Mobile devices now rival desktop computers as a method of web browsing. Even so, many web applications are still designed with the desktop setting in mind. As screen sizes of mobile devices continue to get larger, operating smartphones single-handedly becomes increasingly difficult. This paper explores the possibility of automatic operating hand detection by capturing users' touch traces during normal browsing activities. Automatic operating hand detection would enable web applications to adapt their interfaces and better suit the user's laterality. Supervised classifiers were constructed for the primary goal of operating hand detection (left, right), but also to detect hand posture (thumb, index). Both classifiers use features extracted from the touch traces and button clicks on a dataset of 174 users. The resulting classifiers featured true positive rates of 96.0% and 70.1% respectively when tested using 10-fold cross-validation. While previous studies achieved similarly accurate results for operating hand (94.1%) and posture (82.6%) detection, the approach proposed by this paper is not platform-specific and does not rely on access to gyroscopes or accelerometers.

Crowdsensing (CS) is a new data collection paradigm based on the willingness of people to utilize their mobile devices to sense and transmit data of interest. Given the large amount of cellular users, mobile sensor networks will be able to collect enough data to address large-scale societal problems in a fast, easy, and cost-effective manner. One important issue in CS is that of privacy; without appropriate privacy-preserving mechanisms, many users will not be willing to participate in the data collection process. This paper presents the state-of-the-art in privacy-preserving mechanisms for CS systems. After a general description of CS systems and their main components, this paper addresses the most important issues to consider in the design, implementation, and evaluation of privacy-preserving mechanisms. Then, following a new taxonomy, the most important mechanisms available in the literature are described and qualitatively evaluated. Finally, this paper presents research challenges that should be addressed in order to improve the performance of future privacy-preserving mechanisms for CS systems.

This paper is motivated by work on a real-time Android navigation system using accelerometer, gyroscope, and camera data. We observed that our attempts at combining data from these different sensors yielded time series with jitter, i.e., inaccurate timestamps, that negatively affected program correctness and reliability. Thus, the aim of this paper is to help Android developers anticipate, assess, and understand problems with data quality in sensor-dependent applications. Our analysis focuses on jitter in timestamps obtained from Android's SensorManager and CameraManager services. We demonstrate the presence and severity of jitter obtained through these services and explain the characteristics of Android that originate jitter, resulting in a taxonomy of the various sources of jitter. Finally, we discuss the results of a quantitative analysis of jitter performed on three Android mobile devices (HTC One M8, Google Nexus 5, and Asus Zenfone 2) and provide recommendations on how Android developers can design sensing applications that will behave correctly across the majority of mobile devices.

In 2010, There were more than forty million doctor visits of people with lower joints complaints, including more than one million surgeries involving total or partial hip, knee, and ankle replacement in the US. Generally, these procedures require some level of post-op physical therapy (PT), to recover most of the walking capabilities. Therefore, it is important to have a method to assess the walking capabilities of the patients in order to track their improvement over time. This paper presents a smartphone-based system to perform the Functional Gait Analysis test to assess the balance and fall risk of patients with walking difficulties. The paper addresses most of the shortcomings of current systems for the same purpose, including: 1) low cost, as it uses one off-the-shelf smartphone and the sensors embedded in it; 2) self-care, as it does not need of a specialist or physician; 3) mobile; 4) accurate, as it eliminates the ambiguities incurred by specialists; 5) information-based, as it enhances the diagnostic including other metrics that assess the gait of individual limbs and provides historical data to assess the evolution of the patient over time; and 6) easy to use and unobtrusive.

