Timely Data Delivery in a Realistic Bus Network

Abstract—WiFi-enabled buses and stops may form the backbone of a metropolitan delay tolerant network, that exploits nearby communications, temporary storage at stops, and predictable bus mobility to deliver non-real time information. This paper studies the problem of how to route data from its source to its destination in order to maximize the delivery probability by a given deadline. We assume to know the bus schedule, but we take into account that randomness, due to road traffic conditions or passengers boarding and alighting, affects bus mobility. We propose a simple stochastic model for bus arrivals at stops, supported by a study of real-life traces collected in a large urban network. A succinct graph representation of this model allows us to devise an optimal (under our model) single-copy routing algorithm and then extend it to cases where several copies of the same data are permitted. Through an extensive simulation study, we compare the optimal routing algorithm with three other approaches: minimizing the expected traversal time over our graph, minimizing the number of hops a packet can travel, and a recently-proposed heuristic based on bus frequencies. Our optimal algorithm outperforms all of them, but most of the times it essentially reduces to minimizing the expected traversal time. For values of deadlines close to the expected delivery time, the multi-copy extension requires only 10 copies to reach almost the performance of the costly flooding approach. I

Performance Assessment of Aggregation and Deaggregation Algorithms in Vehicular Delay-Tolerant Networks

Vehicular Delay-Tolerant Networks (VDTNs) are a new approach for vehicular communications where vehicles cooperate with each other, acting as the communication infrastructure, to provide low-cost asynchronous opportunistic communications. These communication technologies assume variable delays and bandwidth constraints characterized by a non-transmission control protocol/ internet protocol architecture but interacting with it at the edge of the network. VDTNs are based on the principle of asynchronous communications, bundleoriented communication from the DTN architecture, employing a store-carryand- forward routing paradigm. In this sense, VDTNs should use the tight network resources optimizing each opportunistic contact among nodes. At the ingress edge nodes, incoming IP Packets (datagrams) are assembled into large data packets, called bundles. The bundle aggregation process plays an important role on the performance of VDTN applications. Then, this paper presents three aggregation algorithms based on time, bundle size, and a hybrid solution with combination of both. Furthermore, the following four aggregation schemes with quality of service (QoS) support are proposed: 1) single-class bundle with N = M, 2) composite-class bundle with N = M, 3) single-class bundle with N > M, and 4) composite-class bundle with N > M, where N is the number of classes of incoming packets and M is the number of priorities supported by the VDTN core network. The proposed mechanisms were evaluated through a laboratory testbed, called VDTN@Lab. The adaptive hybrid approach and the composite-class schemes present the best performance for different types of traffic load and best priorities distribution, respectively

Improved Fair-Zone technique using Mobility Prediction in WSN

The self-organizational ability of ad-hoc Wireless Sensor Networks (WSNs) has led them to be the most popular choice in ubiquitous computing. Clustering sensor nodes organizing them hierarchically have proven to be an effective method to provide better data aggregation and scalability for the sensor network while conserving limited energy. It has some limitation in energy and mobility of nodes. In this paper we propose a mobility prediction technique which tries overcoming above mentioned problems and improves the life time of the network. The technique used here is Exponential Moving Average for online updates of nodal contact probability in cluster based network.Comment: 10 pages, 7 figures, Published in International Journal Of Advanced Smart Sensor Network Systems (IJASSN