Recent years have witnessed the impacts of distributed content sharing (Wikipedia, Blogger), social networks (Facebook, MySpace), sensor networks, and pervasive computing. We believe that significant more impact is latent in the convergence of these ideas on the mobile phone platform. Phones can be envisioned as people-centric sensors capable of aggregating participatory as well as sensory inputs from local surroundings. The inputs can be visualized in different dimensions, such as space and time. When plugged into the Internet, the collaborative inputs from phones may enable a high resolution view of the world. This paper presents the architecture and implementation of one such system, called Micro-Blog. New kinds of application-driven challenges are identified and addressed in the context of this system. Implemented on Nokia N95 mobile phones, Micro-Blog was distributed to volunteers for real life use. Promising feedback suggests that Micro-Blog can be a deployable tool for sharing, browsing, and querying global information.

Characterizing mobility or contact patterns in a campus environment is of interest for a variety of reasons. Existing studies of these patterns can be classified into two basic approaches – model based and measurement based. The model based approach involves constructing a mathematical model to generate movement patterns while the measurement based approach measures locations and proximity of wireless devices to infer mobility patterns. In this paper, we take a completely different approach. First we obtain the class schedules and class rosters from a university-wide Intranet learning portal, and use this information to infer contacts made between students. The value of our approach is in the population size involved in the study, where contact patterns among 22341 students are analyzed. This paper presents the characteristics of these contact patterns, and explores how these patterns affect three scenarios. We first look at the characteristics from the DTN perspective, where we study inter-contact time and time distance between pairs of students. Next, we present how these characteristics impact the spread of mobile computer viruses, and show that viruses can spread to virtually the entire student population within a day. Finally, we consider aggregation of information from a large number of mobile, distributed sources, and demonstrate that the contact patterns can be exploited to design efficient aggregation algorithms, in which only a small number of nodes (less than 0.5%) is needed to aggregate a large fraction (over 90%) of the data.

Number: CR-PRL-2008-08-0001

Abstract—Delay Tolerant Networks are wireless networks where disconnections may occur frequently due to propagation phenomena, node mobility, and power outages. Propagation delays may also be long due to the operational environment (e.g. deep space, underwater). In order to achieve data delivery in such challenging networking environments, researchers have proposed the use of store-carry-and-forward protocols: there, a node may store a message in its buffer and carry it along for long periods of time, until an appropriate forwarding opportunity arises. Additionally, multiple message replicas are often propagated to increase delivery probability. This combination of long-term storage and replication imposes a high storage overhead on untethered nodes (e.g. handhelds). Thus, efficient buffer management policies are necessary to decide which messages should be discarded, when node buffers are operated close to their capacity. In this paper, we propose efficient buffer management policies for delay tolerant networks. We show that traditional buffer management policies like drop-tail or drop-front fail to consider all relevant information in this context and are, thus, sub-optimal. Using the theory of encounter-based message dissemination, we propose an optimal buffer management policy based on global knowledge about the network. Our policy can be tuned either to minimize the average delivery delay or to maximize the average delivery rate. Finally, we introduce a distributed algorithm that uses statistical learning to approximate the global knowledge required by the the optimal algorithm, in practice. Using simulations based on a synthetic mobility model and real mobility traces, we show that our buffer management policy based on statistical learning successfully approximates the performance of the optimal policy in all considered scenarios. At the same time, our policy outperforms existing ones in terms of both average delivery rate and delivery delay. I.

Abstract — Over recent years, mobile Internet devices such as laptops, PDAs, smart phones etc, have become extremely popular and widespread. Once on board of a vehicle, these devices can automatically connect to the vehicle processor and thus greatly amplify the communications and processing capabilities available to the owner in a “pedestrian mode. ” We envision that this “amplification ” opportunity will be one of the drivers of car to car and car to curb communications. In fact, the car communications system will not be used exclusively for mobile Internet access, but also as a distributed platform for the “opportunistic ” cooperation among people with shared interests/goals. Exchanging safety messages among vehicles is a compelling example. Stretching opportunistic cooperation well beyond safety messages, we discuss in this paper the concept of virtual “flea market ” over VANET called FleaNet. In FleaNet, customers, either mobile (i.e., vehicles) or stationary (i.e., pedestrians, roadside shop owner), express their demands/offers, e.g., want to buy or sell an item, via radio queries. These queries are opportunistically disseminated exploiting in part the mobility of other customers in order to find the customer/vendor with matching needs/resources. In the paper we identify the key performance metrics, namely query resolution latency, scalability, and mobility. Based on the metrics, using models and simulation, we show that FleaNet can efficiently support a market place over vehicular networks. I.

