Greedy Routing Research Articles

Greedy Routing on Complex Networks

This paper proposes a new routing strategy on complex networks. Based on the idea of greedy algorithm, our routing strategy chooses the node that has the highest probability to reach destination with the studies of max degree search strategy. In the meantime, the dynamic information like queue length will affect influence our strategy in order to increase the capacity of network. The result of simulation shows our strategy has a better performance compare to other local routing strategy. This strategy can be used on different kinds of complex networks.

Exploiting Virtual Coordinates for Improved Routing Performance in Sensor Networks

We present the Virtual Cord Protocol (VCP), which exploits virtual coordinates to provide efficient and failure tolerant routing and data management in sensor networks. VCP maintains a virtual cord interconnecting all the nodes in the network and which, operating similar to a Distributed Hash Table (DHT), provides means for inserting data fragments into sensor nodes and retrieving them. Furthermore, it supports service discovery using indirections. VCP uses two mechanisms for finding paths to nodes and associated data items: First, it relies on the virtual cord that always provides a path toward the destination. Second, locally available neighborhood information is exploited for greedy routing. Our simulation results show that VCP is able to find paths close to the shortest path (achieving a stretch ratio of less than 125 percent) with very low overhead. We also extended VCP with data replication mechanisms to improve failure handling. The routing performance of VCP, which clearly outperforms other ad hoc routing protocols such as Dynamic MANET On Demand (DYMO), is similar to other virtual addressing schemes, e.g., Virtual Ring Routing (VRR). However, we improved VCP to handle frequent node failures in an optimized way. The presented results outline the capabilities of VCP to handle such cases more efficiently compared to other protocols. We also compared the capabilities to reliably store and retrieve data in the network to Geographic Hash Tables (GHTs). VCP, in the worst case, performs similar to GHTs, but outperforms this protocol in most cases, especially when complex routing is involved.

Performance Evaluation Of Hole Avoidance Techniques In Geographic Forwarding For Mobile Ad Hoc Networks

Ad hoc networks prefer reactive routing over proactive routing due to the rapid changes in a nodes position. Geographic position based routing is a convenient method to route a packet from a source to a destination based on the local information alone. Geographic forwarding adopts a greedy routing technique that selects a forwarding node that is closer to the destination than itself. When a node cannot find any such neighbour, it is said to be in a hole and should recover to find an alternate path of delivery. The common recovery technique used in the literature is face routing. This paper compares the performance of face routing technique with two other recovery mechanisms proposed in the literature that uses limited flooding and directional flooding. It is found that sectoring is more efficient than topology and perimeter forwarding in terms of delivery rate, end to end delay, control overhead, average path length, and number of forwarding nodes.

Spray and forward: Efficient routing based on the Markov location prediction model for DTNs

Typical delay tolerant networks (DTNs) often suffer from long and variable delays, frequent connectivity disruptions, and high bit error rates. In DTNs, the design of an efficient routing algorithm is one of the key issues. The existing methods improve the accessibility probability of the data transmission by transmitting many copies of the packet to the network, but they may cause a high network overhead. To address the tradeoff between a successful delivery ratio and the network overhead, we propose a DTN routing algorithm based on the Markov location prediction model, called the spray and forward routing algorithm (SFR). Based on historical information of the nodes, the algorithm uses the second-order Markov forecasting mechanism to predict the location of the destination node, and then forwards the data by greedy routing, which reduces the copies of packets by spraying the packets in a particular direction. In contrast to a fixed mode where a successful-delivery ratio and routing overhead are contradictory, a hybrid strategy with multi-copy forwarding is able to reduce the copies of the packets efficiently and at the same time maintain an acceptable successful-delivery ratio. The simulation results show that the proposed SFR is efficient enough to provide better network performance than the spray and wait routing algorithm, in scenarios with sparse node density and fast mobility of the nodes.

