Mobile Ad Hoc Networks (MANETs) provide rapidly deployable and self-configuring network capacity required in many critical applications, e.g., battlefields, disaster relief and wide area sensing. In this paper we study the problem of efficient data delivery in sparse MANETs where network partitions can last for a significant period. Previous approaches rely on the use of either long range communication which leads to rapid draining of nodes ’ limited batteries, or existing node mobility which results in low data delivery rates and large delays. In this paper, we describe a Message Ferrying (MF) approach to address the problem. MF is a mobility-assisted approach which utilizes a set of special mobile nodes called message ferries (or ferries for short) to provide communication service for nodes in the deployment area. The main idea behind the MF approach is to introduce non-randomness in the movement of nodes and exploit such non-randomness to help deliver data. We study two variations of MF, depending on whether ferries or nodes initiate proactive movement. The MF design exploits mobility to improve data delivery performance and reduce energy consumption in nodes. We evaluate the performance of MF via extensive ns simulations which confirm the MF approach is efficient in both data delivery and energy consumption under a variety of network conditions.

CarTel is a mobile sensor computing system designed to collect, process, deliver, and visualize data from sensors located on mobile units such as automobiles. A CarTel node is a mobile embedded computer coupled to a set of sensors. Each node gathers and processes sensor readings locally before delivering them to a central portal, where the data is stored in a database for further analysis and visualization. In the automotive context, a variety of on-board and external sensors collect data as users drive. CarTel provides a simple query-oriented programming interface, handles large amounts of heterogeneous data from sensors, and handles intermittent and variable network connectivity. CarTel nodes rely primarily on opportunistic wireless (e.g., Wi-Fi, Bluetooth) connectivity—to the Internet, or to “data mules ” such as other CarTel nodes, mobile phone flash memories, or USB keys—to communicate with the portal. CarTel applications run on the portal, using a delaytolerant continuous query processor, ICEDB, to specify how the mobile nodes should summarize, filter, and dynamically prioritize data. The portal and the mobile nodes use a delaytolerant network stack, CafNet, to communicate. CarTel has been deployed on six cars, running on a small scale in Boston and Seattle for over a year. It has been used to analyze commute times, analyze metropolitan Wi-Fi deployments, and for automotive diagnostics.

"Access is the killer app" [3] is the vision of the Daedalus project at U.C. Berkeley. Being able to be connected seamlessly anytime anywhere to the best network still remains an unfulfilled goal. Often, even determining the "best" network is a challenging task because of the widespread deployment of overlapping wireless networks. In this paper, we describe a policy-enabled handoff system that allows users to express policies on what is the "best" wireless system at any moment, and make tradeoffs among network characteristics and dynamics such as cost, performance and power consumption. We designed a performance reporting scheme estimating current network conditions, which serves as input to the policy specification. A primary goal of this work is to make it possible to balance the bandwidth load across networks with comparable performance. To avoid the problem of handoff instability, i.e., many mobile hosts making the same handoff decision at essentially the same time, we designed r...

Abstract — Infostations provide a new way to look at the problem of providing high data rate wireless access. By allowing delayed message delivery, we can lift the constraint on ubiquitous coverage inherited from voice cellular systems. The reduction of coverage results in significant capacity gains, showing the possibility for low cost broadband wireless data services. We give an overview of ongoing research on the Infostation concept.

Multihop data delivery through vehicular ad hoc networks is complicated by the fact that vehicular networks are highly mobile and frequently disconnected. To address this issue, we adopt the idea of carry and forward, where a moving vehicle carries a packet until a new vehicle moves into its vicinity and forwards the packet. Being different from existing carry and forward solutions, we make use of predictable vehicle mobility, which is limited by traffic pattern and road layout. Based on the existing traffic pattern, a vehicle can find the next road to forward the packet to reduce the delay. We propose several vehicle-assisted data delivery (VADD) protocols to forward the packet to the best road with the lowest data-delivery delay. Experimental results show that the proposed VADD protocols outperform existing solutions in terms of packet-delivery ratio, data packet delay, and protocol overhead. Among the proposed VADD protocols, the Hybrid Probe (H-VADD) protocol has a much better performance.

