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.
There are several attempts to obtain delivery guarantee for greedy routing algorithms. The authors of @cite_25 propose face routing , which guarantees delivery in two-dimensional unit disk graphs (UDG). Face routing is applied to a planar sub-network obtained by considering the Gabriel Graph @cite_25 @cite_16 , the Relative Neighborhood Graph @cite_30 , or the Morelia Graph @cite_0 . In @cite_19 a greedy-face-greedy (GFG) approach is considered, where greedy routing is based on COP as in @cite_20 and face routing is similar to the one in @cite_25 . Energy-aware routing is also proposed in LEARN @cite_17 , SPFSP @cite_21 , End-to-End (EtE) @cite_11 , and EEGR @cite_8 .
@cite_30 @cite_11 @cite_8 @cite_21 @cite_0 @cite_19 @cite_16 @cite_25 @cite_20 @cite_17
2063295648 2100013559 2160745122 2165689920 1846633197 2036935881 2072369710 2156689181 2035540448 2133937062
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. It was recently reported that all known face and combined greedy-face routing variants cannot guarantee message delivery in arbitrary undirected planar graphs. The purpose of this article is to clarify that this is not the truth in general. We show that specifically in relative neighborhood and Gabriel graphs 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 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. A prominent approach is to visit a sequence of faces which are intersected by the line connecting the source and destination node. Whenever encountering an edge which is intersecting with this line, the critical part is to decide if face traversal has to change to the next adjacent one or not. Failures may occur from incorporating face routing procedures that force to change the traversed face at each intersection. Recently observed routing failures which were produced by the GPSR protocol in arbitrary planar graphs result from incorporating such a face routing variant. They cannot be constructed by the well known GFG algorithm which does not force changing the face anytime. Beside methods which visit the faces intersected by the source destination line, we discuss face routing variants which simply restart face routing whenever the next face has to be explored. We give the first complete and formal proofs that several proposed face routing, and combined greedyface routing schemes do guarantee delivery in specific graph classes or even any arbitrary planar graphs. We also discuss the reasons why other methods may fail to deliver a message or even end up in a loop. In a document network such as a citation network of scientific documents, web-logs, etc., the content produced by authors exhibits their interest in certain topics. In addition some authors influence other authors' interests. In this work, we propose to model the influence of cited authors along with the interests of citing authors. Moreover, we hypothesize that apart from the citations present in documents, the context surrounding the citation mention provides extra topical information about the cited authors. However, associating terms in the context to the cited authors remains an open problem. We propose novel document generation schemes that incorporate the context while simultaneously modeling the interests of citing authors and influence of the cited authors. Our experiments show significant improvements over baseline models for various evaluation criteria such as link prediction between document and cited author, and quantitatively explaining unseen text. Purpose – The purpose of this paper is to suggest an alternative to the widely used Times Cited criterion for analysing citation networks. The approach involves taking account of the natures of the papers that cite a given paper, so as to differentiate between papers that attract the same number of citations.Design methodology approach – ArticleRank is an algorithm that has been derived from Google's PageRank algorithm to measure the influence of journal articles. ArticleRank is applied to two datasets – a citation network based on an early paper on webometrics, and a self‐citation network based on the 19 most cited papers in the Journal of Documentation – using citation data taken from the Web of Knowledge database.Findings – ArticleRank values provide a different ranking of a set of papers from that provided by the corresponding Times Cited values, and overcomes the inability of the latter to differentiate between papers with the same numbers of citations. The difference in rankings between Times Cited ...