Message and time efficient multi-broadcast schemes

We consider message and time efficient broadcasting and multi-broadcasting in wireless ad-hoc networks, where a subset of nodes, each with a unique rumor, wish to broadcast their rumors to all destinations while minimizing the total number of transmissions and total time until all rumors arrive to their destination. Under centralized settings, we introduce a novel approximation algorithm that provides almost optimal results with respect to the number of transmissions and total time, separately. Later on, we show how to efficiently implement this algorithm under distributed settings, where the nodes have only local information about their surroundings. In addition, we show multiple approximation techniques based on the network collision detection capabilities and explain how to calibrate the algorithms' parameters to produce optimal results for time and messages.Comment: In Proceedings FOMC 2013, arXiv:1310.459

Communication Efficient Self-Stabilizing Leader Election

This paper presents a randomized self-stabilizing algorithm that elects a leader r in a general n-node undirected graph and constructs a spanning tree T rooted at r. The algorithm works under the synchronous message passing network model, assuming that the nodes know a linear upper bound on n and that each edge has a unique ID known to both its endpoints (or, alternatively, assuming the KT? model). The highlight of this algorithm is its superior communication efficiency: It is guaranteed to send a total of O? (n) messages, each of constant size, till stabilization, while stabilizing in O? (n) rounds, in expectation and with high probability. After stabilization, the algorithm sends at most one constant size message per round while communicating only over the (n - 1) edges of T. In all these aspects, the communication overhead of the new algorithm is far smaller than that of the existing (mostly deterministic) self-stabilizing leader election algorithms. The algorithm is relatively simple and relies mostly on known modules that are common in the fault free leader election literature; these modules are enhanced in various subtle ways in order to assemble them into a communication efficient self-stabilizing algorithm

New techniques for geographic routing

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 141-148).As wireless sensor networks continue to grow in size, we are faced with the prospect of emerging wireless networks with hundreds or thousands of nodes. Geographic routing algorithms are a promising alternative to tradition ad hoc routing algorithms in this new domain for point-to-point routing, but deployments of such algorithms are currently uncommon because of some practical difficulties. This dissertation explores techniques that address two major issues in the deployment of geographic routing algorithms: (i) the costs associated with distributed planarization and (ii) the unavailability of location information. We present and evaluate two new algorithms for geographic routing: Greedy Distributed Spanning Tree Routing (GDSTR) and Greedy Embedding Spring Coordinates (GSpring). Unlike previous geographic routing algorithms which require the planarization of the network connectivity graph, GDSTR switches to routing on a spanning tree instead of a planar graph when packets end up at dead ends during greedy forwarding. To choose a direction on the tree that is most likely to make progress towards the destination, each GDSTR node maintains a summary of the area covered by the subtree below each of its tree neighbors using convex hulls.(cont.) This distributed data structure is called a hull tree. GDSTR not only requires an order of magnitude less bandwidth to maintain these hull trees than CLDP, the only distributed planarization algorithm that is known to work with practical radio networks, it often achieves better routing performance than previous planarization-based geographic routing algorithms. GSpring is a new virtual coordinate assignment algorithm that derives good coordinates for geographic routing when location information is not available. Starting from a set of initial coordinates for a set of elected perimeter nodes, GSpring uses a modified spring relaxation algorithm to incrementally adjust virtual coordinates to increase the convexity of voids in the virtual routing topology. This reduces the probability that packets will end up in dead ends during greedy forwarding, and improves the routing performance of existing geographic routing algorithms. The coordinates derived by GSpring yield comparable routing performance to that for actual physical coordinates and significantly better performance than that for NoGeo, the best existing algorithm for deriving virtual coordinates for geographic routing. Furthermore, GSpring is the first known algorithm that is able to derive coordinates that achieve better geographic routing performance than actual physical coordinates for networks with obstacles.by Ben Wing Lup Leong.Ph.D

New Techniques for Geographic Routing

PhD thesisAs wireless sensor networks continue to grow in size, we are facedwith the prospect of emerging wireless networks with hundreds orthousands of nodes. Geographic routing algorithms are a promisingalternative to tradition ad hoc routing algorithms in this new domainfor point-to-point routing, but deployments of such algorithms arecurrently uncommon because of some practical difficulties.This dissertation explores techniques that address two major issues inthe deployment of geographic routing algorithms: (i) the costsassociated with distributed planarization and (ii) the unavailabilityof location information. We present and evaluate two new algorithmsfor geographic routing: Greedy Distributed Spanning Tree Routing(GDSTR) and Greedy Embedding Spring Coordinates (GSpring).Unlike previous geographic routing algorithms which require theplanarization of the network connectivity graph, GDSTR switches torouting on a spanning tree instead of a planar graph when packets endup at dead ends during greedy forwarding. To choose a direction on thetree that is most likely to make progress towards the destination,each GDSTR node maintains a summary of the area covered by the subtreebelow each of its tree neighbors using convex hulls. This distributeddata structure is called a hull tree. GDSTR not only requires an orderof magnitude less bandwidth to maintain these hull trees than CLDP,the only distributed planarization algorithm that is known to workwith practical radio networks, it often achieves better routingperformance than previous planarization-based geographic routingalgorithms.GSpring is a new virtual coordinate assignment algorithm that derivesgood coordinates for geographic routing when location information isnot available. Starting from a set of initial coordinates for a set ofelected perimeter nodes, GSpring uses a modified spring relaxationalgorithm to incrementally adjust virtual coordinates to increase theconvexity of voids in the virtual routing topology. This reduces theprobability that packets will end up in dead ends during greedyforwarding, and improves the routing performance of existinggeographic routing algorithms.The coordinates derived by GSpring yield comparable routingperformance to that for actual physical coordinates and significantlybetter performance than that for NoGeo, the best existing algorithmfor deriving virtual coordinates for geographic routing. Furthermore,GSpring is the first known algorithm that is able to derivecoordinates that achieve better geographic routing performance thanactual physical coordinates for networks with obstacles