Cabernet is a system for delivering data to and from moving vehicles using open 802.11 (WiFi) access points encountered opportunistically during travel. Using open WiFi access from the road can be challenging. Network connectivity in Cabernet is both fleeting (access points are typically within range for a few seconds) and intermittent (because the access points do not provide continuous coverage), and suffers from high packet loss rates over the wireless channel. On the positive side, WiFi data transfers, when available, can occur at broadband speeds. In this paper, we introduce two new components for improving open WiFi data delivery to moving vehicles: The first, QuickWiFi, is a streamlined client-side process to establish end-to-end connectivity, reducing mean connection time to less than 400 ms, from over 10 seconds when using standard wireless networking software. The second part, CTP, is a transport protocol that distinguishes congestion on the wired portion of the path from losses over the wireless link, resulting in a 2 × throughput improvement over TCP. To characterize the amount of open WiFi capacity available to vehicular users, we deployed Cabernet on a fleet of 10 taxis in the Boston area. The long-term average transfer rate achieved was approximately 38 Mbytes/hour per car (86 kbit/s), making Cabernet a viable system for a number of non-interactive applications.

This paper presents a framework to address new data management challenges introduced by data-intensive, perva-sive computing environments. These challenges include a spatio-temporal variation of data and data source availability, lack of a global catalog and schema, and no guarantee of reconnection among peers due to the serendipitous nature of the environment. An important aspect of our solution is to treat devices as semi-autonomous peers guided in their interactions by profiles and context. The profiles are grounded in a semantically rich language and represent informa-tion about users, devices and data described in terms of “beliefs”, “desires”, and “intentions”. We present a prototype implementation of this framework over combined Bluetooth and Ad-Hoc 802.11 networks, and present experimental and simulation results that validate our approach and measure system performance.

Abstract — When highly mobile nodes are interconnected via wireless links, the resulting network can be used as a transit network to connect other disjoint ad-hoc networks. In this paper, we compare five different opportunistic forwarding schemes, which vary in their overhead, their success rate, and the amount of knowledge about neighboring nodes that they require. In particular, we present the MOVE algorithm, which uses velocity information to make intelligent opportunistic forwarding decisions. Using auxiliary information to make forwarding decisions provides a reasonable trade-off between resource overhead and performance. I.

Comparing market estimates for wireless personal communication and considering recent proposals for wide band multimedia services with the existing spectrum allocations for these types of systems show that spectrum resource management remains an important topic in the near and distant future. In this paper we present a quite general formulation of the radio resource management problem. We briefly review some the work previously published and give an outlook over some of the key problems in resource management in future wireless multimedia systems is given. 1. Introduction The rapid increase of the size of wireless mobile community and their demands for high speed, multimedia communications stands in clear contrast to the rather limited spectrum resource that have been allocated in international agreements. Efficient spectrum or Radio Resource Management (RRM) is of paramount importance due to these increasing demands. Fig 1 illustrates the principles of wireless network design. The ne...

Abstract — In this paper, we study minimal power transmission of bursty sources over wireless channels with constraints on mean queuing delay. The power minimizing schedulers adapt power and rate of transmission based on the queue and channel state. We show that packet scheduling based on queue state can be used to trade queuing delay with transmission power, even on additive white Gaussian noise channels. Our extensive simulations show that small increases in average delay can lead to substantial savings in transmission power, thereby providing another avenue for mobile devices to save on battery power. We propose a lowcomplexity scheduler that has near optimal performance. We also construct a variable rate QAM based transmission scheme to show the benefits of the proposed formulation in a practical communication system. Power optimal schedulers with absolute packet delay constraints are also studied and their performance is evaluated via simulations. Index Terms — Packet scheduling, power control, queuing delay, traffic regulation, wireless channels. I.