Intrusion detection is an important problem in sensor networks. Prior works in static sensor environments show that constructing sensor barriers with random sensor deployment can be effective for intrusion detection. In response to the recent surge of interest in mobile sensor applications, this paper studies the intrusion detection problem in a mobile sensor network, where it is believed that mobile sensors can improve barrier coverage. Specifically, we focus on providing$k$-barrier coverage against moving intruders. This problem becomes particularly challenging given that the trajectories of sensors and intruders need to be captured. We first demonstrate that this problem is similar to the classical kinetic theory of gas molecules in physics. We then derive the inherent relationship between barrier coverage performance and a set of crucial system parameters including sensor density, sensing range, and sensor and intruder mobility. We examine the correlations and sensitivity from the system parameters, and we derive the minimum number of mobile sensors that needs to be deployed in order to maintain the$k$-barrier coverage for a mobile sensor network. Finally, we show that the coverage performance can be improved by an order of magnitude with the same number of sensors when compared to that of the static sensor environment.

Target Tracking is an important problem in sensor networks, where it dictates how accurate a target's position can be measured. In response to the recent surge of interest in mobile sensor applications, this paper studies the target tracking problem in a mobile sensor network (MSN), where it is believed that mobility can be exploited to improve the tracking resolution. This problem becomes particularly challenging given the mobility of both sensors and targets, in which the trajectories of sensors and targets need to be captured. We derive the inherent relationship between the tracking resolution and a set of crucial system parameters including sensor density, sensing range, sensor and target mobility. We investigate the correlations and sensitivity from a set of system parameters and we derive the minimum number of mobile sensors that are required to maintain the resolution for target tracking in an MSN. The simulation results demonstrate that the tracking performance can be improved by an order of magnitude with the same number of sensors when compared with that of the static sensor environment.

In this paper, we study the message delivery capacity problem in delay-constrained mobile sensor networks. The message delivery capacity specifies the maximum percentage of sensing messages that can be successfully delivered to sink nodes within a given time constraint. This captures the overall system capacity in terms of successful sensing message delivery. By taking full advantage of sensor mobility and rendezvous during senor node encounters, messages can be delivered to a sink node either directly or through relays by other sensor nodes. In this paper, for the first time, we present the delay-constrained message delivery capacity formulation in mobile sensor networks. The objective is to maximize the message delivery capacity subject to the delay and buffering constraints. We first identify a number of unique challenges involved in such systems including message relay and buffer replacement mechanisms, and we derive the capacity bound under perfect message relay and buffer replacement mechanisms. Due to an unrealistic assumption about the foreknowledge of sensor moving trajectories, we next proceed to propose a practical algorithm to approximate the maximal message delivery capacity based on current global network knowledge. Furthermore, a distributed algorithm is proposed to reduce the control overhead for information exchange. Finally, we evaluate the algorithms and examine their sensitivity with respect to delay constraints, buffer size and message relay, and replacement schemes.

In this paper, we study the delay-constrained message delivery capacity formulation in mobile wireless networks. The message delivery capacity specifies the maximum percentage of messages that can be successfully delivered to base stations within a given time constraint. By taking full advantage of node mobility and rendezvous during mobile node encounter, messages can be delivered to a base station either directly or through relays by other nodes. We first identify a number of unique challenges involved in such systems including message relay and buffer replacement mechanisms and then derive the capacity bound under perfect message relay and buffer replacement mechanisms. We next prove that this problem is NP-hard. We proceed to propose a practical algorithm to approximate the maximal message delivery capacity. Finally, we evaluate the algorithm and examine the sensitivity with delay constraint, buffer size and message relay and replacement schemes.

In this paper, we study the delay-constrained information coverage problem in mobile wireless networks. Motivated by real application needs, our formulation takes advantage of the node mobility for information collection, which takes place when a node moves into the proximity of stationary base stations. To the best of our knowledge, we present the first formulation for the delay-constrained information coverage problem, which targets at optimal base stations placement with the objective of maximizing information collection within a constrained time. We prove that this problem is NP- hard and we develop theoretical analysis to derive its upper and lower performance bounds. We then develop approximation techniques and use simulations to verify their effectiveness.

Intrusion detection is an important problem in sensor networks. Prior works in static sensor environments show that constructing sensor barriers with random sensor deployment can be effective for intrusion detection. In response to the recent surge of interest in mobile sensor applications, this paper studies the intrusion detection problem in a mobile sensor network, where it is believed that mobile sensors can improve barrier coverage. Specifically, we focus on providing k-barrier coverage against moving intruders. This problem becomes particularly challenging given that the trajectories of sensors and intruders need to be captured.

The peer-to-peer (P2P) live video streaming system has been demonstrated to have great potential in the public Internet; the large-scale deployment of such systems, however, critically relies on how effective they can deal with the high dynamics encountered, in particular during flash crowd. The rationale behind is that the scaling in P2P live video streaming systems is heavily determined by the timing requirement that streaming applications demand. In this paper, we present an analytical and experimental study on the inherent relationship between the time constraint and the system scale. We develop a generic model for P2P live video streaming that focuses on the peer joining process during flash crowd. We first illustrate that the simple notion of "demand vs. supply" model is insufficient in describing the system scale. By computing the peer start-up time distribution, we demonstrate that the scale is affected by several key factors, especially the peer uploading capacity and the initial system size. We further show the scale is essentially bounded by the timing requirement and the system's capability to accommodate flash crowd is subject to a maximum limit.

As handheld devices are getting increasingly popular for delivering multimedia content, this paper presents our ongoing project in developing open source peer-to-peer video streaming solution over the Symbian platform. Specifically, we describe the system architecture and key components, and discuss the challenges and limitations.