Capability information: A cost-effective information model for multi-hop routing of wireless ad hoc networks in the real environment

In greedy routing, each relay node forwards the message to a neighbor (also called the successor) that is closer to the destination. However, the successor candidate set (SCS) is different every time the relative location of the relay node to the destination changes. The configuration in the entire network, when all succeeding paths from a relay node are blocked by local minima, is irregular and its concern region cannot be determined unless the routing actually initiates. In the real deployment environment of the wireless ad hoc networks, the link quality also changes dynamically. This brings a challenge for the local decision of the greedy advance to precisely adjust its SCS for the flip-flop of link quality that blocks the non-detour path ahead. This paper introduces a new information model to a non-detour routing, also called progressive routing, under the impact of dynamic blocks. As a result, each 1-hop advance, by sacrificing little routing flexibility, can avoid those unsafe situations and remains on a non-detour path. In our model, each node prepares the information in a proactive mode, but can use it for all different paths passing through, saving the cost and delay in the reactive mode. We focus on an “everyone” model, in which each node will apply the same generic process in a fully distributed manner, in order to achieve a scalable and reliable solution. In detail, we discuss how in a sample realistic environment the pattern of SCS can be interpreted in a single safety descriptor ∈ [ 0 , 1 ] at each node. It indicates the maximum probability of a successful non-detour path from this node to the edge of networks. The larger value the more likely the non-detour routing will be successful and the more stable the path will be. We illustrate the effectiveness of this indirect reference information in the corresponding routing in terms of the success of non-detour path constitution and the ability of self-adjustment for dynamics in the networks, while the cost of information construction and update propagation is minimized. The results are compared with the best results known to date.

A Subjectively Influenced Router for Vehicles in a Four-Junction Traffic System

A subjectively influenced router for vehicles in a four- junction traffic system is presented. The router is based on a 3-layer Backpropagation Neural Network (BPNN) and a greedy routing procedure. The BPNN detects priorities of vehicles based on the subjective criteria. The subjective criteria and the routing procedure depend on the routing plan towards vehicles depending on the user. The routing procedure selects vehicles from their junctions based on their priorities and route them concurrently to the traffic system. That is, when the router is provided with a desired vehicles selection criteria and routing procedure, it routes vehicles with a reasonable junction clearing time. The cost evaluation of the router determines its efficiency. In the case of a routing conflict, the router will route the vehicles in a consecutive order and quarantine faulty vehicles. The simulations presented indicate that the presented approach is an effective strategy of structuring a subjective vehicle router.

An Energy-efficient Multi-candidate Greedy Routing Scheme in Wireless Sensor Networks

Sleep and wake-up scheduling of sensor nodes is an efficient solution to prolong the network lifetime. However, existing scheduling algorithms may significantly decrease the number of active nodes so that the network may be intermittently-connected. In such networks, traditional geographic routing protocols are inappropriate to obtain low latency routes due to route discovery and data forwarding latency. In this paper, we propose a novel \emph{multi-candidate greedy routing} (MGR) scheme that makes the best effort to find minimum latency routes in the sensor networks. In MGR, each source node sends an RREQ to a set of first wake-up forwarder candidates and selects a route with minimum estimated delivery latency based on their replies. Moreover, to cope with the unreliability of wireless links, we introduce an add-on algorithm for MGR, called \emph{multilevel of link quality requirement-based packet forwarding} (MLRPF), which helps to increase the energy efficiency of MGR while still guaranteeing a low delivery latency. Simulation results demonstrate that MLRPF increases the routing performance of MGR significantly compared with PRRxDistance \cite{7}, DGF \cite{3}, and ODML \cite{2} in terms of packet delivery latency and energy efficiency.

A model framework for greedy routing in a sensor network with a stochastic power scheme

A stochastic model is formulated and analyzed to study the advancements of messages under greedy routing in a sensor network with a power-saving scheme. The aim of this model is give a better understanding of stochastic dependencies arising in the system and to offer a method of computing the advancement of message under greedy routing. We observe that the majority of the stochastic dependence from a routing path is captured by including only the previous forwarding node location. We examine a simple uncoordinated power-saving scheme with a new understanding of its effects on local node density. We propose a method for sensibly limiting the number of transmission reattempts before concluding there is no node in the forwarding region. All expressions involving multidimensional integrals are derived and evaluated readily with quasi-Monte Carlo integration methods. An importance sampling function is derived to speed up the quasi-Monte Carlo methods. The integral expressions are compared to simulations and give very agreeable results.

