pipelines and maps their 3D spatial topology. This study expands upon previous research by developing new sensing techniques that identify variable-diameter pipes and differentiate 90-degree pipe turns from 45-degree pipe bends.

As the application of WSNs for long-term monitoring purposes becomes real, the issue of WSN system health monitoring grows increasingly important. Manually understanding the root causes of an observed behavior is time-consuming and difficult, often knowledge of prior behavior is necessary for understanding the potential risk on the long-term system performance. The challenges lie in the balance between the amount of system data collected and the level of detail in which state can be inferred from this data. In this paper, we propose a lightweight runtime logging and corresponding network state inference mechanism that enables scalable WSN health monitoring. Concretely, we propose that nodes only report their internal state on the occurrence of important events. Having a very low computational complexity and message overhead within the sensor network, reported events are analyzed at a less constrained network sink.

This study presents TriopusNet, a mobile wireless sensor network system for autonomous sensor deployment in pipeline monitoring. TriopusNet works by automatically releasing sensor nodes from a centralized repository located at the source of the water pipeline. During automated deployment, TriopusNet runs a sensor deploy-ment algorithm to determine node placement. While a node is flowing inside the pipeline, it performs placement by extending its mechanical arms to latch itself onto the pipe's inner surface. By continuously releasing nodes into pipes, the TriopusNet system builds a wireless network of interconnected sensor nodes. When a node runs at a low battery level or experiences a fault, the TriopusNet system releases a fresh node from the repository and performs a node replacement algorithm to replace the failed node with the fresh one. We have evaluated the TriopusNet system by creating and collecting real data from an experimental pipeline testbed. Comparing with the non-automated static deployment, TriopusNet is able to use less sensor nodes to cover a sensing area in the pipes while maintaining network connectivity among nodes with high data collection rate. Experimental results also show that TriopusNet can recover from the network disconnection caused by a battery-depleted node and successfully replace the battery-depleted node with a fresh node.

The effective end-to-end transport of delay-sensitive voice data has long been a problem in multimedia networking. One of the major issues is determining the sending rate of real-time VoIP streams such that the user experience is maximized per unit network resource consumed. A particularly interesting complication that remains to be addressed is that the available bandwidth is often dynamic. Thus, it is unclear whether a marginal increase warrants better user experience. If a user naively tunes the sending rate to the optimum at any given opportunity, the user experience could fluctuate.

We present TUIC, a technology that enables tangible interaction on capacitive multi-touch devices, such as iPad, iPhone, and 3M's multi-touch displays, without requiring any hardware modifications. TUIC simulates finger touches on capacitive displays using passive materials and active modulation circuits embedded inside tangible objects, and can be used with multi-touch gestures simultaneously. TUIC consists of three approaches to sense and track objects: spatial, frequency, and hybrid (spatial plus frequency). The spatial approach, also known as 2D markers, uses geometric, multi-point touch patterns to encode object IDs. Spatial tags are straightforward to construct and are easily tracked when moved, but require sufficient spacing between the multiple touch points. The frequency approach uses modulation circuits to generate high-frequency touches to encode object IDs in the time domain. It requires fewer touch points and allows smaller tags to be built. The hybrid approach combines both spatial and frequency tags to construct small tags that can be reliably tracked when moved and rotated. We show three applications demonstrating the above approaches on iPads and 3M's multi-touch displays.

Real-time video transcoding that is often needed for robust video broadcasting over heterogeneous networks is not supported in most existing devices. To address this problem, we propose a collaborative strategy that leverages the peering architecture of peer-to-peer Internet protocol television networks and makes the computational resources of peers sharable. The video transcoding task is distributed among the peers and completed collaboratively. A prototype of the live video broadcasting system is evaluated over a 100-node testbed on the PlanetLab. The experimental results show that the proposed strategy works effectively even when the majority of the peers have limited computational resource and bandwidth.