Participatory Sensing (PS) is a new data collection paradigm based on the voluntary participation of many cellular users equipped with smart applications, a large diversity of sensors, and Internet connectivity at all times. Although many PS-based applications can be foreseen to solve interesting and useful problems, many of them have not been fully implemented and used in practice because of privacy concerns. Compounding the problem, privacy-preserving mechanisms introduce additional issues. For example, one of the most important problems is that of the quality of the information provided by the PS system to the final users. The problem is that, in order to protect the privacy of the users, most privacy-preserving mechanisms modify their real locations, which makes the reported data as if it had been measured from a different location, introducing noise or false information in the system and to the final users. Another important problem is that of the energy consumption. Privacy-preserving mechanisms consume extra energy and users are not very willing to use PS applications if they drain their batteries considerably faster. This paper proposes a hybrid privacy-preserving mechanism that combines anonymization, data obfuscation, and encryption techniques to increase the quality of information and privacy protection without increasing the energy consumption in a significant manner. A new algorithm is proposed that dynamically changes the cell sizes of the grid of the area of interest according to the variability of the variable of interest being measured and chooses different privacy-preserving mechanisms depending on the size of the cell. In small cells, where users can be identified easier, the algorithm uses encryption techniques to protect the privacy of the users and increase the quality of the information, as the reported location is the real location. On the other hand, anonymization and data obfuscation techniques are used in bigger cells where the variability of the variable of interest is low and therefore it is more important to protect the real location (privacy) of the user. We evaluated our hybrid approach and other privacy-preserving mechanisms using a real PS system for air pollution monitoring. Our experiments show the better performance of the proposed hybrid mechanism and the existing trade-offs in terms of privacy, quality of information to the final user, and energy consumption.

This paper presents a novel framework that includes an inhomogeneous (time-variant) Hidden Markov Model (HMM) and learning from data concepts. The framework either recognizes or estimates user contextual inferences called `user states' within the concept of Human Activity Recognition (HAR) for future context-aware applications. Context-aware applications require continuous data acquisition and interpretation from one or more sensor reading(s). Therefore, device battery lifetimes need to be extended due to the fact that constantly running built-in sensors deplete device batteries rapidly. In this sense, a framework is constructed to fulfill requirements needed by applications and to prolong device battery lifetimes. The ultimate goal of this paper is to present an accurate user state representation model, and to maximize power efficiency while the model operates. Most importantly, this research intends to create and clarify a generic framework to guide the development of future context-aware applications. Moreover, topics such as user profile adaptability and variant sensory sampling operations are examined. The proposed framework is validated by simulations and implemented in a HAR-based application by the smartphone accelerometer. According to the results, the proposed framework shows an increase in power efficiency of 60% for an accuracy range from 75% up to 96%, depending on user profiles.

On behalf of the chairs and technical program committees of the different workshops, it is with great pleasure that we welcome you to Madrid for the 2013 IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks (WoWMoM). We are certain that you will enjoy the excellent quality of the technical program and the workshops, as well as the fine places and food of Madrid and surrounding cities.

Context-aware applications have been the focus of extensive research, yet their implementation in mobile devices usually becomes challenging due to restrictions of processing and energy. In this work, we present, demonstrate, and evaluate a mobile platform for real-time human activity recognition. The evaluation results indicate that the system can be implemented in real scenarios meeting accuracy, response time, and energy consumption requirements.

Context-aware applications have been the focus of extensive research yet their implementation in mobile devices usually becomes challenging due to restrictions in regards to processing power and energy. In this paper, we propose a mobile platform to provide real-time human activity recognition. Our system features (1) an efficient library, MECLA, for the mobile evaluation of classification algorithms; and (2) a mobile application for real-time human activity recognition running within a Body Area Network. The evaluation indicates that the system can be implemented in real scenarios meeting accuracy, response time, and energy consumption requirements.

Participatory sensing (PS) systems rely on the willingness of mobile users to participate in the collection and reporting of data using a variety of sensors either embedded or integrated in their cellular phones. However, this new data collection paradigm has not been very successful yet mainly because of the lack of incentives for participation. Although several incentive schemes have been proposed to encourage user participation, none has used location information and imposed budget and coverage constraints, which will make the scheme more realistic and efficient. We propose a recurrent reverse auction incentive mechanism with a greedy algorithm that selects a representative subset of the users according to their location given a fixed budget. Compared to existing mechanisms, our incentive scheme improves the area covered by more than 60 percent acquiring a more representative set of samples after every round while maintaining the same number of active users in the system and spending the same budget.