Convex Subspace Routing (CSR): Routing via anchor-based convex virtual subspaces in sensor networks

Convex Subspace Routing (CSR) is a novel approach for routing in sensor networks using anchor-based virtual coordinates. Unlike geographical routing schemes that require physical location information of nodes, obtaining which is often difficult, error-prone and costly, the Virtual Coordinate (VC) based schemes simply characterize each node by a vector of shortest hop distances to a selected subset of nodes known as anchors. Even though VC based routing (VCR) schemes benefits from having connectivity information implicitly embedded within the VCs, VCs lack the directional information available with physical coordinates. The major issues affecting routing using VCs are addressed. Due to local minima problem in the virtual space, the VCR schemes rely on backtracking or hill climbing techniques to overcome the local minima. Convex Subspace Routing, in contrast, avoids using anchors that cause local minima. It dynamically selects subsets of anchors that define subspaces to provide convex distance functions from source to destination. Consequently, it is less sensitive to anchor placement and over anchoring, and does not require tracking route history for backtracking, resulting in shorter packet lengths and energy efficient operation. Three techniques for selection of convex subspaces are proposed and evaluated. Performance evaluation for several different network topologies indicates that CSR significantly outperforms the existing VCR scheme, Logical Coordinate Routing (LCR), while being competitive with geographic coordinate based Greedy Perimeter Stateless Routing (GPSR), even though latter makes use of node location information.

Position-based Routing Algorithm for Improving Reliability of Inter-Vehicle Communication

A vehicular ad-hoc network (VANET) consists of vehicles that form a network without any additional infrastructure, thus allowing the vehicles to communicate with each other. VANETs have unique characteristics, including high node mobility and rapidly changing network topology. Because of these characteristics, routing algorithms based on greedy forwarding such as greedy perimeter stateless routing (GPSR) are known to be very suitable for a VANET. However, greedy forwarding just selects the node nearest to the destination node as a relay node within its transmission range. This increases the possibility of a local maximum and link loss because of the high mobility of vehicles and the road characteristics in urban areas. Therefore, this paper proposes a reliability-improving position-based routing (RIPR) algorithm to solve those problems. The RIPR algorithm predicts the positions, velocities, and moving directions of vehicles after receiving beacon messages, and estimates information about road characteristics to select the relay node. Thus, it can reduce the possibility of getting a local maximum and link breakage. Simulation results using ns-2 revealed that the proposed routing protocol performs much better than the existing routing protocols based on greedy forwarding.

Navigating in a Graph by Aid of Its Spanning Tree Metric

Let $G=(V,E)$ be a graph and T be a spanning tree of G. We consider the following strategy in advancing in G from a vertex x towards a target vertex y: from a current vertex z (initially, $z=x$), unless $z=y$, go to a neighbor of z in G that is closest to y in T (breaking ties arbitrarily). In this strategy, each vertex has full knowledge of its neighborhood in G and can use the distances in T to navigate in G. Thus, additionally to standard local information (the neighborhood $N_G(v)$), the only global information that is available to each vertex v is the topology of the spanning tree T (in fact, v can know only a very small piece of information about T and still be able to infer from it the necessary tree-distances). For each source vertex x and target vertex y, this way, a path, called a greedy routing path, is produced. Denote by $g_{G,T}(x,y)$ the length of a longest greedy routing path that can be produced for x and y using this strategy and T. We say that a spanning tree T of a graph G is an additive r-carcass for G if $g_{G,T}(x,y)\leq d_G(x,y)+r$ for each ordered pair $x,y\in V$. In this paper, we investigate the problem, given a graph family $\mathcal{F}$, of whether a small integer r exists such that any graph $G\in\mathcal{F}$ admits an additive r-carcass. We show that rectilinear $p\times q$ grids, hypercubes, distance-hereditary graphs, dually chordal graphs (and, therefore, strongly chordal graphs and interval graphs) all admit additive 0-carcasses. Furthermore, every chordal graph G admits an additive $(\omega+1)$-carcass (where $\omega$ is the size of a maximum clique of G), each 3-sun-free chordal graph admits an additive 2-carcass, and each chordal bipartite graph admits an additive 4-carcass. In particular, any k-tree admits an additive $(k+2)$-carcass. All those carcasses are easy to construct in sequential as well as in distributed settings.