Peer-to-peer (P2P) based live video streaming system has emerged as a promising solution for the Internet video streaming applications, partly evident from commercial deployment of several large-scale P2P streaming systems. The key is to leverage the resources available at end users, which offers great potential to scale in the Internet. Flash crowd poses a unique challenge for live streaming systems, in which there could be potentially hundred of thousands of users joining the system during the initial few minutes of a live program. This adds considerable difficulty in particular for a P2P based system in quickly ramping to a scale that can provide reasonable streaming services for newly incoming peers. In this paper, we examine the system dynamics under flash crowd based on measurements obtained from the Coolstreaming system. We are particularly concerned with the impact and user behaviors during flash crowd. The results reveal a number of interesting observations: (1) the system can scale up to a limit during the flash crowd; (2) there is a strong correlation between the number of short sessions and joining rate due to the resource competition among newly joined peers; (3) the user behavior during flash crowd can be best captured by the number of retries and the impatience time.

The peer-to-peer (P2P) based video streaming has emerged as a promising solution for Internet video distribution. Leveraging the resource available at end users, this approach poses great potential to scale in the Internet. We have now seen the commercial P2P streaming systems that are orders of magnitude larger than the earlier academic systems. We believe understanding its basic principles and limitations are important in the design of future systems. The Coolstreaming, first released in summer 2004, arguably represented the first successful large-scale P2P live streaming system. Since then, the system has been significantly modified and commercially launched. This paper takes an inside look at the new Coolstreaming system by exposing its design options and rationale behind them, and examines their implications on streaming performance. Specifically, by leveraging a large set of traces obtained from recent live event broadcast and extensive simulations, we study the workload characteristics, system dynamics, and impact from a variety of system parameters. We demonstrate that there is a highly skewed resource distribution in such systems and the performance is mostly affected by the system dynamics. In addition, we show that there are inherent correlations and fundamental trade-off among different system parameters, which can be further explored to enhance the system performance.

Mobile sensor networks are desirable in a variety of application scenarios, in which information collection is no doubt of great importance. In this paper, we present a mobile sensor network architecture consisting of a potentially large number of mobile sensors and a single or multiple stationary s

In recent years, there has been significant interest in adopting the peer-to-peer (P2P) technology for Internet live video streaming. There are primarily two reasons behind this development: the elimination of infrastructure support and the self-scaling property of P2P systems. The success of our system Coolstreaming represented one of the earliest large-scale P2P video streaming experiments. Since then, there have been several large-scale commercial deployments. With desirable content, these systems have the potential to scale orders of magnitude beyond the existing academic P2P prototypes. However, to transform this potential into reality, we need to understand the key design trade-offs and principles, as well as the design limitations of these systems. There are two main design decisions in a P2P streaming system: (i) How to form an overlay, and (ii) How to deliver the content. Coolstreaming adopts a gossiping protocol for overlay construction, and a swarm-based protocol for content delivery. While these protocols provide excellent flexibility and effectiveness in dealing with system dynamics and random failure, their impact on the performance and the system scalability remain less known. This paper takes an inside look at a commercial system based on the Coolstreaming, called Coolstreaming+. We explore its design choices and the impact of these choices on streaming performance. Specifically, by using internal traces generated by recent live broadcast events, we study the workload, performance, and dynamics of the system. Based on these traces, we show that (1) the churn is the most critical factor that affects the overall performance of the system, and (2) there is a highly skew resource distribution in P2P streaming systems, which has significant impact on resource allocation. We further discuss the impact of these observations on the system properties, and present solutions to deal with various design challenges. In particular, we suggest solutions to deal with the excessive start-up time and high failure rates during flash crowd, which are two of the main challenges any streaming system needs to address.

Peer-to-peer (P2P) technology has found much success in applications like file distributions and VoIP yet, its adoption in live video streaming remains as an elusive goal. Our recent success in Coolstreaming system brings promises in this direction; however, it also reveals that there exist many practical engineering problems in real live streaming systems over the Internet. Our focus in this paper is on a nonoptimal real working system, in which we illustrate a set of existing practical problems and how they could be handled. We believe this is essential in providing the basic understanding of P2P streaming systems. This paper uses a set of real traces and attempts to develop some theoretical basis to demonstrate that a random peer partnership selection with a hybrid pull-push scheme has the potentially to scale. Specifically, first, we describe the fundamental system design tradeoffs and key changes in the design of a Coolstreaming system including substreaming, buffer management, scheduling and the adopt of a hybrid pull-push mechanism over the original pull-based content delivery approach; second, we examine the overlay topology and its convergence; third, using a combination of real traces and analysis, we quantitatively provide the insights on how the buffering technique resolves the problems associated with dynamics and heterogeneity; fourth, we show how substream and path diversity can help to alleviate the impact from congestion and churns; fifth, we discuss the system scalability and limitations.

This paper investigates the problem of call admission control in multi-service wireless cellular networks. Prior studies on call admission control have largely adopted a static approach based on a variation of guard channel policy. Given the highly dynamic traffic behavior in multi-service wireless cellular networks, we believe that a dynamic approach is essential in providing the required service guarantee and the necessary service differentiation for different types of traffic. In this paper, we focus on the connection level performance, and introduce a stable dynamic call admission (SDCA) policy that can effectively deal with the mixed type of traffic. The main objectives of the proposed SDCA are: 1) it has to enforce the QoS guarantee on the dropping probabilities of all traffic; 2) it needs to provide fairness among different class of traffic; and 3) it should maintain stability over a broad range of traffic rates. Its performance is well supported by simulation results.