We introduce and evaluate a very simple landmark-based network partition technique called Hierarchical Bipartition Routing (HBR) to support routing with delivery guarantee in wireless ad hoc sensor networks. It is a simple routing protocol that can easily be combined with any other greedy routing algorithm to obtain delivery guarantee. The efficiency of HBR increases if the network is sparse and contains obstacles. The space necessary to store the additional routing information at a node u is on average not larger than the size necessary to store the IDs of the neighbors of u. The amount of work to setup the complete data structure is on average proportional to flooding the entire network log(n) times, where n is the total number of sensor nodes. We evaluate the performance of HBR in combination with two simple energy-aware geographic greedy routing algorithms based on physical coordinates and virtual coordinates, respectively. Our simulations show that the difference between using HBR and a weighted shortest path to escape a dead-end is only a few percent in typical cases.
Most algorithms based on position awareness first try to deliver the packet using greedy techniques. For example, the simplest greedy routing technique @cite_28 will forward the packet to the neighbor closest to the destination. Most Forward Routing (MFR) @cite_3 and Nearest with Forwarding Progress (NFP) @cite_32 consider the projected distance on the source-destination line. MFR tries to get closer to the destination by sending the packet to the neighbor with maximum projected distance, while NFP suggests to adjust the transmission power by sending the packet to the neighbor with the smallest projected distance.
@cite_28 @cite_32 @cite_3
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In this article we propose several new progress based, localized, power, and cost aware algorithms for routing in ad hoc wireless networks. These algorithms attempt to minimize the total power and or cost needed to route a message from source to destination. In localized algorithms, each node makes routing decisions solely on the basis of location of itself, its neighbors and destination. The new algorithms are based on the notion of proportional progress. A node currently holding the packet will forward it to a neighbor, closer to destination than itself, which minimizes the ratio of power and or cost to reach that neighbor, and the progress made, measured as the reduction in distance to destination, or projection along the line to destination. First, we propose Power Progress, Iterative Power Progress, Projection Power Progress, and Iterative Projection Power Progress algorithms, where the proportional progress is defined in terms of power measure. The power metrics are then replaced by cost or power-co... Existing position-based unicast routing algorithms which forward packets in the geographic direction of the destination require that the forwarding node knows the positions of all neighbors in its transmission range. This information on direct neighbors is gained by observing beacon messages each node sends out periodically. Due to mobility, the information that a node receives about its neighbors becomes outdated, leading either to a significant decrease in the packet delivery rate or to a steep increase in load on the wireless channel as node mobility increases. In this paper, we propose a mechanism to perform position-based unicast forwarding without the help of beacons. In our contention-based forwarding scheme (CBF) the next hop is selected through a distributed contention process based on the actual positions of all current neighbors. For the contention process, CBF makes use of biased timers. To avoid packet duplication, the first node that is selected suppresses the selection of further nodes. We propose three suppression strategies which vary with respect to forwarding efficiency and suppression characteristics. We analyze the behavior of CBF with all three suppression strategies and compare it to an existing greedy position-based routing approach by means of simulation with ns-2. Our results show that CBF significantly reduces the load on the wireless channel required to achieve a specific delivery rate compared to the load a beacon-based greedy forwarding strategy generates. Geographic routing is one of the most widely-accepted techniques to route information in large-scale wireless sensor networks. It is based on a greedy forwarding strategy by which a sensor node selects as next hop relay the most promising neighbor (according to some metric) among those being closer to the destination than itself. This decision is based solely on the position of its neighbors and the destination. Given that sensor nodes are usually operated by batteries, energy-efficiency is a very important metric to be considered by the routing protocol. In this paper we present Locally-Optimal Source Routing (LOSR), a new localized and energy-efficient geographic routing algorithm for wireless sensor networks. Unlike existing energy-efficient geographic routing algorithms, in which current node routing the packet only considers nodes closer to destination than itself, LOSR uses all nodes in the neighborhood to compute a local energy-optimal path formed only by neighbors of the current node towards the selected next hop. Then, source routing is used to force data packets to follow that locally optimal path until next hop is reached. Our simulation results show that the proposed algorithm outperforms the best existing solution, over a variety of network densities and scenarios. We present Greedy Perimeter Stateless Routing (GPSR), a novel routing protocol for wireless datagram networks that uses the positions of routers and a packet's destination to make packet forwarding decisions. GPSR makes greedy forwarding decisions using only information about a router's immediate neighbors in the network topology. When a packet reaches a region where greedy forwarding is impossible, the algorithm recovers by routing around the perimeter of the region. By keeping state