In this paper, we present a comprehensive analysis of the performance of a wireless sensor network based target tracking system using the Particle Filter. In particular, we evaluate the effect of various network design parameters such as the number of nodes, number of generated particles, and sampling interval on the tracking accuracy and computation time of the tracking system. Based on our analysis, we also present recommendations on suitable values for the relevant network design parameters, which provide a reasonable tradeoff between accuracy and computational expense for this problem. In addition, we also analyse the theoretical Cram´er-Rao Bound as the benchmark for the best possible tracking performance. We demonstrate that the results from our simulations closely match the theoretical bounds. We also present initial results from experiments comprising of a 25 node wireless sensor network. Initial experimental results are promising and show that the PF based estimation is suitable for detection and tracking using inexpensive wireless sensor network devices.

It is an undeniable fact that people want information. Unfortunately, even in today`s highly automated society, a lot of the information we desire is still manually collected. An example is fuel prices where websites providing fuel price information either send their workers out to manually collect the prices or depend on volunteers manually relaying the information. This paper proposes a novel application of wireless sensor networks to automatically collect fuel prices from camera images of road-side price board (billboard) of service (or gas) stations. Our system exploits the ubiquity of mobile phones that have cameras as well as users contributing and sharing data. In our proposed system, cameras of contributing users will be automatically triggered when they get close to a service station. These images will then be processed by computer vision algorithms to extract the fuel prices. In this paper, we will describe the system architecture and present results from our computer vision algorithms. Based on 52 images, our system achieves a hit rate of 92.3% for correctly detecting the fuel price board from the image background and reads the prices correctly in 87.7% of them. To the best of our knowledge, this is the first instance of a sensor network being used for collecting consumer pricing information. © 2008 Springer-Verlag Berlin Heidelberg.

Success of Wireless Sensor Networks largely depends whether the deployed network can provide desired coverage with acceptable network lifetime. This paper proposes a distributed protocol for ensuring area coverage using a combination of mobile and static sensor nodes. Most of the assumptions made in our approach are realistic (sensing model, movement thresholds based on real radio characteristics etc.) and implementable in real-life applications. We demonstrate that, for different type of initial deployments, our proposed movement algorithms consume only 30-40% of the energy consumed by the basic virtual force algorithm. We formulated our problem as Integer Linear Program to arrive at idealistic optimal solutions that form basis of our performance comparison. We validated our results through extensive discrete event simulations. © Springer-Verlag Berlin Heidelberg 2007.

Over the past decade, the problem of achieving fair bandwidth allocation on a link shared by multiple traffic flows has been extensively researched. However, as these flows traverse a computer network, they share many different kinds of resources, such as links, buffers, and router CPU. The ultimate goal should hence be overall fairness in the allocation of multiple resources rather than a single specific resource such as link bandwidth. In this paper, we present a novel scheduler, called Prediction-based Composite Fair Queuing (PCFQ), which jointly allocates the fair share of the link bandwidth and processing resources to all competing flows. We derive the worst-case delay bound, the work complexity, and the relative fairness bound for the PCFQ scheduler and show that it outperforms a system consisting of separate bandwidth and CPU schedulers. We further present simulation results which illustrate the improved performance characteristics achieved by PCFQ. We also demonstrate that our composite scheduler can be easily implemented on an off-the-shelf network processor such as the Intel IXP 2400. Experimental results from the IXP 2400 implementation highlight the effectiveness and high performance of this algorithm in a real-world system.

Over the past decade, the problem of fair bandwidth allocation among contending traffic flows on a link has been extensively researched. However, as these flows traverse a computer network, they share different kinds of resources ( e. g., links, buffers, router CPU). The ultimate goal should hence be overall fairness in the allocation of multiple resources rather than a specific resource. Moreover, conventional resource scheduling algorithms depend strongly upon the assumption of prior knowledge of network parameters and cannot handle variations or lack of information about these parameters. In this paper, we present a novel scheduler called the Composite Bandwidth and CPU Scheduler ( CBCS), which jointly allocates the fair share of the link bandwidth as well as processing resource to all competing flows. CBCS also uses a simple and adaptive online prediction scheme for reliably estimating the processing times of the incoming data packets. Analytically, we prove that CBCS is efficient, with a per-packet work complexity of O(1). Finally, we present simulation results and experimental outcomes from a real-world implementation of CBCS on an Intel IXP 2400 network processor. Our results highlight the improved performance achieved by CBCS and demonstrate the ease with which it can be implemented on off-the-shelf hardware.

The concept of providing mobile Internet connectivity for passengers in public transport vehicles, where users connect to a local network that attaches to the Internet via a mobile router and a wireless link, has become increasingly popular in recent years, as evidenced by the growing amount of commercially available systems and associated research and standardization activities. The challenge of providing wireless connectivity to networks in motion is compounded by the highly dynamic nature of the user population and the strict Quality-of-Service (QoS) requirements of many applications typical of such environments. As a result, several protocols extending Internet QoS support approaches to on-board mobile networks have been proposed in the past. In this paper, we focus on modeling and performance evaluation of periodical aggregation of resource reservation messages, which forms the basis of the On-Board RSVP protocol. We present a model consisting of a discrete-time, multiple-server and finite-capacity queueing system with bulk arrivals and departures, conduct a detailed analysis of the model, and use it to evaluate the performance of the resource reseration aggregation scheme in a practical scenario. The validity of our model is also backed by extensive simulation results. © 2007 IEEE.