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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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 Due to mobility, the information that a node receives about its neighbors becomes outdated, leading either to a significant decrease in the packet delivery rate or to a steep increase in load on the wireless channel as node mobility increases.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. 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. 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. This paper presents two efficient flooding algorithms based on 1-hop neighbor information. In the first part of the paper, we consider sender-based flooding algorithms, specifically the algorithm proposed by In their paper, propose a sender-based flooding algorithm that can achieve local optimality by selecting the minimum number of forwarding nodes in the lowest computational time complexity O(n logn), where n is the number of neighbors. We show that this optimality only holds for a subclass of sender-based algorithms. We propose an efficient sender-based flooding algorithm based on 1-hop neighbor information that reduces the time complexity of computing forwarding nodes to O(n). In Liu's algorithm, n nodes are selected to forward the message in the worst case, whereas in our proposed algorithm, the number of forwarding nodes in the worst case is 11. In the second part of the paper we propose a simple and highly efficient receiver-based flooding algorithm. When nodes are uniformly distributed, we prove that the probability of two neighbor nodes broadcasting the same messageneighbor nodes broadcasting the same message exponentially decreases when the distance between them decreases or when the node density increases. The analytical results are confirmed using simulation. 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... In this paper, we propose a selection region based multihop routing protocol with directional antennas for wireless mobile ad hoc networks, where the selection region is defined by two parameters: a reference distance and the beamwidth of the directional antenna. At each hop, we choose the nearest node to the transmitter within the selection region as the next hop relay. By maximizing the expected density of progress, we present an upper bound for the optimum reference distance and derive the relationship between the optimum reference distance and the optimum transmission probability. Compared with the results with routing strategy using omnidirectional antennas in [1], we find interestingly that the optimum transmission probability is a constant independent of the beamwidth, the expected density of progress with the new routing strategy is increased significantly, and the computational complexity involved in the relay selection is also greatly reduced. Compact routing addresses the tradeoff between table sizes and stretch, which is the worst-case ratio between the length of the path a packet is routed through by the scheme and the length of an actual shortest path from source to destination. We adapt the compact routing scheme by Thorup and Zwick [2001] to optimize it for power-law graphs. We analyze our adapted routing scheme based on the theory of unweighted random power-law graphs with fixed expected degree sequence by [2000]. Our result is the first analytical bound coupled to the parameter of the power-law graph model for a compact routing scheme. Let n denote the number of nodes in the network. We provide a labeled routing scheme that, after a stretch--5 handshaking step (similar to DNS lookup in TCP IP), routes messages along stretch--3 paths. We prove that, instead of routing tables with O(n1 2) bits (O suppresses factors logarithmic in n) as in the general scheme by Thorup and Zwick, expected sizes of O(nγ log n) bits are sufficient, and that all the routing tables can be constructed at once in expected time O(n1+γ log n), with γ = τ-22 τ-3 + e, where τ∈(2,3) is the power-law exponent and e 0 (which implies e With the same techniques as for the compact routing scheme, we also adapt the approximate distance oracle by Thorup and Zwick [2001, 2005] for stretch-3 and we obtain a new upper bound of expected O(n1+γ) for space and preprocessing for random power-law graphs. Our distance oracle is the first one optimized for power-law graphs. Furthermore, we provide a linear-space data structure that can answer 5--approximate distance queries in time at most O(n1 4+e) (similar to γ, the exponent actually depends on τ and lies between e and 1 4 + e). We study a basic buffer management problem that arises in network switches. Consider @math input ports, each of which is equipped with a buffer (queue) of limited capacity. Data packets arrive online and can be stored in the buffers if space permits; otherwise packet loss occurs. In each time step the switch can transmit one packet from one of the buffers to the output port. The goal is to maximize the number of transmitted packets. Simple arguments show that any work-conserving algorithm, which serves any nonempty buffer, is 2-competitive. Azar and Richter recently presented a randomized online algorithm and gave lower bounds for deterministic and randomized strategies. In practice, greedy algorithms are very important because they are fast, use little extra memory, and reduce packet loss by always serving a longest queue. In this paper we first settle the competitive performance of the entire family of greedy strategies. We prove that greedy algorithms are not better than 2-competitive no matter how ties are broken. Our lower bound proof uses a new recursive construction for building adversarial buffer configurations that may be of independent interest. We also give improved lower bounds for deterministic and randomized online algorithms. In this paper we present the first deterministic online algorithm that is better than 2-competitive. We develop a modified greedy algorithm, called semigreedy, and prove that it achieves a competitive ratio of @math . The new algorithm is simple, fast, and uses little extra memory. Only when the risk of packet loss is low does it not serve the longest queue. Additionally we study scenarios when an online algorithm is granted additional resources. We consider resource augmentation with respect to memory and speed; i.e., an online algorithm may be given larger buffers or higher transmission rates. We analyze greedy and other online strategies. Position-based routing, as it is used by protocols like Greedy Perimeter Stateless Routing (GPSR) [5], is very well suited for highly dynamic environments such as inter-vehicle communication on highways. However, it has been discussed that radio obstacles [4], as they are found in