Saving DTNs' battery power to prolong the system life time has been an important research topic which scientists try to optimize. Most researches fall into two categories - Time Division Multiple Access based ones, and Low Power Listening ones by turning the listener's radio on/off intermittenly with long sending preambles. In this paper we propose solving the problem from a whole new angle - by using the motes' physical behavior, which is detectable by relatively energy-cheap accelerometer, as the judgment for turning the radio on/off. This scheme can be used in combination with any energy efficient DTN MAC protocols. We evaluate the protocol by running simulations with real hikers' traces and the result is shown in the evaluation section.

This paper presents PipeProbe, a mobile sensor system for determining the spatial topology of hidden water pipelines behind walls. PipeProbe works by dropping a tiny wireless sensor capsule into the source of the water pipelines. As the PipeProbe capsule traverses the pipelines, it gathers and transmits pressure and angular velocity readings. Through spatio-temporal analysis on the sensor readings, our algorithm locates all turning points in the pipelines and maps their 3D spatial topology. We evaluated the PipeProbe system by developing a prototype and using data collected in our experimental testbed. Results show that the PipeProbe system successfully located and estimated 90% of all pipe tube lengths within 8-cm accuracy on average tube lengths of 76 cm. PipeProbe also successfully located 90% of all turning points within 15-cm accuracy on average length paths of 335cm.

Wi-Fi ingerprint-based localization is currently the most promising approach to building metropolitan-scale localization systems for both indoor and outdoor environments. A Wi-Fi fingerprint localization system makes use of a radio map that contains Wi-Fi signals received at various locations, and uses the map for location estimation. Thus, the accuracy of a Wi-Fi fingerprint localization system greatly depends on the quality of its radio map. This paper explores various properties of a metropolitan radio map that may affect the accuracy of Wi-Fi fingerprint localization systems. In this study, metropolitan-scale radio maps are obtained using war walking and war driving. These maps contain hundreds of thousands of access points and signal samples. A detailed comparison analysis of selected radio map properties reveals how different map properties affect the difference between the positional accuracies of the driving and walking radio maps in Wi-Fi fingerprint-based localization.

Determining how to transport delay-sensitive voice data has long been a problem in multimedia networking. The difficulty arises because voice and best-effort data are different by nature. It would not be fair to give priority to voice traffic and starve its best-effort counterpart; however, the voice data delivered might not be perceptible if each voice call is limited to the rate of an average TCP flow. To address the problem, we approach it from a user-centric perspective by tuning the voice data rate based on user satisfaction. Our contribution in this work is threefold. First, we investigate how Skype, the largest and fastest growing VoIP service on the Internet, adapts its voice data rate (i.e., the redundancy ratio) to network conditions. Second, by exploiting implementations of public domain codecs, we discover that Skype's mechanism is not really geared to user satisfaction. Third, based on a set of systematic experiments that quantify user satisfaction under different levels of packet loss and burstiness, we derive a concise model that allows user-centric redundancy control. The model can be easily incorporated into general VoIP services (not only Skype) to ensure consistent user satisfaction.

We propose PipeProbe, a mobile sensor system for mapping water pipelines hidden inside cement walls or under floor coverings. PipeProbe works by dropping a tiny sensor capsule into the source of the water pipelines. As the PipeProbe capsule traverses the pipelines, it gathers accelerometer and water pressure readings. Through a novel estimation method based on Bernoulli's principle, we reconstruct the 3D spatial layout of the water pipelines. The PipeProbe system is non-intrusive and requires no alteration to the water pipeline infrastructure.

The objective of YushanNet is to provide a reliable and robust system for hiker tracking in Yushan National Park, Taiwan. The aggregated information can help national parks to provide various services to tourists, and the collected hiking traces can provide more precise information to professional rescue teams if there are hikers lost in the mountains. YushanNet is a delay and disruption tolerant system. In the system, each hiker is required to carry a matchbox-size device, which consists of a ZigBee-based mote and a GPS receiver, and the device records its hiking trace, along with encounter information with other devices. Then, the recorded data is disseminated in the network in a store-carry-and-forward fashion, until it reaches one of the base stations along the trail. In this demo, we will present the design, implementation, and deployment of the YushanNet system, and we will demonstrate the system using a small-scale network scenario.