Location-based information systems (LBIS) have shown growth in the last years thanks to the popularization of cheap GPS-enabled mobile devices with connectivity to the Internet. At the same time, users have made their locations more available than ever, representing a major privacy problem, as attackers could easily determine their victims' common paths or actual locations. As a result, some techniques have been designed to protect the users' private information while allowing Location Based Service systems (LBS) to continue growing. Location obfuscation is a technique that alters, substitutes, or generalizes the real location of the users to protect them against malicious attacks. Moreover, there are activities that require a high level of accuracy while also maintaining the protection of the location, such as fleet management or transportation of valuables. In this work, a light-weight and fully reversible location obfuscation technique named Matlock is presented. Matlock, based on matrix obfuscation, requires low computation per operation and hides the location in both spatial and temporal dimensions. The performance evaluation shows how this technique alters the location of paths from different geographical regions, produces a non-morphologically similar path to the original path, and generates increasing distance functions between the original and the obfuscated paths, which together should reduce the probability of using estimation techniques to perform deobfuscation of the information.

This paper presents a multiobjective model for the simultaneous optimization of the number of relays and the energy dissipation when deploying a wireless sensor networks to monitor specific locations in an area. In order to solve the model, a hybrid evolutionary algorithm with two local searches is proposed an implemented. As the algorithm returns a set of efficient solutions, the tradeoff among placements in their number of relays with their energy dissipation is explored. The evaluation shows that the energy can be diminished greatly by choosing not the most efficient placement in terms of number of relays but other placement with more relays. In our experiments, it was found that the solution with one or two more relay sensors than the efficient placement helped greatly in diminishing the energy. The proposed algorithm also showed better approximations than an approximation problem in the literature to the minimal number of relays.

Real-time location-based tracking applications require of continuous GPS calculations and transmissions, which consume a considerable amount of the phone's battery. As a result, methods have been devised to reduce the amount of GPS calculations and transmissions without sacrificing the tracking capabilities of the applications. One of these methods is based on a state machine that dynamically changes the frequency of GPS updates according to the user direction, speed, received signal strength, and other factors. However, the state machine, although efficient in terms of energy savings, still presents one major problem: it does not take into account the presence of noise in GPS data. In order to distinguish between actual GPS data and noise, three versions of the Kalman filter have been implemented within the state machine. These modified Kalman filters remove noisy GPS fixes with little to no input from the user in a very efficient manner. The filters are discussed in detail and tested against one another to determine which one removes GPS noise better and which one reduces the energy consumption in the cellular phone more with no loss of valuable tracking data. Experiments conducted show the Adaptive Kalman Filter as the best performer. No loss of valuable tracking data is seen while it introduces a significant decrease in the number of “asleep” fixes. The Adaptive Robust Kalman Filter is the second best performer of the three filters. It shows no loss of tracking data, while a slightly less decrease in “sleep” fixes. Testing shows that the Robust Kalman Filter is the worst performer of the three. This is because the Robust Kalman Filter is the slowest version to “wake up” and make transitions to a “sleep” state.

Topology control is a well-known strategy to save energy and extend the lifetime of wireless sensor networks. It consists of topology construction and topology maintenance algorithms. While topology construction builds a reduced topology, topology maintenance changes the reduced topology when the current one is no longer optimal. The selection of an appropriate topology maintenance technique is rarely included in the evaluation of topology control solutions, even though the impact of such decision in the lifetime of the network (in terms of number of nodes or coverage) has been shown before. This paper makes two important contributions. First, it introduces a new topology construction algorithm called A3Cov, based on the A3 protocol, which increases the coverage ratio considerably compared to the original version. Second, the A3Cov protocol is evaluated jointly with four topology maintenance techniques to determine the influence of the different maintenance schemes on the area coverage and the network lifetime. The results show that the dynamic global topology maintenance techniques with A3Cov provide the best coverage and network lifetime for a substantially longer period of time compared to the ACOS protocol.