only about the local topology, GPSR scales better in per-router state than shortest-path and ad-hoc routing protocols as the number of network destinations increases. Under mobility's frequent topology changes, GPSR can use local topology information to find correct new routes quickly. We describe the GPSR protocol, and use extensive simulation of mobile wireless networks to compare its performance with that of Dynamic Source Routing. Our simulations demonstrate GPSR's scalability on densely deployed wireless networks. We propose a novel localized routing protocol for wireless sensor networks (WSN) that is energy-efficient and guarantees delivery. We prove that it is constant factor of the optimum for dense networks. To forward a packet, a node s in graph G computes the cost of the energy weighted shortest path (SP) between s and each of its neighbors which are closer to the destination than itself. It then selects node x which minimizes the ratio of the cost of the SP to the progress towards the destination. It then sends the message to the first node on the SP from s to x: say node x'. Node x' restarts the same greedy routing process until the destination is reached or the routing fails. To recover from failure, our algorithm invokes face routing that guarantees delivery. This work is the first to optimize energy consumption of face routing. First, we build a connected dominating set from graph G, second we compute its Gabriel graph to obtain the planar graph G'. Face routing is applied on G' only to decide which edges to follow in the recovery process. On each edge, greedy routing is used. This two-phase (greedy-Face) end-to-end routing process (EtE) reiterates until the final destination is reached. Simulation results show that EtE outperforms several existing geographical routing on energy consumption metric. Large scale decentralized communication systems have motivated a new trend towards online routing where routing decisions are performed based on a limited and localized knowledge of the network. Geometrical greedy routing has been among the simplest and most common online routing schemes. While a geometrical online routing scheme is expected to deliver each packet to the point in the network that is closest to the destination, geometrical greedy routing, when applied over generalized substrate graphs, does not guarantee such delivery as its forwarding decision might deliver packets to a localized minimum instead. This letter investigates the necessary and sufficient conditions of greedy supporting graphs that would guarantee such delivery when used as a greedy routing substrate. We present an overview of ad hoc routing protocols that make forwarding decisions based on the geographical position of a packet's destination. Other than the destination's position, each node need know only its own position and the position of its one-hop neighbors in order to forward packets. Since it is not necessary to maintain explicit routes, position-based routing does scale well even if the network is highly dynamic. This is a major advantage in a mobile ad hoc network where the topology may change frequently. The main prerequisite for position-based routing is that a sender can obtain the current position of the destination. Therefore, previously proposed location services are discussed in addition to position-based packet forwarding strategies. We provide a qualitative comparison of the approaches in both areas and investigate opportunities for future research. This paper describes Extremely Opportunistic Routing (ExOR), a new unicast routing technique for multi-hop wireless networks. ExOR forwards each packet through a sequence of nodes, deferring the choice of each node in the sequence until after the previous node has transmitted the packet on its radio. ExOR then determines which node, of all the nodes that successfully received that transmission, is the node closest to the destination. That closest node transmits the packet. The result is that each hop moves the packet farther (or average) than the hops of the best possible pre-determined route.The ExOR design addresses the challenge of choosing a forwarding node after transmission using a distributed algorithm. First, when a node transmits a packet, it includes in the packet a simple schedule describing the priority order in which the potential receivers should forward the packet. The node computes the schedule based on shared measurements of inter-node delivery rates. ExOR then uses a distributed slotted MAC protocol for acknowledgements to ensure that the receivers agree who the highest priority receiver was.The efficacy of ExOR depends mainly on the rate at which the reception probability falls off with distance. Simulations based on measured radio characteristics [6] suggest that ExOR reduces the total number of transmissions by nearly a factor of two over the best possible pre-determined route. In wireless ad hoc networks (WANets), multihop routing may result in a radio knowing the content of transmissions of nearby radios. This knowledge can be used to improve spatial reuse in the network, thereby enhancing network throughput. Consider two radios, Alice and Bob, that are neighbors in a WANet not employing spread-spectrum multiple access. Suppose that Alice transmits a packet to Bob for which Bob is not the final destination. Later, Bob forwards that packet on to the destination. Any transmission by Bob not intended for Alice usually causes interference that prevents Alice from receiving a packet from any of her neighbors. However, if Bob is transmitting a packet that he previously received from Alice, then Alice knows the content of the interfering packet, and this knowledge can allow Alice to receive a packet from one of her neighbors during Bob's transmission. In this paper, we develop overlapped transmission techniques based on this idea and analyze several factors affecting their performance. We then develop a MAC protocol based on the IEEE 802.11 standard to support overlapped transmission in a WANet. The resulting overlapped CSMA (OCSMA) protocol