A Unified Wormhole Attack Detection Framework for Mobile Ad hoc Networks

The Internet is experiencing an evolution towards a ubiquitous network paradigm, via the so-called internet-of-things (IoT), where small wireless computing devices like sensors and actuators are integrated into daily activities. Simultaneously, infrastructure-less systems such as mobile ad hoc networks (MANET) are gaining popularity since they provide the possibility for devices in wireless sensor networks or vehicular ad hoc networks to share measured and monitored information without having to be connected to a base station. While MANETs offer many advantages, including self-configurability and application in rural areas which lack network infrastructure, they also present major challenges especially in regard to routing security. In a highly dynamic MANET, where nodes arbitrarily join and leave the network, it is difficult to ensure that nodes are trustworthy for multi-hop routing. Wormhole attacks belong to most severe routing threats because they are able to disrupt a major part of the network traffic, while concomitantly being extremely difficult to detect. This thesis presents a new unified wormhole attack detection framework which is effective for all known wormhole types, alongside incurring low false positive rates, network loads and computational time, for a variety of diverse MANET scenarios. The framework makes three original technical contributions: i) a new accurate wormhole detection algorithm based on packet traversal time and hop count analysis (TTHCA) which identifies infected routes, ii) an enhanced, dynamic traversal time per hop analysis (TTpHA) detection model which is adaptable to node radio range fluctuations, and iii) a method for automatically detecting time measurement tampering in both TTHCA and TTpHA. The thesis findings indicate that this new wormhole detection framework provides significant performance improvements compared to other existing solutions by accurately, efficiently and robustly detecting all wormhole variants under a wide range of network conditions

Underwater Data Collection Using Robotic Sensor Networks

We examine the problem of utilizing an autonomous underwater vehicle (AUV) to collect data from an underwater sensor network. The sensors in the network are equipped with acoustic modems that provide noisy, range-limited communication. The AUV must plan a path that maximizes the information collected while minimizing travel time or fuel expenditure. We propose AUV path planning methods that extend algorithms for variants of the Traveling Salesperson Problem (TSP). While executing a path, the AUV can improve performance by communicating with multiple nodes in the network at once. Such multi-node communication requires a scheduling protocol that is robust to channel variations and interference. To this end, we examine two multiple access protocols for the underwater data collection scenario, one based on deterministic access and another based on random access. We compare the proposed algorithms to baseline strategies through simulated experiments that utilize models derived from experimental test data. Our results demonstrate that properly designed communication models and scheduling protocols are essential for choosing the appropriate path planning algorithms for data collection.United States. Office of Naval Research (ONR N00014-09-1-0700)United States. Office of Naval Research (ONR N00014-07-1-00738)National Science Foundation (U.S.) (NSF 0831728)National Science Foundation (U.S.) (NSF CCR-0120778)National Science Foundation (U.S.) (NSF CNS-1035866

Design and analysis of adaptive hierarchical low-power long-range networks

A new phase of evolution of Machine-to-Machine (M2M) communication has started where vertical Internet of Things (IoT) deployments dedicated to a single application domain gradually change to multi-purpose IoT infrastructures that service different applications across multiple industries. New networking technologies are being deployed operating over sub-GHz frequency bands that enable multi-tenant connectivity over long distances and increase network capacity by enforcing low transmission rates to increase network capacity. Such networking technologies allow cloud-based platforms to be connected with large numbers of IoT devices deployed several kilometres from the edges of the network. Despite the rapid uptake of Long-power Wide-area Networks (LPWANs), it remains unclear how to organize the wireless sensor network in a scaleable and adaptive way. This paper introduces a hierarchical communication scheme that utilizes the new capabilities of Long-Range Wireless Sensor Networking technologies by combining them with broadly used 802.11.4-based low-range low-power technologies. The design of the hierarchical scheme is presented in detail along with the technical details on the implementation in real-world hardware platforms. A platform-agnostic software firmware is produced that is evaluated in real-world large-scale testbeds. The performance of the networking scheme is evaluated through a series of experimental scenarios that generate environments with varying channel quality, failing nodes, and mobile nodes. The performance is evaluated in terms of the overall time required to organize the network and setup a hierarchy, the energy consumption and the overall lifetime of the network, as well as the ability to adapt to channel failures. The experimental analysis indicate that the combination of long-range and short-range networking technologies can lead to scalable solutions that can service concurrently multiple applications