This paper presents ABLA, a novel multiobjective ant colony-based optimization algorithm to address the bin packing problem with load balancing. ABLA incorporates (1) a new probabilistic decision rule that builds solutions by making use of individual pheromone matrices for each objective function; (2) a new pheromone updating approach in which ants deposit variable amounts of pheromone; (3) two new local search methods to improve load balancing: LBH and LBH-AB; and (4) the Pareto dominance approach to select optimal solutions. ABLA is compared to a Multiobjective Max-Min Ant System (MO-MMAS) and an adapted multiobjective version of the First-Fit Decreasing (FFD) algorithm, which is the best known ρ-approximation algorithm for the bin packing problem. Results show that ABLA finds better solutions than both FFD and MO-MMAS, and that LBH and LBH-AB noticeably improve the load balancing across bins.

It is widely known that in wireless sensor networks (WSN), energy efficiency is of utmost importance. As a result, a common protocol design guideline has been to trade off some performance metrics such as throughput and delay for energy. This has also gone well in line with many applications for WSN. However, there are other applications with real-time constraints, such as those involved in surveillance or control loops, for which WSN still need to be energy efficient but also need to provide better performance, particularly latency. This paper presents a WSN cross-layer design approach involving the physical, MAC, and network layers that not only preserves the energy efficiency of current alternatives but also coordinates the transfer of packets from source to destination in such a way that latency and jitter are improved considerably. Our simulations show how LEMR (Latency, Energy, MAC and Routing), the proposed protocol, outperforms the well-known TMAC and S-MAC protocols in both performance metrics.

Topology control is a well-known strategy to save energy and extend the lifetime of wireless sensor networks. This paper introduces the A3 (a tree) algorithm, a simple, distributed, and energy-efficient topology construction mechanism that finds a sub-optimal Connected Dominating Set (CDS) to turn unnecessary nodes off while keeping the network connected and providing complete communication coverage. A3 utilizes a weighted distance-energy-based metric that permits the network operator to trade off the lengths of the branches (distance) for the robustness and durability of the tree (energy). Comparisons with other well-known topology construction mechanisms show the superiority of the proposed scheme in terms of the number of active nodes and energy efficiency. Simulation experiments show that to achieve complete communication coverage, A3 needs only 6% and 41% of the nodes active in dense and sparse scenarios, versus 8% and 43% and 5% and 43% of the EECDS and CDS- Rule-K algorithms, respectively. More importantly, the proposed protocol presents a low linearly bounded worst-case amount of messages per node that limits the overhead and the energy usage compared to a non-linear increase of the EECDS and CDS-Rule- K algorithms.

Voice over IP and video applications continue to increase the amount of real-time traffic over the Internet. These applications utilize the UDP protocol because TCP is not suitable for streaming applications since its congestion control mechanism can change the connection's transmission rate drastically, affecting the user-perceived quality of the transmission. Nonetheless, the use of end-to-end flow and congestion control mechanisms for streaming applications has been acknowledged as an important measure to ease or eliminate the congestion collapse problem in the Internet, and the unfairness problem that exist when TCP and UDP share the same congested bottleneck link. In this paper, we propose the smooth fair TCP SACK-based (SF-SACK) protocol to address these problems. SF-SACK implements the well-known end-to-end window-based congestion control algorithm of TCP but uses an additive increase smooth decrease (AISD) strategy that considers history in the evolution of the congestion window. Through simulations and experimentation, we show that if SF-SACK is used by both streaming and data-oriented applications, streaming applications receive a smooth service, and fairness is achieved. If SF-SACK is used for streaming applications only, it is unfair to TCP (not TCP-friendly) but substantially fairer and beneficial than UDP.

Many methods for end-to-end capacity estimation over wired networks assume that link capacities are constant and that all cross-traffic interaction occurs through queuing delays at node buffers. However, wireless ad hoc networks do not conform to these assumptions due to the shared and unreliable nature of the transmission medium. In this paper we distinguish the concept of end-to-end bandwidth (the maximum rate that can be achieved when the resources along the path are not shared with competing traffic) from that of end-to-end capacity (the minimum transmission rate among the nodes conforming the path) and show that the former is a random variable distributed within some range, which depends on the packet length, among other factors. After developing a simple theoretical framework to compare with, we devise a simple and effective dispersion-based method to estimate the mean end-to-end bandwidth for any packet length. The method is shown to be efficient, to converge quickly to an accurate estimate for any packet length, to be robust against cross-traffic, and to timely track bandwidth variations.