As the R&D experience accumulates, there is a rising interest of wireless sensor network (WSN) deployment in the urban environment. For mission critical applications such as healthcare and workplace safety, in particular, it is essential that the data dissemination mechanisms satisfy two important quality of service (QoS) requirements: (1) high delivery rate and (2) low transmission delay. Proposed in this work is a cross-layer designed data dissemination mechanism, referred to as Cross-Layer Diffusion (XD), in which notions in the path discovery (routing) component are exploited by data forwarding (MAC) component to improve the delivery rate and transmission delay. Using traces collected from a prototype WSN deployed in urban environment, we compare XD to the state-of-the-art mechanisms and find that XD is not only more efficient but also more practical.

In this work, we present an experimental study, in which we deploy a 14-node 802.15.4-based sensor network in our department building. Using the k-nearest-neighbor (KNN) method to the estimation of location, we implement an RSSI-signature-based localization system on top of the network.

We propose PipeProbe, a mobile sensor system for mapping hidden water pipelines inside cement walls or under floor coverings. PipeProbe works by dropping a sensor capsule into the source of the water pipelines. As the PipeProbe capsule traverses the pipelines, it gathers water pressure and accelerometer readings. Given the pressure sensor readings, we can identify the height of PipeProbe. Accelerometer is used to recognize different types of water pipeline shape when PipeProbe travels through. The PipeProbe system is non-intrusive and requires no alteration to the water pipeline infrastructure.

Boundary detection is a form of location-aware services that aims at detecting targets crossing certain critical regions. Typically, a lower location sampling rate contributes to a lower level of energy consumption but, in the meantime, delays the detection of boundary crossing events. Opting to enable energy-efficient boundary detection services, we propose a mobility-aware mechanism that adapts the location sampling rate to the target mobility. Results from our simulations and live experiments confirm that the proposed adaptive sampling mechanism is effective. In particular, when experimented with realistic errors measured from a live radio-frequency-based localization system, the energy consumption can be reduced significantly to 20 percent.

Understanding the impact of network conditions on player satisfaction, which is one of the major concerns of network game designers, is a popular research topic. Of the various ways to gauge user satisfaction, in this paper, we focus on how network quality affects a player's decision to leave a game prematurely. To answer this question, we analyze a 1,356-million-packet trace from a large commercial massively multiplayer online role-playing game (MMORPG) called ShenZhou Online. We show that both network delay and network loss significantly affect a player's decision to leave a game prematurely. It is feasible to predict whether players will quit prematurely based on the network conditions they experience. The proposed model can determine the relative impact of different types of network impairment. For our traces, the degrees of player intolerance to network delay, delay jitter, client packet loss, and server packet loss are in the proportion of 1:2:4:3 approximately. The model can also be used to make system design decisions. Through simulations, we show that by prioritizing server processing according to the goodness of network conditions, employing dejitter buffers, or replacing TCP with a more lightweight transport protocol, the probability of premature departure can be significantly reduced. In this way, we demonstrate how our model of players' network experience provides feedback for the design of online games.

This work proposes the novel use of spinning beacons for precise indoor localization. The proposed "SpinLoc" (Spinning Indoor Localization) system uses "spinning" (i.e., rotating) beacons to create and detect predictable and highly distinguishable Doppler signals for sub-meter localization accuracy. The system analyzes Doppler frequency shifts of signals from spinning beacons, which are then used to calculate orientation angles to a target. By obtaining orientation angles from two or more beacons, SpinLoc can precisely locate stationary or slow-moving targets. After designing and implementing the system using MICA2 motes, its performance was tested in an indoor garage environment. The experimental results revealed a median error of 40~50 centimeters and a 90% error of 70~90 centimeters.

HotStreaming is an overlay peer-to-peer (P2P) based IPTV system. It integrates the innovations in both overlay networking and video coding for optimal user experience. The HotStreaming system is composed of three key components: partnership formation, data request scheduling and multiple description coding (MDC). In the partnership formation component, we propose two policies to reduce the time of disconnection and the number of isolated peers. In the MDC component, we adopt MDC with spatial-temporal hybrid interpolation (MDC-STHI), which makes the peers in a P2P network to adjust the streaming traffic according to their bandwidth limitation and capability of devices. The experimental results show that the HotStreaming system improves the video quality over a lossy and dynamic networking environment.