urban areas, have a significant negative impact on the performance of position-based routing. In prior work [6] we presented a position-based approach which alleviates this problem and is able to find robust routes within city environments. It is related to the idea of position-based source routing as proposed in [1] for terminode routing. The algorithm needs global knowledge of the city topology as it is provided by a static street map. Given this information the sender determines the junctions that have to be traversed by the packet using the Dijkstra shortest path algorithm. Forwarding between junctions is then done in a position-based fashion. In this short paper we show how position-based routing can be aplied to a city scenario without assuming that nodes have access to a static street map and without using source routing. In this paper, we propose a cross-layer deflect routing scheme that improves effective throughput of multi-hop millimeter-wave wireless personal area network (mmWave WPAN) system. The upcoming mmWave WPAN is designed to provide Gbps-order transmission capability, targeting applications like high definition TV (HDTV) transmission, high speed wireless docking and gaming etc. Adopting multi-hop relay offers solutions to the issues existing in mmWave WPAN system such as limited coverage range caused by the significant path loss, dramatic communication link change due to the unexpected blockage of the line-of-sight (LOS) path etc. However, multi-hop relay on the other hand decreases the effective throughput because of the required extra time. As a result, the compromised throughput may not be able to support the above applications which are greedy for data rate. Inspired by the fact that the significant path loss of millimeter-wave environment can provide good space isolation, our proposed scheme manages to improve the multi-hop throughput by sharing time slots for relay path with direct path for other transmissions. We also propose two algorithms, namely random fit deflect routing (RFDR) and best fit deflect routing (BFDR), to find the relay path on which the interference due to time slot sharing is low enough to guarantee the concurrent transmissions. Computer simulations show that, in realistic 60GHz environment, the effective multi-hop throughput can be improved up to 45 . This paper is meant to be an illustration of the use of stochastic geometry for analyzing the performance of routing in large wireless ad hoc (mobile or mesh) networks. In classical routing strategies used in such networks, packets are transmitted on a pre-defined route that is usually obtained by a shortest-path routing protocol. In this paper we review some recent ideas concerning a new routing technique which is opportunistic in the sense that each packet at each hop on its (specific) route from an origin to a destination takes advantage of the actual pattern of nodes that captured its recent (re)transmission in order to choose the next relay. The paper focuses both on the distributed algorithms allowing such a routing technique to work and on the evaluation of the gain in performance it brings compared to classical mechanisms. On the algorithmic side, we show that it is possible to implement this opportunistic technique in such a way that the current transmitter of a given packet does not need to know its next relay a priori, but the nodes that capture this transmission (if any) perform a self-selection procedure to choose the packet relay node and acknowledge the transmitter. We also show that this routing technique works well with various medium access protocols (such as Aloha, CSMA, TDMA). Finally, we show that the above relay self-selection procedure can be optimized in the sense that it is the node that optimizes some given utility criterion (e.g. minimize the remaining distance to the final destination), which is chosen as the relay. The performance evaluation part is based on stochastic geometry and combines simulation as analytical models. The main result is that such opportunistic schemes very significantly outperform classical routing schemes when properly optimized and provided at least a small number of nodes in the network know their geographical positions exactly. In this paper we propose a novel relay selection method for cooperation communication networks using fuzzy logic. Many efforts have been made in the literature to select the superior relay based on relay's SNR SER and or relay's reputation (in cooperation stimulation methods). We jointly consider four criteria for the process of relay selection, relay's SNR SER, relay's reputation, relaying strategy and relay location. We consider the condition in which network users employ different relaying strategies, i.e., some relay nodes employ decode-and-forward strategy, some nodes employ amplify-and-forward strategy, and the other ones employ compress-and-forward strategy. Also, we categorize the network users into LM clusters and take into account the relative distance of potential relay nodes from the source and destination nodes in the process of relay selection. This relative distance has significant impact on the average achievable rate in destination node. Finally, by using a fuzzy logic decision making method, we select the “best relay” based on these four criteria. 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. As the Internet becomes more mature, there is a realization that improving the performance of routers has the potential to substantially improve Internet performance in general. Currently, most routers forward packets in a First-In-First-Out (FIFO) order. However, the diversity of applications supported by modern IP-based networks has resulted in unpredictable packet flows, and heterogeneous network traffic. Thus, it is becoming more reasonable to consider differentiating between different types of packets, and perhaps to consider allowing packets to specify a deadline by which it must be processed. These issues have made buffer management at routers a critical issue in providing effective quality of service to the various applications that use the network. In this paper, we study an online problem in which each packet is described by its discrete arrival time, non-negative weight and discrete deadline; arriving packets are buffered for delivery and all packets have the same processing time. The packets arrive online, and our objective is to maximize the sum of weights of those packets that are sent by their deadlines. We describe an online deterministic algorithm with a competitive ratio of 1.854, improving the best previous known competitive ratio of 1.939 ( STACS 2004). The algorithmic framework we use has several interesting features. First, we do not use a potential function. Instead, after