improves spatial reuse and end-to-end throughput in several scenarios. Routing in ad hoc networks is a complicated task because of many reasons. The nodes are low-memory, low-powered, and they cannot maintain routing tables large enough for well-known routing protocols. Because of that, greedy forwarding at intermediate nodes is desirable in ad hoc networks. Also, for traffic engineering, multi-path capabilities are important. So, it is desirable to define routes at the source like in source based routing (SBR) while performing greedy forwarding at intermediate nodes. We investigate trajectory-based routing (TBR) which was proposed as a middle-ground between SBR and greedy forwarding techniques. In TBR, source encodes trajectory to be traversed and embeds it into each packet. Upon the arrival of each packet, intermediate nodes decode the trajectory and employ greedy forwarding techniques such that the packet follows its trajectory as much as possible. In this paper, we address various issues regarding implementation of TBR. We also provide techniques to efficiently forward packets along a trajectory defined as a parametric curve. We use the well-known Bezier parametric curve for encoding trajectories into packets at source. Based on this trajectory encoding, we develop and evaluate various greedy forwarding algorithms In this paper, we present a novel packet forwarding scheme for wireless ad hoc networks --- “Direction” Forwarding (DFR). Popular routing protocols such as DSDV and AODV use “predecessor” based forwarding, namely, the packet is forwarded to the predecessor on the shortest path from the destination, as advertised during the last update. Predecessor forwarding may fail in large scale networks where the routing update rate must be reduced by the need to maintain link O H below reasonable levels. However, if nodes are mobile, routing table entries may become “stale” very rapidly. DFR is designed to overcome the “stale” routing table entry problem. When the routing update arrives, the node remembers not only the predecessor delivering the update, but also the update “direction” of arrival. When a packet must be forwarded to destination, it is first forwarded to the node ID found in the routing table. If the node has moved and ID forwarding fails, the packet is “direction” forwarded to the “most promising” node in the indicated direction. At first glance, DFR seems to combine the features of table based routing and geo-routing. However, direction forwarding differs from geo-routing in that the direction is learned from the routing updates, instead of being computed from the destination coordinates. Thus, DFR does not require destination coordinates, a global coordinate system, or a Geo Location Server. In the paper we show the application of DFR to a scalable routing scheme, LANMAR. Through simulation experiments we show that DFR substantially enhances LANMAR performance in large, mobile network scenarios. Many algorithms for routing in sensor networks exploit greedy forwarding strategies to get packets to their destinations. We study a fundamental difficulty such strategies face: the "local minimum phenomena" that can cause packets to get stuck. We give a definition of stuck nodes where packets may get stuck in greedy multi-hop forwarding, and develop a local rule, the TENT rule, for each node in the network to test whether a packet can get stuck at that node. To help the packets get out of stuck nodes, we describe a distributed algorithm, BOUNDHOLE, to build routes around holes, which are connected regions of the network with boundaries consisting of all the stuck nodes. We show that these hole-surrounding routes can be used in many applications such as geographic routing, path migration, information storage mechanisms and identification of regions of interest. This paper considers the problem of designing power efficient routing with guaranteed delivery for sensor networks with known distances between neighbors but unknown geographic locations. We propose Hector, a hybrid energy efficient tree-based optimized routing protocol, based on two sets of virtual coordinates. One set is based on rooted tree coordinates, and the other is based on hop distances toward several landmarks. In our algorithm, the node currently holding the packet forwards it to its neighbor that optimizes ratio of power cost over distance progress with landmark coordinates, among nodes that reduce landmark coordinates and do not increase tree coordinates. If such a node does not exist then forwarding is made to the neighbor that reduces tree based distance and optimizes power cost over tree distance progress ratio. Our simulations show the superiority of our algorithm over existing alternatives while guaranteeing delivery, and only up to 30 additional power compared to centralized shortest weighted path algorithm. We propose a practical and scalable technique for point-to-point routing in wireless sensornets. This method, called Beacon Vector Routing (BVR), assigns coordinates to nodes based on the vector of hop count distances to a small set of beacons, and then defines a distance metric on these coordinates. BVR routes packets greedily, forwarding to the next hop that is the closest (according to this beacon vector distance metric) to the destination. We evaluate this approach through a combination of high-level simulation to investigate scaling and design tradeoffs, and a prototype implementation over real testbeds as a necessary reality check. We propose to use Vehicular ad hoc networks (VANET) as the infrastructure for an urban cyber-physical system for gathering up-to-date data about a city, like traffic conditions or environmental parameters. In this context, it is critical to design a data collection protocol that enables retrieving the data from the vehicles in almost real-time in an efficient way for urban scenarios. We propose Back off-based Per-hop Forwarding (BPF), a broadcast-based receiver-oriented protocol that uses the destination location information to select the forwarding order among the nodes