NTUStreaming is an overlay P2P-based IPTV system that integrates innovations in both overlay networking and video coding for optimal user experience. The system consists of three key components: partnership formation, robust video coding, and video segment request scheduling. For partnership formation, a graph construction mechanism TYPHOON based on epidemic algorithms is developed to reduce disconnect time and isolated peers. For robust video coding, a multiple description coding (MDC) scheme with spatial-temporal hybrid interpolation (STHI) is proposed to adjust streaming traffic according to the bandwidth and device capability of each peer. For request scheduling, an optimization algorithm is developed by taking the available bandwidth and the video segment type into account. Experimental results show that NTUStreaming is able to deliver optimal video quality in lossy and dynamic networking environments.

There has been a significant amount of work analyzing the Internet AS (Autonomous System)-level topology which gives rise to a number of topology models. Although each of these models is being refined to fit better a particular set of graph properties over time, there is a more fundamental need in knowing the topology invariants. To address this need, we examine how the Internet AS-level topology evolves, using a variety of graph metrics,-a super set of what has been used in recent works. We discover that the AS-level topology shows a clear converging trend only in the normalized Laplacian spectrum (nls). From the theory of nls, we discover further that the converging trend indicates a stabilizing ratio of leaf to core ASes (or customer to provider ASes) on the Internet.

Abstract — Online gaming is one of the most profitable busi-nesses on the Internet. Among various threats to continuous player subscriptions, network lags are particularly notorious. It is widely known that frequent and long lags frustrate game players, but whether the players actually take action and leave a game is unclear. Motivated to answer this question, we apply survival analysis to a 1, 356-million-packet trace from a sizeable MMORPG, called ShenZhou Online. We find that both network delay and network loss significantly affect a player’s willingness to continue a game. For ShenZhou Online, the degrees of player “intolerance ” of minimum RTT, RTT jitter, client loss rate, and server loss rate are in the proportion of 1:2:11:6. This indicates that 1) while many network games provide “ping time, ” i.e., the RTT, to players to facilitate server selection, it would be more useful to provide information about delay jitters; and 2) players are much less tolerant of network loss than delay. This is due to the game designer’s decision to transfer data in TCP, where packet loss not only results in additional packet delays due to in-order delivery and retransmission, but also a lower sending rate.

Energy efficiency and positional accuracy are often contradictive goals. We propose to decrease power consumption without sacrificing significant accuracy by developing an energy-aware localization that adapts the sampling rate to target's mobility level. In this paper, an energy-aware adaptive localization system based on signal strength fingerprinting is designed, implemented, and evaluated. Promising to satisfy an application's requirements on positional accuracy, our system tries to adapt its sampling rate to reduce its energy consumption. The contribution of this paper is three-fold. (1) We have developed a model to predict the positional error of a real working positioning engine under different mobility levels of mobile targets, estimation error from the positioning engine, processing and networking delay in the location infrastructure, and sampling rate of location information. (2) In a real test environment, our energy-saving method solves the mobility estimation error problem by utilizing additional sensors on mobile targets. The result is that we can improve the prediction accuracy by as much as 37.01%. (3) We implemented our energy-saving methods inside a working localization infrastructure and conducted performance evaluation in a real office environment. Our performance results show as much as 49.76 % reduction in power consumption

The success of Skype has inspired a generation of peer-to-peer-based solutions for satisfactory real-time multimedia services over the Internet. However, fundamental questions, such as whether VoIP services like Skype are good enough in terms of user satisfaction,have not been formally addressed. One of the major challenges lies in the lack of an easily accessible and objective index to quantify the degree of user satisfaction.In this work, we propose a model, geared to Skype, but generalizable to other VoIP services, to quantify VoIP user satisfaction based on a rigorous analysis of the call duration from actual Skype traces. The User Satisfaction Index (USI) derived from the model is unique in that 1) it is composed by objective source-and network-level metrics, such as the bit rate, bit rate jitter, and round-trip time, 2) unlike speech quality measures based on voice signals, such as the PESQ model standardized by ITU-T, the metrics are easily accessible and computable for real-time adaptation, and 3) the model development only requires network measurements, i.e., no user surveys or voice signals are necessary. Our model is validated by an independent set of metrics that quantifies the degree of user interaction from the actual traces.