each step we modify the adversary's buffer. Second, we introduce "dummy packets" to facilitate the decision making. In a localized routing algorithm, each node currently holding a message makes forwarding decision solely based on the position information about itself, its neighbors and destination. In a unit graph, two nodes can communicate if and only if the distance between them is no more than the transmission radius, which is the same for each node. This paper proposes localized routing algorithms, aimed at minimizing total power for routing a message or maximizing the total number of routing tasks that a network can perform before a partition. The algorithms are combinations of known greedy power and or cost aware localized routing algorithms and an algorithm that guarantees delivery. A shortcut procedure is introduced in later algorithm to enhance its performance. Another improvement is to restrict the routing to nodes in a dominating set. These improvements require two-hop knowledge at each node. The efficiency of proposed algorithms is verified experimentally by comparing their power savings, and the number of routing tasks a network can perform before a node loses all its energy, with the corresponding shortest weighted path algorithms and localized algorithms that use fixed transmission power at each node. Significant energy savings are obtained, and feasibility of applying power and cost-aware localized schemes is demonstrated. Copyright © 2004 John Wiley & Sons, Ltd. Our work is motivated by impromptu (or ''as-you-go'') deployment of wireless relay nodes along a path, a need that arises in many situations. In this paper, the path is modeled as starting at the origin (where there is the data sink, e.g., the control center), and evolving randomly over a lattice in the positive quadrant. A person walks along the path deploying relay nodes as he goes. At each step, the path can, randomly, either continue in the same direction or take a turn, or come to an end, at which point a data source (e.g., a sensor) has to be placed, that will send packets to the data sink. A decision has to be made at each step whether or not to place a wireless relay node. Assuming that the packet generation rate by the source is very low, and simple link-by-link scheduling, we consider the problem of sequential relay placement so as to minimize the expectation of an end-to-end cost metric (a linear combination of the sum of convex hop costs and the number of relays placed). This impromptu relay placement problem is formulated as a total cost Markov decision process. First, we derive the optimal policy in terms of an optimal placement set and show that this set is characterized by a boundary (with respect to the position of the last placed relay) beyond which it is optimal to place the next relay. Next, based on a simpler one-step-look-ahead characterization of the optimal policy, we propose an algorithm which is proved to converge to the optimal placement set in a finite number of steps and which is faster than value iteration. We show by simulations that the distance threshold based heuristic, usually assumed in the literature, is close to the optimal, provided that the threshold distance is carefully chosen. In this paper, we consider the CSMA CA multihop networks where the two end-nodes transmit their packets to each other and each intermediate node adopts network coding for delivering bidirectional flows. In addition, the neighbor nodes are randomly uniformly deployed with the Poisson Point Process. By varying the combination of the physical carrier-sensing range of the transmitter node and the target signal-to-interference ratio (SIR) set by the receiver node, we can control the interference level in the network and the degree of spatial reuse of a frequency band. The larger the carrier-sensing range is, the smaller the interference level, while the smaller the opportunity of getting a channel by a node. Similarly, the higher the target SIR value is, the more probable the retransmission (by the exponential random backoff) is, while the better the link quality on successful transmission is getting. Under this tradeoff context, we find the optimal combinations of these two factors that make the end-to-end throughput of the flow maximal for three different retransmission schemes. 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. With the development of ad hoc networks, some researchers proposed several geometric routing protocols which depend on the planarization of the network connectivity graph to guarantee the delivery of the packet between any pair of nodes in the network. In this paper, we proposed a new online routing algorithm GLNFR (greedy and local neighbor face routing) for finding paths between the nodes of the ad hoc networks by storing a small amount of local face information at each node. The localized Delaunay triangulation was used to be the backbone of wireless network on which the GLNFR routing algorithm runs. It has the better scalability and adaptability for the change of ad hoc networks. Experiment on NS have been conducted. The results show that the delivery rate of packets and routing protocol message cost under such novel routing protocols performs better than others proposed before. We consider the optimal online packet scheduling problem in a single-user energy harvesting wireless communication system, where energy is harvested from natural renewable sources, making future energy arrivals instants and amounts random in nature. The most general case of arbitrary energy arrivals is considered where neither the future energy arrival instants or amount, nor their distribution is known. The problem considered is to adaptively change the transmission rate according to the causal energy arrival information, such that the time by which all packets are delivered is minimized. We assume that all bits have arrived and are ready at the source before the transmission begins. For a minimization problem, the utility of an online algorithm is tested by finding its competitive ratio or competitiveness that is defined to be the maximum of the ratio of the gain of the online algorithm with the optimal offline algorithm over all input sequences. We derive a lower and upper bound on the competitive ratio of any online algorithm to minimize the total transmission time in an energy harvesting system. The upper bound is obtained using a lazy' transmission policy that chooses its transmission power to minimize the transmission time assuming that no further energy arrivals are going to occur in future. The lazy transmission policy is shown to be strictly two-competitive. We also derive an adversarial lower bound that shows that competitive ratio of any online algorithm is at least 1.325.