Abstract The pervasiveness of the transport control protocol (TCP) and the proliferation of wireless local area networks (WLAN) of the 802.11 type make the topic of TCP performance over last hop wireless networks very relevant. The Snoop protocol, a link layer solution introduced several years ago to improve the performance of TCP in this scenario, has been shown to neglect its benefits to the most widely used TCP version, TCP SACK. In this paper, we introduce the TCP SACK‐Aware Snoop protocol to address this problem. Our results indicate that the TCP SACK‐Aware Snoop protocol improves the performance of TCP SACK by around 30% compared with the original Snoop protocol and by about 8% in an environment where no TCP enhancing mechanism is in place. In addition, we introduce further modifications to the proposed protocol to make its advantages available to any TCP sender. We also show that the mechanism does not introduce unfairness among TCP sources and somewhat protects TCP against UDP traffic. Our results show important throughput improvements to all TCP versions and demonstrate that the TCP SACK‐Aware Snoop protocol shields TCP from last hop wireless losses providing throughtput values very close to the maximum possible. Copyright © 2006 John Wiley & Sons, Ltd.

Location-based routing (LBR) is one of the most widely used routing strategies in large-scale wireless sensor networks (WSN). With LBR, small, cheap and resource constrained nodes can perform the routing function without the need of complex computations and large amount of memory space. Further, the nodes don't need to incur in energy consuming periodic advertisements because routing tables, in the traditional sense, are not needed. One important assumption made on most LBR protocols is the availability of a location service or mechanism that the nodes can utilize to find other nodes positions. Although several mechanisms exist in the literature, no efficient mechanism is available for a source to find the location of the sink or sinks. In this paper, we introduce the Anchor Location Service (ALS) protocol, a grid-based location service strategy for source nodes to find the sinks' locations and support location-based routing in large-scale wireless sensor networks. We describe the grid set up and query processes and evaluate the delay and overhead of this mechanism by varying the number of sinks, considering networks of different sizes, and the case where the sink nodes move, not common in the literature. Using simulations, we demonstrate that ALS provides the required service in a scalable and efficient manner.

In this paper, we present a low cost and flexible testbed to evaluate the performance of available bandwidth estimation tools in a common and controlled environment. In addition, we include a model based on a network of M/M/I queues to have an analytical reference to compare the experiments with. We then utilize the proposed testbed and model to evaluate the performance of Pathload, IGI, and Spruce, three well-known bandwidth estimation tools. Our main results indicate that Pathload is the most accurate tool but the slowest to converge. IGI, on the other hand, is the fastest tool but the least accurate. Spruce is the least intrusive tool with intermediate accuracy and convergence time

Groups of autonomous and semi-autonomous robots are being used in many different applications. Similarly, wireless ad hoc networks are being used more and more as their communication platform of choice because they are infrastructureless, self-configurable and self-forming networks with multi-hop capabilities. However, uncontrolled node mobility may still cause partitions in the network topology, isolating robots from the network or even losing them, hindering the mission's success. In this paper, we propose a cross layer design-based control layer algorithm that finds and maintains stable links among the mobile nodes and the main controller

Localization is a key function in Wireless Sensor Networks (WSNs). Many applications and internal mechanisms require nodes to know their location. This work proposes a new sequential estimation algorithm for distributed cooperative localization, whose simplicity makes it amenable to self-localization in Wireless Sensor Networks (WSNs), characterized by their restricted resources in energy and computation. The algorithm is inspired in sequential Monte-Carlo estimation techniques, viz. particle filters, that excel in robustness and simplicity for estimation applications. However, particle filters require significant amounts of memory and computational power for managing large numbers of particles. The presented technique reduces the number of particles, while retaining the convergence, accuracy and simplicity properties, as demonstrated in simulation experiments.