TCP employs a self-clocking scheme that times the sending of packets. In that, the data packets are sent in a burst when the returning acknowledgement packets are received. This self-clocking scheme (also known as ack-clocking) is deemed a key factor to the the burstiness of TCP traffic and the source of various performance problems-high packet loss, long delay, and high delay jitter. Previous work has suggested contradictively the effectiveness of TCP pacing as a remedy to alleviate the traffic burstiness. In this paper, we analyze systematically, and in more robust experiments the impact of network variabilities on the behavior of TCP clocking schemes. We find that 1) aggregated pacing traffic could be burstier than aggregated ack-clocking traffic. Physical explanation and experimental simulations are provided to support this argument. 2) The round-trip time heterogeneity and flow multiplexing significantly influence the behaviors of both ack-clocking and pacing schemes. Evaluating the performance of clocking schemes without considering these effects is prone to inconsistent results. 3) Pacing outperforms ack-clocking in more realistic settings from the traffic burstiness point of view.

Wi-Fi based indoor location systems have been shown to be both cost-effective and accurate, since they can attain meter-level positioning accuracy by using existing Wi-Fi infrastructure in the environment. However, two major technical challenges persist for current Wi-Fi based location systems, instability in positioning accuracy due to changing environmental dynamics, and the need for manual offline calibration during site survey. To address these two challenges, three environmental factors (people, doors, and humidity) that can interfere with radio signals and cause positioning inaccuracy are identified. Then, we have proposed a sensor-assisted adaptation method that employs RFID sensors and environment sensors to adapt the location systems automatically to the changing environmental dynamics. The proposed adaptation method performs online calibration to build multiple context-aware radio maps under various environmental conditions. Experiments were performed on the sensor-assisted adaptation method. The experimental results show that the proposed adaptive method can avoid adverse reduction in positioning accuracy under changing environmental dynamics.

Envisioning a new generation of sensor network applications in healthcare and workplace safety, we seek mechanisms that provide timely and reliable transmissions of mission-critical data. Inspired by the physics in magnetism, we propose a simple diffusion-based data dissemination mechanism, referred to as the magnetic diffusion (MD). In that, the data sink, functioning like the magnet, propagates the magnetic charge to set up the magnetic field. Under the influence of the magnetic field, the sensor data, functioning like the metallic nails, are attracted towards the sink. We compare MD to the state-of-the-art mechanisms and find that MD 1) performs the best in timely delivery of data, 2) achieves high data reliability in the presence of network dynamics, and yet 3) works as energy efficiently as the state of the art. These suggest that MD is an effective data dissemination solution to the mission-critical applications.

Online gaming is one of the most profitable businesses over the Internet. Among all genres of the online games, the popularity of the MMORPG (Massive Multiplayer Online Role Playing Games) is especially prominent in Asia. Opting for a better understanding of the game traffic and the economic well being of the Internet, we analyze a 1,356-million-packet trace from a sizeable MMORPG, ShenZhou Online. This work is, as far as we know, the first formal analysis on the MMORPG server traces.We find that the MMORPG and FPS (First-Person Shooting) games are similar in that they both generate small packets and require low bandwidths. In particular, the bandwidth requirement of MMORPG is even lower due to the less real-time game play. More distinctive are the strong periodicity, temporal locality, and irregularity observed in the MMORPG traffic. The periodicity is due to a common practice in game implementation, where the game state updates are accumulated within a fixed time window before transmission. The temporal locality in the game traffic is largely due to the game nature where one action leads to another. The irregularity, particular unique in MMORPG traffic, is due to the diversity of game design where the user behavior can be drastically different depending on the quest at hand.