Location-based social applications (LBSAs) rely on the location coordinates of the users to provide services. Today, smartphones using these applications act as simple clients and send out user locations to untrusted third-party servers. These servers have the application logic to provide the service, and in the process collect large amounts of user location information over time. This design, however, is shown to be susceptible to large-scale user privacy compromises even if several location cloaking techniques are employed. In this position paper, we argue that the LBSAs should adapt an approach where the untrusted third-party servers are treated simply as encrypted data stores, and the application functionality be moved to the client devices. The location coordinates are encrypted, when shared, and can be decrypted only by the users that the data is intended for. This approach significantly improves user location privacy. We argue that this approach not only improves privacy, but it is also flexible enough to support a wide variety of location-based applications used today. In this paper, we identify the key building blocks necessary to construct the applications in this approach, give examples of using the building blocks by constructing several applications, and outline the privacy properties provided by this approach. We believe our approach provides a practical alternative design for LBSAs that is deployable today. 1.

Nodes in wireless ad hoc networks are often limited in terms of resources, such as storage, power, and bandwidth. A downside of this is the fact that local storage at one node cannot accommodate the vast amount of data contained in the network. In this paper, we present Shared-State, a scheme for storage, replication, and distribution of common-interest data in wireless networks of resourceconstrained devices (e.g. sensor nodes or embedded devices). SharedState works under the assumption that individual nodes would greatly benefit from having access to the wealth of information in the network, but are unable to store it locally at once. SharedState strives to make data available to every node by providing local access to a subset of the whole collection of data items in the network at any moment in time and ensuring that this subset is updated periodically. This is accomplished by probabilistic propagation and replication of data items, ensuring the availability and persistence of information in the face of changing network conditions. We evaluate the performance of SharedState by studying the effectiveness with which nodes can gather information from the network. In addition, we optimize the bandwidth usage of our proposed solution by minimizing unnecessary communication based on feedback from the local neighborhood. 1.

A variety of mobile phone applications are on the rise, many of which utilize physical location to express the context of information. This paper argues that physical location alone, unless remarkably precise, may not be sufficient to express this context. Even slight localization errors may cause a mobile phone to be placed in a grocery store, as opposed to its actual location in an adjacent coffee shop. Applications such as location specific advertisements, can get affected. This paper proposes accelerometer augmented mobile phone localization (AAMPL), a system that uses accelerometer signatures to place mobile phones in the right context. Early evaluation on Nokia N95 phones shows that AAMPL can correct locations derived from Google Maps. We believe that AAMPL can be extended to additional sensors (like light and sound) to further aid GPS-free localization.

Abstract—In this paper, we present a novel, multi-period spraying algorithm for routing in Delay Tolerant Networks (DTN). The goal is to minimize the average copy count used per message until the delivery while maintaining the predefined message delivery rate by the given deadline. In each period, some number of additional copies are sprayed into the network, followed by the wait for message delivery. At any time instance, the total number of message copies distributed to the network depends on the urgency of achieving the delivery rate by the given deadline for that message. Waiting for early delivery in the initial periods with small number of copies in existence decreases the average number of copies sprayed in the network till delivery. We first discuss 2- and 3-period variants of our algorithm and then we also give an idea how the presented approach can be extended to more periods. We present an in-depth analysis of the algorithm and validate the analytical results with simulations. The results demonstrate that our multi-period spraying algorithm outperforms the algorithms with single spraying period.

Abstract—Existing routing algorithms for Delay Tolerant Networks (DTNs) assume that nodes are willing to forward packets for others. In the real world, however, most people are socially selfish; i.e., they are willing to forward packets for nodes with whom they have social ties but not others, and such willingness varies with the strength of the social tie. Following the philosophy of design for user, we propose a Social Selfishness Aware Routing (SSAR) algorithm to allow user selfishness and provide better routing performance in an efficient way. To select a forwarding node, SSAR considers both users ’ willingness to forward and their contact opportunity, resulting in a better forwarding strategy than purely contact-based approaches. Moreover, SSAR formulates the data forwarding process as a Multiple Knapsack Problem with Assignment Restrictions (MKPAR) to satisfy user demands for selfishness and performance. Trace-driven simulations show that SSAR allows users to maintain selfishness and achieves better routing performance with low transmission cost. I.