No abstract available.

The increasing deployment of unresponsive streaming applications has triggered the design of a number of new mechanisms and protocols to reduce the potential risk of unfairness and congestion collapse in the Internet. Fair non-per flow active queue management (AQM) schemes, such as BLACK, have recently been proposed to maintain fairness when unresponsive constant bit rate UDP flows share a bottleneck link with responsive TCP traffic. Similarly, TCP-friendly protocols have been developed to provide smooth congestion control that is suitable for multimedia applications while still being compatible with TCP. However, the performance of these fair AQM mechanisms has not been evaluated when different TCP-friendly flows compete against TCP versions. As TCP-friendly protocols react to packet drops differently from TCP, the various AQM schemes might punish some flows unfairly. However, this aspect has not been studied yet. The paper provides two key contributions. First, it provides the first comprehensive evaluation of fair AQM schemes under the presence of various types of TCP friendly traffic. From experimental results, we found that a fair AQM scheme must be chosen not only based on its performance or capability to deal with unresponsive flows as is usually done, but also considering its performance when other types of flows are included, such as TCP-friendly sources. Second, the paper presents an enhanced version of BLACK that outperforms all of the other fair non per-flow state information AQM schemes.

It has been demonstrated that advertising the availability of wavelength and converter resources in all-optical DWDM transport networks with sparse wavelength conversion capabilities can drastically improve the blocking performance of these networks thus achieving better usage of the network resources. An important aspect with consequences in network performance is when to originate the wavelength-availability and converter-availability link state advertisements (LSAs). Frequent link-state advertisements could overwhelm the network control plane with many update messages that need to be processed. On the other hand, delaying these advertisements could result in inaccurate link-state information thus degrading the network blocking performance. In this paper, we propose two different link-state update policies to advertise the availability of wavelength and converter resource in all-optical DWDM transport networks with sparse wavelength conversion capabilities. The first one is very simple and serves as our base policy for comparison. The second policy, which is very efficient in handling the dynamic nature of all-optical DWDM networks with different degrees of wavelength conversion, reduces the number of LSAs considerably while maintaining the call blocking probability.

Future applications will need steady transfer rates in the order of gigabits or even terabits per second in order to exchange exabytes of data in a reasonable amount of time and support collaborative scientific work. Although it is expected that next generation optical networks, computing and storage technologies will support this scenario, it has been shown that communications protocols, and in particular the widely used TCP protocol, will become the bottleneck. In this paper we present a performance evaluation of TCP Tahoe, Reno, New Reno, SACK, Vegas, Westwood and highspeed TCP over optical channels. We compared them in the same environment and found that the window-based mechanism of current TCP implementations is not suitable to achieve high link utilization, and that other congestion control mechanisms, such as the ones utilized by Vegas and Westwood, are more appropriate and provide better performance. In addition, we propose a simple modification to TCP Vegas that further improves its performance.

Wireless sensor networks (WSN) consist of thousands of tiny and low cost nodes with very limited energy, computing power and communication capabilities. We consider these issues in the design of a simple, scalable, energy-efficient location aided routing (SELAR) protocol for WSN. In SELAR, location and energy information of neighboring nodes together with the location information of the sink node are used to perform the routing function. Through simulations, we show that SELAR performs considerably better than flooding in terms of network lifetime, energy distribution, and amount of data delivered.

In this paper, we propose a novel routing framework for all-optical dense wavelength-division-multiplexing transport networks with sparse wavelength conversion capabilities. The routing framework includes an integer linear programming formulation to handle the static lightpath establishment problem and a novel open shortest path first protocol extension that advertises the availability of wavelength usage and wavelength conversion resources. Our routing framework addresses the limitations of the extensions presented in the literature because it also includes: 1) an efficient flooding protocol that is suitable for the dynamic nature of these networks and 2) an efficient route and wavelength computation engine that minimizes connection costs without hindering the blocking probability.