With the creative use of sensors, in the future, sensor networks could impact on a wide variety of applications from national security to consumer electronics. Sharing the vision and emphasizing the energy efficiency of data dissemination for resource inventory applications, we propose a novel data aggregation strategy and algorithms to obtain the population of the objects (i.e., the resource) to be sensed in the networks. With a set of cautiously validated simulations, we show that the energy consumption in applying our solution is only one third of the original case and scalable to the object population. Experimental results also show that we are able to obtain consistent lower and upper bounds at 70% and 180% of the exact population. While we show the solution works effectively for resource inventory applications, this work suggests more profoundly that there is yet design space to explore in application-specific data aggregation for energy conservation.

Current multicast routing protocols can be classified into three types according to how the multicast tree is established: broadcast and prune (e.g., DVMRP, PIM-DM), membership advertisement (e.g., MO-SPF), and rendezvous-based (e.g., CBT, PIM-SM). Rendezvous-based protocols associate with each logical multicast group address, a physical unicast address, referred to as the 'core' or 'rendezvous point' (RP). Members first join a multicast tree rooted at this rendezvous point in order to receive data packets sent to the group. Rendezvous mechanisms are well suited to large wide-area networks because they distribute group-specific data and membership information only to those routers that are on the multicast distribution tree. However, rendezvous protocols require a bootstrap mechanism to map each logical multicast address to its current physical rendezvous point address. The bootstrap mechanism must adapt to network and router failures but should minimize unnecessary changes in the group-to-RP mapping. In addition, the bootstrap mechanism should be transparent to the hosts. This paper describes and analyzes the bootstrap mechanism developed for PIM-SM. The mechanism employs an algorithmic mapping of multicast group to rendezvous point address, based on a set of available RPs distributed throughout a multicast domain. The primary evaluation measures are convergence time, message distribution overhead, balanced assignment of groups to RPs, and host impact. The mechanism as a whole, and the design lessons in particular, are applicable to other rendezvous-based multicast routing protocols as well.

Using the ns-2-simulator to experiment with different aspects of user- or session-behaviors and network configurations and focusing on the qualitative aspects of a wavelet-based scaling analysis, we present a systematic investigation into how and why variability and feedback-control contribute to the intriguing scaling properties observed in actual Internet traces (as our benchmark data, we use measured Internet traffic from an ISP). We illustrate how variability of both user aspects and network environments (i) causes self-similar scaling behavior over large time scales, (ii) determines a more or less pronounced change in scaling behavior around a specific time scale, and (iii) sets the stage for the emergence of surprisingly rich scaling dynamics over small time scales; i.e., multifractal scaling. Moreover, our scaling analyses indicate whether or not open-loop controls such as UDP or closed-loop controls such as TCP impact the local or small-scale behavior of the traffic and how they contribute to the observed multifractal nature of measured Internet traffic. In fact, our findings suggest an initial physical explanation for why measured Internet traffic over small time scales is highly complex and suggest novel ways for detecting and identifying, for example, performance bottlenecks.This paper focuses on the qualitative aspects of a wavelet-based scaling analysis rather than on the quantitative use for which it was originally designed. We demonstrate how the presented techniques can be used for analyzing a wide range of different kinds of network-related measurements in ways that were not previously feasible. We show that scaling analysis has the ability to extract relevant information about the time-scale dynamics of Internet traffic, thereby, we hope, making these techniques available to a larger segment of the networking research community.

Due to the complexity and scale of the current Internet, large scale simulation is an increasingly important tool to evaluate network protocol design. Parallel and distributed simulation is one appropriate approach to the simulation scalability problem, but it can require expensive hardware and have high overhead. We investigate a complementary solution-simulation abstraction. Just as a custom simulator includes only details necessary for the task at hand, a general simulator can support configurable levels of detail for different simulations. We demonstrate two abstraction techniques in multicast simulations and show that they each help to gain one order of magnitude in performance. Although abstraction simulations are not identical to more detailed simulations, in many cases these differences are small and result in minimal changes in the conclusions drawn from simulations.