A new approach to shortest paths on networks based on the quantum bosonic mechanism

This paper presents quantum bosonic shortest path searching (QBSPS), a natural, practical and highly heuristic physical algorithm for reasoning about the recognition of network structure via quantum dynamics. QBSPS is based on an Anderson-like itinerant bosonic system in which a boson's Green function is used as a navigation pointer for one to accurately approach the terminals. QBSPS is demonstrated by rigorous mathematical and physical proofs and plenty of simulations, showing how it can be used as a greedy routing to seek the shortest path between different locations. In methodology, it is an interesting and new algorithm rooted in the quantum mechanism other than combinatorics. In practice, for the all-pairs shortest-path problem in a random scale-free network with N vertices, QBSPS runs in O(μ(N) ln ln N) time. In application, we suggest that the corresponding experimental realizations are feasible by considering path searching in quantum optical communication networks; in this situation, the method performs a pure local search on networks without requiring the global structure that is necessary for current graph algorithms.

Design and analysis of a multi-candidate selection scheme for greedy routing in wireless sensor networks

Sleep and wake-up scheduling of sensor nodes is an efficient solution to prolong the network lifetime. However, existing scheduling algorithms may significantly decrease the number of active nodes so that the network may be intermittently connected. In such networks, traditional geographic routing protocols are inappropriate to obtain low latency routes due to route discovery and data forwarding latency. In this paper, we propose a novel multi-candidate selection (MCS) scheme for greedy routing that makes the best effort to find minimum latency routes in the sensor networks. In MCS, each source node sends an RREQ to a list of first wake-up forwarder candidates and selects a route with minimum estimated delivery latency based on their replies. The route found by MCS may be longer than that of distance-based greedy forwarding (DGF) ( Finn, 1987). Hence, we introduce a latency-adaptive distance-based multi-candidate selection scheme for greedy forwarding to find routes with a small number of hops and acceptable delivery latency. Probabilistic analysis and simulation results demonstrate that MCS increases the routing performance significantly compared with DGF and ODML ( Su et al., 2008) in terms of delivery latency.

Up-Down Links Dualpath Greedy Routing Protocol for Wireless Sensor Networks

Greedy geographic routing is attractive in wireless sensor networks because of its efficiency and scalability. This paper presents an up-down links dualpath greedy routing (UDLDGR) protocol for wireless sensor networks. The routing protocol not only reserves the features of greedy forwarding algorithm, which is simple, efficient, but also uses different relay nodes to serve as routing nodes for up and down routing paths, makes the energy consumption more balanced. The greatest advantage of UDLDGR is it trades off only small cost for the source node to obtain two different transmission paths information. The multipath strengthens the network reliability, such as load balancing and robustness to failures. Our simulation results show that UDLDGR can improve system lifetime by 20---100% compared to single path approaches.

Distributed computation of virtual coordinates for greedy routing in sensor networks

Sensor networks are emerging as a paradigm for future computing, but pose a number of challenges in the fields of networking and distributed computation. One challenge is to devise a greedy routing protocol—one that routes messages through the network using only information available at a node or its neighbors. Modeling the connectivity graph of a sensor network as a 3-connected planar graph, we describe how to compute on the network in a distributed and local manner a special geometric embedding of the graph. This embedding supports a geometric routing protocol called “greedy routing” based on the “virtual” coordinates of the nodes derived from the embedding.

Three-dimensional greedy routing in large-scale random wireless sensor networks

In this paper, we investigate how to design greedy routing to achieve sustainable and scalable in a large-scale three-dimensional (3D) sensor network. Several 3D position-based routing protocols were proposed to seek either delivery guarantee or energy-efficiency in 3D wireless networks. However, recent results [1,2] showed that there is no deterministic localized routing algorithm that guarantees either delivery of packets or energy-efficiency of its routes in 3D networks. In this paper, we focus on design of 3D greedy routing protocols which can guarantee delivery of packets and/or energy-efficiency of their paths with high probability in a randomly deployed 3D sensor network. In particular, we first study the asymptotic critical transmission radius for 3D greedy routing to ensure the packet delivery in large-scale random 3D sensor networks, then propose a refined 3D greedy routing protocol to achieve energy-efficiency of its paths with high probability. We also conduct extensive simulations to confirm our theoretical results.