receiving the packet. BFP does not require nodes to exchange periodic messages with their neighbors communicating their locations to keep a low management message overhead. It uses geographic information about the final destination node in the header of each data packet to route it in a hop-by-hop basis. It takes advantage of redundant forwarding to increase packet delivery to a destination, what is more critical in an urban scenario than in a highway, where the road topology does not represent a challenge for forwarding. We evaluate the performance of the BPF protocol using ns-3 and a Manhattan grid topology and compare it with well-known broadcast suppression techniques. Our results show that BPF achieves significantly higher packet delivery rates at a reduced redundancy cost. Opportunistic routing is widely known to have substantially better performance than traditional unicast routing in wireless networks with lossy links. However, wireless sensor networks are heavily duty-cycled, i.e. they frequently enter deep sleep states to ensure long network life-time. This renders existing opportunistic routing schemes impractical, as they assume that nodes are always awake and can overhear other transmissions. In this paper, we introduce a novel opportunistic routing metric that takes duty cycling into account. By analytical performance modeling and simulations, we show that our routing scheme results in significantly reduced delay and improved energy efficiency compared to traditional unicast routing. The method is based on a new metric, EDC, that reflects the expected number of duty cycled wakeups that are required to successfully deliver a packet from source to destination. We devise distributed algorithms that find the EDC-optimal forwarding, i.e. the optimal subset of neighbors that each node should permit to forward its packets. We compare the performance of the new routing with ETX-optimal single path routing in both simulations and testbed-based experiments. We show that complex (scale-free) network topologies naturally emerge from hyperbolic metric spaces. Hyperbolic geometry facilitates maximally efficient greedy forwarding in these networks. Greedy forwarding is topology-oblivious. Nevertheless, greedy packets find their destinations with 100 probability following almost optimal shortest paths. This remarkable efficiency sustains even in highly dynamic networks. Our findings suggest that forwarding information through complex networks, such as the Internet, is possible without the overhead of existing routing protocols, and may also find practical applications in overlay networks for tasks such as application-level routing, information sharing, and data distribution. Routing of packets in mobile ad hoc networks with a large number of nodes or with high mobility is a very difficult task and current routing protocols do not really scale well with these scenarios. The beacon-less routing algorithm (BLR) presented in this paper is a routing protocol that makes use of location information to reduce routing overhead. However, unlike other position-based routing protocols, BLR does not require nodes to periodically broadcast Hello-messages (called beaconing), and thus avoids drawbacks such as extensive use of scarce battery-power, interferences with regular data transmission, and performance degradation. BLR selects a forwarding node in a distributed manner among all its neighboring nodes with having information neither about their positions nor even about their existence. Data packets are broadcasted and the protocol takes care that just one of the receiving nodes forwards the packet. Optimized forwarding is achieved by applying a concept of dynamic forwarding delay. Consequently, the node that computes the shortest forwarding delay relays the packet first. This forwarding is detected by the other nodes and suppresses them to relay the same packet any further. Analytical results and simulation experiments indicate that BLR provides efficient and robust routing in highly dynamic mobile ad hoc networks. Efficient and cost effective data collection from smart city sensors through vehicular networks is crucial for many applications, such as travel comfort, safety and urban sensing. Static and mobile sensors data can be gathered through the vehicles that will be used as data mules and, while moving, they will be able to access road side units (RSUs), and then, send the data to a server in the cloud. Therefore, it is important to research how to use opportunistic vehicular networks to forward data packets through each other in a multi-hop fashion until they reach the destination. This paper proposes a novel data forwarding algorithm for urban vehicular networks taking into consideration the rank of each vehicle, which is based on the probability to reach a road side unit. The proposed forwarding algorithm is evaluated in the mOVERS emulator considering different forwarding decisions, such as, no restriction on broadcasting packets to neighboring On-Board Units (OBUs), restriction on broadcasting by the average rank of neighboring OBUs, and the number of hops between source and destination. Results show that, by restricting the broadcast messages in the proposed algorithm, we are able to reduce the network's overhead, therefore increasing the packet delivery ratio between the sensors and the server. This paper considers (p, q )-Epidemic Routing, a class of store-carry-forward routing schemes, for sparsely populated mobile ad hoc networks. Our forwarding scheme includes Two-Hop Forwarding and the conventional Epidemic Routing as special cases. In such forwarding schemes, the original packet is copied many times and its packet copies spread over the network. Therefore those packet copies should be deleted after a packet reaches the destination. We analyze the performance of (p, q)-Epidemic Routing with VACCINE recovery scheme. Unlike most of the existing studies, we discuss the performance of (p, q)-Epidemic Routing in depth, taking account of the recovery process that deletes unnecessary packets from the network.