Data transmission system and method

A method of transmitting data packets, where randomness is added to the schedule. Universal broadcast schedules using encoding and randomization techniques are also discussed, together with optimal randomized schedules and an approximation algorithm for finding near-optimal schedules

Anti-Jamming Schedules for Wireless Data Broadcast Systems

Modern society is heavily dependent on wireless networks for providing voice and data communications. Wireless data broadcast has recently emerged as an attractive way to disseminate dynamic data to a large number of clients. In data broadcast systems, the server proactively transmits the information on a downlink channel; the clients access the data by listening to the channel. Wireless data broadcast systems can serve a large number of heterogeneous clients, minimizing power consumption as well as protecting the privacy of the clients' locations. The availability and relatively low cost of antennas resulted in a number of potential threats to the integrity of the wireless infrastructure. In particular, the data broadcast systems are vulnerable to jamming, i.e., the use of active signals to prevent data broadcast. The goal of jammers is to cause disruption, resulting in long waiting times and excessive power consumption. In this paper we investigate efficient schedules for wireless data broadcast that perform well in the presence of a jammer. We show that the waiting time of client can be reduced by adding redundancy to the schedule and establish upper and lower bounds on the achievable minimum waiting time under different requirements on the staleness of the transmitted data

Anti-Jamming Schedules for Wireless Broadcast Systems

Modern society is heavily dependent on wireless networks for providing voice and data communications. Wireless data broadcast has recently emerged as an attractive way to disseminate data to a large number of clients. In data broadcast systems, the server proactively transmits the information on a downlink channel; the clients access the data by listening to the channel. Wireless data broadcast systems can serve a large number of heterogeneous clients, minimizing power consumption as well as protecting the privacy of the clients' locations. The availability and relatively low cost of antennas resulted in a number of potential threats to the integrity of the wireless infrastructure. The existing solutions and schedules for wireless data broadcast are vulnerable to jamming, i.e., the use of active signals to prevent data distribution. The goal of jammers is to disrupt the normal operation of the broadcast system, which results in high waiting time and excessive power consumption for the clients. In this paper we investigate efficient schedules for wireless data broadcast that perform well in the presence of a jammer. We show that the waiting time of client can be efficiently reduced by adding redundancy to the schedule. The main challenge in the design of redundant broadcast schedules is to ensure that the transmitted information is always up-to-date. Accordingly, we present schedules that guarantee low waiting time and low staleness of data in the presence of a jammer. We prove that our schedules are optimal if the jamming signal has certain energy limitations

Improving the Multi-Channel Hybrid Data Dissemination System

A major problem with the Internet and web-based applications is the scalable delivery of data. Lack of scalability can hinder performance and decrease the ability of a system to perform as originally designed. One of the most promising solutions to this scalability problem is to use a multiple channel hybrid data dissemination server to deliver requested information to users. This solution provides the high scalability found in multicast, with the low latency found in unicast. A multiple channel hybrid server works by using a push-based multicast channel to deliver the most popular data to users, and reserves the pull-based unicast channel for user requests and delivery of less popular data.The adoption of a multiple channel hybrid data dissemination server, however, introduces a variety of data management problems. In this dissertation, we propose an improved multiple channel hybrid data dissemination model, and propose solutions to three fundamental data management problems that arise in any multiple channel hybrid scheme. In particular, we address the push popularity problem, the document classification problem, and the bandwidth division problem. We also propose a multicast pull channel to the common two-channel hybrid scheme. Our hypothesis that this new channel both improves scalability, and decreases variances in response times, is confirmed by our extensive experimental results. We develop a fully functioning architecture for our three-channel hybrid scheme. In a real world environment, our middleware is shown to provide high scalability for overloaded web servers, while keeping the response times experienced by clients at a minimum. Further, we demonstrate that the practical impact of this work extends to other broadcast-based environments, such as a wireless network

Scheduling for Efficient Data Broadcast over Two Channels

As wireless computer networks grow more popular, we are faced with the problem of providing scalable, high-bandwidth service to a growing number of users. In the wireless domain, “data push” promises to provide superior performance for many applications [1]. The broadcast domain that is typical of wireless communication is very effective in distributing information to large audiences. Work has been done to schedule data broadcast from a server to many clients using the broadcast disk model [3]. However, little of it has looked at methods for more than one channel. We examine a simple two-channel broadcast model and present some interesting scheduling results for this model

Scheduling for Efficient Data Broadcast over Two Channels

Abstract — The broadcast disk provides a way to distribute data to many clients simultaneously. A central server fixes a set of data and a schedule for sending it, and then repeatedly sends the data according to the schedule. Clients listen for data until it is broadcast. We look at the problem of scheduling for two separate channels, where each can have a different broadcast schedule. Our metric for measuring schedule performance is expected delivery time (EDT), the expected value of the total elapsed time between when a client starts listening for data and when the client is completely finished receiving the data. We fix the first channel with a schedule that is optimal for an average case, and look at how to schedule for the second channel. We show two interesting results for sending two items over two channels. The first is that all schedules with equal portions of the two items in the second channel have the same EDT. The second is that for a situation that is symmetric in the two items the optimal schedule is asymmetric with respect to these items. I