Abstract In order to understand the behaviour of upper‐layer protocols and to design or fine tune their parameters over wireless networks, it is common to assume that the underlying channel is a flat Rayleigh fading channel. Such channels are commonly modeled as finite state Markov chains. Recently, hidden Markov models have also been employed to characterize these channels. In this paper, we study the different models that have been proposed along with the analysis of their validity. We start by presenting some preliminary concepts related to the modeling of the wireless communications channel. We then proceed to introduce finite state Markov channel models (FSMCs) along with the relations between them and the modulation schemes, error control protocols and channel coding. We propose and study the effects of taking into account the fading process in its characterization. We finish with a discussion on hidden Markov models for Rayleigh fading channel modeling. Copyright © 2004 John Wiley & Sons, Ltd.

In this paper, we present the BLACK scheme that aims to prevent the unfairness problem generated by high bandwidth unresponsive flows. The scheme needs to store only a small amount of state information to maintain and exercise its fairness mechanism and utilizes a packet sampling technique that estimates both the flow's buffer occupancy fraction and the number of active flows. When working in conjunction with RED, BLACK has shown not only to be able to handle unresponsive traffic, but also improve the fairness among TCP connections with different round-trip delays in some scenarios.

Several traffic characterization studies have been performed on wireless LAN with the main objective of realizing good and accurate models, in particular to model the errors in the wireless channel. In this paper we are more interested in the effects of those errors on the higher layer protocol. Using two freely available tools to send and receive real-time streams and collect and analyze traces, we send MPEG-4 encoded video frames over a 11 Mbit/s, 802.11b wireless LAN to characterize the errors in the channel and the effect of those errors on the quality of the movie. We performed an experiment considering three distances from the access point (10, 50 and 75 feet away) and four packet sizes (500, 750, 1000 and 1500 bytes). We found that a tradeoff exists between the packet size and the amount of information lost. Small packets affect B and/or P frames most of the time and when they, affect I frames the amount of information lost is minimal. On the other hand, small packets also produce bigger error bursts, affecting I frames more. Packets of 750 bytes are a good compromise. In addition, we found that the distribution of the error length and error free length in number of packets is similar to those found in the former 2 Mbit/s wireless LAN.

Several attempts have been made to assess the performance of TCP over wireless networks and several solutions have been proposed to improve its performance. Even though many different TCP versions and solutions exist, so far they have not been studied together. In this paper we include a simulation-based performance analysis of the most important TCP versions over wireless networks. In addition, we analyze those TCP versions in the same environment but including the Snoop protocol and find that TCP Vegas and SACK present an opposite behavior.

In spite of the availability of sophisticated network quality of service (QoS) guaranteeing mechanisms, it is apparent that a large number of applications will continue using the best effort service class. The main reason for this is that the QoS guaranteeing mechanisms are complex and many applications are not capable of using these complex services. At the same time, the standard best effort service is rather unpredictable and hence insufficient for many applications. Thus augmenting best effort services to an appropriate standard without incurring a high level of complexity is a necessary. In this paper two such augmentations are described in the context of the UBR service ATM networks. Selective packet discarding is used to achieve the necessary goals.

The performance analyses of selective packet dropping policies have usually been performed using homogeneous traffic sources and under one node scenarios. In this paper we focus our attention not only on heterogeneous sources but also heterogeneous environments. We present simulation results of application level performance for heterogeneous traffic sources under three different packet dropping schemes: partial packet discard (PPD), early packet discard (EPD), and preemptive partial packet discard (pPPD). In addition, we also present simulation results for homogeneous sources over multi-hop networks with heterogeneous packet dropping policies.

Selective packet dropping policies have been used to reduce congestion and transmission of traffic that would inevitably be retransmitted in ATM networks. Common dropping policies proposed are drop-tail, partial packet discard (PPD), early packet discard (EPD) and their recent variations. However, depending on various circumstances, particularly in multi-hop networking environments, application throughput may be quite poor and newer schemes are necessary. In this paper, we first study the performance of existing dropping schemes and identify their shortcomings. Then we propose a new dropping policy called preemptive PPD (pPPD) that exhibits superior performance.