HyPeer: Structured overlay with flexible-choice routing

The various designs of peer-to-peer distributed hash tables (DHTs) differ mostly in their performance and the properties they provide. They usually rely on a single greedy routing strategy aiming at achieving short communication paths. In this paper, we propose a new peer-to-peer DHT overlay design, HyPeer, that uses the “flexible-choice routing” principle to support multiple routing strategies, each driven by a different objective: fault tolerance, load balance, low latency. Our overlay is loosely based on a hypercube structure providing redundant paths that can be selectively followed at runtime according to the desired goal. HyPeer approximates a hypercube by extending a ring-based DHT overlay and controlling the placement of nodes when they join the network. Experimental evaluation confirms that HyPeer succeeds in improving the routing performance according to our three design objectives, while only slightly increasing the average path length.

A generalized greedy routing algorithm for 2-connected graphs

Geometric routing by using virtual locations is an elegant way for solving network routing problems. In its simplest form, greedy routing, a message is simply forwarded to a neighbor that is closer to the destination. One main drawback of this approach is that the coordinates of the virtual locations require Ω ( n log n ) bits to represent, which makes this scheme infeasible in some applications. The essence of the geometric routing is the following: When an origin vertex u wants to send a message to a destination vertex w , it forwards the message to a neighbor t , solely based on the location information of u , w and all neighbors of u . In the greedy routing scheme, the decision is based on decreasing distance. For this idea to work, however, the decision needs not be based on decreasing distance. As long as the decision is made locally, this scheme will work fine. In this paper, we introduce a version of greedy routing which we call generalized greedy routing algorithm. Instead of relying on decreasing distance, a generalized greedy routing algorithm uses other criteria to determine routing paths, solely based on local information. We present simple generalized greedy routing algorithms based on s t -coordinates (consisting of two integers between 0 and n − 1 ), which are derived from an s t -orientation of a 2-connected plane graph. We also generalize this result to arbitrary trees. Both algorithms are natural and simple to be implemented.

On Delivery Guarantees and Worst-Case Forwarding Bounds of Elementary Face Routing Components in Ad Hoc and Sensor Networks

In this paper, we provide a thorough theoretical study on delivery guarantees, loop-free operation, and worst-case behavior of face and combined greedy-face routing. We show that under specific planar topology control schemes, recovery from a greedy routing failure is always possible without changing between any adjacent faces. Guaranteed delivery then follows from guaranteed recovery while traversing the very first face. In arbitrary planar graphs, however, a proper face selection mechanism is of importance since recovery from a greedy routing failure may require visiting a sequence of faces before greedy routing can be restarted again. We provide complete and formal proofs that several proposed face routing and combined greedy-face routing schemes guarantee message delivery in specific planar graph classes or even in arbitrary planar graphs. We also discuss the reasons why other methods fail to deliver a message or even end up in a loop. In addition, we investigate the behavior of face routing in arbitrary not necessarily planar networks and show, while delivery guarantees cannot be supported in such a general case, most face and combined greedy-face routing variants support at least loop-free operation. For those variants, we derive worst-case upper bounds on the number of forwarding steps.

Greedy Local Routing Strategy for Autonomous Global Load Balancing Based on Three-Dimensional Potential Field

We discuss a traffic load balancing scheme for three-dimensional (3D) wireless mesh networks (WMNs), which deals with global load balancing through only one-hop local information. With a finite element method (FEM), we derive a distributed form of a solution for 3D Poisson's equation to construct a routing metric sensitive to traffic loads. For practical validation, we implement it on an IEEE 802.11-based WMN testbed platform. Experiment results show that our protocol chooses routing paths more efficiently for network-wide load balancing than a state-of-the-art routing protocol, OLSR-ETX.